diff --git a/.gitignore b/.gitignore index 554e7f5..ca4bce1 100644 --- a/.gitignore +++ b/.gitignore @@ -77,6 +77,9 @@ dmypy.json # uv uv.lock +# MkDocs build output +site/ + # OS .DS_Store Thumbs.db diff --git a/README.md b/README.md index f759fd6..d4f80cd 100644 --- a/README.md +++ b/README.md @@ -15,7 +15,7 @@ [![Code style: pyink](https://img.shields.io/badge/code%20style-pyink-black)](https://github.com/google/pyink) [![Type checked: mypy](https://img.shields.io/badge/type%20checked-mypy-blue)](https://mypy-lang.org/) -**[PyPI](https://pypi.org/project/adk-redis/)** • **[Documentation](https://redis.io/docs/latest/integrate/google-adk/)** • **[Examples](examples/)** • **[Agent Memory Server](https://github.com/redis/agent-memory-server)** • **[RedisVL](https://docs.redisvl.com)** +**[PyPI](https://pypi.org/project/adk-redis/)** • **[Documentation](https://redis-developer.github.io/adk-redis/)** • **[Examples](examples/)** • **[Agent Memory Server](https://github.com/redis/agent-memory-server)** • **[RedisVL](https://docs.redisvl.com)** @@ -27,12 +27,14 @@ | Surface | What you get | Backed by | |---|---|---| -| **Sessions** (`RedisWorkingMemorySessionService`) | `BaseSessionService` with auto-summarization and context-window management | Agent Memory Server (REST) | -| **Long-term memory** (`RedisLongTermMemoryService`) | `BaseMemoryService` with semantic search and recency boosting | Agent Memory Server (REST) | -| **Memory tools** (`SearchMemoryTool`, `CreateMemoryTool`, ...) | LLM-controlled memory operations | Agent Memory Server (REST) | -| **RedisVL MCP** (native `McpToolset` against `rvl mcp`) | | `rvl mcp` server (`redisvl[mcp]`) | -| **Search tools with REST** (5 in-process tools) | Vector, hybrid, range, text, SQL search as `BaseTool` subclasses | RedisVL (Python) | -| **Semantic cache** (`RedisVLCacheProvider`, `LangCacheProvider`) | Skip repeat LLM calls and tool calls by semantic similarity | RedisVL `SemanticCache` or [Redis LangCache](https://redis.io/langcache) | +| **Sessions** | `BaseSessionService` with auto-summarization and context-window management | Agent Memory Server | +| **Long-term memory** | `BaseMemoryService` with semantic search and recency boosting | Agent Memory Server | +| **Memory tools** | LLM-controlled memory CRUD operations | Agent Memory Server | +| **Search tools** | Vector, hybrid, range, text, and SQL search as `BaseTool` subclasses | RedisVL | +| **MCP search** | `search-records` / `upsert-records` via ADK's native `McpToolset` | `rvl mcp` server | +| **Semantic cache** | Skip repeat LLM calls by semantic similarity | RedisVL or [Redis LangCache](https://redis.io/langcache) | + +→ *[Full documentation](https://redis-developer.github.io/adk-redis/)* --- @@ -42,64 +44,21 @@ pip install adk-redis ``` -Optional extras (combine as needed): +Optional extras: ```bash pip install 'adk-redis[memory]' # sessions + long-term memory services pip install 'adk-redis[search]' # RedisVL-backed search tools -pip install 'adk-redis[sql]' # RedisSQLSearchTool (sql-redis) +pip install 'adk-redis[sql]' # RedisSQLSearchTool pip install 'adk-redis[langcache]' # managed semantic cache provider -pip install 'adk-redis[all]' # all of the above -pip install 'adk-redis[all,examples]' # plus dotenv etc. for running examples - -# For the RedisVL MCP server (used with ADK's native McpToolset): -pip install 'redisvl[mcp]>=0.18.2' -``` - -### Verify - -```bash -python -c "from adk_redis import __version__; print(__version__)" -``` - -### Development install - -```bash -git clone https://github.com/redis-developer/adk-redis.git -cd adk-redis -pip install uv -uv sync --all-extras +pip install 'adk-redis[all]' # everything above ``` --- -## Quick Start - -### Prerequisites +## Quick start -- Python 3.10+ -- Redis 8.4+ with the Redis Query Engine (Search). Local Docker: - ```bash - docker run -d --name redis -p 6379:6379 redis:8.4 - docker exec redis redis-cli ping # -> PONG - ``` -- For session / memory services: a running [Agent Memory Server](https://github.com/redis/agent-memory-server) (default port 8088). Quick start: - ```bash - docker run -d --name agent-memory-server -p 8088:8088 \ - -e REDIS_URL=redis://host.docker.internal:6379 \ - -e GEMINI_API_KEY=YOUR_KEY \ - -e GENERATION_MODEL=gemini/gemini-2.5-flash \ - -e EMBEDDING_MODEL=gemini/text-embedding-004 \ - redislabs/agent-memory-server:0.13.2 \ - agent-memory api --host 0.0.0.0 --port 8088 --task-backend=asyncio - ``` - On Linux, `host.docker.internal` is not routable by default; use `--network=host` and `REDIS_URL=redis://127.0.0.1:6379`, or set `REDIS_URL` to the Docker-bridge gateway (typically `redis://172.17.0.1:6379`). AMS supports 100+ LLM and embedding providers via [LiteLLM](https://docs.litellm.ai/). See [Agent Memory Server setup](docs/user_guide/how_to_guides/memory_server_setup.md) for the full configuration matrix. - -For Redis Cloud, Redis Enterprise, or troubleshooting, see [Redis setup](docs/user_guide/how_to_guides/redis_setup.md). - -### Sessions + long-term memory - -Two-tier memory: working memory (per session) and long-term memory (cross-session). Both implement ADK's service interfaces and slot into any `Runner`. +**Prerequisites:** Python 3.10+, Redis 8.4+, and (for memory features) a running [Agent Memory Server](https://github.com/redis/agent-memory-server). See the [Quickstart](https://redis-developer.github.io/adk-redis/user_guide/01_integration/) for full setup steps. ```python from google.adk import Agent @@ -116,16 +75,12 @@ session_service = RedisWorkingMemorySessionService( config=RedisWorkingMemorySessionServiceConfig( api_base_url="http://localhost:8088", default_namespace="my_app", - model_name="gpt-4o", - context_window_max=8000, ), ) memory_service = RedisLongTermMemoryService( config=RedisLongTermMemoryServiceConfig( api_base_url="http://localhost:8088", default_namespace="my_app", - extraction_strategy="discrete", - recency_boost=True, ), ) @@ -143,241 +98,38 @@ runner = Runner( ) ``` -How it works: the session service stores conversation events in working memory and auto-summarizes when the token budget is hit; the memory service runs background extraction to long-term memory and surfaces a recency-boosted semantic search. - -### Search over a Redis index (in-process) - -```python -from google.adk import Agent -from redisvl.index import SearchIndex -from redisvl.utils.vectorize import HFTextVectorizer - -from adk_redis import RedisVectorQueryConfig, RedisVectorSearchTool - -vectorizer = HFTextVectorizer(model="redis/langcache-embed-v2") -index = SearchIndex.from_existing("products", redis_url="redis://localhost:6379") - -search_tool = RedisVectorSearchTool( - index=index, - vectorizer=vectorizer, - config=RedisVectorQueryConfig(num_results=5), - return_fields=["name", "description", "price"], - name="search_product_catalog", - description="Find products by semantic similarity to the user's query.", -) - -agent = Agent( - model="gemini-2.5-flash", - name="search_agent", - instruction="Help users find products.", - tools=[search_tool], -) -``` - -All five search tools accept custom `name` / `description` so the LLM sees a domain-specific tool rather than a generic search helper. - -### Search over a Redis index (MCP) - -Run `rvl mcp --config mcp_config.yaml` separately, then connect the agent with ADK's standard `McpToolset`: - -```python -from google.adk import Agent -from google.adk.tools.mcp_tool import McpToolset -from google.adk.tools.mcp_tool.mcp_session_manager import StdioConnectionParams -from mcp import StdioServerParameters - -agent = Agent( - model="gemini-2.5-flash", - name="mcp_search_agent", - instruction="Use the search-records tool to answer questions.", - tools=[ - McpToolset( - connection_params=StdioConnectionParams( - server_params=StdioServerParameters( - command="rvl", - args=[ - "mcp", - "--config", - "/path/to/mcp_config.yaml", - "--read-only", - ], - ), - timeout=30, - ), - tool_filter=["search-records"], - ), - ], -) -``` - -For an already-running remote server, swap `StdioConnectionParams` for `StreamableHTTPConnectionParams(url="http://localhost:8765/mcp", headers={"Authorization": "Bearer ..."})`. - -See [examples/redisvl_mcp_search/](examples/redisvl_mcp_search/) for a runnable demo (knowledge-base corpus, hybrid mode, paired with the in-process [examples/redis_search_tools/](examples/redis_search_tools/) example). - -### Semantic cache - -```python -from google.adk import Agent -from redisvl.utils.vectorize import HFTextVectorizer - -from adk_redis import ( - LLMResponseCache, - RedisVLCacheProvider, - RedisVLCacheProviderConfig, - create_llm_cache_callbacks, -) - -provider = RedisVLCacheProvider( - config=RedisVLCacheProviderConfig( - redis_url="redis://localhost:6379", - ttl=3600, - distance_threshold=0.1, - ), - vectorizer=HFTextVectorizer(model="redis/langcache-embed-v2"), -) -llm_cache = LLMResponseCache(provider=provider) -before_cb, after_cb = create_llm_cache_callbacks(llm_cache) - -agent = Agent( - model="gemini-2.5-flash", - name="cached_agent", - before_model_callback=before_cb, - after_model_callback=after_cb, -) -``` - -For a managed alternative that needs no local vectorizer, swap in `LangCacheProvider` / `LangCacheProviderConfig` from `adk_redis`. - ---- - -## Search tools - -Two parallel paths for RAG over a Redis index. Pick by deployment shape. - -| Path | Use when | -|---|---| -| **In-process** | Single ADK process, fast onboarding, Python-side `FilterExpression` composition, per-tool customization. | -| **MCP** (ADK's `McpToolset` against `rvl mcp`) | One Redis index served to multiple agents (Python, JS, Claude Desktop). Server-side `--read-only` / bearer auth. Schema-aware tool descriptions. | - -### In-process tools - -| Tool | Best for | Notes | -|---|---|---| -| `RedisVectorSearchTool` | Semantic similarity | KNN vector search with metadata filters | -| `RedisHybridSearchTool` | Combined search | Vector + BM25; native `FT.HYBRID` on Redis 8.4+, aggregation fallback below | -| `RedisRangeSearchTool` | Threshold retrieval | Distance-bounded vector search. **No MCP equivalent.** | -| `RedisTextSearchTool` | Keyword search | BM25 full-text; no embeddings needed | -| `RedisSQLSearchTool` | SQL-style filters | `SELECT ... WHERE` with `:param` placeholders. Requires `adk-redis[sql]`. **No MCP equivalent.** | - -All five accept any vectorizer supported by RedisVL (OpenAI, HuggingFace, Cohere, Mistral, Voyage AI, custom) and any `FilterExpression` from `redisvl.query.filter`. - -### MCP - -Use ADK's standard `McpToolset` against a running [RedisVL MCP server](https://docs.redisvl.com) (`rvl mcp`). The server is configured per index via YAML and exposes: - -- `search-records`: `vector`, `fulltext`, or `hybrid` (chosen at server start). Tool description includes filter and return-field hints derived from the bound index schema. -- `upsert-records`: write path (suppress with `--read-only`). - -Supports `stdio`, `sse`, and `streamable-http` transports; bearer auth on HTTP. Requires `redisvl[mcp]` and a `rvl mcp` server. See the [Quick Start MCP snippet](#search-over-a-redis-index-mcp) above for the wiring. - -For the full decision matrix and runnable demo, see [docs/user_guide/how_to_guides/search_tools.md](docs/user_guide/how_to_guides/search_tools.md). - ---- - -## Memory backends - -Two ways to ingest, store, and retrieve memory with Agent Memory Server, both interoperable: - -| Approach | What it is | Reach for it when | -|---|---|---| -| **ADK Services** (`RedisLongTermMemoryService`, `RedisWorkingMemorySessionService`) | The `BaseMemoryService` and `BaseSessionService` implementations. ADK calls AMS for you. | You want framework-managed sessions and automatic memory extraction. Most production cases. | -| **REST tools** (`MemoryPromptTool`, `SearchMemoryTool`, `CreateMemoryTool`, `UpdateMemoryTool`, `DeleteMemoryTool`, `GetMemoryTool`) | `BaseTool` subclasses that call AMS REST directly. The LLM decides when to invoke them. | You want the agent to control when memory is read or written. | - -Both approaches use REST and operate on the same underlying memory. If you need MCP access to Agent Memory Server, use ADK's native `McpToolset` with `SseConnectionParams` pointed at the AMS `/sse` endpoint. - ---- - -## Semantic cache - -Two providers, both implementing `BaseCacheProvider`. Pair either with `LLMResponseCache` or `ToolCache` and wire via `create_llm_cache_callbacks` / `create_tool_cache_callbacks`. - -| Provider | Hosted | Vectorizer | Best for | -|---|---|---|---| -| `RedisVLCacheProvider` | Self-hosted Redis | Required (any RedisVL vectorizer) | Full control, your data stays in your Redis | -| `LangCacheProvider` | Managed via [Redis LangCache](https://redis.io/langcache) | Server-side (none needed locally) | Zero-infra cache; no local Redis needed | - -Both honor a configurable `distance_threshold` and per-entry `ttl`. - ---- - -## Requirements - -- Python 3.10, 3.11, 3.12, or 3.13 -- Google ADK 1.0+ (tested through 2.0 GA) -- RedisVL 0.18.2+ when the `search`, `langcache`, or `sql` extra is installed -- Redis 8.4+ (or Redis Cloud with Search) when using search tools or the cache providers -- For session / memory services: a running [Agent Memory Server](https://github.com/redis/agent-memory-server) -- For `RedisSQLSearchTool`: `sql-redis` (installed by `adk-redis[sql]`) -- For the RedisVL MCP server: install `redisvl[mcp]>=0.18.2` and use the `rvl mcp` CLI; connect from ADK with `McpToolset` +→ *More examples: [search tools](https://redis-developer.github.io/adk-redis/user_guide/how_to_guides/search_tools/), [MCP search](https://redis-developer.github.io/adk-redis/concepts/search/), [semantic caching](https://redis-developer.github.io/adk-redis/user_guide/how_to_guides/semantic_cache/)* --- ## Examples -All examples run via `adk web` and ship with a README and `.env.example`. +All examples run via `adk web` and ship with a README and `.env.example`. See the [Examples index](https://redis-developer.github.io/adk-redis/examples/) for descriptions. -| Example | Demonstrates | +| Category | Examples | |---|---| -| [`simple_redis_memory`](examples/simple_redis_memory/) | Two-tier memory + auto-summarization | -| [`travel_agent_memory_hybrid`](examples/travel_agent_memory_hybrid/) | Framework-managed memory: `RedisWorkingMemorySessionService` + `RedisLongTermMemoryService` in a custom FastAPI runner | -| [`travel_agent_memory_tools`](examples/travel_agent_memory_tools/) | LLM-controlled memory: REST `SearchMemoryTool` / `CreateMemoryTool` / etc. in a default ADK runner | -| [`fitness_coach_mcp`](examples/fitness_coach_mcp/) | AMS memory exposed over MCP via ADK's native `McpToolset` | -| [`redis_search_tools`](examples/redis_search_tools/) | In-process RAG with vector + text + range search tools | -| [`redis_sql_search`](examples/redis_sql_search/) | `RedisSQLSearchTool` answering catalog questions via parameterized SQL | -| [`redisvl_mcp_search`](examples/redisvl_mcp_search/) | Same knowledge base as `redis_search_tools/`, served via `rvl mcp` over MCP | -| [`semantic_cache`](examples/semantic_cache/) | Self-hosted semantic cache via `RedisVLCacheProvider` | -| [`langcache_cache`](examples/langcache_cache/) | Managed semantic cache via `LangCacheProvider` | - -The two travel-agent examples use the same Agent Memory Server backend; the difference is whether the agent talks to AMS through framework services (`hybrid`) or LLM-driven tool calls (`tools`). +| **Memory and sessions** | [`simple_redis_memory`](examples/simple_redis_memory/) · [`travel_agent_memory_hybrid`](examples/travel_agent_memory_hybrid/) · [`travel_agent_memory_tools`](examples/travel_agent_memory_tools/) · [`fitness_coach_mcp`](examples/fitness_coach_mcp/) | +| **Search** | [`redis_search_tools`](examples/redis_search_tools/) · [`redis_sql_search`](examples/redis_sql_search/) · [`redisvl_mcp_search`](examples/redisvl_mcp_search/) | +| **Caching** | [`semantic_cache`](examples/semantic_cache/) · [`langcache_cache`](examples/langcache_cache/) | --- ## Development -This project follows the [Google Python Style Guide](https://google.github.io/styleguide/pyguide.html), matching the [ADK-Python core](https://github.com/google/adk-python) project conventions. - -### Setup - ```bash git clone https://github.com/redis-developer/adk-redis.git cd adk-redis make dev # install with all extras + dev deps -make check # format-check + lint + type-check + test -``` - -### Targets - -```bash -make format # apply pyink + isort -make lint # ruff check -make type-check # mypy -make test # all tests (unit + integration) -make test-unit # unit tests only (no Redis required) -make test-integration # integration suite (needs Redis 8.4+ at REDIS_URL) -make redis-up # start a redis:8.4 container on :6399 for integration -make redis-down # stop and remove that container -make test-cov # coverage report +make check # format, lint, type-check, and test ``` -See [CONTRIBUTING.md](CONTRIBUTING.md) for testing, style, and PR conventions. +See [CONTRIBUTING.md](CONTRIBUTING.md) for the full guide. --- ## Contributing -Open an [issue](https://github.com/redis-developer/adk-redis/issues) for bugs and feature requests, or submit a PR following [CONTRIBUTING.md](CONTRIBUTING.md). Documentation and example contributions are equally welcome. - ---- +Open an [issue](https://github.com/redis-developer/adk-redis/issues) or submit a PR following [CONTRIBUTING.md](CONTRIBUTING.md). ## License @@ -385,14 +137,8 @@ Apache 2.0. See [LICENSE](LICENSE). --- -## Helpful links - -- [PyPI](https://pypi.org/project/adk-redis/): install with `pip install adk-redis` -- [Redis setup](docs/user_guide/how_to_guides/redis_setup.md): local, Docker, and Redis Cloud -- [Agent Memory Server setup](docs/user_guide/how_to_guides/memory_server_setup.md): full AMS configuration -- [Integration walkthrough](docs/user_guide/01_integration.md): end-to-end wiring -- [Search tools guide](docs/user_guide/how_to_guides/search_tools.md): in-process vs MCP, decision matrix -- [Google ADK](https://github.com/google/adk-python): agent framework -- [Agent Memory Server](https://github.com/redis/agent-memory-server): memory backend -- [RedisVL](https://docs.redisvl.com/): Redis Vector Library -- [Redis LangCache](https://redis.io/langcache): managed semantic cache +## Links + +- **[Documentation](https://redis-developer.github.io/adk-redis/)**: concepts, how-to guides, API reference +- [Google ADK](https://github.com/google/adk-python) · [Agent Memory Server](https://github.com/redis/agent-memory-server) · [RedisVL](https://docs.redisvl.com) · [Redis LangCache](https://redis.io/langcache) +- [ADK + Redis on redis.io](https://redis.io/docs/latest/integrate/google-adk/) diff --git a/docs/user_guide/01_integration.md b/docs/user_guide/01_integration.md index 775cfdf..7e6c25b 100644 --- a/docs/user_guide/01_integration.md +++ b/docs/user_guide/01_integration.md @@ -4,8 +4,7 @@ Get an ADK agent running with Redis-backed sessions and long-term memory in three steps. For the concepts behind each feature, see the [Concepts](../concepts/index.md) section. -> **Full guide on redis.io:** -> [redis.io/docs/latest/integrate/google-adk/](https://redis.io/docs/latest/integrate/google-adk/) +> **See also:** [ADK + Redis on redis.io](https://redis.io/docs/latest/integrate/google-adk/) for additional coverage. ## 1. Start infrastructure diff --git a/docs/user_guide/how_to_guides/memory_server_setup.md b/docs/user_guide/how_to_guides/memory_server_setup.md index 0cd2349..bcadae1 100644 --- a/docs/user_guide/how_to_guides/memory_server_setup.md +++ b/docs/user_guide/how_to_guides/memory_server_setup.md @@ -1,6 +1,6 @@ # Agent Memory Server Setup Guide -> **Canonical docs:** See [redis.io/docs/latest/integrate/google-adk/](https://redis.io/docs/latest/integrate/google-adk/) for the full integration guide. This file is a quick-reference for contributors. +> **See also:** [ADK + Redis on redis.io](https://redis.io/docs/latest/integrate/google-adk/) for additional coverage. Complete setup instructions for Redis Agent Memory Server. diff --git a/docs/user_guide/how_to_guides/redis_setup.md b/docs/user_guide/how_to_guides/redis_setup.md index 2b349e5..27d1473 100644 --- a/docs/user_guide/how_to_guides/redis_setup.md +++ b/docs/user_guide/how_to_guides/redis_setup.md @@ -1,6 +1,6 @@ # Redis Setup Guide -> **Canonical docs:** See [redis.io/docs/latest/integrate/google-adk/](https://redis.io/docs/latest/integrate/google-adk/) for the full integration guide. This file is a quick-reference for contributors. +> **See also:** [ADK + Redis on redis.io](https://redis.io/docs/latest/integrate/google-adk/) for additional coverage. 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-  self._provider = provider
-  self._config = config or LLMResponseCacheConfig()
-  # Track pending prompts by session ID for after_model_callback
-  self._pending_prompts: dict[str, str] = {}
-
-
- - - -
- - - - - - - - - - -
- - -

- before_model_callback - - - - async - - -

-
before_model_callback(callback_context: CallbackContext, llm_request: LlmRequest) -> Optional[LlmResponse]
-
- -
- -

Check cache before making LLM call.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- callback_context - - CallbackContext - -
-

The callback context with session info.

-
- 		- required -
- llm_request - - LlmRequest - -
-

The LLM request being made.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Optional[LlmResponse] - -
-

LlmResponse if cache hit, None to proceed with LLM call.

-
-
- - -
- Source code in src/adk_redis/cache/llm_cache.py - 
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async def before_model_callback(
-    self,
-    callback_context: CallbackContext,
-    llm_request: LlmRequest,
-) -> Optional[LlmResponse]:
-  """Check cache before making LLM call.
-
-  Args:
-      callback_context: The callback context with session info.
-      llm_request: The LLM request being made.
-
-  Returns:
-      LlmResponse if cache hit, None to proceed with LLM call.
-  """
-  if self._config.first_message_only and not self._is_first_message(
-      callback_context
-  ):
-    logger.debug("Not first message, skipping cache check")
-    return None
-
-  prompt = self._extract_prompt(llm_request)
-  if not prompt:
-    logger.debug("No prompt found in request")
-    return None
-
-  cache_key = self._build_cache_key(prompt, callback_context)
-  cache_entry = await self._provider.check(cache_key)
-
-  if cache_entry:
-    logger.info("Cache hit for prompt: %s", prompt[:50])
-    return LlmResponse(
-        content=types.Content(
-            role="model",
-            parts=[types.Part(text=cache_entry.response)],
-        )
-    )
-
-  logger.debug("Cache miss for prompt: %s", prompt[:50])
-  # Store prompt for after_model_callback
-  session_key = self._get_session_key(callback_context)
-  self._pending_prompts[session_key] = cache_key
-  return None
-
-
-
- -
- -
- - -

- after_model_callback - - - - async - - -

-
after_model_callback(callback_context: CallbackContext, llm_response: LlmResponse) -> Optional[LlmResponse]
-
- -
- -

Store response in cache after LLM call.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- callback_context - - CallbackContext - -
-

The callback context with session info.

-
- 		- required -
- llm_response - - LlmResponse - -
-

The LLM response to cache.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Optional[LlmResponse] - -
-

None to pass through the original response.

-
-
- - -
- Source code in src/adk_redis/cache/llm_cache.py - 
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async def after_model_callback(
-    self,
-    callback_context: CallbackContext,
-    llm_response: LlmResponse,
-) -> Optional[LlmResponse]:
-  """Store response in cache after LLM call.
-
-  Args:
-      callback_context: The callback context with session info.
-      llm_response: The LLM response to cache.
-
-  Returns:
-      None to pass through the original response.
-  """
-  session_key = self._get_session_key(callback_context)
-  cache_key = self._pending_prompts.pop(session_key, None)
-
-  if not cache_key:
-    logger.debug("No pending prompt for session, skipping cache store")
-    return None
-
-  # Don't cache error responses
-  if llm_response.error_message:
-    logger.debug("Response has error, skipping cache store")
-    return None
-
-  # Don't cache function call responses
-  if llm_response.content and llm_response.content.parts:
-    for part in llm_response.content.parts:
-      if hasattr(part, "function_call") and part.function_call:
-        logger.debug("Response is function call, skipping cache store")
-        return None
-
-  response_text = self._extract_response_text(llm_response)
-  if not response_text:
-    logger.debug("No text in response, skipping cache store")
-    return None
-
-  await self._provider.store(cache_key, response_text)
-  logger.info("Cached response for prompt: %s", cache_key[:50])
-  return None
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- LLMResponseCacheConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for LLM response caching.

- - -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
first_message_only - bool - -
-

Only cache first message in session.

-
-
include_app_name - bool - -
-

Include app name in cache key.

-
-
include_user_id - bool - -
-

Include user ID in cache key.

-
-
include_session_id - bool - -
-

Include session ID in cache key.

-
-
- - - - - - - - - - - -
- - - - - - - - - - - - -
- -
- -
- -
- - - -

- BaseCacheProvider - - -

- - -
-

- Bases: ABC

- - - -

Abstract base class for cache providers.

- - - - - - - - - - - -
- - - - - - - - - - -
- - -

- check - - - - abstractmethod - async - - -

-
check(prompt: str, **kwargs: Any) -> Optional[CacheEntry]
-
- -
- -

Check if a semantically similar prompt exists in the cache.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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@abstractmethod
-async def check(self, prompt: str, **kwargs: Any) -> Optional[CacheEntry]:
-  """Check if a semantically similar prompt exists in the cache."""
-  pass
-
-
-
- -
- -
- - -

- store - - - - abstractmethod - async - - -

-
store(prompt: str, response: str, metadata: Optional[dict[str, Any]] = None, **kwargs: Any) -> None
-
- -
- -

Store a prompt-response pair in the cache.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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@abstractmethod
-async def store(
-    self,
-    prompt: str,
-    response: str,
-    metadata: Optional[dict[str, Any]] = None,
-    **kwargs: Any,
-) -> None:
-  """Store a prompt-response pair in the cache."""
-  pass
-
-
-
- -
- -
- - -

- clear - - - - abstractmethod - async - - -

-
clear(**kwargs: Any) -> None
-
- -
- -

Clear all entries from the cache.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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@abstractmethod
-async def clear(self, **kwargs: Any) -> None:
-  """Clear all entries from the cache."""
-  pass
-
-
-
- -
- -
- - -

- close - - - - abstractmethod - async - - -

-
close() -> None
-
- -
- -

Close the cache provider and release resources.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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@abstractmethod
-async def close(self) -> None:
-  """Close the cache provider and release resources."""
-  pass
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- CacheEntry - - - - dataclass - - -

-
CacheEntry(prompt: str, response: str, distance: Optional[float] = None, metadata: Optional[dict[str, Any]] = None)
-
- -
- - - -

Represents a cached entry.

- - - - - - - - - - - -
- - - - - - - - - - - - -
- -
- -
- -
- - - -

- LangCacheProvider - - -

-
LangCacheProvider(config: LangCacheProviderConfig)
-
- -
-

- Bases: BaseCacheProvider

- - - -

Cache provider using Redis LangCache (managed semantic cache service).

-

LangCache is a managed semantic caching service that handles embedding -generation, storage, and retrieval. Unlike RedisVLCacheProvider, it does -not require a local vectorizer — embeddings are handled server-side.

-

Requires redisvl>=0.11.1 with LangCache support.

- -

Initialize the LangCache cache provider.

- - -

Parameters:

- - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- config - - LangCacheProviderConfig - -
-

Configuration for the LangCache provider.

-
- 		- required -
- - -

Raises:

- - - - - - - - - - - - - -
TypeDescription
- ImportError - -
-

If redisvl>=0.11.1 is not installed.

-
-
- - - - - - - - -
- Source code in src/adk_redis/cache/_provider.py - 
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def __init__(self, config: LangCacheProviderConfig):
-  """Initialize the LangCache cache provider.
-
-  Args:
-    config: Configuration for the LangCache provider.
-
-  Raises:
-    ImportError: If redisvl>=0.11.1 is not installed.
-  """
-  try:
-    from redisvl.extensions.cache.llm import LangCacheSemanticCache
-  except ImportError as e:
-    raise ImportError(
-        "redisvl>=0.11.1 with LangCache support is required for "
-        "LangCacheProvider. Install it with: "
-        "pip install 'adk-redis[langcache]'"
-    ) from e
-
-  self._config = config
-  self._cache = LangCacheSemanticCache(
-      name=config.name,
-      server_url=config.server_url,
-      cache_id=config.cache_id,
-      api_key=config.api_key.get_secret_value(),
-      ttl=config.ttl,
-      use_exact_search=config.use_exact_search,
-      use_semantic_search=config.use_semantic_search,
-      distance_scale="redis",
-  )
-
-
- - - -
- - - - - - - - - - -
- - -

- check - - - - async - - -

-
check(prompt: str, **kwargs: Any) -> Optional[CacheEntry]
-
- -
- -

Check for a semantically similar prompt in LangCache.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- prompt - - str - -
-

The prompt to check.

-
- 		- required -
- **kwargs - - Any - -
-

Additional keyword arguments (e.g., distance_threshold).

-
- 		- {} -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Optional[CacheEntry] - -
-

A CacheEntry if a cache hit is found, None otherwise.

-
-
- - -
- Source code in src/adk_redis/cache/_provider.py - 
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async def check(self, prompt: str, **kwargs: Any) -> Optional[CacheEntry]:
-  """Check for a semantically similar prompt in LangCache.
-
-  Args:
-    prompt: The prompt to check.
-    **kwargs: Additional keyword arguments (e.g., distance_threshold).
-
-  Returns:
-    A CacheEntry if a cache hit is found, None otherwise.
-  """
-  distance_threshold = kwargs.get(
-      "distance_threshold", self._config.distance_threshold
-  )
-  acheck_kwargs: dict[str, Any] = {"prompt": prompt}
-  if distance_threshold is not None:
-    acheck_kwargs["distance_threshold"] = distance_threshold
-  result = await self._cache.acheck(**acheck_kwargs)
-  if result:
-    logger.debug("LangCache hit for prompt: %s", prompt[:50])
-    return CacheEntry(
-        prompt=prompt,
-        response=result[0]["response"],
-        distance=result[0].get("vector_distance"),
-        metadata=result[0].get("metadata"),
-    )
-  logger.debug("LangCache miss for prompt: %s", prompt[:50])
-  return None
-
-
-
- -
- -
- - -

- store - - - - async - - -

-
store(prompt: str, response: str, metadata: Optional[dict[str, Any]] = None, **kwargs: Any) -> None
-
- -
- -

Store a prompt-response pair in LangCache.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- prompt - - str - -
-

The prompt text.

-
- 		- required -
- response - - str - -
-

The response text.

-
- 		- required -
- metadata - - Optional[dict[str, Any]] - -
-

Optional metadata to store alongside the entry.

-
- 		- None -
- **kwargs - - Any - -
-

Additional keyword arguments (e.g., ttl).

-
- 		- {} -
- - -
- Source code in src/adk_redis/cache/_provider.py - 
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async def store(
-    self,
-    prompt: str,
-    response: str,
-    metadata: Optional[dict[str, Any]] = None,
-    **kwargs: Any,
-) -> None:
-  """Store a prompt-response pair in LangCache.
-
-  Args:
-    prompt: The prompt text.
-    response: The response text.
-    metadata: Optional metadata to store alongside the entry.
-    **kwargs: Additional keyword arguments (e.g., ttl).
-  """
-  astore_kwargs: dict[str, Any] = {
-      "prompt": prompt,
-      "response": response,
-      "metadata": metadata,
-  }
-  # Only override TTL when an explicit, non-None value is provided.
-  ttl = kwargs.get("ttl")
-  if ttl is not None:
-    astore_kwargs["ttl"] = ttl
-  await self._cache.astore(**astore_kwargs)
-  logger.debug("LangCache stored response for prompt: %s", prompt[:50])
-
-
-
- -
- -
- - -

- clear - - - - async - - -

-
clear(**kwargs: Any) -> None
-
- -
- -

Clear all entries from the LangCache.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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async def clear(self, **kwargs: Any) -> None:
-  """Clear all entries from the LangCache."""
-  await self._cache.aclear()
-  logger.info("LangCache cleared")
-
-
-
- -
- -
- - -

- close - - - - async - - -

-
close() -> None
-
- -
- -

Close the LangCache provider and release resources.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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async def close(self) -> None:
-  """Close the LangCache provider and release resources."""
-  await self._cache.adisconnect()
-  logger.debug("LangCache provider closed")
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- LangCacheProviderConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for LangCache (managed semantic cache) provider.

-

LangCache is a managed semantic caching service provided by Redis. -It requires a cache_id and api_key from the LangCache service.

- - - - - - - - - - - -
- - - - - - - - - - - - -
- -
- -
- -
- - - -

- RedisVLCacheProvider - - -

-
RedisVLCacheProvider(config: RedisVLCacheProviderConfig, vectorizer: Any)
-
- -
-

- Bases: BaseCacheProvider

- - - -

Cache provider using RedisVL's SemanticCache.

- -

Initialize the RedisVL cache provider.

- - - - - - - - -
- Source code in src/adk_redis/cache/_provider.py - 
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def __init__(self, config: RedisVLCacheProviderConfig, vectorizer: Any):
-  """Initialize the RedisVL cache provider."""
-  try:
-    from redisvl.extensions.cache.llm import SemanticCache
-  except ImportError as e:
-    raise ImportError(
-        "redisvl is required for RedisVLCacheProvider. "
-        "Install it with: pip install redisvl>=0.18.2"
-    ) from e
-
-  self._config = config
-  self._vectorizer = vectorizer
-  self._cache = SemanticCache(
-      name=config.name,
-      redis_url=config.redis_url,
-      ttl=config.ttl,
-      distance_threshold=config.distance_threshold,
-      vectorizer=vectorizer,
-      overwrite=True,  # Overwrite existing index if schema doesn't match
-  )
-
-
- - - -
- - - - - - - - - - -
- - -

- check - - - - async - - -

-
check(prompt: str, **kwargs: Any) -> Optional[CacheEntry]
-
- -
- -

Check for a semantically similar prompt in the cache.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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async def check(self, prompt: str, **kwargs: Any) -> Optional[CacheEntry]:
-  """Check for a semantically similar prompt in the cache."""
-  result = await asyncio.to_thread(self._cache.check, prompt=prompt)
-  if result:
-    logger.debug("Cache hit for prompt: %s", prompt[:50])
-    return CacheEntry(
-        prompt=prompt,
-        response=result[0]["response"],
-        distance=result[0].get("vector_distance"),
-    )
-  logger.debug("Cache miss for prompt: %s", prompt[:50])
-  return None
-
-
-
- -
- -
- - -

- store - - - - async - - -

-
store(prompt: str, response: str, metadata: Optional[dict[str, Any]] = None, **kwargs: Any) -> None
-
- -
- -

Store a prompt-response pair in the cache.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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async def store(
-    self,
-    prompt: str,
-    response: str,
-    metadata: Optional[dict[str, Any]] = None,
-    **kwargs: Any,
-) -> None:
-  """Store a prompt-response pair in the cache."""
-  await asyncio.to_thread(self._cache.store, prompt=prompt, response=response)
-  logger.debug("Stored response for prompt: %s", prompt[:50])
-
-
-
- -
- -
- - -

- clear - - - - async - - -

-
clear(**kwargs: Any) -> None
-
- -
- -

Clear all entries from the cache.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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-176
async def clear(self, **kwargs: Any) -> None:
-  """Clear all entries from the cache."""
-  await asyncio.to_thread(self._cache.clear)
-  logger.info("Cache cleared")
-
-
-
- -
- -
- - -

- close - - - - async - - -

-
close() -> None
-
- -
- -

Close the cache provider and release resources.

- - -
- Source code in src/adk_redis/cache/_provider.py - 
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async def close(self) -> None:
-  """Close the cache provider and release resources."""
-  if hasattr(self._cache, "_index") and hasattr(self._cache._index, "client"):
-    await asyncio.to_thread(self._cache._index.client.close)
-  logger.debug("RedisVL cache provider closed")
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisVLCacheProviderConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for RedisVL cache provider.

- - - - - - - - - - - -
- - - - - - - - - - - - -
- -
- -
- -
- - - -

- ToolCache - - -

-
ToolCache(provider: BaseCacheProvider, config: Optional[ToolCacheConfig] = None)
-
- -
- - - -

Cache service for tool call results.

-

This service caches tool results using semantic similarity matching -on the tool name and arguments. It can be configured to only cache -specific tools.

- -

Initialize the tool cache.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- provider - - BaseCacheProvider - -
-

The cache provider to use for storage.

-
- 		- required -
- config - - Optional[ToolCacheConfig] - -
-

Configuration for caching behavior.

-
- 		- None -
- - - - - - - - -
- Source code in src/adk_redis/cache/tool_cache.py - 
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def __init__(
-    self,
-    provider: BaseCacheProvider,
-    config: Optional[ToolCacheConfig] = None,
-):
-  """Initialize the tool cache.
-
-  Args:
-      provider: The cache provider to use for storage.
-      config: Configuration for caching behavior.
-  """
-  self._provider = provider
-  self._config = config or ToolCacheConfig()
-  # Track pending tool calls by session key for after_tool_callback
-  self._pending_calls: dict[str, str] = {}
-
-
- - - -
- - - - - - - - - - -
- - -

- before_tool_callback - - - - async - - -

-
before_tool_callback(tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext) -> Optional[Dict[str, Any]]
-
- -
- -

Check cache before executing tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- tool - - BaseTool - -
-

The tool being called.

-
- 		- required -
- args - - Dict[str, Any] - -
-

The arguments for the tool call.

-
- 		- required -
- tool_context - - ToolContext - -
-

The tool context with session info.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Optional[Dict[str, Any]] - -
-

Dict if cache hit (skips tool execution), None to proceed.

-
-
- - -
- Source code in src/adk_redis/cache/tool_cache.py - 
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async def before_tool_callback(
-    self,
-    tool: BaseTool,
-    args: Dict[str, Any],
-    tool_context: ToolContext,
-) -> Optional[Dict[str, Any]]:
-  """Check cache before executing tool.
-
-  Args:
-      tool: The tool being called.
-      args: The arguments for the tool call.
-      tool_context: The tool context with session info.
-
-  Returns:
-      Dict if cache hit (skips tool execution), None to proceed.
-  """
-  tool_name = tool.name
-  if not self._should_cache_tool(tool_name):
-    logger.debug("Tool %s not in cache list, skipping", tool_name)
-    return None
-
-  cache_key = self._build_cache_key(tool_name, args, tool_context)
-  cache_entry = await self._provider.check(cache_key)
-
-  if cache_entry:
-    logger.info("Cache hit for tool: %s", tool_name)
-    try:
-      return json.loads(cache_entry.response)  # type: ignore[no-any-return]
-    except (json.JSONDecodeError, TypeError):
-      return {"result": cache_entry.response}
-
-  logger.debug("Cache miss for tool: %s", tool_name)
-  # Store cache key for after_tool_callback
-  session_key = self._get_session_key(tool_context)
-  self._pending_calls[session_key] = cache_key
-  return None
-
-
-
- -
- -
- - -

- after_tool_callback - - - - async - - -

-
after_tool_callback(tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext, tool_response: Dict[str, Any]) -> Optional[Dict[str, Any]]
-
- -
- -

Store tool result in cache after execution.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- tool - - BaseTool - -
-

The tool that was called.

-
- 		- required -
- args - - Dict[str, Any] - -
-

The arguments used for the tool call.

-
- 		- required -
- tool_context - - ToolContext - -
-

The tool context with session info.

-
- 		- required -
- tool_response - - Dict[str, Any] - -
-

The result from the tool execution.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Optional[Dict[str, Any]] - -
-

None to pass through the original response.

-
-
- - -
- Source code in src/adk_redis/cache/tool_cache.py - 
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async def after_tool_callback(
-    self,
-    tool: BaseTool,
-    args: Dict[str, Any],
-    tool_context: ToolContext,
-    tool_response: Dict[str, Any],
-) -> Optional[Dict[str, Any]]:
-  """Store tool result in cache after execution.
-
-  Args:
-      tool: The tool that was called.
-      args: The arguments used for the tool call.
-      tool_context: The tool context with session info.
-      tool_response: The result from the tool execution.
-
-  Returns:
-      None to pass through the original response.
-  """
-  session_key = self._get_session_key(tool_context)
-  cache_key = self._pending_calls.pop(session_key, None)
-
-  if not cache_key:
-    logger.debug("No pending cache key for tool, skipping store")
-    return None
-
-  # Serialize the tool response
-  try:
-    response_str = json.dumps(tool_response, default=str)
-  except (TypeError, ValueError):
-    response_str = str(tool_response)
-
-  await self._provider.store(cache_key, response_str)
-  logger.info("Cached result for tool: %s", tool.name)
-  return None
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- ToolCacheConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for tool result caching.

- - -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
tool_names - Optional[Set[str]] - -
-

Set of tool names to cache. None means cache all tools.

-
-
include_app_name - bool - -
-

Include app name in cache key.

-
-
include_user_id - bool - -
-

Include user ID in cache key.

-
-
include_session_id - bool - -
-

Include session ID in cache key.

-
-
- - - - - - - - - - - -
- - - - - - - - - - - - -
- -
- -
- - -
- - -

- create_llm_cache_callbacks - - -

-
create_llm_cache_callbacks(cache: LLMResponseCache) -> Tuple[BeforeModelCallback, AfterModelCallback]
-
- -
- -

Create callback functions for LLM response caching.

-

This factory function wraps the LLMResponseCache methods into standalone -callback functions compatible with ADK's Agent constructor.

- - -

Parameters:

- - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- cache - - LLMResponseCache - -
-

The LLMResponseCache instance to use.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Tuple[BeforeModelCallback, AfterModelCallback] - -
-

A tuple of (before_model_callback, after_model_callback) functions.

-
-
- - -
- Example - 
llm_cache = LLMResponseCache(provider=provider)
-before_cb, after_cb = create_llm_cache_callbacks(llm_cache)
-
-agent = Agent(
-    name="my_agent",
-    before_model_callback=before_cb,
-    after_model_callback=after_cb,
-)
-
-
- -
- Source code in src/adk_redis/cache/callbacks.py - 
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def create_llm_cache_callbacks(
-    cache: LLMResponseCache,
-) -> Tuple[BeforeModelCallback, AfterModelCallback]:
-  """Create callback functions for LLM response caching.
-
-  This factory function wraps the LLMResponseCache methods into standalone
-  callback functions compatible with ADK's Agent constructor.
-
-  Args:
-      cache: The LLMResponseCache instance to use.
-
-  Returns:
-      A tuple of (before_model_callback, after_model_callback) functions.
-
-  Example:
-      ```python
-      llm_cache = LLMResponseCache(provider=provider)
-      before_cb, after_cb = create_llm_cache_callbacks(llm_cache)
-
-      agent = Agent(
-          name="my_agent",
-          before_model_callback=before_cb,
-          after_model_callback=after_cb,
-      )
-      ```
-  """
-
-  async def before_model_callback(
-      callback_context: CallbackContext,
-      llm_request: LlmRequest,
-  ) -> Optional[LlmResponse]:
-    return await cache.before_model_callback(callback_context, llm_request)  # type: ignore[return-value,no-any-return]
-
-  async def after_model_callback(
-      callback_context: CallbackContext,
-      llm_response: LlmResponse,
-  ) -> Optional[LlmResponse]:
-    return await cache.after_model_callback(callback_context, llm_response)  # type: ignore[return-value,no-any-return]
-
-  return before_model_callback, after_model_callback  # type: ignore[return-value]
-
-
-
- -
- -
- - -

- create_tool_cache_callbacks - - -

-
create_tool_cache_callbacks(cache: ToolCache) -> Tuple[BeforeToolCallback, AfterToolCallback]
-
- -
- -

Create callback functions for tool result caching.

-

This factory function wraps the ToolCache methods into standalone -callback functions compatible with ADK's Agent constructor.

- - -

Parameters:

- - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- cache - - ToolCache - -
-

The ToolCache instance to use.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Tuple[BeforeToolCallback, AfterToolCallback] - -
-

A tuple of (before_tool_callback, after_tool_callback) functions.

-
-
- - -
- Example - 
tool_cache = ToolCache(provider=provider)
-before_cb, after_cb = create_tool_cache_callbacks(tool_cache)
-
-agent = Agent(
-    name="my_agent",
-    before_tool_callback=before_cb,
-    after_tool_callback=after_cb,
-)
-
-
- -
- Source code in src/adk_redis/cache/callbacks.py - 
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def create_tool_cache_callbacks(
-    cache: ToolCache,
-) -> Tuple[BeforeToolCallback, AfterToolCallback]:
-  """Create callback functions for tool result caching.
-
-  This factory function wraps the ToolCache methods into standalone
-  callback functions compatible with ADK's Agent constructor.
-
-  Args:
-      cache: The ToolCache instance to use.
-
-  Returns:
-      A tuple of (before_tool_callback, after_tool_callback) functions.
-
-  Example:
-      ```python
-      tool_cache = ToolCache(provider=provider)
-      before_cb, after_cb = create_tool_cache_callbacks(tool_cache)
-
-      agent = Agent(
-          name="my_agent",
-          before_tool_callback=before_cb,
-          after_tool_callback=after_cb,
-      )
-      ```
-  """
-
-  async def before_tool_callback(
-      tool: BaseTool,
-      args: Dict[str, Any],
-      tool_context: ToolContext,
-  ) -> Optional[Dict[str, Any]]:
-    return await cache.before_tool_callback(tool, args, tool_context)  # type: ignore[return-value]
-
-  async def after_tool_callback(
-      tool: BaseTool,
-      args: Dict[str, Any],
-      tool_context: ToolContext,
-      tool_response: Dict[str, Any],
-  ) -> Optional[Dict[str, Any]]:
-    return await cache.after_tool_callback(  # type: ignore[return-value]
-        tool, args, tool_context, tool_response
-    )
-
-  return before_tool_callback, after_tool_callback  # type: ignore[return-value]
-
-
-
- -
- - - -
- -
- -
- - - - - - - - - - - - - - - - -
-
- - - - - -
- - - -
- - - -
-
-
-
- -
- - - - - - - - - - - - - \ No newline at end of file diff --git a/site/api/python/cache/index.md b/site/api/python/cache/index.md deleted file mode 100644 index 7ac3343..0000000 --- a/site/api/python/cache/index.md +++ /dev/null @@ -1,957 +0,0 @@ -# cache - -## cache - -Semantic caching for ADK agents using Redis. - -### LLMResponseCache - -```python -LLMResponseCache(provider: BaseCacheProvider, config: Optional[LLMResponseCacheConfig] = None) -``` - -Cache service for LLM responses. - -This service caches LLM responses using semantic similarity matching. It can be configured to only cache first messages in a session to reduce API costs for common initial queries. - -Initialize the LLM response cache. - -Parameters: - -| Name | Type | Description | Default | -| ---------- | ---------------------------------- | -------------------------------------- | ---------- | -| `provider` | `BaseCacheProvider` | The cache provider to use for storage. | *required* | -| `config` | `Optional[LLMResponseCacheConfig]` | Configuration for caching behavior. | `None` | - -Source code in `src/adk_redis/cache/llm_cache.py` - -```python -def __init__( - self, - provider: BaseCacheProvider, - config: Optional[LLMResponseCacheConfig] = None, -): - """Initialize the LLM response cache. - - Args: - provider: The cache provider to use for storage. - config: Configuration for caching behavior. - """ - self._provider = provider - self._config = config or LLMResponseCacheConfig() - # Track pending prompts by session ID for after_model_callback - self._pending_prompts: dict[str, str] = {} -``` - -#### before_model_callback - -```python -before_model_callback(callback_context: CallbackContext, llm_request: LlmRequest) -> Optional[LlmResponse] -``` - -Check cache before making LLM call. - -Parameters: - -| Name | Type | Description | Default | -| ------------------ | ----------------- | --------------------------------------- | ---------- | -| `callback_context` | `CallbackContext` | The callback context with session info. | *required* | -| `llm_request` | `LlmRequest` | The LLM request being made. | *required* | - -Returns: - -| Type | Description | -| ----------------------- | -------------------------------------------------------- | -| `Optional[LlmResponse]` | LlmResponse if cache hit, None to proceed with LLM call. | - -Source code in `src/adk_redis/cache/llm_cache.py` - -```python -async def before_model_callback( - self, - callback_context: CallbackContext, - llm_request: LlmRequest, -) -> Optional[LlmResponse]: - """Check cache before making LLM call. - - Args: - callback_context: The callback context with session info. - llm_request: The LLM request being made. - - Returns: - LlmResponse if cache hit, None to proceed with LLM call. - """ - if self._config.first_message_only and not self._is_first_message( - callback_context - ): - logger.debug("Not first message, skipping cache check") - return None - - prompt = self._extract_prompt(llm_request) - if not prompt: - logger.debug("No prompt found in request") - return None - - cache_key = self._build_cache_key(prompt, callback_context) - cache_entry = await self._provider.check(cache_key) - - if cache_entry: - logger.info("Cache hit for prompt: %s", prompt[:50]) - return LlmResponse( - content=types.Content( - role="model", - parts=[types.Part(text=cache_entry.response)], - ) - ) - - logger.debug("Cache miss for prompt: %s", prompt[:50]) - # Store prompt for after_model_callback - session_key = self._get_session_key(callback_context) - self._pending_prompts[session_key] = cache_key - return None -``` - -#### after_model_callback - -```python -after_model_callback(callback_context: CallbackContext, llm_response: LlmResponse) -> Optional[LlmResponse] -``` - -Store response in cache after LLM call. - -Parameters: - -| Name | Type | Description | Default | -| ------------------ | ----------------- | --------------------------------------- | ---------- | -| `callback_context` | `CallbackContext` | The callback context with session info. | *required* | -| `llm_response` | `LlmResponse` | The LLM response to cache. | *required* | - -Returns: - -| Type | Description | -| ----------------------- | ------------------------------------------- | -| `Optional[LlmResponse]` | None to pass through the original response. | - -Source code in `src/adk_redis/cache/llm_cache.py` - -```python -async def after_model_callback( - self, - callback_context: CallbackContext, - llm_response: LlmResponse, -) -> Optional[LlmResponse]: - """Store response in cache after LLM call. - - Args: - callback_context: The callback context with session info. - llm_response: The LLM response to cache. - - Returns: - None to pass through the original response. - """ - session_key = self._get_session_key(callback_context) - cache_key = self._pending_prompts.pop(session_key, None) - - if not cache_key: - logger.debug("No pending prompt for session, skipping cache store") - return None - - # Don't cache error responses - if llm_response.error_message: - logger.debug("Response has error, skipping cache store") - return None - - # Don't cache function call responses - if llm_response.content and llm_response.content.parts: - for part in llm_response.content.parts: - if hasattr(part, "function_call") and part.function_call: - logger.debug("Response is function call, skipping cache store") - return None - - response_text = self._extract_response_text(llm_response) - if not response_text: - logger.debug("No text in response, skipping cache store") - return None - - await self._provider.store(cache_key, response_text) - logger.info("Cached response for prompt: %s", cache_key[:50]) - return None -``` - -### LLMResponseCacheConfig - -Bases: `BaseModel` - -Configuration for LLM response caching. - -Attributes: - -| Name | Type | Description | -| -------------------- | ------ | ------------------------------------ | -| `first_message_only` | `bool` | Only cache first message in session. | -| `include_app_name` | `bool` | Include app name in cache key. | -| `include_user_id` | `bool` | Include user ID in cache key. | -| `include_session_id` | `bool` | Include session ID in cache key. | - -### BaseCacheProvider - -Bases: `ABC` - -Abstract base class for cache providers. - -#### check - -```python -check(prompt: str, **kwargs: Any) -> Optional[CacheEntry] -``` - -Check if a semantically similar prompt exists in the cache. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -@abstractmethod -async def check(self, prompt: str, **kwargs: Any) -> Optional[CacheEntry]: - """Check if a semantically similar prompt exists in the cache.""" - pass -``` - -#### store - -```python -store(prompt: str, response: str, metadata: Optional[dict[str, Any]] = None, **kwargs: Any) -> None -``` - -Store a prompt-response pair in the cache. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -@abstractmethod -async def store( - self, - prompt: str, - response: str, - metadata: Optional[dict[str, Any]] = None, - **kwargs: Any, -) -> None: - """Store a prompt-response pair in the cache.""" - pass -``` - -#### clear - -```python -clear(**kwargs: Any) -> None -``` - -Clear all entries from the cache. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -@abstractmethod -async def clear(self, **kwargs: Any) -> None: - """Clear all entries from the cache.""" - pass -``` - -#### close - -```python -close() -> None -``` - -Close the cache provider and release resources. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -@abstractmethod -async def close(self) -> None: - """Close the cache provider and release resources.""" - pass -``` - -### CacheEntry - -```python -CacheEntry(prompt: str, response: str, distance: Optional[float] = None, metadata: Optional[dict[str, Any]] = None) -``` - -Represents a cached entry. - -### LangCacheProvider - -```python -LangCacheProvider(config: LangCacheProviderConfig) -``` - -Bases: `BaseCacheProvider` - -Cache provider using Redis LangCache (managed semantic cache service). - -LangCache is a managed semantic caching service that handles embedding generation, storage, and retrieval. Unlike RedisVLCacheProvider, it does not require a local vectorizer — embeddings are handled server-side. - -Requires redisvl>=0.11.1 with LangCache support. - -Initialize the LangCache cache provider. - -Parameters: - -| Name | Type | Description | Default | -| -------- | ------------------------- | ----------------------------------------- | ---------- | -| `config` | `LangCacheProviderConfig` | Configuration for the LangCache provider. | *required* | - -Raises: - -| Type | Description | -| ------------- | ------------------------------------ | -| `ImportError` | If redisvl>=0.11.1 is not installed. | - -Source code in `src/adk_redis/cache/_provider.py` - -```python -def __init__(self, config: LangCacheProviderConfig): - """Initialize the LangCache cache provider. - - Args: - config: Configuration for the LangCache provider. - - Raises: - ImportError: If redisvl>=0.11.1 is not installed. - """ - try: - from redisvl.extensions.cache.llm import LangCacheSemanticCache - except ImportError as e: - raise ImportError( - "redisvl>=0.11.1 with LangCache support is required for " - "LangCacheProvider. Install it with: " - "pip install 'adk-redis[langcache]'" - ) from e - - self._config = config - self._cache = LangCacheSemanticCache( - name=config.name, - server_url=config.server_url, - cache_id=config.cache_id, - api_key=config.api_key.get_secret_value(), - ttl=config.ttl, - use_exact_search=config.use_exact_search, - use_semantic_search=config.use_semantic_search, - distance_scale="redis", - ) -``` - -#### check - -```python -check(prompt: str, **kwargs: Any) -> Optional[CacheEntry] -``` - -Check for a semantically similar prompt in LangCache. - -Parameters: - -| Name | Type | Description | Default | -| ---------- | ----- | -------------------------------------------------------- | ---------- | -| `prompt` | `str` | The prompt to check. | *required* | -| `**kwargs` | `Any` | Additional keyword arguments (e.g., distance_threshold). | `{}` | - -Returns: - -| Type | Description | -| ---------------------- | ----------------------------------------------------- | -| `Optional[CacheEntry]` | A CacheEntry if a cache hit is found, None otherwise. | - -Source code in `src/adk_redis/cache/_provider.py` - -```python -async def check(self, prompt: str, **kwargs: Any) -> Optional[CacheEntry]: - """Check for a semantically similar prompt in LangCache. - - Args: - prompt: The prompt to check. - **kwargs: Additional keyword arguments (e.g., distance_threshold). - - Returns: - A CacheEntry if a cache hit is found, None otherwise. - """ - distance_threshold = kwargs.get( - "distance_threshold", self._config.distance_threshold - ) - acheck_kwargs: dict[str, Any] = {"prompt": prompt} - if distance_threshold is not None: - acheck_kwargs["distance_threshold"] = distance_threshold - result = await self._cache.acheck(**acheck_kwargs) - if result: - logger.debug("LangCache hit for prompt: %s", prompt[:50]) - return CacheEntry( - prompt=prompt, - response=result[0]["response"], - distance=result[0].get("vector_distance"), - metadata=result[0].get("metadata"), - ) - logger.debug("LangCache miss for prompt: %s", prompt[:50]) - return None -``` - -#### store - -```python -store(prompt: str, response: str, metadata: Optional[dict[str, Any]] = None, **kwargs: Any) -> None -``` - -Store a prompt-response pair in LangCache. - -Parameters: - -| Name | Type | Description | Default | -| ---------- | -------------------------- | ----------------------------------------------- | ---------- | -| `prompt` | `str` | The prompt text. | *required* | -| `response` | `str` | The response text. | *required* | -| `metadata` | `Optional[dict[str, Any]]` | Optional metadata to store alongside the entry. | `None` | -| `**kwargs` | `Any` | Additional keyword arguments (e.g., ttl). | `{}` | - -Source code in `src/adk_redis/cache/_provider.py` - -```python -async def store( - self, - prompt: str, - response: str, - metadata: Optional[dict[str, Any]] = None, - **kwargs: Any, -) -> None: - """Store a prompt-response pair in LangCache. - - Args: - prompt: The prompt text. - response: The response text. - metadata: Optional metadata to store alongside the entry. - **kwargs: Additional keyword arguments (e.g., ttl). - """ - astore_kwargs: dict[str, Any] = { - "prompt": prompt, - "response": response, - "metadata": metadata, - } - # Only override TTL when an explicit, non-None value is provided. - ttl = kwargs.get("ttl") - if ttl is not None: - astore_kwargs["ttl"] = ttl - await self._cache.astore(**astore_kwargs) - logger.debug("LangCache stored response for prompt: %s", prompt[:50]) -``` - -#### clear - -```python -clear(**kwargs: Any) -> None -``` - -Clear all entries from the LangCache. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -async def clear(self, **kwargs: Any) -> None: - """Clear all entries from the LangCache.""" - await self._cache.aclear() - logger.info("LangCache cleared") -``` - -#### close - -```python -close() -> None -``` - -Close the LangCache provider and release resources. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -async def close(self) -> None: - """Close the LangCache provider and release resources.""" - await self._cache.adisconnect() - logger.debug("LangCache provider closed") -``` - -### LangCacheProviderConfig - -Bases: `BaseModel` - -Configuration for LangCache (managed semantic cache) provider. - -LangCache is a managed semantic caching service provided by Redis. It requires a cache_id and api_key from the LangCache service. - -### RedisVLCacheProvider - -```python -RedisVLCacheProvider(config: RedisVLCacheProviderConfig, vectorizer: Any) -``` - -Bases: `BaseCacheProvider` - -Cache provider using RedisVL's SemanticCache. - -Initialize the RedisVL cache provider. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -def __init__(self, config: RedisVLCacheProviderConfig, vectorizer: Any): - """Initialize the RedisVL cache provider.""" - try: - from redisvl.extensions.cache.llm import SemanticCache - except ImportError as e: - raise ImportError( - "redisvl is required for RedisVLCacheProvider. " - "Install it with: pip install redisvl>=0.18.2" - ) from e - - self._config = config - self._vectorizer = vectorizer - self._cache = SemanticCache( - name=config.name, - redis_url=config.redis_url, - ttl=config.ttl, - distance_threshold=config.distance_threshold, - vectorizer=vectorizer, - overwrite=True, # Overwrite existing index if schema doesn't match - ) -``` - -#### check - -```python -check(prompt: str, **kwargs: Any) -> Optional[CacheEntry] -``` - -Check for a semantically similar prompt in the cache. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -async def check(self, prompt: str, **kwargs: Any) -> Optional[CacheEntry]: - """Check for a semantically similar prompt in the cache.""" - result = await asyncio.to_thread(self._cache.check, prompt=prompt) - if result: - logger.debug("Cache hit for prompt: %s", prompt[:50]) - return CacheEntry( - prompt=prompt, - response=result[0]["response"], - distance=result[0].get("vector_distance"), - ) - logger.debug("Cache miss for prompt: %s", prompt[:50]) - return None -``` - -#### store - -```python -store(prompt: str, response: str, metadata: Optional[dict[str, Any]] = None, **kwargs: Any) -> None -``` - -Store a prompt-response pair in the cache. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -async def store( - self, - prompt: str, - response: str, - metadata: Optional[dict[str, Any]] = None, - **kwargs: Any, -) -> None: - """Store a prompt-response pair in the cache.""" - await asyncio.to_thread(self._cache.store, prompt=prompt, response=response) - logger.debug("Stored response for prompt: %s", prompt[:50]) -``` - -#### clear - -```python -clear(**kwargs: Any) -> None -``` - -Clear all entries from the cache. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -async def clear(self, **kwargs: Any) -> None: - """Clear all entries from the cache.""" - await asyncio.to_thread(self._cache.clear) - logger.info("Cache cleared") -``` - -#### close - -```python -close() -> None -``` - -Close the cache provider and release resources. - -Source code in `src/adk_redis/cache/_provider.py` - -```python -async def close(self) -> None: - """Close the cache provider and release resources.""" - if hasattr(self._cache, "_index") and hasattr(self._cache._index, "client"): - await asyncio.to_thread(self._cache._index.client.close) - logger.debug("RedisVL cache provider closed") -``` - -### RedisVLCacheProviderConfig - -Bases: `BaseModel` - -Configuration for RedisVL cache provider. - -### ToolCache - -```python -ToolCache(provider: BaseCacheProvider, config: Optional[ToolCacheConfig] = None) -``` - -Cache service for tool call results. - -This service caches tool results using semantic similarity matching on the tool name and arguments. It can be configured to only cache specific tools. - -Initialize the tool cache. - -Parameters: - -| Name | Type | Description | Default | -| ---------- | --------------------------- | -------------------------------------- | ---------- | -| `provider` | `BaseCacheProvider` | The cache provider to use for storage. | *required* | -| `config` | `Optional[ToolCacheConfig]` | Configuration for caching behavior. | `None` | - -Source code in `src/adk_redis/cache/tool_cache.py` - -```python -def __init__( - self, - provider: BaseCacheProvider, - config: Optional[ToolCacheConfig] = None, -): - """Initialize the tool cache. - - Args: - provider: The cache provider to use for storage. - config: Configuration for caching behavior. - """ - self._provider = provider - self._config = config or ToolCacheConfig() - # Track pending tool calls by session key for after_tool_callback - self._pending_calls: dict[str, str] = {} -``` - -#### before_tool_callback - -```python -before_tool_callback(tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext) -> Optional[Dict[str, Any]] -``` - -Check cache before executing tool. - -Parameters: - -| Name | Type | Description | Default | -| -------------- | ---------------- | ----------------------------------- | ---------- | -| `tool` | `BaseTool` | The tool being called. | *required* | -| `args` | `Dict[str, Any]` | The arguments for the tool call. | *required* | -| `tool_context` | `ToolContext` | The tool context with session info. | *required* | - -Returns: - -| Type | Description | -| -------------------------- | ---------------------------------------------------------- | -| `Optional[Dict[str, Any]]` | Dict if cache hit (skips tool execution), None to proceed. | - -Source code in `src/adk_redis/cache/tool_cache.py` - -```python -async def before_tool_callback( - self, - tool: BaseTool, - args: Dict[str, Any], - tool_context: ToolContext, -) -> Optional[Dict[str, Any]]: - """Check cache before executing tool. - - Args: - tool: The tool being called. - args: The arguments for the tool call. - tool_context: The tool context with session info. - - Returns: - Dict if cache hit (skips tool execution), None to proceed. - """ - tool_name = tool.name - if not self._should_cache_tool(tool_name): - logger.debug("Tool %s not in cache list, skipping", tool_name) - return None - - cache_key = self._build_cache_key(tool_name, args, tool_context) - cache_entry = await self._provider.check(cache_key) - - if cache_entry: - logger.info("Cache hit for tool: %s", tool_name) - try: - return json.loads(cache_entry.response) # type: ignore[no-any-return] - except (json.JSONDecodeError, TypeError): - return {"result": cache_entry.response} - - logger.debug("Cache miss for tool: %s", tool_name) - # Store cache key for after_tool_callback - session_key = self._get_session_key(tool_context) - self._pending_calls[session_key] = cache_key - return None -``` - -#### after_tool_callback - -```python -after_tool_callback(tool: BaseTool, args: Dict[str, Any], tool_context: ToolContext, tool_response: Dict[str, Any]) -> Optional[Dict[str, Any]] -``` - -Store tool result in cache after execution. - -Parameters: - -| Name | Type | Description | Default | -| --------------- | ---------------- | ------------------------------------- | ---------- | -| `tool` | `BaseTool` | The tool that was called. | *required* | -| `args` | `Dict[str, Any]` | The arguments used for the tool call. | *required* | -| `tool_context` | `ToolContext` | The tool context with session info. | *required* | -| `tool_response` | `Dict[str, Any]` | The result from the tool execution. | *required* | - -Returns: - -| Type | Description | -| -------------------------- | ------------------------------------------- | -| `Optional[Dict[str, Any]]` | None to pass through the original response. | - -Source code in `src/adk_redis/cache/tool_cache.py` - -```python -async def after_tool_callback( - self, - tool: BaseTool, - args: Dict[str, Any], - tool_context: ToolContext, - tool_response: Dict[str, Any], -) -> Optional[Dict[str, Any]]: - """Store tool result in cache after execution. - - Args: - tool: The tool that was called. - args: The arguments used for the tool call. - tool_context: The tool context with session info. - tool_response: The result from the tool execution. - - Returns: - None to pass through the original response. - """ - session_key = self._get_session_key(tool_context) - cache_key = self._pending_calls.pop(session_key, None) - - if not cache_key: - logger.debug("No pending cache key for tool, skipping store") - return None - - # Serialize the tool response - try: - response_str = json.dumps(tool_response, default=str) - except (TypeError, ValueError): - response_str = str(tool_response) - - await self._provider.store(cache_key, response_str) - logger.info("Cached result for tool: %s", tool.name) - return None -``` - -### ToolCacheConfig - -Bases: `BaseModel` - -Configuration for tool result caching. - -Attributes: - -| Name | Type | Description | -| -------------------- | -------------------- | ------------------------------------------------------- | -| `tool_names` | `Optional[Set[str]]` | Set of tool names to cache. None means cache all tools. | -| `include_app_name` | `bool` | Include app name in cache key. | -| `include_user_id` | `bool` | Include user ID in cache key. | -| `include_session_id` | `bool` | Include session ID in cache key. | - -### create_llm_cache_callbacks - -```python -create_llm_cache_callbacks(cache: LLMResponseCache) -> Tuple[BeforeModelCallback, AfterModelCallback] -``` - -Create callback functions for LLM response caching. - -This factory function wraps the LLMResponseCache methods into standalone callback functions compatible with ADK's Agent constructor. - -Parameters: - -| Name | Type | Description | Default | -| ------- | ------------------ | ------------------------------------- | ---------- | -| `cache` | `LLMResponseCache` | The LLMResponseCache instance to use. | *required* | - -Returns: - -| Type | Description | -| ------------------------------------------------ | ------------------------------------------------------------------- | -| `Tuple[BeforeModelCallback, AfterModelCallback]` | A tuple of (before_model_callback, after_model_callback) functions. | - -Example - -```python -llm_cache = LLMResponseCache(provider=provider) -before_cb, after_cb = create_llm_cache_callbacks(llm_cache) - -agent = Agent( - name="my_agent", - before_model_callback=before_cb, - after_model_callback=after_cb, -) -``` - -Source code in `src/adk_redis/cache/callbacks.py` - -````python -def create_llm_cache_callbacks( - cache: LLMResponseCache, -) -> Tuple[BeforeModelCallback, AfterModelCallback]: - """Create callback functions for LLM response caching. - - This factory function wraps the LLMResponseCache methods into standalone - callback functions compatible with ADK's Agent constructor. - - Args: - cache: The LLMResponseCache instance to use. - - Returns: - A tuple of (before_model_callback, after_model_callback) functions. - - Example: - ```python - llm_cache = LLMResponseCache(provider=provider) - before_cb, after_cb = create_llm_cache_callbacks(llm_cache) - - agent = Agent( - name="my_agent", - before_model_callback=before_cb, - after_model_callback=after_cb, - ) - ``` - """ - - async def before_model_callback( - callback_context: CallbackContext, - llm_request: LlmRequest, - ) -> Optional[LlmResponse]: - return await cache.before_model_callback(callback_context, llm_request) # type: ignore[return-value,no-any-return] - - async def after_model_callback( - callback_context: CallbackContext, - llm_response: LlmResponse, - ) -> Optional[LlmResponse]: - return await cache.after_model_callback(callback_context, llm_response) # type: ignore[return-value,no-any-return] - - return before_model_callback, after_model_callback # type: ignore[return-value] -```` - -### create_tool_cache_callbacks - -```python -create_tool_cache_callbacks(cache: ToolCache) -> Tuple[BeforeToolCallback, AfterToolCallback] -``` - -Create callback functions for tool result caching. - -This factory function wraps the ToolCache methods into standalone callback functions compatible with ADK's Agent constructor. - -Parameters: - -| Name | Type | Description | Default | -| ------- | ----------- | ------------------------------ | ---------- | -| `cache` | `ToolCache` | The ToolCache instance to use. | *required* | - -Returns: - -| Type | Description | -| ---------------------------------------------- | ----------------------------------------------------------------- | -| `Tuple[BeforeToolCallback, AfterToolCallback]` | A tuple of (before_tool_callback, after_tool_callback) functions. | - -Example - -```python -tool_cache = ToolCache(provider=provider) -before_cb, after_cb = create_tool_cache_callbacks(tool_cache) - -agent = Agent( - name="my_agent", - before_tool_callback=before_cb, - after_tool_callback=after_cb, -) -``` - -Source code in `src/adk_redis/cache/callbacks.py` - -````python -def create_tool_cache_callbacks( - cache: ToolCache, -) -> Tuple[BeforeToolCallback, AfterToolCallback]: - """Create callback functions for tool result caching. - - This factory function wraps the ToolCache methods into standalone - callback functions compatible with ADK's Agent constructor. - - Args: - cache: The ToolCache instance to use. - - Returns: - A tuple of (before_tool_callback, after_tool_callback) functions. - - Example: - ```python - tool_cache = ToolCache(provider=provider) - before_cb, after_cb = create_tool_cache_callbacks(tool_cache) - - agent = Agent( - name="my_agent", - before_tool_callback=before_cb, - after_tool_callback=after_cb, - ) - ``` - """ - - async def before_tool_callback( - tool: BaseTool, - args: Dict[str, Any], - tool_context: ToolContext, - ) -> Optional[Dict[str, Any]]: - return await cache.before_tool_callback(tool, args, tool_context) # type: ignore[return-value] - - async def after_tool_callback( - tool: BaseTool, - args: Dict[str, Any], - tool_context: ToolContext, - tool_response: Dict[str, Any], - ) -> Optional[Dict[str, Any]]: - return await cache.after_tool_callback( # type: ignore[return-value] - tool, args, tool_context, tool_response - ) - - return before_tool_callback, after_tool_callback # type: ignore[return-value] -```` diff --git a/site/api/python/index.html b/site/api/python/index.html deleted file mode 100644 index 33d6840..0000000 --- a/site/api/python/index.html +++ /dev/null @@ -1,1627 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Python package - Google ADK + Redis - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
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Python package reference

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Auto-generated reference for the adk_redis package, generated from -Google-style docstrings via mkdocstrings.

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    Sessions

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    Redis-backed implementation of the ADK session service contract.

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    Memory

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    Memory service backed by Agent Memory Server.

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RedisLongTermMemoryService(config: RedisLongTermMemoryServiceConfig | None = None)
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Long-term memory service implementation using Redis Agent Memory Server.

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This service provides production-grade memory capabilities including: -- Two-tier memory architecture (working memory + long-term memory) -- Automatic memory extraction (semantic facts, episodic events, preferences) -- Topic and entity extraction -- Auto-summarization when context window is exceeded -- Recency-boosted semantic search -- Deduplication and memory compaction -- https://github.com/redis/agent-memory-server

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- Example - 
from adk_redis import (
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-    RedisLongTermMemoryServiceConfig,
-)
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-config = RedisLongTermMemoryServiceConfig(
-    api_base_url="http://localhost:8000",
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Initialize the Redis Long-Term Memory Service.

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Configuration for the service. If None, uses defaults.

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TypeDescription
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If agent-memory-client package is not installed.

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def __init__(self, config: RedisLongTermMemoryServiceConfig | None = None):
-  """Initialize the Redis Long-Term Memory Service.
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-  Args:
-      config: Configuration for the service. If None, uses defaults.
-
-  Raises:
-      ImportError: If agent-memory-client package is not installed.
-  """
-  self._config = config or RedisLongTermMemoryServiceConfig()
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Add a session's events to the Agent Memory Server.

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Converts ADK Session events to WorkingMemory messages and stores them -in the Agent Memory Server. The server will automatically: -- Extract semantic and episodic memories based on the configured strategy -- Perform topic and entity extraction -- Summarize context when the token limit is exceeded -- Promote memories to long-term storage via background tasks

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The ADK Session containing events to store.

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@override
-async def add_session_to_memory(self, session: "Session") -> None:
-  """Add a session's events to the Agent Memory Server.
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-  Converts ADK Session events to WorkingMemory messages and stores them
-  in the Agent Memory Server. The server will automatically:
-  - Extract semantic and episodic memories based on the configured strategy
-  - Perform topic and entity extraction
-  - Summarize context when the token limit is exceeded
-  - Promote memories to long-term storage via background tasks
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-  Args:
-      session: The ADK Session containing events to store.
-  """
-  try:
-    working_memory = self._build_working_memory(session)
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-    if not working_memory.messages:
-      logger.debug("No messages to store for session %s", session.id)
-      return
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-    response = await self._client.put_working_memory(
-        session_id=session.id,
-        memory=working_memory,
-        user_id=session.user_id,
-    )
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-    logger.info(
-        "Stored %d messages for session %s (context: %.1f%% used)",
-        len(working_memory.messages),
-        session.id,
-        response.context_percentage_total_used or 0,
-    )
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-  except Exception as e:
-    logger.error(
-        "Failed to add session %s to memory: %s",
-        session.id,
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search_memory(*, app_name: str, user_id: str, query: str) -> SearchMemoryResponse
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Search for memories using the Agent Memory Server.

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Performs semantic search against long-term memory with optional -recency boosting. Results are filtered by namespace (derived from -app_name) and user_id.

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NameTypeDescriptionDefault
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The application name (used as namespace if not configured).

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The user ID to filter memories.

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The search query for semantic matching.

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Returns:

- - - - - - - - - - - - - -
TypeDescription
- SearchMemoryResponse - -
-

SearchMemoryResponse containing matching MemoryEntry objects.

-
-
- - -
- Source code in src/adk_redis/memory/long_term_memory.py - 
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@override
-async def search_memory(
-    self, *, app_name: str, user_id: str, query: str
-) -> SearchMemoryResponse:
-  """Search for memories using the Agent Memory Server.
-
-  Performs semantic search against long-term memory with optional
-  recency boosting. Results are filtered by namespace (derived from
-  app_name) and user_id.
-
-  Args:
-      app_name: The application name (used as namespace if not configured).
-      user_id: The user ID to filter memories.
-      query: The search query for semantic matching.
-
-  Returns:
-      SearchMemoryResponse containing matching MemoryEntry objects.
-  """
-  try:
-    recency_config = (
-        self._build_recency_config() if self._config.recency_boost else None
-    )
-
-    namespace = self._config.default_namespace or app_name
-
-    results = await self._client.search_long_term_memory(
-        text=query,
-        namespace={"eq": namespace},
-        user_id={"eq": user_id},
-        distance_threshold=self._config.distance_threshold,
-        recency=recency_config,
-        limit=self._config.search_top_k,
-    )
-
-    memories = []
-    for record in results.memories:
-      content = types.Content(parts=[types.Part(text=record.text)])
-      memory_entry = MemoryEntry(content=content)
-      memories.append(memory_entry)
-
-    logger.info(
-        "Found %d memories for query '%s' (namespace=%s, user=%s)",
-        len(memories),
-        query[:50],
-        namespace,
-        user_id,
-    )
-    return SearchMemoryResponse(memories=memories)
-
-  except Exception as e:
-    logger.error("Failed to search memories: %s", e)
-    return SearchMemoryResponse(memories=[])
-
-
-
- -
- -
- - -

- close - - - - async - - -

-
close() -> None
-
- -
- -

Close the memory service and cleanup resources.

- - -
- Source code in src/adk_redis/memory/long_term_memory.py - 
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async def close(self) -> None:
-  """Close the memory service and cleanup resources."""
-  if "_client" in self.__dict__:
-    # Check for initialized client without triggering cached_property
-    await self._client.close()
-    # Clear the cached property
-    del self._client
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisLongTermMemoryServiceConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for Redis Long-Term Memory Service.

- - -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
api_base_url - str - -
-

Base URL of the Agent Memory Server.

-
-
timeout - float - -
-

HTTP request timeout in seconds.

-
-
default_namespace - str | None - -
-

Default namespace for memory operations.

-
-
search_top_k - int - -
-

Maximum number of memories to retrieve per search.

-
-
distance_threshold - float | None - -
-

Maximum distance threshold for search results (0.0-1.0).

-
-
recency_boost - bool - -
-

Enable recency-aware re-ranking of search results.

-
-
semantic_weight - float - -
-

Weight for semantic similarity in recency boosting (0.0-1.0).

-
-
recency_weight - float - -
-

Weight for recency score in recency boosting (0.0-1.0).

-
-
freshness_weight - float - -
-

Weight for freshness component within recency score.

-
-
novelty_weight - float - -
-

Weight for novelty component within recency score.

-
-
half_life_last_access_days - float - -
-

Half-life in days for last_accessed decay.

-
-
half_life_created_days - float - -
-

Half-life in days for created_at decay.

-
-
extraction_strategy - Literal['discrete', 'summary', 'preferences', 'custom'] - -
-

Memory extraction strategy (discrete, summary, preferences, custom).

-
-
extraction_strategy_config - dict[str, Any] - -
-

Additional configuration for the extraction strategy.

-
-
model_name - str | None - -
-

Model name for context window management and summarization.

-
-
context_window_max - int | None - -
-

Maximum context window tokens (overrides model default).

-
-
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- - - - - - - - - - - - - \ No newline at end of file diff --git a/site/api/python/memory/index.md b/site/api/python/memory/index.md deleted file mode 100644 index 27ddfa8..0000000 --- a/site/api/python/memory/index.md +++ /dev/null @@ -1,272 +0,0 @@ -# memory - -## memory - -Redis memory services for ADK. - -### RedisLongTermMemoryService - -```python -RedisLongTermMemoryService(config: RedisLongTermMemoryServiceConfig | None = None) -``` - -Bases: `BaseMemoryService` - -Long-term memory service implementation using Redis Agent Memory Server. - -This service provides production-grade memory capabilities including: - -- Two-tier memory architecture (working memory + long-term memory) -- Automatic memory extraction (semantic facts, episodic events, preferences) -- Topic and entity extraction -- Auto-summarization when context window is exceeded -- Recency-boosted semantic search -- Deduplication and memory compaction -- https://github.com/redis/agent-memory-server - -Requires the `agent-memory-client` package to be installed. - -Example - -```python -from adk_redis import ( - RedisLongTermMemoryService, - RedisLongTermMemoryServiceConfig, -) - -config = RedisLongTermMemoryServiceConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", - recency_boost=True, -) -memory_service = RedisLongTermMemoryService(config=config) - -# Use with ADK agent -agent = Agent( - name="my_agent", - memory_service=memory_service, -) -``` - -Initialize the Redis Long-Term Memory Service. - -Parameters: - -| Name | Type | Description | Default | -| -------- | ---------------------------------- | ----------- | ------------------------------------------------------ | -| `config` | \`RedisLongTermMemoryServiceConfig | None\` | Configuration for the service. If None, uses defaults. | - -Raises: - -| Type | Description | -| ------------- | ------------------------------------------------ | -| `ImportError` | If agent-memory-client package is not installed. | - -Source code in `src/adk_redis/memory/long_term_memory.py` - -```python -def __init__(self, config: RedisLongTermMemoryServiceConfig | None = None): - """Initialize the Redis Long-Term Memory Service. - - Args: - config: Configuration for the service. If None, uses defaults. - - Raises: - ImportError: If agent-memory-client package is not installed. - """ - self._config = config or RedisLongTermMemoryServiceConfig() -``` - -#### add_session_to_memory - -```python -add_session_to_memory(session: 'Session') -> None -``` - -Add a session's events to the Agent Memory Server. - -Converts ADK Session events to WorkingMemory messages and stores them in the Agent Memory Server. The server will automatically: - -- Extract semantic and episodic memories based on the configured strategy -- Perform topic and entity extraction -- Summarize context when the token limit is exceeded -- Promote memories to long-term storage via background tasks - -Parameters: - -| Name | Type | Description | Default | -| --------- | ----------- | ------------------------------------------- | ---------- | -| `session` | `'Session'` | The ADK Session containing events to store. | *required* | - -Source code in `src/adk_redis/memory/long_term_memory.py` - -```python -@override -async def add_session_to_memory(self, session: "Session") -> None: - """Add a session's events to the Agent Memory Server. - - Converts ADK Session events to WorkingMemory messages and stores them - in the Agent Memory Server. The server will automatically: - - Extract semantic and episodic memories based on the configured strategy - - Perform topic and entity extraction - - Summarize context when the token limit is exceeded - - Promote memories to long-term storage via background tasks - - Args: - session: The ADK Session containing events to store. - """ - try: - working_memory = self._build_working_memory(session) - - if not working_memory.messages: - logger.debug("No messages to store for session %s", session.id) - return - - response = await self._client.put_working_memory( - session_id=session.id, - memory=working_memory, - user_id=session.user_id, - ) - - logger.info( - "Stored %d messages for session %s (context: %.1f%% used)", - len(working_memory.messages), - session.id, - response.context_percentage_total_used or 0, - ) - - except Exception as e: - logger.error( - "Failed to add session %s to memory: %s", - session.id, - e, - ) -``` - -#### search_memory - -```python -search_memory(*, app_name: str, user_id: str, query: str) -> SearchMemoryResponse -``` - -Search for memories using the Agent Memory Server. - -Performs semantic search against long-term memory with optional recency boosting. Results are filtered by namespace (derived from app_name) and user_id. - -Parameters: - -| Name | Type | Description | Default | -| ---------- | ----- | ----------------------------------------------------------- | ---------- | -| `app_name` | `str` | The application name (used as namespace if not configured). | *required* | -| `user_id` | `str` | The user ID to filter memories. | *required* | -| `query` | `str` | The search query for semantic matching. | *required* | - -Returns: - -| Type | Description | -| ---------------------- | ------------------------------------------------------------- | -| `SearchMemoryResponse` | SearchMemoryResponse containing matching MemoryEntry objects. | - -Source code in `src/adk_redis/memory/long_term_memory.py` - -```python -@override -async def search_memory( - self, *, app_name: str, user_id: str, query: str -) -> SearchMemoryResponse: - """Search for memories using the Agent Memory Server. - - Performs semantic search against long-term memory with optional - recency boosting. Results are filtered by namespace (derived from - app_name) and user_id. - - Args: - app_name: The application name (used as namespace if not configured). - user_id: The user ID to filter memories. - query: The search query for semantic matching. - - Returns: - SearchMemoryResponse containing matching MemoryEntry objects. - """ - try: - recency_config = ( - self._build_recency_config() if self._config.recency_boost else None - ) - - namespace = self._config.default_namespace or app_name - - results = await self._client.search_long_term_memory( - text=query, - namespace={"eq": namespace}, - user_id={"eq": user_id}, - distance_threshold=self._config.distance_threshold, - recency=recency_config, - limit=self._config.search_top_k, - ) - - memories = [] - for record in results.memories: - content = types.Content(parts=[types.Part(text=record.text)]) - memory_entry = MemoryEntry(content=content) - memories.append(memory_entry) - - logger.info( - "Found %d memories for query '%s' (namespace=%s, user=%s)", - len(memories), - query[:50], - namespace, - user_id, - ) - return SearchMemoryResponse(memories=memories) - - except Exception as e: - logger.error("Failed to search memories: %s", e) - return SearchMemoryResponse(memories=[]) -``` - -#### close - -```python -close() -> None -``` - -Close the memory service and cleanup resources. - -Source code in `src/adk_redis/memory/long_term_memory.py` - -```python -async def close(self) -> None: - """Close the memory service and cleanup resources.""" - if "_client" in self.__dict__: - # Check for initialized client without triggering cached_property - await self._client.close() - # Clear the cached property - del self._client -``` - -### RedisLongTermMemoryServiceConfig - -Bases: `BaseModel` - -Configuration for Redis Long-Term Memory Service. - -Attributes: - -| Name | Type | Description | -| ---------------------------- | --------------------------------------------------------- | -------------------------------------------------------------------- | -| `api_base_url` | `str` | Base URL of the Agent Memory Server. | -| `timeout` | `float` | HTTP request timeout in seconds. | -| `default_namespace` | \`str | None\` | -| `search_top_k` | `int` | Maximum number of memories to retrieve per search. | -| `distance_threshold` | \`float | None\` | -| `recency_boost` | `bool` | Enable recency-aware re-ranking of search results. | -| `semantic_weight` | `float` | Weight for semantic similarity in recency boosting (0.0-1.0). | -| `recency_weight` | `float` | Weight for recency score in recency boosting (0.0-1.0). | -| `freshness_weight` | `float` | Weight for freshness component within recency score. | -| `novelty_weight` | `float` | Weight for novelty component within recency score. | -| `half_life_last_access_days` | `float` | Half-life in days for last_accessed decay. | -| `half_life_created_days` | `float` | Half-life in days for created_at decay. | -| `extraction_strategy` | `Literal['discrete', 'summary', 'preferences', 'custom']` | Memory extraction strategy (discrete, summary, preferences, custom). | -| `extraction_strategy_config` | `dict[str, Any]` | Additional configuration for the extraction strategy. | -| `model_name` | \`str | None\` | -| `context_window_max` | \`int | None\` | diff --git a/site/api/python/sessions/index.html b/site/api/python/sessions/index.html deleted file mode 100644 index 00d6561..0000000 --- a/site/api/python/sessions/index.html +++ /dev/null @@ -1,3161 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Sessions - Google ADK + Redis - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - Skip to content - - -
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- - - - - - - - - - - - - - - - - - - - - -

sessions

- - -
- - - -

- sessions - - -

- -
- -

Redis session services for ADK.

- - - - - - - - - - -
- - - - - - - - - -
- - - -

- RedisWorkingMemorySessionService - - -

-
RedisWorkingMemorySessionService(config: RedisWorkingMemorySessionServiceConfig | None = None)
-
- -
-

- Bases: BaseSessionService

- - - -

Session service using Redis Agent Memory Server's Working Memory API.

-

This service provides session management backed by Agent Memory Server: -- Session storage in Working Memory -- Automatic context summarization when token limit exceeded -- Background memory extraction to Long-Term Memory -- Incremental message appending -- https://github.com/redis/agent-memory-server

-

Requires the agent-memory-client package to be installed.

- - -
- Example - 
from adk_redis import (
-    RedisWorkingMemorySessionService,
-    RedisWorkingMemorySessionServiceConfig,
-)
-
-config = RedisWorkingMemorySessionServiceConfig(
-    api_base_url="http://localhost:8000",
-    default_namespace="my_app",
-)
-session_service = RedisWorkingMemorySessionService(config=config)
-
-# Use with ADK runner
-runner = Runner(
-    agent=agent,
-    session_service=session_service,
-)
-
-
-

Initialize the Redis Working Memory Session Service.

- - -

Parameters:

- - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- config - - RedisWorkingMemorySessionServiceConfig | None - -
-

Configuration for the service. If None, uses defaults.

-
- 		- None -
- - - - - - - - -
- Source code in src/adk_redis/sessions/working_memory.py - 
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def __init__(
-    self, config: RedisWorkingMemorySessionServiceConfig | None = None
-):
-  """Initialize the Redis Working Memory Session Service.
-
-  Args:
-      config: Configuration for the service. If None, uses defaults.
-  """
-  self._config = config or RedisWorkingMemorySessionServiceConfig()
-
-
- - - -
- - - - - - - - - - -
- - -

- create_session - - - - async - - -

-
create_session(*, app_name: str, user_id: str, state: dict[str, Any] | None = None, session_id: str | None = None) -> Session
-
- -
- -

Create a new session in Working Memory.

-

Uses get_or_create_working_memory to prevent accidental overwrites -of existing sessions.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- app_name - - str - -
-

Application name (used as namespace if not configured).

-
- 		- required -
- user_id - - str - -
-

User identifier.

-
- 		- required -
- state - - dict[str, Any] | None - -
-

Initial session state.

-
- 		- None -
- session_id - - str | None - -
-

Optional session ID (generated if not provided).

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Session - -
-

The created Session.

-
-
- - -
- Source code in src/adk_redis/sessions/working_memory.py - 
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@override
-async def create_session(
-    self,
-    *,
-    app_name: str,
-    user_id: str,
-    state: dict[str, Any] | None = None,
-    session_id: str | None = None,
-) -> Session:
-  """Create a new session in Working Memory.
-
-  Uses get_or_create_working_memory to prevent accidental overwrites
-  of existing sessions.
-
-  Args:
-      app_name: Application name (used as namespace if not configured).
-      user_id: User identifier.
-      state: Initial session state.
-      session_id: Optional session ID (generated if not provided).
-
-  Returns:
-      The created Session.
-  """
-  from agent_memory_client.models import MemoryStrategyConfig
-
-  session_id = (
-      session_id.strip()
-      if session_id and session_id.strip()
-      else str(uuid.uuid4())
-  )
-  namespace = self._get_namespace(app_name)
-
-  strategy_config = MemoryStrategyConfig(
-      strategy=self._config.extraction_strategy,
-      config=self._config.extraction_strategy_config,
-  )
-
-  # Use get_or_create to prevent accidental overwrites
-  client = self._get_client()
-  created, working_memory = await client.get_or_create_working_memory(
-      session_id=session_id,
-      namespace=namespace,
-      user_id=user_id,
-      long_term_memory_strategy=strategy_config,
-  )
-
-  if not created:
-    logger.warning(
-        "Session %s already exists in namespace %s, returning existing",
-        session_id,
-        namespace,
-    )
-    # Return existing session data
-    return self._working_memory_response_to_session(
-        working_memory, app_name, user_id
-    )
-
-  # Update with initial state and TTL if provided
-  if state or self._config.session_ttl_seconds:
-    if state:
-      working_memory.data = state
-    if self._config.session_ttl_seconds:
-      working_memory.ttl_seconds = self._config.session_ttl_seconds
-    await client.put_working_memory(
-        session_id=session_id,
-        memory=working_memory,
-        user_id=user_id,
-    )
-
-  logger.info("Created session %s in namespace %s", session_id, namespace)
-
-  return Session(
-      id=session_id,
-      app_name=app_name,
-      user_id=user_id,
-      state=state or {},
-      events=[],
-      last_update_time=time.time(),
-  )
-
-
-
- -
- -
- - -

- get_session - - - - async - - -

-
get_session(*, app_name: str, user_id: str, session_id: str, config: GetSessionConfig | None = None) -> Session | None
-
- -
- -

Retrieve a session from Working Memory.

-

Uses get_or_create_working_memory and checks if session was newly created -to determine if it exists. Passes model_name and context_window_max to -enable automatic context summarization when token limit is exceeded.

-

NOTE: For ADK Runner compatibility, this method now returns the session -even if it was just created. The Runner expects get_session to either -return an existing session OR return a newly created empty session. -Returning None causes the Runner to fail with "Session not found".

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- app_name - - str - -
-

Application name.

-
- 		- required -
- user_id - - str - -
-

User identifier.

-
- 		- required -
- session_id - - str - -
-

Session ID to retrieve.

-
- 		- required -
- config - - GetSessionConfig | None - -
-

Optional configuration for filtering events.

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Session | None - -
-

The Session (existing or newly created).

-
-
- - -
- Source code in src/adk_redis/sessions/working_memory.py - 
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@override
-async def get_session(
-    self,
-    *,
-    app_name: str,
-    user_id: str,
-    session_id: str,
-    config: GetSessionConfig | None = None,
-) -> Session | None:
-  """Retrieve a session from Working Memory.
-
-  Uses get_or_create_working_memory and checks if session was newly created
-  to determine if it exists. Passes model_name and context_window_max to
-  enable automatic context summarization when token limit is exceeded.
-
-  NOTE: For ADK Runner compatibility, this method now returns the session
-  even if it was just created. The Runner expects get_session to either
-  return an existing session OR return a newly created empty session.
-  Returning None causes the Runner to fail with "Session not found".
-
-  Args:
-      app_name: Application name.
-      user_id: User identifier.
-      session_id: Session ID to retrieve.
-      config: Optional configuration for filtering events.
-
-  Returns:
-      The Session (existing or newly created).
-  """
-  from agent_memory_client.exceptions import MemoryNotFoundError
-
-  try:
-    namespace = self._get_namespace(app_name)
-    # Use get_or_create to avoid deprecated get_working_memory
-    client = self._get_client()
-    created, response = await client.get_or_create_working_memory(
-        session_id=session_id,
-        namespace=namespace,
-        user_id=user_id,
-        model_name=self._config.model_name,
-        context_window_max=self._config.context_window_max,
-    )
-
-    # Return the session whether it was just created or already existed
-    # This is required for ADK Runner compatibility
-    session = self._working_memory_response_to_session(
-        response, app_name, user_id
-    )
-
-    if config:
-      if config.num_recent_events:
-        session.events = session.events[-config.num_recent_events :]
-      if config.after_timestamp:
-        session.events = [
-            e for e in session.events if e.timestamp > config.after_timestamp
-        ]
-
-    return session
-
-  except MemoryNotFoundError:
-    return None
-  except Exception as e:
-    logger.error("Failed to get session %s: %s", session_id, e)
-    return None
-
-
-
- -
- -
- - -

- list_sessions - - - - async - - -

-
list_sessions(*, app_name: str, user_id: str | None = None) -> ListSessionsResponse
-
- -
- -

List all sessions for a user from Working Memory.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- app_name - - str - -
-

Application name.

-
- 		- required -
- user_id - - str | None - -
-

User identifier (required for this implementation).

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- ListSessionsResponse - -
-

ListSessionsResponse containing sessions (without events).

-
-
- - -

Raises:

- - - - - - - - - - - - - -
TypeDescription
- ValueError - -
-

If user_id is not provided.

-
-
- - -
- Source code in src/adk_redis/sessions/working_memory.py - 
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@override
-async def list_sessions(
-    self, *, app_name: str, user_id: str | None = None
-) -> ListSessionsResponse:
-  """List all sessions for a user from Working Memory.
-
-  Args:
-      app_name: Application name.
-      user_id: User identifier (required for this implementation).
-
-  Returns:
-      ListSessionsResponse containing sessions (without events).
-
-  Raises:
-      ValueError: If user_id is not provided.
-  """
-  if user_id is None:
-    raise ValueError(
-        "user_id is required for RedisWorkingMemorySessionService"
-    )
-  try:
-    namespace = self._get_namespace(app_name)
-
-    # SDK method: list_sessions returns SessionListResponse
-    # with sessions: list[str] (session IDs only)
-    client = self._get_client()
-    response = await client.list_sessions(
-        namespace=namespace,
-        user_id=user_id,
-    )
-
-    sessions = []
-    for session_id in response.sessions:
-      session = Session(
-          id=session_id,
-          app_name=app_name,
-          user_id=user_id,
-          state={},
-          events=[],
-          last_update_time=time.time(),
-      )
-      sessions.append(session)
-
-    return ListSessionsResponse(sessions=sessions)
-
-  except Exception as e:
-    logger.error("Failed to list sessions: %s", e)
-    return ListSessionsResponse(sessions=[])
-
-
-
- -
- -
- - -

- delete_session - - - - async - - -

-
delete_session(*, app_name: str, user_id: str, session_id: str) -> None
-
- -
- -

Delete a session from Working Memory.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- app_name - - str - -
-

Application name.

-
- 		- required -
- user_id - - str - -
-

User identifier.

-
- 		- required -
- session_id - - str - -
-

Session ID to delete.

-
- 		- required -
- - -
- Source code in src/adk_redis/sessions/working_memory.py - 
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@override
-async def delete_session(
-    self, *, app_name: str, user_id: str, session_id: str
-) -> None:
-  """Delete a session from Working Memory.
-
-  Args:
-      app_name: Application name.
-      user_id: User identifier.
-      session_id: Session ID to delete.
-  """
-  try:
-    namespace = self._get_namespace(app_name)
-    client = self._get_client()
-    await client.delete_working_memory(
-        session_id=session_id,
-        namespace=namespace,
-        user_id=user_id,
-    )
-    logger.info("Deleted session %s", session_id)
-  except Exception as e:
-    logger.error("Failed to delete session %s: %s", session_id, e)
-
-
-
- -
- -
- - -

- append_event - - - - async - - -

-
append_event(session: Session, event: Event) -> Event
-
- -
- -

Append an event to the session in Working Memory.

-

Uses the incremental append API to add a single message without -resending the full conversation history.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- session - - Session - -
-

The session to append to.

-
- 		- required -
- event - - Event - -
-

The event to append.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- Event - -
-

The appended event.

-
-
- - -
- Source code in src/adk_redis/sessions/working_memory.py - 
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@override
-async def append_event(self, session: Session, event: Event) -> Event:
-  """Append an event to the session in Working Memory.
-
-  Uses the incremental append API to add a single message without
-  resending the full conversation history.
-
-  Args:
-      session: The session to append to.
-      event: The event to append.
-
-  Returns:
-      The appended event.
-  """
-  await super().append_event(session=session, event=event)
-  session.last_update_time = event.timestamp
-
-  try:
-    message = self._event_to_message(event)
-    if message:
-      namespace = self._get_namespace(session.app_name)
-      client = self._get_client()
-      await client.append_messages_to_working_memory(
-          session_id=session.id,
-          messages=[message],
-          namespace=namespace,
-          user_id=session.user_id,
-      )
-      logger.debug("Appended message to session %s", session.id)
-  except Exception as e:
-    logger.error("Failed to append event to session %s: %s", session.id, e)
-
-  return event
-
-
-
- -
- -
- - -

- close - - - - async - - -

-
close() -> None
-
- -
- -

Close the session service and cleanup resources.

- - -
- Source code in src/adk_redis/sessions/working_memory.py - 
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async def close(self) -> None:
-  """Close the session service and cleanup resources."""
-  # No longer caching client, so nothing to close
-  pass
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisWorkingMemorySessionServiceConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for Redis Working Memory Session Service.

- - -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
api_base_url - str - -
-

Base URL of the Agent Memory Server.

-
-
timeout - float - -
-

HTTP request timeout in seconds.

-
-
default_namespace - str | None - -
-

Default namespace for session operations.

-
-
model_name - str | None - -
-

Model name for context window management and summarization.

-
-
context_window_max - int | None - -
-

Maximum context window tokens.

-
-
extraction_strategy - Literal['discrete', 'summary', 'preferences', 'custom'] - -
-

Memory extraction strategy.

-
-
extraction_strategy_config - dict[str, Any] - -
-

Additional config for extraction strategy.

-
-
session_ttl_seconds - int | None - -
-

Optional TTL for session expiration.

-
-
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- - - - - - - - - - - - - \ No newline at end of file diff --git a/site/api/python/sessions/index.md b/site/api/python/sessions/index.md deleted file mode 100644 index 9dbf08f..0000000 --- a/site/api/python/sessions/index.md +++ /dev/null @@ -1,493 +0,0 @@ -# sessions - -## sessions - -Redis session services for ADK. - -### RedisWorkingMemorySessionService - -```python -RedisWorkingMemorySessionService(config: RedisWorkingMemorySessionServiceConfig | None = None) -``` - -Bases: `BaseSessionService` - -Session service using Redis Agent Memory Server's Working Memory API. - -This service provides session management backed by Agent Memory Server: - -- Session storage in Working Memory -- Automatic context summarization when token limit exceeded -- Background memory extraction to Long-Term Memory -- Incremental message appending -- https://github.com/redis/agent-memory-server - -Requires the `agent-memory-client` package to be installed. - -Example - -```python -from adk_redis import ( - RedisWorkingMemorySessionService, - RedisWorkingMemorySessionServiceConfig, -) - -config = RedisWorkingMemorySessionServiceConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", -) -session_service = RedisWorkingMemorySessionService(config=config) - -# Use with ADK runner -runner = Runner( - agent=agent, - session_service=session_service, -) -``` - -Initialize the Redis Working Memory Session Service. - -Parameters: - -| Name | Type | Description | Default | -| -------- | ---------------------------------------- | ----------- | ------------------------------------------------------ | -| `config` | \`RedisWorkingMemorySessionServiceConfig | None\` | Configuration for the service. If None, uses defaults. | - -Source code in `src/adk_redis/sessions/working_memory.py` - -```python -def __init__( - self, config: RedisWorkingMemorySessionServiceConfig | None = None -): - """Initialize the Redis Working Memory Session Service. - - Args: - config: Configuration for the service. If None, uses defaults. - """ - self._config = config or RedisWorkingMemorySessionServiceConfig() -``` - -#### create_session - -```python -create_session(*, app_name: str, user_id: str, state: dict[str, Any] | None = None, session_id: str | None = None) -> Session -``` - -Create a new session in Working Memory. - -Uses get_or_create_working_memory to prevent accidental overwrites of existing sessions. - -Parameters: - -| Name | Type | Description | Default | -| ------------ | ---------------- | ------------------------------------------------------- | ------------------------------------------------ | -| `app_name` | `str` | Application name (used as namespace if not configured). | *required* | -| `user_id` | `str` | User identifier. | *required* | -| `state` | \`dict[str, Any] | None\` | Initial session state. | -| `session_id` | \`str | None\` | Optional session ID (generated if not provided). | - -Returns: - -| Type | Description | -| --------- | -------------------- | -| `Session` | The created Session. | - -Source code in `src/adk_redis/sessions/working_memory.py` - -```python -@override -async def create_session( - self, - *, - app_name: str, - user_id: str, - state: dict[str, Any] | None = None, - session_id: str | None = None, -) -> Session: - """Create a new session in Working Memory. - - Uses get_or_create_working_memory to prevent accidental overwrites - of existing sessions. - - Args: - app_name: Application name (used as namespace if not configured). - user_id: User identifier. - state: Initial session state. - session_id: Optional session ID (generated if not provided). - - Returns: - The created Session. - """ - from agent_memory_client.models import MemoryStrategyConfig - - session_id = ( - session_id.strip() - if session_id and session_id.strip() - else str(uuid.uuid4()) - ) - namespace = self._get_namespace(app_name) - - strategy_config = MemoryStrategyConfig( - strategy=self._config.extraction_strategy, - config=self._config.extraction_strategy_config, - ) - - # Use get_or_create to prevent accidental overwrites - client = self._get_client() - created, working_memory = await client.get_or_create_working_memory( - session_id=session_id, - namespace=namespace, - user_id=user_id, - long_term_memory_strategy=strategy_config, - ) - - if not created: - logger.warning( - "Session %s already exists in namespace %s, returning existing", - session_id, - namespace, - ) - # Return existing session data - return self._working_memory_response_to_session( - working_memory, app_name, user_id - ) - - # Update with initial state and TTL if provided - if state or self._config.session_ttl_seconds: - if state: - working_memory.data = state - if self._config.session_ttl_seconds: - working_memory.ttl_seconds = self._config.session_ttl_seconds - await client.put_working_memory( - session_id=session_id, - memory=working_memory, - user_id=user_id, - ) - - logger.info("Created session %s in namespace %s", session_id, namespace) - - return Session( - id=session_id, - app_name=app_name, - user_id=user_id, - state=state or {}, - events=[], - last_update_time=time.time(), - ) -``` - -#### get_session - -```python -get_session(*, app_name: str, user_id: str, session_id: str, config: GetSessionConfig | None = None) -> Session | None -``` - -Retrieve a session from Working Memory. - -Uses get_or_create_working_memory and checks if session was newly created to determine if it exists. Passes model_name and context_window_max to enable automatic context summarization when token limit is exceeded. - -NOTE: For ADK Runner compatibility, this method now returns the session even if it was just created. The Runner expects get_session to either return an existing session OR return a newly created empty session. Returning None causes the Runner to fail with "Session not found". - -Parameters: - -| Name | Type | Description | Default | -| ------------ | ------------------ | ----------------------- | -------------------------------------------- | -| `app_name` | `str` | Application name. | *required* | -| `user_id` | `str` | User identifier. | *required* | -| `session_id` | `str` | Session ID to retrieve. | *required* | -| `config` | \`GetSessionConfig | None\` | Optional configuration for filtering events. | - -Returns: - -| Type | Description | -| --------- | ----------- | -| \`Session | None\` | - -Source code in `src/adk_redis/sessions/working_memory.py` - -```python -@override -async def get_session( - self, - *, - app_name: str, - user_id: str, - session_id: str, - config: GetSessionConfig | None = None, -) -> Session | None: - """Retrieve a session from Working Memory. - - Uses get_or_create_working_memory and checks if session was newly created - to determine if it exists. Passes model_name and context_window_max to - enable automatic context summarization when token limit is exceeded. - - NOTE: For ADK Runner compatibility, this method now returns the session - even if it was just created. The Runner expects get_session to either - return an existing session OR return a newly created empty session. - Returning None causes the Runner to fail with "Session not found". - - Args: - app_name: Application name. - user_id: User identifier. - session_id: Session ID to retrieve. - config: Optional configuration for filtering events. - - Returns: - The Session (existing or newly created). - """ - from agent_memory_client.exceptions import MemoryNotFoundError - - try: - namespace = self._get_namespace(app_name) - # Use get_or_create to avoid deprecated get_working_memory - client = self._get_client() - created, response = await client.get_or_create_working_memory( - session_id=session_id, - namespace=namespace, - user_id=user_id, - model_name=self._config.model_name, - context_window_max=self._config.context_window_max, - ) - - # Return the session whether it was just created or already existed - # This is required for ADK Runner compatibility - session = self._working_memory_response_to_session( - response, app_name, user_id - ) - - if config: - if config.num_recent_events: - session.events = session.events[-config.num_recent_events :] - if config.after_timestamp: - session.events = [ - e for e in session.events if e.timestamp > config.after_timestamp - ] - - return session - - except MemoryNotFoundError: - return None - except Exception as e: - logger.error("Failed to get session %s: %s", session_id, e) - return None -``` - -#### list_sessions - -```python -list_sessions(*, app_name: str, user_id: str | None = None) -> ListSessionsResponse -``` - -List all sessions for a user from Working Memory. - -Parameters: - -| Name | Type | Description | Default | -| ---------- | ----- | ----------------- | --------------------------------------------------- | -| `app_name` | `str` | Application name. | *required* | -| `user_id` | \`str | None\` | User identifier (required for this implementation). | - -Returns: - -| Type | Description | -| ---------------------- | ---------------------------------------------------------- | -| `ListSessionsResponse` | ListSessionsResponse containing sessions (without events). | - -Raises: - -| Type | Description | -| ------------ | --------------------------- | -| `ValueError` | If user_id is not provided. | - -Source code in `src/adk_redis/sessions/working_memory.py` - -```python -@override -async def list_sessions( - self, *, app_name: str, user_id: str | None = None -) -> ListSessionsResponse: - """List all sessions for a user from Working Memory. - - Args: - app_name: Application name. - user_id: User identifier (required for this implementation). - - Returns: - ListSessionsResponse containing sessions (without events). - - Raises: - ValueError: If user_id is not provided. - """ - if user_id is None: - raise ValueError( - "user_id is required for RedisWorkingMemorySessionService" - ) - try: - namespace = self._get_namespace(app_name) - - # SDK method: list_sessions returns SessionListResponse - # with sessions: list[str] (session IDs only) - client = self._get_client() - response = await client.list_sessions( - namespace=namespace, - user_id=user_id, - ) - - sessions = [] - for session_id in response.sessions: - session = Session( - id=session_id, - app_name=app_name, - user_id=user_id, - state={}, - events=[], - last_update_time=time.time(), - ) - sessions.append(session) - - return ListSessionsResponse(sessions=sessions) - - except Exception as e: - logger.error("Failed to list sessions: %s", e) - return ListSessionsResponse(sessions=[]) -``` - -#### delete_session - -```python -delete_session(*, app_name: str, user_id: str, session_id: str) -> None -``` - -Delete a session from Working Memory. - -Parameters: - -| Name | Type | Description | Default | -| ------------ | ----- | --------------------- | ---------- | -| `app_name` | `str` | Application name. | *required* | -| `user_id` | `str` | User identifier. | *required* | -| `session_id` | `str` | Session ID to delete. | *required* | - -Source code in `src/adk_redis/sessions/working_memory.py` - -```python -@override -async def delete_session( - self, *, app_name: str, user_id: str, session_id: str -) -> None: - """Delete a session from Working Memory. - - Args: - app_name: Application name. - user_id: User identifier. - session_id: Session ID to delete. - """ - try: - namespace = self._get_namespace(app_name) - client = self._get_client() - await client.delete_working_memory( - session_id=session_id, - namespace=namespace, - user_id=user_id, - ) - logger.info("Deleted session %s", session_id) - except Exception as e: - logger.error("Failed to delete session %s: %s", session_id, e) -``` - -#### append_event - -```python -append_event(session: Session, event: Event) -> Event -``` - -Append an event to the session in Working Memory. - -Uses the incremental append API to add a single message without resending the full conversation history. - -Parameters: - -| Name | Type | Description | Default | -| --------- | --------- | ------------------------- | ---------- | -| `session` | `Session` | The session to append to. | *required* | -| `event` | `Event` | The event to append. | *required* | - -Returns: - -| Type | Description | -| ------- | ------------------- | -| `Event` | The appended event. | - -Source code in `src/adk_redis/sessions/working_memory.py` - -```python -@override -async def append_event(self, session: Session, event: Event) -> Event: - """Append an event to the session in Working Memory. - - Uses the incremental append API to add a single message without - resending the full conversation history. - - Args: - session: The session to append to. - event: The event to append. - - Returns: - The appended event. - """ - await super().append_event(session=session, event=event) - session.last_update_time = event.timestamp - - try: - message = self._event_to_message(event) - if message: - namespace = self._get_namespace(session.app_name) - client = self._get_client() - await client.append_messages_to_working_memory( - session_id=session.id, - messages=[message], - namespace=namespace, - user_id=session.user_id, - ) - logger.debug("Appended message to session %s", session.id) - except Exception as e: - logger.error("Failed to append event to session %s: %s", session.id, e) - - return event -``` - -#### close - -```python -close() -> None -``` - -Close the session service and cleanup resources. - -Source code in `src/adk_redis/sessions/working_memory.py` - -```python -async def close(self) -> None: - """Close the session service and cleanup resources.""" - # No longer caching client, so nothing to close - pass -``` - -### RedisWorkingMemorySessionServiceConfig - -Bases: `BaseModel` - -Configuration for Redis Working Memory Session Service. - -Attributes: - -| Name | Type | Description | -| ---------------------------- | --------------------------------------------------------- | ------------------------------------------ | -| `api_base_url` | `str` | Base URL of the Agent Memory Server. | -| `timeout` | `float` | HTTP request timeout in seconds. | -| `default_namespace` | \`str | None\` | -| `model_name` | \`str | None\` | -| `context_window_max` | \`int | None\` | -| `extraction_strategy` | `Literal['discrete', 'summary', 'preferences', 'custom']` | Memory extraction strategy. | -| `extraction_strategy_config` | `dict[str, Any]` | Additional config for extraction strategy. | -| `session_ttl_seconds` | \`int | None\` | diff --git a/site/api/python/tools/index.html b/site/api/python/tools/index.html deleted file mode 100644 index 61a59c7..0000000 --- a/site/api/python/tools/index.html +++ /dev/null @@ -1,9868 +0,0 @@ - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Tools - Google ADK + Redis - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
- - - - Skip to content - - -
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tools

- - -
- - - -

- tools - - -

- -
- -

Redis tools for ADK.

- - - - - - - - - - -
- - - - - - - - - -
- - - -

- CreateMemoryTool - - -

-
CreateMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'create_memory', description: str = 'Creates a new long-term memory. Use this when the user asks you to remember something.')
-
- -
-

- Bases: BaseMemoryTool

- - - -

Tool for creating new long-term memories.

-

This tool allows the LLM to explicitly store information in long-term memory. -Use this when the user asks to remember something specific.

- - -
- Example - 
from adk_redis.tools.memory import CreateMemoryTool, MemoryToolConfig
-
-config = MemoryToolConfig(
-    api_base_url="http://localhost:8000",
-    default_namespace="my_app",
-)
-tool = CreateMemoryTool(config=config)
-
-# Use with ADK agent
-agent = Agent(
-    name="my_agent",
-    tools=[tool],
-)
-
-
-

Initialize the Create Memory Tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- config - - MemoryToolConfig | None - -
-

Configuration for the tool. If None, uses defaults.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'create_memory' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Creates a new long-term memory. Use this when the user asks you to remember something.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/memory/create.py - 
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def __init__(
-    self,
-    *,
-    config: MemoryToolConfig | None = None,
-    name: str = "create_memory",
-    description: str = (
-        "Creates a new long-term memory. "
-        "Use this when the user asks you to remember something."
-    ),
-):
-  """Initialize the Create Memory Tool.
-
-  Args:
-      config: Configuration for the tool. If None, uses defaults.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      config=config or MemoryToolConfig(),
-      name=name,
-      description=description,
-  )
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(**kwargs: Any) -> dict[str, Any]
-
- -
- -

Create a new long-term memory.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- content - - -
-

The content of the memory to store.

-
- 		- required -
- topics - - -
-

Optional list of topics/tags.

-
- 		- required -
- memory_type - - -
-

Type of memory (semantic, episodic, message).

-
- 		- required -
- namespace - - -
-

Optional namespace override.

-
- 		- required -
- user_id - - -
-

Optional user ID override.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status and memory_id.

-
-
- - -
- Source code in src/adk_redis/tools/memory/create.py - 
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async def run_async(self, **kwargs: Any) -> dict[str, Any]:
-  """Create a new long-term memory.
-
-  Args:
-      content: The content of the memory to store.
-      topics: Optional list of topics/tags.
-      memory_type: Type of memory (semantic, episodic, message).
-      namespace: Optional namespace override.
-      user_id: Optional user ID override.
-
-  Returns:
-      A dictionary with status and memory_id.
-  """
-  # ADK passes parameters in kwargs['args']
-  args = kwargs.get("args", kwargs)
-
-  content = args.get("content")
-  topics = args.get("topics", [])
-  memory_type_raw = args.get("memory_type", "semantic")
-  namespace = self._get_namespace(args.get("namespace"))
-  user_id = self._get_user_id(args.get("user_id"))
-
-  if not content:
-    return {"status": "error", "message": "content is required"}
-
-  # Map invalid memory types to valid ones
-  # Valid types: 'semantic', 'episodic', 'message'
-  memory_type_map = {
-      "preference": "semantic",
-      "fact": "semantic",
-      "event": "episodic",
-      "experience": "episodic",
-      "conversation": "message",
-  }
-  memory_type = memory_type_map.get(memory_type_raw, memory_type_raw)
-  if memory_type not in ("semantic", "episodic", "message"):
-    memory_type = "semantic"  # Default fallback
-
-  try:
-    # Use add_memory_tool which creates a memory in a session context
-    # We'll use a temporary session ID for standalone memory creation
-    import uuid
-
-    session_id = f"standalone_{uuid.uuid4().hex[:8]}"
-
-    client = self._get_client()
-    response = await client.add_memory_tool(
-        session_id=session_id,
-        text=content,
-        memory_type=memory_type,
-        topics=topics if topics else None,
-        namespace=namespace,
-        user_id=user_id,
-    )
-
-    # Response is a dict with 'success' key and summary
-    if response.get("success"):
-      # Extract memory ID from summary if available, or use session_id as fallback
-      memory_id = response.get("memory_id", session_id)
-      return {
-          "status": "success",
-          "memory_id": memory_id,
-          "message": response.get("summary", "Memory created successfully"),
-      }
-    else:
-      return {
-          "status": "error",
-          "message": response.get("summary", "Failed to create memory"),
-      }
-
-  except Exception as e:
-    logger.error("Failed to create memory: %s", e)
-    return {
-        "status": "error",
-        "message": f"Failed to create memory: {str(e)}",
-    }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- DeleteMemoryTool - - -

-
DeleteMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'delete_memory', description: str = 'Deletes one or more long-term memories by ID. Use this when the user asks you to forget something.')
-
- -
-

- Bases: BaseMemoryTool

- - - -

Tool for deleting long-term memories.

-

This tool allows the LLM to delete specific memories by ID. -Use this when the user asks to forget something.

- - -
- Example - 
from adk_redis.tools.memory import DeleteMemoryTool, MemoryToolConfig
-
-config = MemoryToolConfig(
-    api_base_url="http://localhost:8000",
-    default_namespace="my_app",
-)
-tool = DeleteMemoryTool(config=config)
-
-# Use with ADK agent
-agent = Agent(
-    name="my_agent",
-    tools=[tool],
-)
-
-
-

Initialize the Delete Memory Tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- config - - MemoryToolConfig | None - -
-

Configuration for the tool. If None, uses defaults.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'delete_memory' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Deletes one or more long-term memories by ID. Use this when the user asks you to forget something.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/memory/delete.py - 
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def __init__(
-    self,
-    *,
-    config: MemoryToolConfig | None = None,
-    name: str = "delete_memory",
-    description: str = (
-        "Deletes one or more long-term memories by ID. "
-        "Use this when the user asks you to forget something."
-    ),
-):
-  """Initialize the Delete Memory Tool.
-
-  Args:
-      config: Configuration for the tool. If None, uses defaults.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      config=config or MemoryToolConfig(),
-      name=name,
-      description=description,
-  )
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(**kwargs: Any) -> dict[str, Any]
-
- -
- -

Delete long-term memories by ID.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- memory_ids - - -
-

List of memory IDs to delete.

-
- 		- required -
- namespace - - -
-

Optional namespace override.

-
- 		- required -
- user_id - - -
-

Optional user ID override.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status and deleted_count.

-
-
- - -
- Source code in src/adk_redis/tools/memory/delete.py - 
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async def run_async(self, **kwargs: Any) -> dict[str, Any]:
-  """Delete long-term memories by ID.
-
-  Args:
-      memory_ids: List of memory IDs to delete.
-      namespace: Optional namespace override.
-      user_id: Optional user ID override.
-
-  Returns:
-      A dictionary with status and deleted_count.
-  """
-  # ADK passes parameters in kwargs['args']
-  args = kwargs.get("args", kwargs)
-
-  memory_ids = args.get("memory_ids", [])
-  self._get_namespace(args.get("namespace"))
-  self._get_user_id(args.get("user_id"))
-
-  if not memory_ids:
-    return {"status": "error", "message": "memory_ids is required"}
-
-  try:
-    # delete_long_term_memories only takes memory_ids
-    client = self._get_client()
-    response = await client.delete_long_term_memories(
-        memory_ids=memory_ids,
-    )
-
-    # Response is AckResponse with 'status' field containing message like "ok, deleted 2 memories"
-    status_msg = response.status
-
-    # Parse the deleted count from the status message
-    import re
-
-    match = re.search(r"deleted (\d+)", status_msg)
-    deleted_count = int(match.group(1)) if match else 0
-
-    is_success = "ok" in status_msg.lower()
-
-    return {
-        "status": "success" if is_success else "error",
-        "deleted_count": deleted_count,
-        "message": status_msg,
-    }
-
-  except Exception as e:
-    logger.error("Failed to delete memories: %s", e)
-    return {
-        "status": "error",
-        "message": f"Failed to delete memories: {str(e)}",
-    }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- GetMemoryTool - - -

-
GetMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'get_memory', description: str = 'Retrieves a specific long-term memory by its ID. Use this when you need the full details of a known memory.')
-
- -
-

- Bases: BaseMemoryTool

- - - -

Tool for retrieving a specific long-term memory by ID.

-

This tool allows the LLM to retrieve a specific memory when it knows -the memory ID. Use this when you need to access the full details of -a memory that was previously found via search.

- - -
- Example - 
from adk_redis.tools.memory import GetMemoryTool, MemoryToolConfig
-
-config = MemoryToolConfig(
-    api_base_url="http://localhost:8000",
-    default_namespace="my_app",
-)
-tool = GetMemoryTool(config=config)
-
-# Use with ADK agent
-agent = Agent(
-    name="my_agent",
-    tools=[tool],
-)
-
-
-

Initialize the Get Memory Tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- config - - MemoryToolConfig | None - -
-

Configuration for the tool. If None, uses defaults.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'get_memory' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Retrieves a specific long-term memory by its ID. Use this when you need the full details of a known memory.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/memory/get.py - 
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def __init__(
-    self,
-    *,
-    config: MemoryToolConfig | None = None,
-    name: str = "get_memory",
-    description: str = (
-        "Retrieves a specific long-term memory by its ID. "
-        "Use this when you need the full details of a known memory."
-    ),
-):
-  """Initialize the Get Memory Tool.
-
-  Args:
-      config: Configuration for the tool. If None, uses defaults.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      config=config or MemoryToolConfig(),
-      name=name,
-      description=description,
-  )
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(**kwargs: Any) -> dict[str, Any]
-
- -
- -

Retrieve a specific memory by ID.

- - -

Parameters:

- - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- memory_id - - -
-

The unique ID of the memory to retrieve.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status and memory details.

-
-
- - -
- Source code in src/adk_redis/tools/memory/get.py - 
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async def run_async(self, **kwargs: Any) -> dict[str, Any]:
-  """Retrieve a specific memory by ID.
-
-  Args:
-      memory_id: The unique ID of the memory to retrieve.
-
-  Returns:
-      A dictionary with status and memory details.
-  """
-  # ADK passes parameters in kwargs['args']
-  args = kwargs.get("args", kwargs)
-
-  memory_id = args.get("memory_id")
-
-  if not memory_id:
-    return {"status": "error", "message": "memory_id is required"}
-
-  try:
-    client = self._get_client()
-    memory = await client.get_long_term_memory(memory_id=memory_id)
-
-    return {
-        "status": "success",
-        "memory": {
-            "id": memory.id,
-            "content": memory.text,
-            "topics": memory.topics or [],
-            "entities": memory.entities or [],
-            "memory_type": memory.memory_type,
-            "namespace": memory.namespace,
-            "user_id": memory.user_id,
-            "session_id": memory.session_id,
-            "created_at": str(memory.created_at)
-            if memory.created_at
-            else None,
-            "last_accessed": str(memory.last_accessed)
-            if memory.last_accessed
-            else None,
-        },
-    }
-
-  except Exception as e:
-    error_msg = str(e)
-    if "not found" in error_msg.lower() or "404" in error_msg:
-      return {
-          "status": "error",
-          "message": f"Memory with ID '{memory_id}' not found",
-      }
-    logger.error("Failed to get memory: %s", e)
-    return {
-        "status": "error",
-        "message": f"Failed to get memory: {error_msg}",
-    }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- MemoryPromptTool - - -

-
MemoryPromptTool(*, config: MemoryToolConfig | None = None, name: str = 'memory_prompt', description: str = 'Enriches a prompt with relevant memories from long-term storage. Use this to provide personalized context based on past interactions.')
-
- -
-

- Bases: BaseMemoryTool

- - - -

Tool for enriching prompts with relevant memories.

-

This tool searches long-term memory for relevant context and enriches -a system prompt with the retrieved memories. It's useful for providing -the LLM with personalized context based on past interactions.

- - -
- Example - 
from adk_redis.tools.memory import MemoryPromptTool, MemoryToolConfig
-
-config = MemoryToolConfig(
-    api_base_url="http://localhost:8000",
-    default_namespace="my_app",
-)
-tool = MemoryPromptTool(config=config)
-
-# Use with ADK agent
-agent = Agent(
-    name="my_agent",
-    tools=[tool],
-)
-
-
-

Initialize the Memory Prompt Tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- config - - MemoryToolConfig | None - -
-

Configuration for the tool. If None, uses defaults.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'memory_prompt' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Enriches a prompt with relevant memories from long-term storage. Use this to provide personalized context based on past interactions.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/memory/prompt.py - 
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def __init__(
-    self,
-    *,
-    config: MemoryToolConfig | None = None,
-    name: str = "memory_prompt",
-    description: str = (
-        "Enriches a prompt with relevant memories from long-term storage. "
-        "Use this to provide personalized context based on past interactions."
-    ),
-):
-  """Initialize the Memory Prompt Tool.
-
-  Args:
-      config: Configuration for the tool. If None, uses defaults.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      config=config or MemoryToolConfig(),
-      name=name,
-      description=description,
-  )
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(**kwargs: Any) -> dict[str, Any]
-
- -
- -

Enrich a prompt with relevant memories.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- query - - -
-

The query to search for relevant memories.

-
- 		- required -
- system_prompt - - -
-

Optional base system prompt to enrich.

-
- 		- required -
- namespace - - -
-

Optional namespace override.

-
- 		- required -
- user_id - - -
-

Optional user ID override.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status and enriched_prompt.

-
-
- - -
- Source code in src/adk_redis/tools/memory/prompt.py - 
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async def run_async(self, **kwargs: Any) -> dict[str, Any]:
-  """Enrich a prompt with relevant memories.
-
-  Args:
-      query: The query to search for relevant memories.
-      system_prompt: Optional base system prompt to enrich.
-      namespace: Optional namespace override.
-      user_id: Optional user ID override.
-
-  Returns:
-      A dictionary with status and enriched_prompt.
-  """
-  # ADK passes parameters in kwargs['args']
-  args = kwargs.get("args", kwargs)
-
-  query = args.get("query")
-  system_prompt = args.get("system_prompt", "")
-  namespace = self._get_namespace(args.get("namespace"))
-  user_id = self._get_user_id(args.get("user_id"))
-
-  if not query:
-    return {"status": "error", "message": "query is required"}
-
-  try:
-    # memory_prompt requires either session_id or long_term_search
-    # We'll use long_term_search to search long-term memories
-    long_term_search = {
-        "limit": self._config.search_top_k,
-    }
-
-    client = self._get_client()
-    response = await client.memory_prompt(
-        query=query,
-        user_id=user_id,
-        namespace=namespace,
-        long_term_search=long_term_search,
-    )
-
-    # Extract the enriched prompt and combine with system prompt if provided
-    enriched_prompt = response.get("prompt", query)
-    if system_prompt:
-      enriched_prompt = f"{system_prompt}\n\n{enriched_prompt}"
-
-    memories_used = len(response.get("memories", []))
-
-    return {
-        "status": "success",
-        "enriched_prompt": enriched_prompt,
-        "memories_used": memories_used,
-    }
-
-  except Exception as e:
-    logger.error("Failed to enrich prompt: %s", e)
-    return {
-        "status": "error",
-        "message": f"Failed to enrich prompt: {str(e)}",
-    }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- MemoryToolConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Shared configuration for all Redis Agent Memory tools.

-

This configuration is used by all memory tools to connect to the -Agent Memory Server and manage memory operations.

- - -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
api_base_url - str - -
-

Base URL of the Agent Memory Server.

-
-
timeout - float - -
-

HTTP request timeout in seconds.

-
-
default_namespace - str - -
-

Default namespace for memory operations.

-
-
default_user_id - str | None - -
-

Default user ID for memory operations (optional).

-
-
search_top_k - int - -
-

Default maximum number of memories to retrieve.

-
-
distance_threshold - float | None - -
-

Maximum distance threshold for search (0.0-1.0).

-
-
recency_boost - bool - -
-

Enable recency-aware re-ranking of search results.

-
-
semantic_weight - float - -
-

Weight for semantic similarity (0.0-1.0).

-
-
recency_weight - float - -
-

Weight for recency score (0.0-1.0).

-
-
freshness_weight - float - -
-

Weight for freshness within recency score.

-
-
novelty_weight - float - -
-

Weight for novelty within recency score.

-
-
half_life_last_access_days - float - -
-

Half-life in days for last_accessed decay.

-
-
half_life_created_days - float - -
-

Half-life in days for created_at decay.

-
-
deduplicate - bool - -
-

Enable deduplication when creating memories.

-
-
- - -
- Example - 
from adk_redis.tools.memory import MemoryToolConfig
-
-config = MemoryToolConfig(
-    api_base_url="http://localhost:8000",
-    default_namespace="my_app",
-    recency_boost=True,
-)
-
-
- - - - - - - - - - -
- - - - - - - - - - - - -
- -
- -
- -
- - - -

- SearchMemoryTool - - -

-
SearchMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'search_memory', description: str = 'Searches long-term memory for relevant information. Use this to recall facts, preferences, or past interactions.')
-
- -
-

- Bases: BaseMemoryTool

- - - -

Tool for searching long-term memories.

-

This tool performs semantic search against long-term memory with optional -recency boosting. Use this when the LLM needs to recall specific information -from past interactions.

- - -
- Example - 
from adk_redis.tools.memory import SearchMemoryTool, MemoryToolConfig
-
-config = MemoryToolConfig(
-    api_base_url="http://localhost:8000",
-    default_namespace="my_app",
-    recency_boost=True,
-)
-tool = SearchMemoryTool(config=config)
-
-# Use with ADK agent
-agent = Agent(
-    name="my_agent",
-    tools=[tool],
-)
-
-
-

Initialize the Search Memory Tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- config - - MemoryToolConfig | None - -
-

Configuration for the tool. If None, uses defaults.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'search_memory' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Searches long-term memory for relevant information. Use this to recall facts, preferences, or past interactions.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/memory/search.py - 
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def __init__(
-    self,
-    *,
-    config: MemoryToolConfig | None = None,
-    name: str = "search_memory",
-    description: str = (
-        "Searches long-term memory for relevant information. "
-        "Use this to recall facts, preferences, or past interactions."
-    ),
-):
-  """Initialize the Search Memory Tool.
-
-  Args:
-      config: Configuration for the tool. If None, uses defaults.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      config=config or MemoryToolConfig(),
-      name=name,
-      description=description,
-  )
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(**kwargs: Any) -> dict[str, Any]
-
- -
- -

Search for relevant memories.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- query - - -
-

The search query.

-
- 		- required -
- limit - - -
-

Maximum number of memories to return.

-
- 		- required -
- namespace - - -
-

Optional namespace override.

-
- 		- required -
- user_id - - -
-

Optional user ID override.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status and list of memories.

-
-
- - -
- Source code in src/adk_redis/tools/memory/search.py - 
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async def run_async(self, **kwargs: Any) -> dict[str, Any]:
-  """Search for relevant memories.
-
-  Args:
-      query: The search query.
-      limit: Maximum number of memories to return.
-      namespace: Optional namespace override.
-      user_id: Optional user ID override.
-
-  Returns:
-      A dictionary with status and list of memories.
-  """
-  # ADK passes parameters in kwargs['args']
-  args = kwargs.get("args", kwargs)
-
-  query = args.get("query")
-  limit = args.get("limit", self._config.search_top_k)
-  namespace = self._get_namespace(args.get("namespace"))
-  user_id = self._get_user_id(args.get("user_id"))
-
-  if not query:
-    return {"status": "error", "message": "query is required"}
-
-  try:
-    # Use search_long_term_memory which supports namespace filtering
-    client = self._get_client()
-    from agent_memory_client.filters import Namespace
-    from agent_memory_client.filters import UserId
-
-    ns = Namespace(eq=namespace)
-    uid = UserId(eq=user_id) if user_id else None
-    response = await client.search_long_term_memory(
-        text=query,
-        namespace=ns,
-        user_id=uid,
-        distance_threshold=self._config.distance_threshold,
-        limit=limit,
-    )
-
-    # Response is a MemoryRecordResults object with .memories attribute
-    memories = []
-    for memory in response.memories:
-      memories.append(
-          {
-              "id": memory.id,
-              "content": memory.text,
-              "score": getattr(memory, "dist", 0.0),
-              "topics": memory.topics or [],
-              "memory_type": memory.memory_type,
-              "created_at": str(memory.created_at)
-              if memory.created_at
-              else None,
-          }
-      )
-
-    return {
-        "status": "success",
-        "memories": memories,
-        "count": len(memories),
-    }
-
-  except Exception as e:
-    logger.error("Failed to search memories: %s", e)
-    return {
-        "status": "error",
-        "message": f"Failed to search memories: {str(e)}",
-    }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- UpdateMemoryTool - - -

-
UpdateMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'update_memory', description: str = 'Updates an existing long-term memory. Use this when the user asks to modify or correct stored information.')
-
- -
-

- Bases: BaseMemoryTool

- - - -

Tool for updating existing long-term memories.

-

This tool allows the LLM to modify the content or metadata of existing memories. -Use this when the user asks to update or correct previously stored information.

- - -
- Example - 
from adk_redis.tools.memory import UpdateMemoryTool, MemoryToolConfig
-
-config = MemoryToolConfig(
-    api_base_url="http://localhost:8000",
-    default_namespace="my_app",
-)
-tool = UpdateMemoryTool(config=config)
-
-# Use with ADK agent
-agent = Agent(
-    name="my_agent",
-    tools=[tool],
-)
-
-
-

Initialize the Update Memory Tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- config - - MemoryToolConfig | None - -
-

Configuration for the tool. If None, uses defaults.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'update_memory' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Updates an existing long-term memory. Use this when the user asks to modify or correct stored information.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/memory/update.py - 
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def __init__(
-    self,
-    *,
-    config: MemoryToolConfig | None = None,
-    name: str = "update_memory",
-    description: str = (
-        "Updates an existing long-term memory. "
-        "Use this when the user asks to modify or correct stored information."
-    ),
-):
-  """Initialize the Update Memory Tool.
-
-  Args:
-      config: Configuration for the tool. If None, uses defaults.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      config=config or MemoryToolConfig(),
-      name=name,
-      description=description,
-  )
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(**kwargs: Any) -> dict[str, Any]
-
- -
- -

Update an existing long-term memory.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- memory_id - - -
-

The ID of the memory to update.

-
- 		- required -
- content - - -
-

New content for the memory.

-
- 		- required -
- topics - - -
-

New list of topics/tags.

-
- 		- required -
- namespace - - -
-

Optional namespace override.

-
- 		- required -
- user_id - - -
-

Optional user ID override.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status and updated memory info.

-
-
- - -
- Source code in src/adk_redis/tools/memory/update.py - 
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async def run_async(self, **kwargs: Any) -> dict[str, Any]:
-  """Update an existing long-term memory.
-
-  Args:
-      memory_id: The ID of the memory to update.
-      content: New content for the memory.
-      topics: New list of topics/tags.
-      namespace: Optional namespace override.
-      user_id: Optional user ID override.
-
-  Returns:
-      A dictionary with status and updated memory info.
-  """
-  # ADK passes parameters in kwargs['args']
-  args = kwargs.get("args", kwargs)
-
-  memory_id = args.get("memory_id")
-  content = args.get("content")
-  topics = args.get("topics")
-  self._get_namespace(args.get("namespace"))
-  self._get_user_id(args.get("user_id"))
-
-  if not memory_id:
-    return {"status": "error", "message": "memory_id is required"}
-
-  if not content and not topics:
-    return {
-        "status": "error",
-        "message": "At least one of content or topics must be provided",
-    }
-
-  try:
-    # Build updates dict - use 'text' instead of 'content'
-    updates = {}
-    if content:
-      updates["text"] = content
-    if topics is not None:
-      updates["topics"] = topics
-
-    # edit_long_term_memory only takes memory_id and updates dict
-    client = self._get_client()
-    response = await client.edit_long_term_memory(
-        memory_id=memory_id,
-        updates=updates,
-    )
-
-    return {
-        "status": "success",
-        "memory_id": response.id,
-        "message": f"Memory {response.id} updated successfully",
-    }
-
-  except Exception as e:
-    logger.error("Failed to update memory: %s", e)
-    return {
-        "status": "error",
-        "message": f"Failed to update memory: {str(e)}",
-    }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- BaseRedisSearchTool - - -

-
BaseRedisSearchTool(*, name: str, description: str, index: SearchIndex | AsyncSearchIndex, return_fields: list[str] | None = None)
-
- -
-

- Bases: BaseTool

- - - -

Base class for ALL Redis search tools using RedisVL.

-

This class provides common functionality shared by all Redis search tools: -- Index management (sync and async) -- Query execution with proper async handling -- Standard response formatting -- Error handling

-

Subclasses should use _run_search to execute queries with consistent -error handling and response formatting.

- -

Initialize the base Redis search tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- required -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- required -
- index - - SearchIndex | AsyncSearchIndex - -
-

The RedisVL SearchIndex or AsyncSearchIndex to query.

-
- 		- required -
- return_fields - - list[str] | None - -
-

Optional list of fields to return in results.

-
- 		- None -
- - - - - - - - -
- Source code in src/adk_redis/tools/search/_base.py - 
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def __init__(
-    self,
-    *,
-    name: str,
-    description: str,
-    index: SearchIndex | AsyncSearchIndex,
-    return_fields: list[str] | None = None,
-):
-  """Initialize the base Redis search tool.
-
-  Args:
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-      index: The RedisVL SearchIndex or AsyncSearchIndex to query.
-      return_fields: Optional list of fields to return in results.
-  """
-  super().__init__(name=name, description=description)
-  self._index = index
-  self._return_fields = return_fields
-  self._is_async_index = isinstance(index, AsyncSearchIndex)
-
-
- - - -
- - - - - - - - - - - - -
- -
- -
- -
- - - -

- RedisAggregatedHybridQueryConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for aggregated (client-side) Redis hybrid search queries.

-

.. deprecated:: - This config is for older Redis/RedisVL versions. For newer setups - (RedisVL >= 0.13.0, Redis >= 8.4.0), prefer RedisHybridQueryConfig - which uses native server-side hybrid search for better performance.

-

This config uses AggregateHybridQuery which performs client-side hybrid -search using FT.AGGREGATE with weighted score combination. It works with -any Redis version that has RediSearch installed.

- - -
- Recommended for -
    -
  • Redis < 8.4.0
    • -
  • RedisVL < 0.13.0
    • -
  • Environments where native FT.HYBRID is not available
    • -
-
- -
- Example - 
from adk_redis import (
-    RedisHybridSearchTool,
-    RedisAggregatedHybridQueryConfig,
-)
-
-config = RedisAggregatedHybridQueryConfig(
-    text_field_name="content",
-    alpha=0.7,  # 70% text, 30% vector
-)
-tool = RedisHybridSearchTool(index=index, vectorizer=vectorizer, config=config)
-
-
- -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
text_field_name - str - -
-

Name of the text field for BM25 search.

-
-
vector_field_name - str - -
-

Name of the vector field for similarity search.

-
-
text_scorer - str - -
-

Text scoring algorithm (default: "BM25STD").

-
-
alpha - float - -
-

Weight for text score (default: 0.7). Higher values favor -text matching over vector similarity. Combined score is: -alpha * text_score + (1 - alpha) * vector_score

-
-
num_results - int - -
-

Number of results to return.

-
-
dtype - str - -
-

Data type of the vector.

-
-
stopwords - str | set[str] | None - -
-

Stopwords to remove from query.

-
-
dialect - int - -
-

RediSearch query dialect version.

-
-
text_weights - dict[str, float] | None - -
-

Optional field weights for text scoring.

-
-
- - - - - - - - - - - -
- - - - - - - - - - -
- - -

- to_query_kwargs - - -

-
to_query_kwargs(text: str, vector: list[float], return_fields: list[str] | None = None, filter_expression: Any | None = None) -> dict[str, Any]
-
- -
- -

Convert config to AggregateHybridQuery kwargs.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- text - - str - -
-

The query text for BM25 matching.

-
- 		- required -
- vector - - list[float] - -
-

The query vector embedding.

-
- 		- required -
- return_fields - - list[str] | None - -
-

Optional list of fields to return.

-
- 		- None -
- filter_expression - - Any | None - -
-

Optional filter expression to apply.

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

Dictionary of kwargs suitable for AggregateHybridQuery constructor.

-
-
- - -
- Source code in src/adk_redis/tools/search/_config.py - 
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def to_query_kwargs(
-    self,
-    text: str,
-    vector: list[float],
-    return_fields: list[str] | None = None,
-    filter_expression: Any | None = None,
-) -> dict[str, Any]:
-  """Convert config to AggregateHybridQuery kwargs.
-
-  Args:
-      text: The query text for BM25 matching.
-      vector: The query vector embedding.
-      return_fields: Optional list of fields to return.
-      filter_expression: Optional filter expression to apply.
-
-  Returns:
-      Dictionary of kwargs suitable for AggregateHybridQuery constructor.
-  """
-  return {
-      "text": text,
-      "text_field_name": self.text_field_name,
-      "vector": vector,
-      "vector_field_name": self.vector_field_name,
-      "text_scorer": self.text_scorer,
-      "alpha": self.alpha,
-      "dtype": self.dtype,
-      "num_results": self.num_results,
-      "return_fields": return_fields,
-      "stopwords": self.stopwords,
-      "dialect": self.dialect,
-      "text_weights": self.text_weights,
-      "filter_expression": filter_expression,
-  }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisHybridQueryConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for native Redis hybrid search queries.

-

Uses Redis's native FT.HYBRID command for server-side hybrid search -combining semantic vector similarity with keyword-based BM25 text matching.

- - -
- Requirements -
    -
  • RedisVL >= 0.13.0
    • -
  • Redis >= 8.4.0
    • -
  • redis-py >= 7.1.0
    • -
-

For older Redis/RedisVL versions, use RedisAggregatedHybridQueryConfig instead.

- - -
- Example - 
from adk_redis import (
-    RedisHybridSearchTool,
-    RedisHybridQueryConfig,
-)
-
-config = RedisHybridQueryConfig(
-    text_field_name="content",
-    combination_method="LINEAR",
-    linear_alpha=0.7,  # 70% text, 30% vector
-)
-tool = RedisHybridSearchTool(index=index, vectorizer=vectorizer, config=config)
-
-
- -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
text_field_name - str - -
-

Name of the text field for BM25 search.

-
-
vector_field_name - str - -
-

Name of the vector field for similarity search.

-
-
vector_param_name - str - -
-

Name of the parameter substitution for vector blob.

-
-
text_scorer - str - -
-

Text scoring algorithm (default: "BM25STD").

-
-
yield_text_score_as - str | None - -
-

Field name to yield the text score as.

-
-
vector_search_method - str | None - -
-

Vector search method - "KNN" or "RANGE".

-
-
knn_ef_runtime - int - -
-

Exploration factor for HNSW when using KNN.

-
-
range_radius - float | None - -
-

Search radius when using RANGE vector search.

-
-
range_epsilon - float - -
-

Epsilon for RANGE search accuracy.

-
-
yield_vsim_score_as - str | None - -
-

Field name to yield vector similarity score as.

-
-
combination_method - str | None - -
-

Score combination method - "RRF" or "LINEAR".

-
-
linear_alpha - float - -
-

Weight of text score when using LINEAR (0.0-1.0).

-
-
rrf_window - int - -
-

Window size for RRF combination.

-
-
rrf_constant - int - -
-

Constant for RRF combination.

-
-
yield_combined_score_as - str | None - -
-

Field name to yield combined score as.

-
-
num_results - int - -
-

Number of results to return.

-
-
dtype - str - -
-

Data type of the vector.

-
-
stopwords - str | set[str] | None - -
-

Stopwords to remove from query.

-
-
text_weights - dict[str, float] | None - -
-

Optional field weights for text scoring.

-
-
- - - - - - - - - - - -
- - - - - - - - - - -
- - -

- to_query_kwargs - - -

-
to_query_kwargs(text: str, vector: list[float], return_fields: list[str] | None = None, filter_expression: Any | None = None) -> dict[str, Any]
-
- -
- -

Convert config to native HybridQuery kwargs.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- text - - str - -
-

The query text for BM25 matching.

-
- 		- required -
- vector - - list[float] - -
-

The query vector embedding.

-
- 		- required -
- return_fields - - list[str] | None - -
-

Optional list of fields to return.

-
- 		- None -
- filter_expression - - Any | None - -
-

Optional filter expression to apply.

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

Dictionary of kwargs suitable for HybridQuery constructor.

-
-
- - -
- Source code in src/adk_redis/tools/search/_config.py - 
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def to_query_kwargs(
-    self,
-    text: str,
-    vector: list[float],
-    return_fields: list[str] | None = None,
-    filter_expression: Any | None = None,
-) -> dict[str, Any]:
-  """Convert config to native HybridQuery kwargs.
-
-  Args:
-      text: The query text for BM25 matching.
-      vector: The query vector embedding.
-      return_fields: Optional list of fields to return.
-      filter_expression: Optional filter expression to apply.
-
-  Returns:
-      Dictionary of kwargs suitable for HybridQuery constructor.
-  """
-  return {
-      "text": text,
-      "text_field_name": self.text_field_name,
-      "vector": vector,
-      "vector_field_name": self.vector_field_name,
-      "vector_param_name": self.vector_param_name,
-      "text_scorer": self.text_scorer,
-      "yield_text_score_as": self.yield_text_score_as,
-      "vector_search_method": self.vector_search_method,
-      "knn_ef_runtime": self.knn_ef_runtime,
-      "range_radius": self.range_radius,
-      "range_epsilon": self.range_epsilon,
-      "yield_vsim_score_as": self.yield_vsim_score_as,
-      "filter_expression": filter_expression,
-      "combination_method": self.combination_method,
-      "rrf_window": self.rrf_window,
-      "rrf_constant": self.rrf_constant,
-      "linear_alpha": self.linear_alpha,
-      "yield_combined_score_as": self.yield_combined_score_as,
-      "dtype": self.dtype,
-      "num_results": self.num_results,
-      "return_fields": return_fields,
-      "stopwords": self.stopwords,
-      "text_weights": self.text_weights,
-  }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisHybridSearchTool - - -

-
RedisHybridSearchTool(*, index: SearchIndex | AsyncSearchIndex, vectorizer: BaseVectorizer, config: RedisHybridQueryConfig | RedisAggregatedHybridQueryConfig | None = None, return_fields: list[str] | None = None, filter_expression: Any | None = None, name: str = 'redis_hybrid_search', description: str = 'Search using both semantic similarity and keyword matching.')
-
- -
-

- Bases: VectorizedSearchTool

- - - -

Hybrid search tool combining vector similarity and BM25 text search.

-

This tool performs a hybrid search that combines semantic vector similarity -with keyword-based BM25 text matching. It automatically detects the installed -RedisVL version and uses the appropriate implementation:

-
    -
  • RedisVL >= 0.13.0: Uses native FT.HYBRID command (server-side fusion) - with RedisHybridQueryConfig. Requires Redis >= 8.4.0.
    • -
  • RedisVL < 0.13.0: Uses AggregateHybridQuery (client-side fusion) - with RedisAggregatedHybridQueryConfig. Works with any Redis version.
    • -
-

Example (native mode - RedisVL >= 0.13.0): - 

from adk_redis import (
-    RedisHybridSearchTool,
-    RedisHybridQueryConfig,
-)
-
-config = RedisHybridQueryConfig(
-    text_field_name="content",
-    combination_method="LINEAR",
-    linear_alpha=0.7,  # 70% text, 30% vector
-)
-tool = RedisHybridSearchTool(
-    index=index,
-    vectorizer=vectorizer,
-    config=config,
-)
-

-

Example (aggregate mode - older versions): - 

from adk_redis import (
-    RedisHybridSearchTool,
-    RedisAggregatedHybridQueryConfig,
-)
-
-config = RedisAggregatedHybridQueryConfig(
-    text_field_name="content",
-    alpha=0.7,  # 70% text, 30% vector
-)
-tool = RedisHybridSearchTool(
-    index=index,
-    vectorizer=vectorizer,
-    config=config,
-)
-

- -

Initialize the hybrid search tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- index - - SearchIndex | AsyncSearchIndex - -
-

The RedisVL SearchIndex or AsyncSearchIndex to query.

-
- 		- required -
- vectorizer - - BaseVectorizer - -
-

The vectorizer for embedding queries.

-
- 		- required -
- config - - RedisHybridQueryConfig | RedisAggregatedHybridQueryConfig | None - -
-

Configuration for query parameters. Can be either: -- RedisHybridQueryConfig: For native FT.HYBRID (RedisVL >= 0.13.0) -- RedisAggregatedHybridQueryConfig: For client-side hybrid (older) -If None, auto-detects based on installed RedisVL version.

-
- 		- None -
- return_fields - - list[str] | None - -
-

Optional list of fields to return in results.

-
- 		- None -
- filter_expression - - Any | None - -
-

Optional filter expression to narrow results.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'redis_hybrid_search' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Search using both semantic similarity and keyword matching.' -
- - -

Raises:

- - - - - - - - - - - - - -
TypeDescription
- ValueError - -
-

If RedisHybridQueryConfig is used with RedisVL < 0.13.0.

-
-
- - -

Warns:

- - - - - - - - - - - - - -
TypeDescription
- DeprecationWarning - -
-

If RedisAggregatedHybridQueryConfig is used when -native hybrid is available (RedisVL >= 0.13.0).

-
-
- - - - - - - - -
- Source code in src/adk_redis/tools/search/hybrid.py - 
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def __init__(
-    self,
-    *,
-    index: SearchIndex | AsyncSearchIndex,
-    vectorizer: BaseVectorizer,
-    config: (
-        RedisHybridQueryConfig | RedisAggregatedHybridQueryConfig | None
-    ) = None,
-    return_fields: list[str] | None = None,
-    filter_expression: Any | None = None,
-    name: str = "redis_hybrid_search",
-    description: str = "Search using both semantic similarity and keyword matching.",
-):
-  """Initialize the hybrid search tool.
-
-  Args:
-      index: The RedisVL SearchIndex or AsyncSearchIndex to query.
-      vectorizer: The vectorizer for embedding queries.
-      config: Configuration for query parameters. Can be either:
-          - RedisHybridQueryConfig: For native FT.HYBRID (RedisVL >= 0.13.0)
-          - RedisAggregatedHybridQueryConfig: For client-side hybrid (older)
-          If None, auto-detects based on installed RedisVL version.
-      return_fields: Optional list of fields to return in results.
-      filter_expression: Optional filter expression to narrow results.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-
-  Raises:
-      ValueError: If RedisHybridQueryConfig is used with RedisVL < 0.13.0.
-
-  Warns:
-      DeprecationWarning: If RedisAggregatedHybridQueryConfig is used when
-          native hybrid is available (RedisVL >= 0.13.0).
-  """
-  super().__init__(
-      name=name,
-      description=description,
-      index=index,
-      vectorizer=vectorizer,
-      return_fields=return_fields,
-  )
-
-  self._supports_native = _supports_native_hybrid(index)
-
-  # Auto-detect config if not provided
-  if config is None:
-    if self._supports_native:
-      config = RedisHybridQueryConfig()
-    else:
-      config = RedisAggregatedHybridQueryConfig()
-
-  # Validate config compatibility with installed version
-  self._use_native = isinstance(config, RedisHybridQueryConfig)
-
-  if self._use_native and not self._supports_native:
-    raise ValueError(
-        "RedisHybridQueryConfig requires RedisVL >= 0.13.0 and Redis >= "
-        f"8.4.0. Installed RedisVL version: {_get_redisvl_version()}, "
-        f"Redis server version: {_get_redis_server_version(index)}. "
-        "Use RedisAggregatedHybridQueryConfig for older versions."
-    )
-
-  if not self._use_native and self._supports_native:
-    warnings.warn(
-        "RedisAggregatedHybridQueryConfig is deprecated for RedisVL >="
-        " 0.13.0. Consider using RedisHybridQueryConfig for native FT.HYBRID"
-        " support with better performance. RedisAggregatedHybridQueryConfig"
-        " will continue to work but uses client-side score combination.",
-        DeprecationWarning,
-        stacklevel=2,
-    )
-
-  self._config = config
-  self._filter_expression = filter_expression
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any]
-
- -
- -

Execute the vector-based search query.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- args - - dict[str, Any] - -
-

Arguments from the LLM, must include 'query'.

-
- 		- required -
- tool_context - - ToolContext - -
-

The tool execution context.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status, count, and results.

-
-
- - -
- Source code in src/adk_redis/tools/search/_base.py - 
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async def run_async(
-    self, *, args: dict[str, Any], tool_context: ToolContext
-) -> dict[str, Any]:
-  """Execute the vector-based search query.
-
-  Args:
-      args: Arguments from the LLM, must include 'query'.
-      tool_context: The tool execution context.
-
-  Returns:
-      A dictionary with status, count, and results.
-  """
-
-  async def build_query_fn(query_text: str, args: dict[str, Any]) -> Any:
-    embedding = await self._vectorizer.aembed(query_text)
-    return self._build_query(query_text, embedding, **args)
-
-  return await self._run_search(args, build_query_fn)
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisRangeQueryConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for Redis vector range search queries.

-

Range search finds all documents within a specified distance threshold -from the query vector, rather than returning a fixed number of results.

- - -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
vector_field_name - str - -
-

Name of the vector field in the index.

-
-
distance_threshold - float - -
-

Maximum distance for results (default: 0.2).

-
-
num_results - int - -
-

Maximum number of results to return.

-
-
dtype - str - -
-

Data type of the vector (default: "float32").

-
-
return_score - bool - -
-

Whether to return vector distance scores.

-
-
dialect - int - -
-

RediSearch query dialect version.

-
-
sort_by - SortSpec - -
-

Field(s) to order results by.

-
-
in_order - bool - -
-

Require query terms in same order as document.

-
-
normalize_vector_distance - bool - -
-

Convert distance to 0-1 similarity score.

-
-
epsilon - float | None - -
-

Range search approximation factor for HNSW/SVS-VAMANA.

-
-
- - - - - - - - - - - -
- - - - - - - - - - -
- - -

- to_query_kwargs - - -

-
to_query_kwargs(vector: list[float], filter_expression: Any | None = None) -> dict[str, Any]
-
- -
- -

Convert config to VectorRangeQuery kwargs.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- vector - - list[float] - -
-

The query vector embedding.

-
- 		- required -
- filter_expression - - Any | None - -
-

Optional filter expression to apply.

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

Dictionary of kwargs suitable for VectorRangeQuery constructor.

-
-
- - -
- Source code in src/adk_redis/tools/search/_config.py - 
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def to_query_kwargs(
-    self, vector: list[float], filter_expression: Any | None = None
-) -> dict[str, Any]:
-  """Convert config to VectorRangeQuery kwargs.
-
-  Args:
-      vector: The query vector embedding.
-      filter_expression: Optional filter expression to apply.
-
-  Returns:
-      Dictionary of kwargs suitable for VectorRangeQuery constructor.
-  """
-  kwargs: dict[str, Any] = {
-      "vector": vector,
-      "vector_field_name": self.vector_field_name,
-      "distance_threshold": self.distance_threshold,
-      "num_results": self.num_results,
-      "dtype": self.dtype,
-      "return_score": self.return_score,
-      "dialect": self.dialect,
-      "sort_by": self.sort_by,
-      "in_order": self.in_order,
-      "normalize_vector_distance": self.normalize_vector_distance,
-      "filter_expression": filter_expression,
-  }
-
-  # Version-dependent: only include if not None
-  if self.epsilon is not None:
-    kwargs["epsilon"] = self.epsilon
-
-  return kwargs
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisRangeSearchTool - - -

-
RedisRangeSearchTool(*, index: SearchIndex | AsyncSearchIndex, vectorizer: BaseVectorizer, config: RedisRangeQueryConfig | None = None, return_fields: list[str] | None = None, filter_expression: Any | None = None, name: str = 'redis_range_search', description: str = 'Find all documents within a similarity threshold.')
-
- -
-

- Bases: VectorizedSearchTool

- - - -

Vector range search tool using distance threshold.

-

This tool finds all documents within a specified distance threshold -from the query vector. Unlike KNN search which returns a fixed number -of results, range search returns all documents that are "close enough" -based on the threshold.

- - -
- Example - 
from redisvl.index import SearchIndex
-from redisvl.utils.vectorize import HFTextVectorizer
-from adk_redis import (
-    RedisRangeSearchTool,
-    RedisRangeQueryConfig,
-)
-
-index = SearchIndex.from_yaml("schema.yaml")
-vectorizer = HFTextVectorizer(model="redis/langcache-embed-v2")
-
-# Using config object (recommended)
-config = RedisRangeQueryConfig(
-    distance_threshold=0.3,  # Only return docs within 0.3 distance
-)
-tool = RedisRangeSearchTool(
-    index=index,
-    vectorizer=vectorizer,
-    config=config,
-    return_fields=["title", "content"],
-)
-
-agent = Agent(model="gemini-2.5-flash", tools=[tool])
-
-
-

Initialize the range search tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- index - - SearchIndex | AsyncSearchIndex - -
-

The RedisVL SearchIndex or AsyncSearchIndex to query.

-
- 		- required -
- vectorizer - - BaseVectorizer - -
-

The vectorizer for embedding queries.

-
- 		- required -
- config - - RedisRangeQueryConfig | None - -
-

Configuration for query parameters. If None, uses defaults. -See RedisRangeQueryConfig for available options including -distance_threshold, vector_field_name, and epsilon.

-
- 		- None -
- return_fields - - list[str] | None - -
-

Optional list of fields to return in results.

-
- 		- None -
- filter_expression - - Any | None - -
-

Optional filter expression to narrow results.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'redis_range_search' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Find all documents within a similarity threshold.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/search/range.py - 
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def __init__(
-    self,
-    *,
-    index: SearchIndex | AsyncSearchIndex,
-    vectorizer: BaseVectorizer,
-    config: RedisRangeQueryConfig | None = None,
-    return_fields: list[str] | None = None,
-    filter_expression: Any | None = None,
-    name: str = "redis_range_search",
-    description: str = "Find all documents within a similarity threshold.",
-):
-  """Initialize the range search tool.
-
-  Args:
-      index: The RedisVL SearchIndex or AsyncSearchIndex to query.
-      vectorizer: The vectorizer for embedding queries.
-      config: Configuration for query parameters. If None, uses defaults.
-          See RedisRangeQueryConfig for available options including
-          distance_threshold, vector_field_name, and epsilon.
-      return_fields: Optional list of fields to return in results.
-      filter_expression: Optional filter expression to narrow results.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      name=name,
-      description=description,
-      index=index,
-      vectorizer=vectorizer,
-      return_fields=return_fields,
-  )
-  self._config = config or RedisRangeQueryConfig()
-  self._filter_expression = filter_expression
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any]
-
- -
- -

Execute the vector-based search query.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- args - - dict[str, Any] - -
-

Arguments from the LLM, must include 'query'.

-
- 		- required -
- tool_context - - ToolContext - -
-

The tool execution context.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status, count, and results.

-
-
- - -
- Source code in src/adk_redis/tools/search/_base.py - 
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async def run_async(
-    self, *, args: dict[str, Any], tool_context: ToolContext
-) -> dict[str, Any]:
-  """Execute the vector-based search query.
-
-  Args:
-      args: Arguments from the LLM, must include 'query'.
-      tool_context: The tool execution context.
-
-  Returns:
-      A dictionary with status, count, and results.
-  """
-
-  async def build_query_fn(query_text: str, args: dict[str, Any]) -> Any:
-    embedding = await self._vectorizer.aembed(query_text)
-    return self._build_query(query_text, embedding, **args)
-
-  return await self._run_search(args, build_query_fn)
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisSQLSearchTool - - -

-
RedisSQLSearchTool(*, index: SearchIndex | AsyncSearchIndex, sql_redis_options: dict[str, Any] | None = None, return_fields: list[str] | None = None, name: str = 'redis_sql_search', description: str = _DEFAULT_DESCRIPTION)
-
- -
-

- Bases: BaseRedisSearchTool

- - - -

Search tool that lets the LLM issue SQL SELECT statements.

-

Wraps redisvl.query.SQLQuery, which translates SQL into Redis -FT.SEARCH / FT.AGGREGATE commands via the optional sql-redis -extra. Use this when an agent benefits from expressing filters and -projections directly in SQL rather than configuring query parameters -field by field.

- - -
- Example - 
from redisvl.index import SearchIndex
-from adk_redis import RedisSQLSearchTool
-
-index = SearchIndex.from_yaml("schema.yaml")
-tool = RedisSQLSearchTool(index=index)
-
-agent = Agent(model="gemini-2.5-flash", tools=[tool])
-
-
- -
- Note -

Requires the sql-redis optional dependency. Install with -pip install 'adk-redis[sql]'.

-
-

Initialize the SQL search tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- index - - SearchIndex | AsyncSearchIndex - -
-

The RedisVL SearchIndex or AsyncSearchIndex to query.

-
- 		- required -
- sql_redis_options - - dict[str, Any] | None - -
-

Optional passthrough options forwarded to the -sql-redis executor. For example, {"schema_cache_strategy": -"load_all"} eagerly loads index schemas. The redisvl default -is lazy loading.

-
- 		- None -
- return_fields - - list[str] | None - -
-

Ignored. SQL SELECT clauses already specify the -projection. Accepted for API symmetry with sibling tools.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'redis_sql_search' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- _DEFAULT_DESCRIPTION -
- - - - - - - - -
- Source code in src/adk_redis/tools/search/sql.py - 
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def __init__(
-    self,
-    *,
-    index: SearchIndex | AsyncSearchIndex,
-    sql_redis_options: dict[str, Any] | None = None,
-    return_fields: list[str] | None = None,
-    name: str = "redis_sql_search",
-    description: str = _DEFAULT_DESCRIPTION,
-):
-  """Initialize the SQL search tool.
-
-  Args:
-      index: The RedisVL SearchIndex or AsyncSearchIndex to query.
-      sql_redis_options: Optional passthrough options forwarded to the
-          sql-redis executor. For example, ``{"schema_cache_strategy":
-          "load_all"}`` eagerly loads index schemas. The redisvl default
-          is lazy loading.
-      return_fields: Ignored. SQL SELECT clauses already specify the
-          projection. Accepted for API symmetry with sibling tools.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      name=name,
-      description=description,
-      index=index,
-      return_fields=return_fields,
-  )
-  self._sql_redis_options = sql_redis_options or {}
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any]
-
- -
- -

Execute the SQL query.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- args - - dict[str, Any] - -
-

Arguments from the LLM. Must include sql. May include -params.

-
- 		- required -
- tool_context - - ToolContext - -
-

The tool execution context.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

Dictionary with status, count, and results (or error).

-
-
- - -
- Source code in src/adk_redis/tools/search/sql.py - 
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async def run_async(
-    self, *, args: dict[str, Any], tool_context: ToolContext
-) -> dict[str, Any]:
-  """Execute the SQL query.
-
-  Args:
-      args: Arguments from the LLM. Must include ``sql``. May include
-          ``params``.
-      tool_context: The tool execution context.
-
-  Returns:
-      Dictionary with status, count, and results (or error).
-  """
-  sql_text = args.get("sql", "")
-  if not sql_text:
-    return {"status": "error", "error": "SQL statement is required."}
-
-  try:
-    query = SQLQuery(
-        sql=sql_text,
-        params=args.get("params"),
-        sql_redis_options=self._sql_redis_options or None,
-    )
-    results = await self._execute_query(query)
-    return {
-        "status": "success",
-        "count": len(results),
-        "results": results,
-    }
-  except Exception as e:  # noqa: BLE001
-    return {"status": "error", "error": str(e)}
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisTextQueryConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for Redis full-text search queries.

-

This config groups all query-specific parameters for TextQuery, -using BM25 scoring for keyword-based search.

- - -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
text_field_name - str - -
-

Name of the text field to search.

-
-
text_scorer - str - -
-

Text scoring algorithm (default: "BM25STD").

-
-
num_results - int - -
-

Number of results to return (default: 10).

-
-
return_score - bool - -
-

Whether to return the text score.

-
-
dialect - int - -
-

RediSearch query dialect version.

-
-
sort_by - SortSpec - -
-

Field(s) to order results by.

-
-
in_order - bool - -
-

Require query terms in same order as document.

-
-
stopwords - str | set[str] | None - -
-

Stopwords to remove from query (default: "english").

-
-
- - - - - - - - - - - -
- - - - - - - - - - -
- - -

- to_query_kwargs - - -

-
to_query_kwargs(text: str, return_fields: list[str] | None = None, filter_expression: Any | None = None) -> dict[str, Any]
-
- -
- -

Convert config to TextQuery kwargs.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- text - - str - -
-

The query text for BM25 matching.

-
- 		- required -
- return_fields - - list[str] | None - -
-

Optional list of fields to return.

-
- 		- None -
- filter_expression - - Any | None - -
-

Optional filter expression to apply.

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

Dictionary of kwargs suitable for TextQuery constructor.

-
-
- - -
- Source code in src/adk_redis/tools/search/_config.py - 
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def to_query_kwargs(
-    self,
-    text: str,
-    return_fields: list[str] | None = None,
-    filter_expression: Any | None = None,
-) -> dict[str, Any]:
-  """Convert config to TextQuery kwargs.
-
-  Args:
-      text: The query text for BM25 matching.
-      return_fields: Optional list of fields to return.
-      filter_expression: Optional filter expression to apply.
-
-  Returns:
-      Dictionary of kwargs suitable for TextQuery constructor.
-  """
-  return {
-      "text": text,
-      "text_field_name": self.text_field_name,
-      "text_scorer": self.text_scorer,
-      "num_results": self.num_results,
-      "return_score": self.return_score,
-      "dialect": self.dialect,
-      "sort_by": self.sort_by,
-      "in_order": self.in_order,
-      "stopwords": self.stopwords,
-      "return_fields": return_fields,
-      "filter_expression": filter_expression,
-  }
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisTextSearchTool - - -

-
RedisTextSearchTool(*, index: SearchIndex | AsyncSearchIndex, config: RedisTextQueryConfig | None = None, return_fields: list[str] | None = None, filter_expression: Any | None = None, name: str = 'redis_text_search', description: str = 'Search for documents using keyword matching.')
-
- -
-

- Bases: BaseRedisSearchTool

- - - -

Full-text search tool using BM25 scoring.

-

This tool performs keyword-based full-text search using BM25 scoring. -Unlike vector search, it doesn't require embeddings - it matches -documents based on keyword relevance.

- - -
- Example - 
from redisvl.index import SearchIndex
-from adk_redis import (
-    RedisTextSearchTool,
-    RedisTextQueryConfig,
-)
-
-index = SearchIndex.from_yaml("schema.yaml")
-
-# Using config object (recommended)
-config = RedisTextQueryConfig(
-    text_field_name="content",
-    num_results=10,
-    text_scorer="BM25STD",
-)
-tool = RedisTextSearchTool(
-    index=index,
-    config=config,
-    return_fields=["title", "content"],
-)
-
-agent = Agent(model="gemini-2.5-flash", tools=[tool])
-
-
-

Initialize the text search tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- index - - SearchIndex | AsyncSearchIndex - -
-

The RedisVL SearchIndex or AsyncSearchIndex to query.

-
- 		- required -
- config - - RedisTextQueryConfig | None - -
-

Configuration for text query parameters. If not provided, -defaults will be used.

-
- 		- None -
- return_fields - - list[str] | None - -
-

Optional list of fields to return in results.

-
- 		- None -
- filter_expression - - Any | None - -
-

Optional filter expression to narrow results.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'redis_text_search' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Search for documents using keyword matching.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/search/text.py - 
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def __init__(
-    self,
-    *,
-    index: SearchIndex | AsyncSearchIndex,
-    config: RedisTextQueryConfig | None = None,
-    return_fields: list[str] | None = None,
-    filter_expression: Any | None = None,
-    name: str = "redis_text_search",
-    description: str = "Search for documents using keyword matching.",
-):
-  """Initialize the text search tool.
-
-  Args:
-      index: The RedisVL SearchIndex or AsyncSearchIndex to query.
-      config: Configuration for text query parameters. If not provided,
-          defaults will be used.
-      return_fields: Optional list of fields to return in results.
-      filter_expression: Optional filter expression to narrow results.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      name=name,
-      description=description,
-      index=index,
-      return_fields=return_fields,
-  )
-  self._config = config or RedisTextQueryConfig()
-  self._filter_expression = filter_expression
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any]
-
- -
- -

Execute the text search query.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- args - - dict[str, Any] - -
-

Arguments from the LLM, must include 'query'.

-
- 		- required -
- tool_context - - ToolContext - -
-

The tool execution context.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status, count, and results.

-
-
- - -
- Source code in src/adk_redis/tools/search/text.py - 
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async def run_async(
-    self, *, args: dict[str, Any], tool_context: ToolContext
-) -> dict[str, Any]:
-  """Execute the text search query.
-
-  Args:
-      args: Arguments from the LLM, must include 'query'.
-      tool_context: The tool execution context.
-
-  Returns:
-      A dictionary with status, count, and results.
-  """
-
-  async def build_query_fn(
-      query_text: str, args: dict[str, Any]
-  ) -> TextQuery:
-    # Get query kwargs from config
-    query_kwargs = self._config.to_query_kwargs(
-        text=query_text,
-        return_fields=self._return_fields,
-        filter_expression=self._filter_expression,
-    )
-    # Allow LLM to override num_results
-    if "num_results" in args:
-      query_kwargs["num_results"] = args["num_results"]
-    return TextQuery(**query_kwargs)
-
-  return await self._run_search(args, build_query_fn)
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisVectorQueryConfig - - -

- - -
-

- Bases: BaseModel

- - - -

Configuration for Redis vector similarity search queries.

-

This config groups all query-specific parameters for VectorQuery, -separating them from tool-level concerns like index and vectorizer.

- - -

Attributes:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescription
vector_field_name - str - -
-

Name of the vector field in the index.

-
-
num_results - int - -
-

Number of results to return (default: 10).

-
-
dtype - str - -
-

Data type of the vector (default: "float32").

-
-
return_score - bool - -
-

Whether to return vector distance scores.

-
-
dialect - int - -
-

RediSearch query dialect version.

-
-
sort_by - SortSpec - -
-

Field(s) to order results by.

-
-
in_order - bool - -
-

Require query terms in same order as document.

-
-
normalize_vector_distance - bool - -
-

Convert distance to 0-1 similarity score.

-
-
hybrid_policy - str | None - -
-

Filter application policy - "BATCHES" or "ADHOC_BF".

-
-
batch_size - int | None - -
-

Batch size when hybrid_policy is "BATCHES".

-
-
ef_runtime - int | None - -
-

HNSW exploration factor at query time.

-
-
search_window_size - int | None - -
-

SVS-VAMANA search window size.

-
-
use_search_history - str | None - -
-

SVS-VAMANA history mode - "OFF", "ON", or "AUTO".

-
-
search_buffer_capacity - int | None - -
-

SVS-VAMANA 2-level compression tuning.

-
-
- - - - - - - - - - - -
- - - - - - - - - - -
- - -

- to_query_kwargs - - -

-
to_query_kwargs(vector: list[float], filter_expression: Any | None = None) -> dict[str, Any]
-
- -
- -

Convert config to VectorQuery kwargs, excluding None version-dependent params.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- vector - - list[float] - -
-

The query vector embedding.

-
- 		- required -
- filter_expression - - Any | None - -
-

Optional filter expression to apply.

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

Dictionary of kwargs suitable for VectorQuery constructor.

-
-
- - -
- Source code in src/adk_redis/tools/search/_config.py - 
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def to_query_kwargs(
-    self, vector: list[float], filter_expression: Any | None = None
-) -> dict[str, Any]:
-  """Convert config to VectorQuery kwargs, excluding None version-dependent params.
-
-  Args:
-      vector: The query vector embedding.
-      filter_expression: Optional filter expression to apply.
-
-  Returns:
-      Dictionary of kwargs suitable for VectorQuery constructor.
-  """
-  # Core parameters always included
-  kwargs: dict[str, Any] = {
-      "vector": vector,
-      "vector_field_name": self.vector_field_name,
-      "num_results": self.num_results,
-      "dtype": self.dtype,
-      "return_score": self.return_score,
-      "dialect": self.dialect,
-      "sort_by": self.sort_by,
-      "in_order": self.in_order,
-      "normalize_vector_distance": self.normalize_vector_distance,
-      "filter_expression": filter_expression,
-  }
-
-  # Version-dependent parameters: only include if not None
-  version_dependent = {
-      "hybrid_policy": self.hybrid_policy,
-      "batch_size": self.batch_size,
-      "ef_runtime": self.ef_runtime,
-      "search_window_size": self.search_window_size,
-      "use_search_history": self.use_search_history,
-      "search_buffer_capacity": self.search_buffer_capacity,
-  }
-  for key, value in version_dependent.items():
-    if value is not None:
-      kwargs[key] = value
-
-  return kwargs
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- RedisVectorSearchTool - - -

-
RedisVectorSearchTool(*, index: SearchIndex | AsyncSearchIndex, vectorizer: BaseVectorizer, config: RedisVectorQueryConfig | None = None, return_fields: list[str] | None = None, filter_expression: Any | None = None, name: str = 'redis_vector_search', description: str = 'Search for semantically similar documents using vector similarity with Redis.')
-
- -
-

- Bases: VectorizedSearchTool

- - - -

Vector similarity search tool using RedisVL.

-

This tool performs K-nearest neighbor (KNN) vector similarity search -over a Redis index. It embeds the query text using the provided -vectorizer and finds the most similar documents.

- - -
- Example - 
from redisvl.index import SearchIndex
-from redisvl.utils.vectorize import HFTextVectorizer
-from redisvl.query.filter import Tag
-from adk_redis import (
-    RedisVectorSearchTool,
-    RedisVectorQueryConfig,
-)
-
-index = SearchIndex.from_yaml("schema.yaml")
-vectorizer = HFTextVectorizer(model="redis/langcache-embed-v2")
-
-# Using config object (recommended)
-config = RedisVectorQueryConfig(
-    num_results=5,
-    ef_runtime=100,  # Higher = better recall
-)
-tool = RedisVectorSearchTool(
-    index=index,
-    vectorizer=vectorizer,
-    config=config,
-    return_fields=["title", "content", "url"],
-    filter_expression=Tag("category") == "redis",
-)
-
-# Use with an agent
-agent = Agent(model="gemini-2.5-flash", tools=[tool])
-
-
-

Initialize the vector search tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- index - - SearchIndex | AsyncSearchIndex - -
-

The RedisVL SearchIndex to query.

-
- 		- required -
- vectorizer - - BaseVectorizer - -
-

The vectorizer for embedding queries.

-
- 		- required -
- config - - RedisVectorQueryConfig | None - -
-

Configuration for query parameters. If None, uses defaults. -See RedisVectorQueryConfig for available options including -num_results, vector_field_name, dtype, and version-dependent -parameters like ef_runtime and hybrid_policy.

-
- 		- None -
- return_fields - - list[str] | None - -
-

Optional list of fields to return in results.

-
- 		- None -
- filter_expression - - Any | None - -
-

Optional RedisVL FilterExpression to narrow results.

-
- 		- None -
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- 'redis_vector_search' -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- 'Search for semantically similar documents using vector similarity with Redis.' -
- - - - - - - - -
- Source code in src/adk_redis/tools/search/vector.py - 
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def __init__(
-    self,
-    *,
-    index: SearchIndex | AsyncSearchIndex,
-    vectorizer: BaseVectorizer,
-    config: RedisVectorQueryConfig | None = None,
-    return_fields: list[str] | None = None,
-    filter_expression: Any | None = None,
-    name: str = "redis_vector_search",
-    description: str = "Search for semantically similar documents using vector similarity with Redis.",
-):
-  """Initialize the vector search tool.
-
-  Args:
-      index: The RedisVL SearchIndex to query.
-      vectorizer: The vectorizer for embedding queries.
-      config: Configuration for query parameters. If None, uses defaults.
-          See RedisVectorQueryConfig for available options including
-          num_results, vector_field_name, dtype, and version-dependent
-          parameters like ef_runtime and hybrid_policy.
-      return_fields: Optional list of fields to return in results.
-      filter_expression: Optional RedisVL FilterExpression to narrow results.
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-  """
-  super().__init__(
-      name=name,
-      description=description,
-      index=index,
-      vectorizer=vectorizer,
-      return_fields=return_fields,
-  )
-  self._config = config or RedisVectorQueryConfig()
-  self._filter_expression = filter_expression
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any]
-
- -
- -

Execute the vector-based search query.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- args - - dict[str, Any] - -
-

Arguments from the LLM, must include 'query'.

-
- 		- required -
- tool_context - - ToolContext - -
-

The tool execution context.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status, count, and results.

-
-
- - -
- Source code in src/adk_redis/tools/search/_base.py - 
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async def run_async(
-    self, *, args: dict[str, Any], tool_context: ToolContext
-) -> dict[str, Any]:
-  """Execute the vector-based search query.
-
-  Args:
-      args: Arguments from the LLM, must include 'query'.
-      tool_context: The tool execution context.
-
-  Returns:
-      A dictionary with status, count, and results.
-  """
-
-  async def build_query_fn(query_text: str, args: dict[str, Any]) -> Any:
-    embedding = await self._vectorizer.aembed(query_text)
-    return self._build_query(query_text, embedding, **args)
-
-  return await self._run_search(args, build_query_fn)
-
-
-
- -
- - - -
- -
- -
- -
- - - -

- VectorizedSearchTool - - -

-
VectorizedSearchTool(*, name: str, description: str, index: SearchIndex | AsyncSearchIndex, vectorizer: BaseVectorizer, return_fields: list[str] | None = None)
-
- -
-

- Bases: BaseRedisSearchTool

- - - -

Base class for Redis search tools that require vector embeddings.

-

This class extends BaseRedisSearchTool with: -- Required vectorizer for embedding queries -- Abstract _build_query method for subclasses to implement

-

Use this as the base class for vector-based search tools like -VectorSearchTool, HybridSearchTool, and RangeSearchTool.

- -

Initialize the vectorized search tool.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- name - - str - -
-

The name of the tool (exposed to LLM).

-
- 		- required -
- description - - str - -
-

The description of the tool (exposed to LLM).

-
- 		- required -
- index - - SearchIndex | AsyncSearchIndex - -
-

The RedisVL SearchIndex or AsyncSearchIndex to query.

-
- 		- required -
- vectorizer - - BaseVectorizer - -
-

The vectorizer for embedding queries (required).

-
- 		- required -
- return_fields - - list[str] | None - -
-

Optional list of fields to return in results.

-
- 		- None -
- - - - - - - - -
- Source code in src/adk_redis/tools/search/_base.py - 
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def __init__(
-    self,
-    *,
-    name: str,
-    description: str,
-    index: SearchIndex | AsyncSearchIndex,
-    vectorizer: BaseVectorizer,
-    return_fields: list[str] | None = None,
-):
-  """Initialize the vectorized search tool.
-
-  Args:
-      name: The name of the tool (exposed to LLM).
-      description: The description of the tool (exposed to LLM).
-      index: The RedisVL SearchIndex or AsyncSearchIndex to query.
-      vectorizer: The vectorizer for embedding queries (required).
-      return_fields: Optional list of fields to return in results.
-  """
-  super().__init__(
-      name=name,
-      description=description,
-      index=index,
-      return_fields=return_fields,
-  )
-  self._vectorizer = vectorizer
-
-
- - - -
- - - - - - - - - - -
- - -

- run_async - - - - async - - -

-
run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any]
-
- -
- -

Execute the vector-based search query.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- args - - dict[str, Any] - -
-

Arguments from the LLM, must include 'query'.

-
- 		- required -
- tool_context - - ToolContext - -
-

The tool execution context.

-
- 		- required -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- dict[str, Any] - -
-

A dictionary with status, count, and results.

-
-
- - -
- Source code in src/adk_redis/tools/search/_base.py - 
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async def run_async(
-    self, *, args: dict[str, Any], tool_context: ToolContext
-) -> dict[str, Any]:
-  """Execute the vector-based search query.
-
-  Args:
-      args: Arguments from the LLM, must include 'query'.
-      tool_context: The tool execution context.
-
-  Returns:
-      A dictionary with status, count, and results.
-  """
-
-  async def build_query_fn(query_text: str, args: dict[str, Any]) -> Any:
-    embedding = await self._vectorizer.aembed(query_text)
-    return self._build_query(query_text, embedding, **args)
-
-  return await self._run_search(args, build_query_fn)
-
-
-
- -
- - - -
- -
- -
- - -
- - -

- create_memory_mcp_toolset - - -

-
create_memory_mcp_toolset(server_url: str = 'http://localhost:8000', tool_filter: list[str] | None = None) -> 'McpToolset'
-
- -
- -

Create an MCP toolset for Agent Memory Server.

-

This function creates an McpToolset configured to connect to the -Agent Memory Server's SSE endpoint. The toolset provides access to -all memory operations via the Model Context Protocol.

- - -

Parameters:

- - - - - - - - - - - - - - - - - - - - - - - -
NameTypeDescriptionDefault
- server_url - - str - -
-

Base URL of the Agent Memory Server (without /sse suffix). -Default: "http://localhost:8000"

-
- 		- 'http://localhost:8000' -
- tool_filter - - list[str] | None - -
-

Optional list of tool names to expose. If None, all -available tools are exposed. Available tools: -- search_long_term_memory -- get_long_term_memory -- create_long_term_memories -- edit_long_term_memory -- delete_long_term_memories -- memory_prompt -- set_working_memory

-
- 		- None -
- - -

Returns:

- - - - - - - - - - - - - -
TypeDescription
- 'McpToolset' - -
-

McpToolset configured for Agent Memory Server.

-
-
- - -

Raises:

- - - - - - - - - - - - - -
TypeDescription
- ImportError - -
-

If google-adk is not installed with MCP support.

-
-
- - -
- Example - 
from google.adk import Agent
-from adk_redis.tools.mcp_memory import create_memory_mcp_toolset
-
-# All memory tools
-all_tools = create_memory_mcp_toolset(
-    server_url="http://localhost:8000",
-)
-
-# Only search and create tools
-limited_tools = create_memory_mcp_toolset(
-    server_url="http://localhost:8000",
-    tool_filter=["search_long_term_memory", "create_long_term_memories"],
-)
-
-agent = Agent(
-    model="gemini-2.0-flash",
-    name="memory_agent",
-    tools=[limited_tools],
-)
-
-
- -
- Source code in src/adk_redis/tools/mcp_memory.py - 
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def create_memory_mcp_toolset(
-    server_url: str = "http://localhost:8000",
-    tool_filter: list[str] | None = None,
-) -> "McpToolset":
-  """Create an MCP toolset for Agent Memory Server.
-
-  This function creates an McpToolset configured to connect to the
-  Agent Memory Server's SSE endpoint. The toolset provides access to
-  all memory operations via the Model Context Protocol.
-
-  Args:
-      server_url: Base URL of the Agent Memory Server (without /sse suffix).
-          Default: "http://localhost:8000"
-      tool_filter: Optional list of tool names to expose. If None, all
-          available tools are exposed. Available tools:
-          - search_long_term_memory
-          - get_long_term_memory
-          - create_long_term_memories
-          - edit_long_term_memory
-          - delete_long_term_memories
-          - memory_prompt
-          - set_working_memory
-
-  Returns:
-      McpToolset configured for Agent Memory Server.
-
-  Raises:
-      ImportError: If google-adk is not installed with MCP support.
-
-  Example:
-      ```python
-      from google.adk import Agent
-      from adk_redis.tools.mcp_memory import create_memory_mcp_toolset
-
-      # All memory tools
-      all_tools = create_memory_mcp_toolset(
-          server_url="http://localhost:8000",
-      )
-
-      # Only search and create tools
-      limited_tools = create_memory_mcp_toolset(
-          server_url="http://localhost:8000",
-          tool_filter=["search_long_term_memory", "create_long_term_memories"],
-      )
-
-      agent = Agent(
-          model="gemini-2.0-flash",
-          name="memory_agent",
-          tools=[limited_tools],
-      )
-      ```
-  """
-  try:
-    from google.adk.tools.mcp_tool import McpToolset
-    from google.adk.tools.mcp_tool.mcp_session_manager import (
-        SseConnectionParams,
-    )
-  except ImportError as e:
-    raise ImportError(
-        "google-adk with MCP support is required. "
-        "Install it with: pip install google-adk[mcp]"
-    ) from e
-
-  # Ensure URL doesn't have trailing slash and add /sse endpoint
-  base_url = server_url.rstrip("/")
-  sse_url = f"{base_url}/sse"
-
-  return McpToolset(
-      connection_params=SseConnectionParams(url=sse_url),
-      tool_filter=tool_filter,
-  )
-
-
-
- -
- - - -
- -
- -
- - - - - - - - - - - - - - - - -
-
- - - - - -
- - - -
- - - -
-
-
-
- -
- - - - - - - - - - - - - \ No newline at end of file diff --git a/site/api/python/tools/index.md b/site/api/python/tools/index.md deleted file mode 100644 index 3576a9a..0000000 --- a/site/api/python/tools/index.md +++ /dev/null @@ -1,2493 +0,0 @@ -# tools - -## tools - -Redis tools for ADK. - -### CreateMemoryTool - -```python -CreateMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'create_memory', description: str = 'Creates a new long-term memory. Use this when the user asks you to remember something.') -``` - -Bases: `BaseMemoryTool` - -Tool for creating new long-term memories. - -This tool allows the LLM to explicitly store information in long-term memory. Use this when the user asks to remember something specific. - -Example - -```python -from adk_redis.tools.memory import CreateMemoryTool, MemoryToolConfig - -config = MemoryToolConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", -) -tool = CreateMemoryTool(config=config) - -# Use with ADK agent -agent = Agent( - name="my_agent", - tools=[tool], -) -``` - -Initialize the Create Memory Tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------- | ------------------ | --------------------------------------------- | ------------------------------------------------------------------------------------------ | -| `config` | \`MemoryToolConfig | None\` | Configuration for the tool. If None, uses defaults. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'create_memory'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Creates a new long-term memory. Use this when the user asks you to remember something.'` | - -Source code in `src/adk_redis/tools/memory/create.py` - -```python -def __init__( - self, - *, - config: MemoryToolConfig | None = None, - name: str = "create_memory", - description: str = ( - "Creates a new long-term memory. " - "Use this when the user asks you to remember something." - ), -): - """Initialize the Create Memory Tool. - - Args: - config: Configuration for the tool. If None, uses defaults. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - config=config or MemoryToolConfig(), - name=name, - description=description, - ) -``` - -#### run_async - -```python -run_async(**kwargs: Any) -> dict[str, Any] -``` - -Create a new long-term memory. - -Parameters: - -| Name | Type | Description | Default | -| ------------- | ---- | --------------------------------------------- | ---------- | -| `content` | | The content of the memory to store. | *required* | -| `topics` | | Optional list of topics/tags. | *required* | -| `memory_type` | | Type of memory (semantic, episodic, message). | *required* | -| `namespace` | | Optional namespace override. | *required* | -| `user_id` | | Optional user ID override. | *required* | - -Returns: - -| Type | Description | -| ---------------- | --------------------------------------- | -| `dict[str, Any]` | A dictionary with status and memory_id. | - -Source code in `src/adk_redis/tools/memory/create.py` - -```python -async def run_async(self, **kwargs: Any) -> dict[str, Any]: - """Create a new long-term memory. - - Args: - content: The content of the memory to store. - topics: Optional list of topics/tags. - memory_type: Type of memory (semantic, episodic, message). - namespace: Optional namespace override. - user_id: Optional user ID override. - - Returns: - A dictionary with status and memory_id. - """ - # ADK passes parameters in kwargs['args'] - args = kwargs.get("args", kwargs) - - content = args.get("content") - topics = args.get("topics", []) - memory_type_raw = args.get("memory_type", "semantic") - namespace = self._get_namespace(args.get("namespace")) - user_id = self._get_user_id(args.get("user_id")) - - if not content: - return {"status": "error", "message": "content is required"} - - # Map invalid memory types to valid ones - # Valid types: 'semantic', 'episodic', 'message' - memory_type_map = { - "preference": "semantic", - "fact": "semantic", - "event": "episodic", - "experience": "episodic", - "conversation": "message", - } - memory_type = memory_type_map.get(memory_type_raw, memory_type_raw) - if memory_type not in ("semantic", "episodic", "message"): - memory_type = "semantic" # Default fallback - - try: - # Use add_memory_tool which creates a memory in a session context - # We'll use a temporary session ID for standalone memory creation - import uuid - - session_id = f"standalone_{uuid.uuid4().hex[:8]}" - - client = self._get_client() - response = await client.add_memory_tool( - session_id=session_id, - text=content, - memory_type=memory_type, - topics=topics if topics else None, - namespace=namespace, - user_id=user_id, - ) - - # Response is a dict with 'success' key and summary - if response.get("success"): - # Extract memory ID from summary if available, or use session_id as fallback - memory_id = response.get("memory_id", session_id) - return { - "status": "success", - "memory_id": memory_id, - "message": response.get("summary", "Memory created successfully"), - } - else: - return { - "status": "error", - "message": response.get("summary", "Failed to create memory"), - } - - except Exception as e: - logger.error("Failed to create memory: %s", e) - return { - "status": "error", - "message": f"Failed to create memory: {str(e)}", - } -``` - -### DeleteMemoryTool - -```python -DeleteMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'delete_memory', description: str = 'Deletes one or more long-term memories by ID. Use this when the user asks you to forget something.') -``` - -Bases: `BaseMemoryTool` - -Tool for deleting long-term memories. - -This tool allows the LLM to delete specific memories by ID. Use this when the user asks to forget something. - -Example - -```python -from adk_redis.tools.memory import DeleteMemoryTool, MemoryToolConfig - -config = MemoryToolConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", -) -tool = DeleteMemoryTool(config=config) - -# Use with ADK agent -agent = Agent( - name="my_agent", - tools=[tool], -) -``` - -Initialize the Delete Memory Tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------- | ------------------ | --------------------------------------------- | ------------------------------------------------------------------------------------------------------ | -| `config` | \`MemoryToolConfig | None\` | Configuration for the tool. If None, uses defaults. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'delete_memory'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Deletes one or more long-term memories by ID. Use this when the user asks you to forget something.'` | - -Source code in `src/adk_redis/tools/memory/delete.py` - -```python -def __init__( - self, - *, - config: MemoryToolConfig | None = None, - name: str = "delete_memory", - description: str = ( - "Deletes one or more long-term memories by ID. " - "Use this when the user asks you to forget something." - ), -): - """Initialize the Delete Memory Tool. - - Args: - config: Configuration for the tool. If None, uses defaults. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - config=config or MemoryToolConfig(), - name=name, - description=description, - ) -``` - -#### run_async - -```python -run_async(**kwargs: Any) -> dict[str, Any] -``` - -Delete long-term memories by ID. - -Parameters: - -| Name | Type | Description | Default | -| ------------ | ---- | ----------------------------- | ---------- | -| `memory_ids` | | List of memory IDs to delete. | *required* | -| `namespace` | | Optional namespace override. | *required* | -| `user_id` | | Optional user ID override. | *required* | - -Returns: - -| Type | Description | -| ---------------- | ------------------------------------------- | -| `dict[str, Any]` | A dictionary with status and deleted_count. | - -Source code in `src/adk_redis/tools/memory/delete.py` - -```python -async def run_async(self, **kwargs: Any) -> dict[str, Any]: - """Delete long-term memories by ID. - - Args: - memory_ids: List of memory IDs to delete. - namespace: Optional namespace override. - user_id: Optional user ID override. - - Returns: - A dictionary with status and deleted_count. - """ - # ADK passes parameters in kwargs['args'] - args = kwargs.get("args", kwargs) - - memory_ids = args.get("memory_ids", []) - self._get_namespace(args.get("namespace")) - self._get_user_id(args.get("user_id")) - - if not memory_ids: - return {"status": "error", "message": "memory_ids is required"} - - try: - # delete_long_term_memories only takes memory_ids - client = self._get_client() - response = await client.delete_long_term_memories( - memory_ids=memory_ids, - ) - - # Response is AckResponse with 'status' field containing message like "ok, deleted 2 memories" - status_msg = response.status - - # Parse the deleted count from the status message - import re - - match = re.search(r"deleted (\d+)", status_msg) - deleted_count = int(match.group(1)) if match else 0 - - is_success = "ok" in status_msg.lower() - - return { - "status": "success" if is_success else "error", - "deleted_count": deleted_count, - "message": status_msg, - } - - except Exception as e: - logger.error("Failed to delete memories: %s", e) - return { - "status": "error", - "message": f"Failed to delete memories: {str(e)}", - } -``` - -### GetMemoryTool - -```python -GetMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'get_memory', description: str = 'Retrieves a specific long-term memory by its ID. Use this when you need the full details of a known memory.') -``` - -Bases: `BaseMemoryTool` - -Tool for retrieving a specific long-term memory by ID. - -This tool allows the LLM to retrieve a specific memory when it knows the memory ID. Use this when you need to access the full details of a memory that was previously found via search. - -Example - -```python -from adk_redis.tools.memory import GetMemoryTool, MemoryToolConfig - -config = MemoryToolConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", -) -tool = GetMemoryTool(config=config) - -# Use with ADK agent -agent = Agent( - name="my_agent", - tools=[tool], -) -``` - -Initialize the Get Memory Tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------- | ------------------ | --------------------------------------------- | --------------------------------------------------------------------------------------------------------------- | -| `config` | \`MemoryToolConfig | None\` | Configuration for the tool. If None, uses defaults. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'get_memory'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Retrieves a specific long-term memory by its ID. Use this when you need the full details of a known memory.'` | - -Source code in `src/adk_redis/tools/memory/get.py` - -```python -def __init__( - self, - *, - config: MemoryToolConfig | None = None, - name: str = "get_memory", - description: str = ( - "Retrieves a specific long-term memory by its ID. " - "Use this when you need the full details of a known memory." - ), -): - """Initialize the Get Memory Tool. - - Args: - config: Configuration for the tool. If None, uses defaults. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - config=config or MemoryToolConfig(), - name=name, - description=description, - ) -``` - -#### run_async - -```python -run_async(**kwargs: Any) -> dict[str, Any] -``` - -Retrieve a specific memory by ID. - -Parameters: - -| Name | Type | Description | Default | -| ----------- | ---- | ---------------------------------------- | ---------- | -| `memory_id` | | The unique ID of the memory to retrieve. | *required* | - -Returns: - -| Type | Description | -| ---------------- | -------------------------------------------- | -| `dict[str, Any]` | A dictionary with status and memory details. | - -Source code in `src/adk_redis/tools/memory/get.py` - -```python -async def run_async(self, **kwargs: Any) -> dict[str, Any]: - """Retrieve a specific memory by ID. - - Args: - memory_id: The unique ID of the memory to retrieve. - - Returns: - A dictionary with status and memory details. - """ - # ADK passes parameters in kwargs['args'] - args = kwargs.get("args", kwargs) - - memory_id = args.get("memory_id") - - if not memory_id: - return {"status": "error", "message": "memory_id is required"} - - try: - client = self._get_client() - memory = await client.get_long_term_memory(memory_id=memory_id) - - return { - "status": "success", - "memory": { - "id": memory.id, - "content": memory.text, - "topics": memory.topics or [], - "entities": memory.entities or [], - "memory_type": memory.memory_type, - "namespace": memory.namespace, - "user_id": memory.user_id, - "session_id": memory.session_id, - "created_at": str(memory.created_at) - if memory.created_at - else None, - "last_accessed": str(memory.last_accessed) - if memory.last_accessed - else None, - }, - } - - except Exception as e: - error_msg = str(e) - if "not found" in error_msg.lower() or "404" in error_msg: - return { - "status": "error", - "message": f"Memory with ID '{memory_id}' not found", - } - logger.error("Failed to get memory: %s", e) - return { - "status": "error", - "message": f"Failed to get memory: {error_msg}", - } -``` - -### MemoryPromptTool - -```python -MemoryPromptTool(*, config: MemoryToolConfig | None = None, name: str = 'memory_prompt', description: str = 'Enriches a prompt with relevant memories from long-term storage. Use this to provide personalized context based on past interactions.') -``` - -Bases: `BaseMemoryTool` - -Tool for enriching prompts with relevant memories. - -This tool searches long-term memory for relevant context and enriches a system prompt with the retrieved memories. It's useful for providing the LLM with personalized context based on past interactions. - -Example - -```python -from adk_redis.tools.memory import MemoryPromptTool, MemoryToolConfig - -config = MemoryToolConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", -) -tool = MemoryPromptTool(config=config) - -# Use with ADK agent -agent = Agent( - name="my_agent", - tools=[tool], -) -``` - -Initialize the Memory Prompt Tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------- | ------------------ | --------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | -| `config` | \`MemoryToolConfig | None\` | Configuration for the tool. If None, uses defaults. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'memory_prompt'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Enriches a prompt with relevant memories from long-term storage. Use this to provide personalized context based on past interactions.'` | - -Source code in `src/adk_redis/tools/memory/prompt.py` - -```python -def __init__( - self, - *, - config: MemoryToolConfig | None = None, - name: str = "memory_prompt", - description: str = ( - "Enriches a prompt with relevant memories from long-term storage. " - "Use this to provide personalized context based on past interactions." - ), -): - """Initialize the Memory Prompt Tool. - - Args: - config: Configuration for the tool. If None, uses defaults. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - config=config or MemoryToolConfig(), - name=name, - description=description, - ) -``` - -#### run_async - -```python -run_async(**kwargs: Any) -> dict[str, Any] -``` - -Enrich a prompt with relevant memories. - -Parameters: - -| Name | Type | Description | Default | -| --------------- | ---- | ------------------------------------------ | ---------- | -| `query` | | The query to search for relevant memories. | *required* | -| `system_prompt` | | Optional base system prompt to enrich. | *required* | -| `namespace` | | Optional namespace override. | *required* | -| `user_id` | | Optional user ID override. | *required* | - -Returns: - -| Type | Description | -| ---------------- | --------------------------------------------- | -| `dict[str, Any]` | A dictionary with status and enriched_prompt. | - -Source code in `src/adk_redis/tools/memory/prompt.py` - -```python -async def run_async(self, **kwargs: Any) -> dict[str, Any]: - """Enrich a prompt with relevant memories. - - Args: - query: The query to search for relevant memories. - system_prompt: Optional base system prompt to enrich. - namespace: Optional namespace override. - user_id: Optional user ID override. - - Returns: - A dictionary with status and enriched_prompt. - """ - # ADK passes parameters in kwargs['args'] - args = kwargs.get("args", kwargs) - - query = args.get("query") - system_prompt = args.get("system_prompt", "") - namespace = self._get_namespace(args.get("namespace")) - user_id = self._get_user_id(args.get("user_id")) - - if not query: - return {"status": "error", "message": "query is required"} - - try: - # memory_prompt requires either session_id or long_term_search - # We'll use long_term_search to search long-term memories - long_term_search = { - "limit": self._config.search_top_k, - } - - client = self._get_client() - response = await client.memory_prompt( - query=query, - user_id=user_id, - namespace=namespace, - long_term_search=long_term_search, - ) - - # Extract the enriched prompt and combine with system prompt if provided - enriched_prompt = response.get("prompt", query) - if system_prompt: - enriched_prompt = f"{system_prompt}\n\n{enriched_prompt}" - - memories_used = len(response.get("memories", [])) - - return { - "status": "success", - "enriched_prompt": enriched_prompt, - "memories_used": memories_used, - } - - except Exception as e: - logger.error("Failed to enrich prompt: %s", e) - return { - "status": "error", - "message": f"Failed to enrich prompt: {str(e)}", - } -``` - -### MemoryToolConfig - -Bases: `BaseModel` - -Shared configuration for all Redis Agent Memory tools. - -This configuration is used by all memory tools to connect to the Agent Memory Server and manage memory operations. - -Attributes: - -| Name | Type | Description | -| ---------------------------- | ------- | -------------------------------------------------- | -| `api_base_url` | `str` | Base URL of the Agent Memory Server. | -| `timeout` | `float` | HTTP request timeout in seconds. | -| `default_namespace` | `str` | Default namespace for memory operations. | -| `default_user_id` | \`str | None\` | -| `search_top_k` | `int` | Default maximum number of memories to retrieve. | -| `distance_threshold` | \`float | None\` | -| `recency_boost` | `bool` | Enable recency-aware re-ranking of search results. | -| `semantic_weight` | `float` | Weight for semantic similarity (0.0-1.0). | -| `recency_weight` | `float` | Weight for recency score (0.0-1.0). | -| `freshness_weight` | `float` | Weight for freshness within recency score. | -| `novelty_weight` | `float` | Weight for novelty within recency score. | -| `half_life_last_access_days` | `float` | Half-life in days for last_accessed decay. | -| `half_life_created_days` | `float` | Half-life in days for created_at decay. | -| `deduplicate` | `bool` | Enable deduplication when creating memories. | - -Example - -```python -from adk_redis.tools.memory import MemoryToolConfig - -config = MemoryToolConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", - recency_boost=True, -) -``` - -### SearchMemoryTool - -```python -SearchMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'search_memory', description: str = 'Searches long-term memory for relevant information. Use this to recall facts, preferences, or past interactions.') -``` - -Bases: `BaseMemoryTool` - -Tool for searching long-term memories. - -This tool performs semantic search against long-term memory with optional recency boosting. Use this when the LLM needs to recall specific information from past interactions. - -Example - -```python -from adk_redis.tools.memory import SearchMemoryTool, MemoryToolConfig - -config = MemoryToolConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", - recency_boost=True, -) -tool = SearchMemoryTool(config=config) - -# Use with ADK agent -agent = Agent( - name="my_agent", - tools=[tool], -) -``` - -Initialize the Search Memory Tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------- | ------------------ | --------------------------------------------- | -------------------------------------------------------------------------------------------------------------------- | -| `config` | \`MemoryToolConfig | None\` | Configuration for the tool. If None, uses defaults. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'search_memory'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Searches long-term memory for relevant information. Use this to recall facts, preferences, or past interactions.'` | - -Source code in `src/adk_redis/tools/memory/search.py` - -```python -def __init__( - self, - *, - config: MemoryToolConfig | None = None, - name: str = "search_memory", - description: str = ( - "Searches long-term memory for relevant information. " - "Use this to recall facts, preferences, or past interactions." - ), -): - """Initialize the Search Memory Tool. - - Args: - config: Configuration for the tool. If None, uses defaults. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - config=config or MemoryToolConfig(), - name=name, - description=description, - ) -``` - -#### run_async - -```python -run_async(**kwargs: Any) -> dict[str, Any] -``` - -Search for relevant memories. - -Parameters: - -| Name | Type | Description | Default | -| ----------- | ---- | ------------------------------------- | ---------- | -| `query` | | The search query. | *required* | -| `limit` | | Maximum number of memories to return. | *required* | -| `namespace` | | Optional namespace override. | *required* | -| `user_id` | | Optional user ID override. | *required* | - -Returns: - -| Type | Description | -| ---------------- | ---------------------------------------------- | -| `dict[str, Any]` | A dictionary with status and list of memories. | - -Source code in `src/adk_redis/tools/memory/search.py` - -```python -async def run_async(self, **kwargs: Any) -> dict[str, Any]: - """Search for relevant memories. - - Args: - query: The search query. - limit: Maximum number of memories to return. - namespace: Optional namespace override. - user_id: Optional user ID override. - - Returns: - A dictionary with status and list of memories. - """ - # ADK passes parameters in kwargs['args'] - args = kwargs.get("args", kwargs) - - query = args.get("query") - limit = args.get("limit", self._config.search_top_k) - namespace = self._get_namespace(args.get("namespace")) - user_id = self._get_user_id(args.get("user_id")) - - if not query: - return {"status": "error", "message": "query is required"} - - try: - # Use search_long_term_memory which supports namespace filtering - client = self._get_client() - from agent_memory_client.filters import Namespace - from agent_memory_client.filters import UserId - - ns = Namespace(eq=namespace) - uid = UserId(eq=user_id) if user_id else None - response = await client.search_long_term_memory( - text=query, - namespace=ns, - user_id=uid, - distance_threshold=self._config.distance_threshold, - limit=limit, - ) - - # Response is a MemoryRecordResults object with .memories attribute - memories = [] - for memory in response.memories: - memories.append( - { - "id": memory.id, - "content": memory.text, - "score": getattr(memory, "dist", 0.0), - "topics": memory.topics or [], - "memory_type": memory.memory_type, - "created_at": str(memory.created_at) - if memory.created_at - else None, - } - ) - - return { - "status": "success", - "memories": memories, - "count": len(memories), - } - - except Exception as e: - logger.error("Failed to search memories: %s", e) - return { - "status": "error", - "message": f"Failed to search memories: {str(e)}", - } -``` - -### UpdateMemoryTool - -```python -UpdateMemoryTool(*, config: MemoryToolConfig | None = None, name: str = 'update_memory', description: str = 'Updates an existing long-term memory. Use this when the user asks to modify or correct stored information.') -``` - -Bases: `BaseMemoryTool` - -Tool for updating existing long-term memories. - -This tool allows the LLM to modify the content or metadata of existing memories. Use this when the user asks to update or correct previously stored information. - -Example - -```python -from adk_redis.tools.memory import UpdateMemoryTool, MemoryToolConfig - -config = MemoryToolConfig( - api_base_url="http://localhost:8000", - default_namespace="my_app", -) -tool = UpdateMemoryTool(config=config) - -# Use with ADK agent -agent = Agent( - name="my_agent", - tools=[tool], -) -``` - -Initialize the Update Memory Tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------- | ------------------ | --------------------------------------------- | -------------------------------------------------------------------------------------------------------------- | -| `config` | \`MemoryToolConfig | None\` | Configuration for the tool. If None, uses defaults. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'update_memory'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Updates an existing long-term memory. Use this when the user asks to modify or correct stored information.'` | - -Source code in `src/adk_redis/tools/memory/update.py` - -```python -def __init__( - self, - *, - config: MemoryToolConfig | None = None, - name: str = "update_memory", - description: str = ( - "Updates an existing long-term memory. " - "Use this when the user asks to modify or correct stored information." - ), -): - """Initialize the Update Memory Tool. - - Args: - config: Configuration for the tool. If None, uses defaults. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - config=config or MemoryToolConfig(), - name=name, - description=description, - ) -``` - -#### run_async - -```python -run_async(**kwargs: Any) -> dict[str, Any] -``` - -Update an existing long-term memory. - -Parameters: - -| Name | Type | Description | Default | -| ----------- | ---- | ------------------------------- | ---------- | -| `memory_id` | | The ID of the memory to update. | *required* | -| `content` | | New content for the memory. | *required* | -| `topics` | | New list of topics/tags. | *required* | -| `namespace` | | Optional namespace override. | *required* | -| `user_id` | | Optional user ID override. | *required* | - -Returns: - -| Type | Description | -| ---------------- | ------------------------------------------------- | -| `dict[str, Any]` | A dictionary with status and updated memory info. | - -Source code in `src/adk_redis/tools/memory/update.py` - -```python -async def run_async(self, **kwargs: Any) -> dict[str, Any]: - """Update an existing long-term memory. - - Args: - memory_id: The ID of the memory to update. - content: New content for the memory. - topics: New list of topics/tags. - namespace: Optional namespace override. - user_id: Optional user ID override. - - Returns: - A dictionary with status and updated memory info. - """ - # ADK passes parameters in kwargs['args'] - args = kwargs.get("args", kwargs) - - memory_id = args.get("memory_id") - content = args.get("content") - topics = args.get("topics") - self._get_namespace(args.get("namespace")) - self._get_user_id(args.get("user_id")) - - if not memory_id: - return {"status": "error", "message": "memory_id is required"} - - if not content and not topics: - return { - "status": "error", - "message": "At least one of content or topics must be provided", - } - - try: - # Build updates dict - use 'text' instead of 'content' - updates = {} - if content: - updates["text"] = content - if topics is not None: - updates["topics"] = topics - - # edit_long_term_memory only takes memory_id and updates dict - client = self._get_client() - response = await client.edit_long_term_memory( - memory_id=memory_id, - updates=updates, - ) - - return { - "status": "success", - "memory_id": response.id, - "message": f"Memory {response.id} updated successfully", - } - - except Exception as e: - logger.error("Failed to update memory: %s", e) - return { - "status": "error", - "message": f"Failed to update memory: {str(e)}", - } -``` - -### BaseRedisSearchTool - -```python -BaseRedisSearchTool(*, name: str, description: str, index: SearchIndex | AsyncSearchIndex, return_fields: list[str] | None = None) -``` - -Bases: `BaseTool` - -Base class for ALL Redis search tools using RedisVL. - -This class provides common functionality shared by all Redis search tools: - -- Index management (sync and async) -- Query execution with proper async handling -- Standard response formatting -- Error handling - -Subclasses should use `_run_search` to execute queries with consistent error handling and response formatting. - -Initialize the base Redis search tool. - -Parameters: - -| Name | Type | Description | Default | -| --------------- | ------------- | --------------------------------------------- | ----------------------------------------------------- | -| `name` | `str` | The name of the tool (exposed to LLM). | *required* | -| `description` | `str` | The description of the tool (exposed to LLM). | *required* | -| `index` | \`SearchIndex | AsyncSearchIndex\` | The RedisVL SearchIndex or AsyncSearchIndex to query. | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return in results. | - -Source code in `src/adk_redis/tools/search/_base.py` - -```python -def __init__( - self, - *, - name: str, - description: str, - index: SearchIndex | AsyncSearchIndex, - return_fields: list[str] | None = None, -): - """Initialize the base Redis search tool. - - Args: - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - index: The RedisVL SearchIndex or AsyncSearchIndex to query. - return_fields: Optional list of fields to return in results. - """ - super().__init__(name=name, description=description) - self._index = index - self._return_fields = return_fields - self._is_async_index = isinstance(index, AsyncSearchIndex) -``` - -### RedisAggregatedHybridQueryConfig - -Bases: `BaseModel` - -Configuration for aggregated (client-side) Redis hybrid search queries. - -.. deprecated:: This config is for older Redis/RedisVL versions. For newer setups (RedisVL >= 0.13.0, Redis >= 8.4.0), prefer RedisHybridQueryConfig which uses native server-side hybrid search for better performance. - -This config uses AggregateHybridQuery which performs client-side hybrid search using FT.AGGREGATE with weighted score combination. It works with any Redis version that has RediSearch installed. - -Recommended for - -- Redis < 8.4.0 -- RedisVL < 0.13.0 -- Environments where native FT.HYBRID is not available - -Example - -```python -from adk_redis import ( - RedisHybridSearchTool, - RedisAggregatedHybridQueryConfig, -) - -config = RedisAggregatedHybridQueryConfig( - text_field_name="content", - alpha=0.7, # 70% text, 30% vector -) -tool = RedisHybridSearchTool(index=index, vectorizer=vectorizer, config=config) -``` - -Attributes: - -| Name | Type | Description | -| ------------------- | ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -| `text_field_name` | `str` | Name of the text field for BM25 search. | -| `vector_field_name` | `str` | Name of the vector field for similarity search. | -| `text_scorer` | `str` | Text scoring algorithm (default: "BM25STD"). | -| `alpha` | `float` | Weight for text score (default: 0.7). Higher values favor text matching over vector similarity. Combined score is: alpha * text_score + (1 - alpha) * vector_score | -| `num_results` | `int` | Number of results to return. | -| `dtype` | `str` | Data type of the vector. | -| `stopwords` | \`str | set[str] | -| `dialect` | `int` | RediSearch query dialect version. | -| `text_weights` | \`dict[str, float] | None\` | - -#### to_query_kwargs - -```python -to_query_kwargs(text: str, vector: list[float], return_fields: list[str] | None = None, filter_expression: Any | None = None) -> dict[str, Any] -``` - -Convert config to AggregateHybridQuery kwargs. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ------------- | --------------------------------- | ------------------------------------ | -| `text` | `str` | The query text for BM25 matching. | *required* | -| `vector` | `list[float]` | The query vector embedding. | *required* | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return. | -| `filter_expression` | \`Any | None\` | Optional filter expression to apply. | - -Returns: - -| Type | Description | -| ---------------- | ------------------------------------------------------------------- | -| `dict[str, Any]` | Dictionary of kwargs suitable for AggregateHybridQuery constructor. | - -Source code in `src/adk_redis/tools/search/_config.py` - -```python -def to_query_kwargs( - self, - text: str, - vector: list[float], - return_fields: list[str] | None = None, - filter_expression: Any | None = None, -) -> dict[str, Any]: - """Convert config to AggregateHybridQuery kwargs. - - Args: - text: The query text for BM25 matching. - vector: The query vector embedding. - return_fields: Optional list of fields to return. - filter_expression: Optional filter expression to apply. - - Returns: - Dictionary of kwargs suitable for AggregateHybridQuery constructor. - """ - return { - "text": text, - "text_field_name": self.text_field_name, - "vector": vector, - "vector_field_name": self.vector_field_name, - "text_scorer": self.text_scorer, - "alpha": self.alpha, - "dtype": self.dtype, - "num_results": self.num_results, - "return_fields": return_fields, - "stopwords": self.stopwords, - "dialect": self.dialect, - "text_weights": self.text_weights, - "filter_expression": filter_expression, - } -``` - -### RedisHybridQueryConfig - -Bases: `BaseModel` - -Configuration for native Redis hybrid search queries. - -Uses Redis's native FT.HYBRID command for server-side hybrid search combining semantic vector similarity with keyword-based BM25 text matching. - -Requirements - -- RedisVL >= 0.13.0 -- Redis >= 8.4.0 -- redis-py >= 7.1.0 - -For older Redis/RedisVL versions, use RedisAggregatedHybridQueryConfig instead. - -Example - -```python -from adk_redis import ( - RedisHybridSearchTool, - RedisHybridQueryConfig, -) - -config = RedisHybridQueryConfig( - text_field_name="content", - combination_method="LINEAR", - linear_alpha=0.7, # 70% text, 30% vector -) -tool = RedisHybridSearchTool(index=index, vectorizer=vectorizer, config=config) -``` - -Attributes: - -| Name | Type | Description | -| ------------------------- | ------------------ | --------------------------------------------------- | -| `text_field_name` | `str` | Name of the text field for BM25 search. | -| `vector_field_name` | `str` | Name of the vector field for similarity search. | -| `vector_param_name` | `str` | Name of the parameter substitution for vector blob. | -| `text_scorer` | `str` | Text scoring algorithm (default: "BM25STD"). | -| `yield_text_score_as` | \`str | None\` | -| `vector_search_method` | \`str | None\` | -| `knn_ef_runtime` | `int` | Exploration factor for HNSW when using KNN. | -| `range_radius` | \`float | None\` | -| `range_epsilon` | `float` | Epsilon for RANGE search accuracy. | -| `yield_vsim_score_as` | \`str | None\` | -| `combination_method` | \`str | None\` | -| `linear_alpha` | `float` | Weight of text score when using LINEAR (0.0-1.0). | -| `rrf_window` | `int` | Window size for RRF combination. | -| `rrf_constant` | `int` | Constant for RRF combination. | -| `yield_combined_score_as` | \`str | None\` | -| `num_results` | `int` | Number of results to return. | -| `dtype` | `str` | Data type of the vector. | -| `stopwords` | \`str | set[str] | -| `text_weights` | \`dict[str, float] | None\` | - -#### to_query_kwargs - -```python -to_query_kwargs(text: str, vector: list[float], return_fields: list[str] | None = None, filter_expression: Any | None = None) -> dict[str, Any] -``` - -Convert config to native HybridQuery kwargs. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ------------- | --------------------------------- | ------------------------------------ | -| `text` | `str` | The query text for BM25 matching. | *required* | -| `vector` | `list[float]` | The query vector embedding. | *required* | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return. | -| `filter_expression` | \`Any | None\` | Optional filter expression to apply. | - -Returns: - -| Type | Description | -| ---------------- | ---------------------------------------------------------- | -| `dict[str, Any]` | Dictionary of kwargs suitable for HybridQuery constructor. | - -Source code in `src/adk_redis/tools/search/_config.py` - -```python -def to_query_kwargs( - self, - text: str, - vector: list[float], - return_fields: list[str] | None = None, - filter_expression: Any | None = None, -) -> dict[str, Any]: - """Convert config to native HybridQuery kwargs. - - Args: - text: The query text for BM25 matching. - vector: The query vector embedding. - return_fields: Optional list of fields to return. - filter_expression: Optional filter expression to apply. - - Returns: - Dictionary of kwargs suitable for HybridQuery constructor. - """ - return { - "text": text, - "text_field_name": self.text_field_name, - "vector": vector, - "vector_field_name": self.vector_field_name, - "vector_param_name": self.vector_param_name, - "text_scorer": self.text_scorer, - "yield_text_score_as": self.yield_text_score_as, - "vector_search_method": self.vector_search_method, - "knn_ef_runtime": self.knn_ef_runtime, - "range_radius": self.range_radius, - "range_epsilon": self.range_epsilon, - "yield_vsim_score_as": self.yield_vsim_score_as, - "filter_expression": filter_expression, - "combination_method": self.combination_method, - "rrf_window": self.rrf_window, - "rrf_constant": self.rrf_constant, - "linear_alpha": self.linear_alpha, - "yield_combined_score_as": self.yield_combined_score_as, - "dtype": self.dtype, - "num_results": self.num_results, - "return_fields": return_fields, - "stopwords": self.stopwords, - "text_weights": self.text_weights, - } -``` - -### RedisHybridSearchTool - -```python -RedisHybridSearchTool(*, index: SearchIndex | AsyncSearchIndex, vectorizer: BaseVectorizer, config: RedisHybridQueryConfig | RedisAggregatedHybridQueryConfig | None = None, return_fields: list[str] | None = None, filter_expression: Any | None = None, name: str = 'redis_hybrid_search', description: str = 'Search using both semantic similarity and keyword matching.') -``` - -Bases: `VectorizedSearchTool` - -Hybrid search tool combining vector similarity and BM25 text search. - -This tool performs a hybrid search that combines semantic vector similarity with keyword-based BM25 text matching. It automatically detects the installed RedisVL version and uses the appropriate implementation: - -- **RedisVL >= 0.13.0**: Uses native FT.HYBRID command (server-side fusion) with RedisHybridQueryConfig. Requires Redis >= 8.4.0. -- **RedisVL < 0.13.0**: Uses AggregateHybridQuery (client-side fusion) with RedisAggregatedHybridQueryConfig. Works with any Redis version. - -Example (native mode - RedisVL >= 0.13.0): - -```python -from adk_redis import ( - RedisHybridSearchTool, - RedisHybridQueryConfig, -) - -config = RedisHybridQueryConfig( - text_field_name="content", - combination_method="LINEAR", - linear_alpha=0.7, # 70% text, 30% vector -) -tool = RedisHybridSearchTool( - index=index, - vectorizer=vectorizer, - config=config, -) -``` - -Example (aggregate mode - older versions): - -```python -from adk_redis import ( - RedisHybridSearchTool, - RedisAggregatedHybridQueryConfig, -) - -config = RedisAggregatedHybridQueryConfig( - text_field_name="content", - alpha=0.7, # 70% text, 30% vector -) -tool = RedisHybridSearchTool( - index=index, - vectorizer=vectorizer, - config=config, -) -``` - -Initialize the hybrid search tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ------------------------ | --------------------------------------------- | --------------------------------------------------------------- | -| `index` | \`SearchIndex | AsyncSearchIndex\` | The RedisVL SearchIndex or AsyncSearchIndex to query. | -| `vectorizer` | `BaseVectorizer` | The vectorizer for embedding queries. | *required* | -| `config` | \`RedisHybridQueryConfig | RedisAggregatedHybridQueryConfig | None\` | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return in results. | -| `filter_expression` | \`Any | None\` | Optional filter expression to narrow results. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'redis_hybrid_search'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Search using both semantic similarity and keyword matching.'` | - -Raises: - -| Type | Description | -| ------------ | -------------------------------------------------------- | -| `ValueError` | If RedisHybridQueryConfig is used with RedisVL < 0.13.0. | - -Warns: - -| Type | Description | -| -------------------- | ------------------------------------------------------------------------------------------------ | -| `DeprecationWarning` | If RedisAggregatedHybridQueryConfig is used when native hybrid is available (RedisVL >= 0.13.0). | - -Source code in `src/adk_redis/tools/search/hybrid.py` - -```python -def __init__( - self, - *, - index: SearchIndex | AsyncSearchIndex, - vectorizer: BaseVectorizer, - config: ( - RedisHybridQueryConfig | RedisAggregatedHybridQueryConfig | None - ) = None, - return_fields: list[str] | None = None, - filter_expression: Any | None = None, - name: str = "redis_hybrid_search", - description: str = "Search using both semantic similarity and keyword matching.", -): - """Initialize the hybrid search tool. - - Args: - index: The RedisVL SearchIndex or AsyncSearchIndex to query. - vectorizer: The vectorizer for embedding queries. - config: Configuration for query parameters. Can be either: - - RedisHybridQueryConfig: For native FT.HYBRID (RedisVL >= 0.13.0) - - RedisAggregatedHybridQueryConfig: For client-side hybrid (older) - If None, auto-detects based on installed RedisVL version. - return_fields: Optional list of fields to return in results. - filter_expression: Optional filter expression to narrow results. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - - Raises: - ValueError: If RedisHybridQueryConfig is used with RedisVL < 0.13.0. - - Warns: - DeprecationWarning: If RedisAggregatedHybridQueryConfig is used when - native hybrid is available (RedisVL >= 0.13.0). - """ - super().__init__( - name=name, - description=description, - index=index, - vectorizer=vectorizer, - return_fields=return_fields, - ) - - self._supports_native = _supports_native_hybrid(index) - - # Auto-detect config if not provided - if config is None: - if self._supports_native: - config = RedisHybridQueryConfig() - else: - config = RedisAggregatedHybridQueryConfig() - - # Validate config compatibility with installed version - self._use_native = isinstance(config, RedisHybridQueryConfig) - - if self._use_native and not self._supports_native: - raise ValueError( - "RedisHybridQueryConfig requires RedisVL >= 0.13.0 and Redis >= " - f"8.4.0. Installed RedisVL version: {_get_redisvl_version()}, " - f"Redis server version: {_get_redis_server_version(index)}. " - "Use RedisAggregatedHybridQueryConfig for older versions." - ) - - if not self._use_native and self._supports_native: - warnings.warn( - "RedisAggregatedHybridQueryConfig is deprecated for RedisVL >=" - " 0.13.0. Consider using RedisHybridQueryConfig for native FT.HYBRID" - " support with better performance. RedisAggregatedHybridQueryConfig" - " will continue to work but uses client-side score combination.", - DeprecationWarning, - stacklevel=2, - ) - - self._config = config - self._filter_expression = filter_expression -``` - -#### run_async - -```python -run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any] -``` - -Execute the vector-based search query. - -Parameters: - -| Name | Type | Description | Default | -| -------------- | ---------------- | --------------------------------------------- | ---------- | -| `args` | `dict[str, Any]` | Arguments from the LLM, must include 'query'. | *required* | -| `tool_context` | `ToolContext` | The tool execution context. | *required* | - -Returns: - -| Type | Description | -| ---------------- | --------------------------------------------- | -| `dict[str, Any]` | A dictionary with status, count, and results. | - -Source code in `src/adk_redis/tools/search/_base.py` - -```python -async def run_async( - self, *, args: dict[str, Any], tool_context: ToolContext -) -> dict[str, Any]: - """Execute the vector-based search query. - - Args: - args: Arguments from the LLM, must include 'query'. - tool_context: The tool execution context. - - Returns: - A dictionary with status, count, and results. - """ - - async def build_query_fn(query_text: str, args: dict[str, Any]) -> Any: - embedding = await self._vectorizer.aembed(query_text) - return self._build_query(query_text, embedding, **args) - - return await self._run_search(args, build_query_fn) -``` - -### RedisRangeQueryConfig - -Bases: `BaseModel` - -Configuration for Redis vector range search queries. - -Range search finds all documents within a specified distance threshold from the query vector, rather than returning a fixed number of results. - -Attributes: - -| Name | Type | Description | -| --------------------------- | ---------- | ---------------------------------------------- | -| `vector_field_name` | `str` | Name of the vector field in the index. | -| `distance_threshold` | `float` | Maximum distance for results (default: 0.2). | -| `num_results` | `int` | Maximum number of results to return. | -| `dtype` | `str` | Data type of the vector (default: "float32"). | -| `return_score` | `bool` | Whether to return vector distance scores. | -| `dialect` | `int` | RediSearch query dialect version. | -| `sort_by` | `SortSpec` | Field(s) to order results by. | -| `in_order` | `bool` | Require query terms in same order as document. | -| `normalize_vector_distance` | `bool` | Convert distance to 0-1 similarity score. | -| `epsilon` | \`float | None\` | - -#### to_query_kwargs - -```python -to_query_kwargs(vector: list[float], filter_expression: Any | None = None) -> dict[str, Any] -``` - -Convert config to VectorRangeQuery kwargs. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ------------- | --------------------------- | ------------------------------------ | -| `vector` | `list[float]` | The query vector embedding. | *required* | -| `filter_expression` | \`Any | None\` | Optional filter expression to apply. | - -Returns: - -| Type | Description | -| ---------------- | --------------------------------------------------------------- | -| `dict[str, Any]` | Dictionary of kwargs suitable for VectorRangeQuery constructor. | - -Source code in `src/adk_redis/tools/search/_config.py` - -```python -def to_query_kwargs( - self, vector: list[float], filter_expression: Any | None = None -) -> dict[str, Any]: - """Convert config to VectorRangeQuery kwargs. - - Args: - vector: The query vector embedding. - filter_expression: Optional filter expression to apply. - - Returns: - Dictionary of kwargs suitable for VectorRangeQuery constructor. - """ - kwargs: dict[str, Any] = { - "vector": vector, - "vector_field_name": self.vector_field_name, - "distance_threshold": self.distance_threshold, - "num_results": self.num_results, - "dtype": self.dtype, - "return_score": self.return_score, - "dialect": self.dialect, - "sort_by": self.sort_by, - "in_order": self.in_order, - "normalize_vector_distance": self.normalize_vector_distance, - "filter_expression": filter_expression, - } - - # Version-dependent: only include if not None - if self.epsilon is not None: - kwargs["epsilon"] = self.epsilon - - return kwargs -``` - -### RedisRangeSearchTool - -```python -RedisRangeSearchTool(*, index: SearchIndex | AsyncSearchIndex, vectorizer: BaseVectorizer, config: RedisRangeQueryConfig | None = None, return_fields: list[str] | None = None, filter_expression: Any | None = None, name: str = 'redis_range_search', description: str = 'Find all documents within a similarity threshold.') -``` - -Bases: `VectorizedSearchTool` - -Vector range search tool using distance threshold. - -This tool finds all documents within a specified distance threshold from the query vector. Unlike KNN search which returns a fixed number of results, range search returns all documents that are "close enough" based on the threshold. - -Example - -```python -from redisvl.index import SearchIndex -from redisvl.utils.vectorize import HFTextVectorizer -from adk_redis import ( - RedisRangeSearchTool, - RedisRangeQueryConfig, -) - -index = SearchIndex.from_yaml("schema.yaml") -vectorizer = HFTextVectorizer(model="redis/langcache-embed-v2") - -# Using config object (recommended) -config = RedisRangeQueryConfig( - distance_threshold=0.3, # Only return docs within 0.3 distance -) -tool = RedisRangeSearchTool( - index=index, - vectorizer=vectorizer, - config=config, - return_fields=["title", "content"], -) - -agent = Agent(model="gemini-2.5-flash", tools=[tool]) -``` - -Initialize the range search tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ----------------------- | --------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `index` | \`SearchIndex | AsyncSearchIndex\` | The RedisVL SearchIndex or AsyncSearchIndex to query. | -| `vectorizer` | `BaseVectorizer` | The vectorizer for embedding queries. | *required* | -| `config` | \`RedisRangeQueryConfig | None\` | Configuration for query parameters. If None, uses defaults. See RedisRangeQueryConfig for available options including distance_threshold, vector_field_name, and epsilon. | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return in results. | -| `filter_expression` | \`Any | None\` | Optional filter expression to narrow results. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'redis_range_search'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Find all documents within a similarity threshold.'` | - -Source code in `src/adk_redis/tools/search/range.py` - -```python -def __init__( - self, - *, - index: SearchIndex | AsyncSearchIndex, - vectorizer: BaseVectorizer, - config: RedisRangeQueryConfig | None = None, - return_fields: list[str] | None = None, - filter_expression: Any | None = None, - name: str = "redis_range_search", - description: str = "Find all documents within a similarity threshold.", -): - """Initialize the range search tool. - - Args: - index: The RedisVL SearchIndex or AsyncSearchIndex to query. - vectorizer: The vectorizer for embedding queries. - config: Configuration for query parameters. If None, uses defaults. - See RedisRangeQueryConfig for available options including - distance_threshold, vector_field_name, and epsilon. - return_fields: Optional list of fields to return in results. - filter_expression: Optional filter expression to narrow results. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - name=name, - description=description, - index=index, - vectorizer=vectorizer, - return_fields=return_fields, - ) - self._config = config or RedisRangeQueryConfig() - self._filter_expression = filter_expression -``` - -#### run_async - -```python -run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any] -``` - -Execute the vector-based search query. - -Parameters: - -| Name | Type | Description | Default | -| -------------- | ---------------- | --------------------------------------------- | ---------- | -| `args` | `dict[str, Any]` | Arguments from the LLM, must include 'query'. | *required* | -| `tool_context` | `ToolContext` | The tool execution context. | *required* | - -Returns: - -| Type | Description | -| ---------------- | --------------------------------------------- | -| `dict[str, Any]` | A dictionary with status, count, and results. | - -Source code in `src/adk_redis/tools/search/_base.py` - -```python -async def run_async( - self, *, args: dict[str, Any], tool_context: ToolContext -) -> dict[str, Any]: - """Execute the vector-based search query. - - Args: - args: Arguments from the LLM, must include 'query'. - tool_context: The tool execution context. - - Returns: - A dictionary with status, count, and results. - """ - - async def build_query_fn(query_text: str, args: dict[str, Any]) -> Any: - embedding = await self._vectorizer.aembed(query_text) - return self._build_query(query_text, embedding, **args) - - return await self._run_search(args, build_query_fn) -``` - -### RedisSQLSearchTool - -```python -RedisSQLSearchTool(*, index: SearchIndex | AsyncSearchIndex, sql_redis_options: dict[str, Any] | None = None, return_fields: list[str] | None = None, name: str = 'redis_sql_search', description: str = _DEFAULT_DESCRIPTION) -``` - -Bases: `BaseRedisSearchTool` - -Search tool that lets the LLM issue SQL SELECT statements. - -Wraps `redisvl.query.SQLQuery`, which translates SQL into Redis `FT.SEARCH` / `FT.AGGREGATE` commands via the optional `sql-redis` extra. Use this when an agent benefits from expressing filters and projections directly in SQL rather than configuring query parameters field by field. - -Example - -```python -from redisvl.index import SearchIndex -from adk_redis import RedisSQLSearchTool - -index = SearchIndex.from_yaml("schema.yaml") -tool = RedisSQLSearchTool(index=index) - -agent = Agent(model="gemini-2.5-flash", tools=[tool]) -``` - -Note - -Requires the `sql-redis` optional dependency. Install with `pip install 'adk-redis[sql]'`. - -Initialize the SQL search tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ---------------- | --------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `index` | \`SearchIndex | AsyncSearchIndex\` | The RedisVL SearchIndex or AsyncSearchIndex to query. | -| `sql_redis_options` | \`dict[str, Any] | None\` | Optional passthrough options forwarded to the sql-redis executor. For example, {"schema_cache_strategy": "load_all"} eagerly loads index schemas. The redisvl default is lazy loading. | -| `return_fields` | \`list[str] | None\` | Ignored. SQL SELECT clauses already specify the projection. Accepted for API symmetry with sibling tools. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'redis_sql_search'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `_DEFAULT_DESCRIPTION` | - -Source code in `src/adk_redis/tools/search/sql.py` - -```python -def __init__( - self, - *, - index: SearchIndex | AsyncSearchIndex, - sql_redis_options: dict[str, Any] | None = None, - return_fields: list[str] | None = None, - name: str = "redis_sql_search", - description: str = _DEFAULT_DESCRIPTION, -): - """Initialize the SQL search tool. - - Args: - index: The RedisVL SearchIndex or AsyncSearchIndex to query. - sql_redis_options: Optional passthrough options forwarded to the - sql-redis executor. For example, ``{"schema_cache_strategy": - "load_all"}`` eagerly loads index schemas. The redisvl default - is lazy loading. - return_fields: Ignored. SQL SELECT clauses already specify the - projection. Accepted for API symmetry with sibling tools. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - name=name, - description=description, - index=index, - return_fields=return_fields, - ) - self._sql_redis_options = sql_redis_options or {} -``` - -#### run_async - -```python -run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any] -``` - -Execute the SQL query. - -Parameters: - -| Name | Type | Description | Default | -| -------------- | ---------------- | ------------------------------------------------------------- | ---------- | -| `args` | `dict[str, Any]` | Arguments from the LLM. Must include sql. May include params. | *required* | -| `tool_context` | `ToolContext` | The tool execution context. | *required* | - -Returns: - -| Type | Description | -| ---------------- | ------------------------------------------------------ | -| `dict[str, Any]` | Dictionary with status, count, and results (or error). | - -Source code in `src/adk_redis/tools/search/sql.py` - -```python -async def run_async( - self, *, args: dict[str, Any], tool_context: ToolContext -) -> dict[str, Any]: - """Execute the SQL query. - - Args: - args: Arguments from the LLM. Must include ``sql``. May include - ``params``. - tool_context: The tool execution context. - - Returns: - Dictionary with status, count, and results (or error). - """ - sql_text = args.get("sql", "") - if not sql_text: - return {"status": "error", "error": "SQL statement is required."} - - try: - query = SQLQuery( - sql=sql_text, - params=args.get("params"), - sql_redis_options=self._sql_redis_options or None, - ) - results = await self._execute_query(query) - return { - "status": "success", - "count": len(results), - "results": results, - } - except Exception as e: # noqa: BLE001 - return {"status": "error", "error": str(e)} -``` - -### RedisTextQueryConfig - -Bases: `BaseModel` - -Configuration for Redis full-text search queries. - -This config groups all query-specific parameters for TextQuery, using BM25 scoring for keyword-based search. - -Attributes: - -| Name | Type | Description | -| ----------------- | ---------- | ---------------------------------------------- | -| `text_field_name` | `str` | Name of the text field to search. | -| `text_scorer` | `str` | Text scoring algorithm (default: "BM25STD"). | -| `num_results` | `int` | Number of results to return (default: 10). | -| `return_score` | `bool` | Whether to return the text score. | -| `dialect` | `int` | RediSearch query dialect version. | -| `sort_by` | `SortSpec` | Field(s) to order results by. | -| `in_order` | `bool` | Require query terms in same order as document. | -| `stopwords` | \`str | set[str] | - -#### to_query_kwargs - -```python -to_query_kwargs(text: str, return_fields: list[str] | None = None, filter_expression: Any | None = None) -> dict[str, Any] -``` - -Convert config to TextQuery kwargs. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ----------- | --------------------------------- | ------------------------------------ | -| `text` | `str` | The query text for BM25 matching. | *required* | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return. | -| `filter_expression` | \`Any | None\` | Optional filter expression to apply. | - -Returns: - -| Type | Description | -| ---------------- | -------------------------------------------------------- | -| `dict[str, Any]` | Dictionary of kwargs suitable for TextQuery constructor. | - -Source code in `src/adk_redis/tools/search/_config.py` - -```python -def to_query_kwargs( - self, - text: str, - return_fields: list[str] | None = None, - filter_expression: Any | None = None, -) -> dict[str, Any]: - """Convert config to TextQuery kwargs. - - Args: - text: The query text for BM25 matching. - return_fields: Optional list of fields to return. - filter_expression: Optional filter expression to apply. - - Returns: - Dictionary of kwargs suitable for TextQuery constructor. - """ - return { - "text": text, - "text_field_name": self.text_field_name, - "text_scorer": self.text_scorer, - "num_results": self.num_results, - "return_score": self.return_score, - "dialect": self.dialect, - "sort_by": self.sort_by, - "in_order": self.in_order, - "stopwords": self.stopwords, - "return_fields": return_fields, - "filter_expression": filter_expression, - } -``` - -### RedisTextSearchTool - -```python -RedisTextSearchTool(*, index: SearchIndex | AsyncSearchIndex, config: RedisTextQueryConfig | None = None, return_fields: list[str] | None = None, filter_expression: Any | None = None, name: str = 'redis_text_search', description: str = 'Search for documents using keyword matching.') -``` - -Bases: `BaseRedisSearchTool` - -Full-text search tool using BM25 scoring. - -This tool performs keyword-based full-text search using BM25 scoring. Unlike vector search, it doesn't require embeddings - it matches documents based on keyword relevance. - -Example - -```python -from redisvl.index import SearchIndex -from adk_redis import ( - RedisTextSearchTool, - RedisTextQueryConfig, -) - -index = SearchIndex.from_yaml("schema.yaml") - -# Using config object (recommended) -config = RedisTextQueryConfig( - text_field_name="content", - num_results=10, - text_scorer="BM25STD", -) -tool = RedisTextSearchTool( - index=index, - config=config, - return_fields=["title", "content"], -) - -agent = Agent(model="gemini-2.5-flash", tools=[tool]) -``` - -Initialize the text search tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ---------------------- | --------------------------------------------- | -------------------------------------------------------------------------------- | -| `index` | \`SearchIndex | AsyncSearchIndex\` | The RedisVL SearchIndex or AsyncSearchIndex to query. | -| `config` | \`RedisTextQueryConfig | None\` | Configuration for text query parameters. If not provided, defaults will be used. | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return in results. | -| `filter_expression` | \`Any | None\` | Optional filter expression to narrow results. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'redis_text_search'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Search for documents using keyword matching.'` | - -Source code in `src/adk_redis/tools/search/text.py` - -```python -def __init__( - self, - *, - index: SearchIndex | AsyncSearchIndex, - config: RedisTextQueryConfig | None = None, - return_fields: list[str] | None = None, - filter_expression: Any | None = None, - name: str = "redis_text_search", - description: str = "Search for documents using keyword matching.", -): - """Initialize the text search tool. - - Args: - index: The RedisVL SearchIndex or AsyncSearchIndex to query. - config: Configuration for text query parameters. If not provided, - defaults will be used. - return_fields: Optional list of fields to return in results. - filter_expression: Optional filter expression to narrow results. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - name=name, - description=description, - index=index, - return_fields=return_fields, - ) - self._config = config or RedisTextQueryConfig() - self._filter_expression = filter_expression -``` - -#### run_async - -```python -run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any] -``` - -Execute the text search query. - -Parameters: - -| Name | Type | Description | Default | -| -------------- | ---------------- | --------------------------------------------- | ---------- | -| `args` | `dict[str, Any]` | Arguments from the LLM, must include 'query'. | *required* | -| `tool_context` | `ToolContext` | The tool execution context. | *required* | - -Returns: - -| Type | Description | -| ---------------- | --------------------------------------------- | -| `dict[str, Any]` | A dictionary with status, count, and results. | - -Source code in `src/adk_redis/tools/search/text.py` - -```python -async def run_async( - self, *, args: dict[str, Any], tool_context: ToolContext -) -> dict[str, Any]: - """Execute the text search query. - - Args: - args: Arguments from the LLM, must include 'query'. - tool_context: The tool execution context. - - Returns: - A dictionary with status, count, and results. - """ - - async def build_query_fn( - query_text: str, args: dict[str, Any] - ) -> TextQuery: - # Get query kwargs from config - query_kwargs = self._config.to_query_kwargs( - text=query_text, - return_fields=self._return_fields, - filter_expression=self._filter_expression, - ) - # Allow LLM to override num_results - if "num_results" in args: - query_kwargs["num_results"] = args["num_results"] - return TextQuery(**query_kwargs) - - return await self._run_search(args, build_query_fn) -``` - -### RedisVectorQueryConfig - -Bases: `BaseModel` - -Configuration for Redis vector similarity search queries. - -This config groups all query-specific parameters for VectorQuery, separating them from tool-level concerns like index and vectorizer. - -Attributes: - -| Name | Type | Description | -| --------------------------- | ---------- | ---------------------------------------------- | -| `vector_field_name` | `str` | Name of the vector field in the index. | -| `num_results` | `int` | Number of results to return (default: 10). | -| `dtype` | `str` | Data type of the vector (default: "float32"). | -| `return_score` | `bool` | Whether to return vector distance scores. | -| `dialect` | `int` | RediSearch query dialect version. | -| `sort_by` | `SortSpec` | Field(s) to order results by. | -| `in_order` | `bool` | Require query terms in same order as document. | -| `normalize_vector_distance` | `bool` | Convert distance to 0-1 similarity score. | -| `hybrid_policy` | \`str | None\` | -| `batch_size` | \`int | None\` | -| `ef_runtime` | \`int | None\` | -| `search_window_size` | \`int | None\` | -| `use_search_history` | \`str | None\` | -| `search_buffer_capacity` | \`int | None\` | - -#### to_query_kwargs - -```python -to_query_kwargs(vector: list[float], filter_expression: Any | None = None) -> dict[str, Any] -``` - -Convert config to VectorQuery kwargs, excluding None version-dependent params. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ------------- | --------------------------- | ------------------------------------ | -| `vector` | `list[float]` | The query vector embedding. | *required* | -| `filter_expression` | \`Any | None\` | Optional filter expression to apply. | - -Returns: - -| Type | Description | -| ---------------- | ---------------------------------------------------------- | -| `dict[str, Any]` | Dictionary of kwargs suitable for VectorQuery constructor. | - -Source code in `src/adk_redis/tools/search/_config.py` - -```python -def to_query_kwargs( - self, vector: list[float], filter_expression: Any | None = None -) -> dict[str, Any]: - """Convert config to VectorQuery kwargs, excluding None version-dependent params. - - Args: - vector: The query vector embedding. - filter_expression: Optional filter expression to apply. - - Returns: - Dictionary of kwargs suitable for VectorQuery constructor. - """ - # Core parameters always included - kwargs: dict[str, Any] = { - "vector": vector, - "vector_field_name": self.vector_field_name, - "num_results": self.num_results, - "dtype": self.dtype, - "return_score": self.return_score, - "dialect": self.dialect, - "sort_by": self.sort_by, - "in_order": self.in_order, - "normalize_vector_distance": self.normalize_vector_distance, - "filter_expression": filter_expression, - } - - # Version-dependent parameters: only include if not None - version_dependent = { - "hybrid_policy": self.hybrid_policy, - "batch_size": self.batch_size, - "ef_runtime": self.ef_runtime, - "search_window_size": self.search_window_size, - "use_search_history": self.use_search_history, - "search_buffer_capacity": self.search_buffer_capacity, - } - for key, value in version_dependent.items(): - if value is not None: - kwargs[key] = value - - return kwargs -``` - -### RedisVectorSearchTool - -```python -RedisVectorSearchTool(*, index: SearchIndex | AsyncSearchIndex, vectorizer: BaseVectorizer, config: RedisVectorQueryConfig | None = None, return_fields: list[str] | None = None, filter_expression: Any | None = None, name: str = 'redis_vector_search', description: str = 'Search for semantically similar documents using vector similarity with Redis.') -``` - -Bases: `VectorizedSearchTool` - -Vector similarity search tool using RedisVL. - -This tool performs K-nearest neighbor (KNN) vector similarity search over a Redis index. It embeds the query text using the provided vectorizer and finds the most similar documents. - -Example - -```python -from redisvl.index import SearchIndex -from redisvl.utils.vectorize import HFTextVectorizer -from redisvl.query.filter import Tag -from adk_redis import ( - RedisVectorSearchTool, - RedisVectorQueryConfig, -) - -index = SearchIndex.from_yaml("schema.yaml") -vectorizer = HFTextVectorizer(model="redis/langcache-embed-v2") - -# Using config object (recommended) -config = RedisVectorQueryConfig( - num_results=5, - ef_runtime=100, # Higher = better recall -) -tool = RedisVectorSearchTool( - index=index, - vectorizer=vectorizer, - config=config, - return_fields=["title", "content", "url"], - filter_expression=Tag("category") == "redis", -) - -# Use with an agent -agent = Agent(model="gemini-2.5-flash", tools=[tool]) -``` - -Initialize the vector search tool. - -Parameters: - -| Name | Type | Description | Default | -| ------------------- | ------------------------ | --------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `index` | \`SearchIndex | AsyncSearchIndex\` | The RedisVL SearchIndex to query. | -| `vectorizer` | `BaseVectorizer` | The vectorizer for embedding queries. | *required* | -| `config` | \`RedisVectorQueryConfig | None\` | Configuration for query parameters. If None, uses defaults. See RedisVectorQueryConfig for available options including num_results, vector_field_name, dtype, and version-dependent parameters like ef_runtime and hybrid_policy. | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return in results. | -| `filter_expression` | \`Any | None\` | Optional RedisVL FilterExpression to narrow results. | -| `name` | `str` | The name of the tool (exposed to LLM). | `'redis_vector_search'` | -| `description` | `str` | The description of the tool (exposed to LLM). | `'Search for semantically similar documents using vector similarity with Redis.'` | - -Source code in `src/adk_redis/tools/search/vector.py` - -```python -def __init__( - self, - *, - index: SearchIndex | AsyncSearchIndex, - vectorizer: BaseVectorizer, - config: RedisVectorQueryConfig | None = None, - return_fields: list[str] | None = None, - filter_expression: Any | None = None, - name: str = "redis_vector_search", - description: str = "Search for semantically similar documents using vector similarity with Redis.", -): - """Initialize the vector search tool. - - Args: - index: The RedisVL SearchIndex to query. - vectorizer: The vectorizer for embedding queries. - config: Configuration for query parameters. If None, uses defaults. - See RedisVectorQueryConfig for available options including - num_results, vector_field_name, dtype, and version-dependent - parameters like ef_runtime and hybrid_policy. - return_fields: Optional list of fields to return in results. - filter_expression: Optional RedisVL FilterExpression to narrow results. - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - """ - super().__init__( - name=name, - description=description, - index=index, - vectorizer=vectorizer, - return_fields=return_fields, - ) - self._config = config or RedisVectorQueryConfig() - self._filter_expression = filter_expression -``` - -#### run_async - -```python -run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any] -``` - -Execute the vector-based search query. - -Parameters: - -| Name | Type | Description | Default | -| -------------- | ---------------- | --------------------------------------------- | ---------- | -| `args` | `dict[str, Any]` | Arguments from the LLM, must include 'query'. | *required* | -| `tool_context` | `ToolContext` | The tool execution context. | *required* | - -Returns: - -| Type | Description | -| ---------------- | --------------------------------------------- | -| `dict[str, Any]` | A dictionary with status, count, and results. | - -Source code in `src/adk_redis/tools/search/_base.py` - -```python -async def run_async( - self, *, args: dict[str, Any], tool_context: ToolContext -) -> dict[str, Any]: - """Execute the vector-based search query. - - Args: - args: Arguments from the LLM, must include 'query'. - tool_context: The tool execution context. - - Returns: - A dictionary with status, count, and results. - """ - - async def build_query_fn(query_text: str, args: dict[str, Any]) -> Any: - embedding = await self._vectorizer.aembed(query_text) - return self._build_query(query_text, embedding, **args) - - return await self._run_search(args, build_query_fn) -``` - -### VectorizedSearchTool - -```python -VectorizedSearchTool(*, name: str, description: str, index: SearchIndex | AsyncSearchIndex, vectorizer: BaseVectorizer, return_fields: list[str] | None = None) -``` - -Bases: `BaseRedisSearchTool` - -Base class for Redis search tools that require vector embeddings. - -This class extends BaseRedisSearchTool with: - -- Required vectorizer for embedding queries -- Abstract \_build_query method for subclasses to implement - -Use this as the base class for vector-based search tools like VectorSearchTool, HybridSearchTool, and RangeSearchTool. - -Initialize the vectorized search tool. - -Parameters: - -| Name | Type | Description | Default | -| --------------- | ---------------- | ------------------------------------------------ | ----------------------------------------------------- | -| `name` | `str` | The name of the tool (exposed to LLM). | *required* | -| `description` | `str` | The description of the tool (exposed to LLM). | *required* | -| `index` | \`SearchIndex | AsyncSearchIndex\` | The RedisVL SearchIndex or AsyncSearchIndex to query. | -| `vectorizer` | `BaseVectorizer` | The vectorizer for embedding queries (required). | *required* | -| `return_fields` | \`list[str] | None\` | Optional list of fields to return in results. | - -Source code in `src/adk_redis/tools/search/_base.py` - -```python -def __init__( - self, - *, - name: str, - description: str, - index: SearchIndex | AsyncSearchIndex, - vectorizer: BaseVectorizer, - return_fields: list[str] | None = None, -): - """Initialize the vectorized search tool. - - Args: - name: The name of the tool (exposed to LLM). - description: The description of the tool (exposed to LLM). - index: The RedisVL SearchIndex or AsyncSearchIndex to query. - vectorizer: The vectorizer for embedding queries (required). - return_fields: Optional list of fields to return in results. - """ - super().__init__( - name=name, - description=description, - index=index, - return_fields=return_fields, - ) - self._vectorizer = vectorizer -``` - -#### run_async - -```python -run_async(*, args: dict[str, Any], tool_context: ToolContext) -> dict[str, Any] -``` - -Execute the vector-based search query. - -Parameters: - -| Name | Type | Description | Default | -| -------------- | ---------------- | --------------------------------------------- | ---------- | -| `args` | `dict[str, Any]` | Arguments from the LLM, must include 'query'. | *required* | -| `tool_context` | `ToolContext` | The tool execution context. | *required* | - -Returns: - -| Type | Description | -| ---------------- | --------------------------------------------- | -| `dict[str, Any]` | A dictionary with status, count, and results. | - -Source code in `src/adk_redis/tools/search/_base.py` - -```python -async def run_async( - self, *, args: dict[str, Any], tool_context: ToolContext -) -> dict[str, Any]: - """Execute the vector-based search query. - - Args: - args: Arguments from the LLM, must include 'query'. - tool_context: The tool execution context. - - Returns: - A dictionary with status, count, and results. - """ - - async def build_query_fn(query_text: str, args: dict[str, Any]) -> Any: - embedding = await self._vectorizer.aembed(query_text) - return self._build_query(query_text, embedding, **args) - - return await self._run_search(args, build_query_fn) -``` - -### create_memory_mcp_toolset - -```python -create_memory_mcp_toolset(server_url: str = 'http://localhost:8000', tool_filter: list[str] | None = None) -> 'McpToolset' -``` - -Create an MCP toolset for Agent Memory Server. - -This function creates an McpToolset configured to connect to the Agent Memory Server's SSE endpoint. The toolset provides access to all memory operations via the Model Context Protocol. - -Parameters: - -| Name | Type | Description | Default | -| ------------- | ----------- | ------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `server_url` | `str` | Base URL of the Agent Memory Server (without /sse suffix). Default: "http://localhost:8000" | `'http://localhost:8000'` | -| `tool_filter` | \`list[str] | None\` | Optional list of tool names to expose. If None, all available tools are exposed. Available tools: - search_long_term_memory - get_long_term_memory - create_long_term_memories - edit_long_term_memory - delete_long_term_memories - memory_prompt - set_working_memory | - -Returns: - -| Type | Description | -| -------------- | ---------------------------------------------- | -| `'McpToolset'` | McpToolset configured for Agent Memory Server. | - -Raises: - -| Type | Description | -| ------------- | ------------------------------------------------ | -| `ImportError` | If google-adk is not installed with MCP support. | - -Example - -```python -from google.adk import Agent -from adk_redis.tools.mcp_memory import create_memory_mcp_toolset - -# All memory tools -all_tools = create_memory_mcp_toolset( - server_url="http://localhost:8000", -) - -# Only search and create tools -limited_tools = create_memory_mcp_toolset( - server_url="http://localhost:8000", - tool_filter=["search_long_term_memory", "create_long_term_memories"], -) - -agent = Agent( - model="gemini-2.0-flash", - name="memory_agent", - tools=[limited_tools], -) -``` - -Source code in `src/adk_redis/tools/mcp_memory.py` - -````python -def create_memory_mcp_toolset( - server_url: str = "http://localhost:8000", - tool_filter: list[str] | None = None, -) -> "McpToolset": - """Create an MCP toolset for Agent Memory Server. - - This function creates an McpToolset configured to connect to the - Agent Memory Server's SSE endpoint. The toolset provides access to - all memory operations via the Model Context Protocol. - - Args: - server_url: Base URL of the Agent Memory Server (without /sse suffix). - Default: "http://localhost:8000" - tool_filter: Optional list of tool names to expose. If None, all - available tools are exposed. Available tools: - - search_long_term_memory - - get_long_term_memory - - create_long_term_memories - - edit_long_term_memory - - delete_long_term_memories - - memory_prompt - - set_working_memory - - Returns: - McpToolset configured for Agent Memory Server. - - Raises: - ImportError: If google-adk is not installed with MCP support. - - Example: - ```python - from google.adk import Agent - from adk_redis.tools.mcp_memory import create_memory_mcp_toolset - - # All memory tools - all_tools = create_memory_mcp_toolset( - server_url="http://localhost:8000", - ) - - # Only search and create tools - limited_tools = create_memory_mcp_toolset( - server_url="http://localhost:8000", - tool_filter=["search_long_term_memory", "create_long_term_memories"], - ) - - agent = Agent( - model="gemini-2.0-flash", - name="memory_agent", - tools=[limited_tools], - ) - ``` - """ - try: - from google.adk.tools.mcp_tool import McpToolset - from google.adk.tools.mcp_tool.mcp_session_manager import ( - SseConnectionParams, - ) - except ImportError as e: - raise ImportError( - "google-adk with MCP support is required. 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rect{fill:var(--md-mermaid-node-bg-color);stroke:var(--md-mermaid-node-fg-color)}.statediagram-state rect.divider{fill:var(--md-default-fg-color--lightest);stroke:var(--md-default-fg-color--lighter)}defs #statediagram-barbEnd{stroke:var(--md-mermaid-edge-color)}[id^=entity] path,[id^=entity] rect{fill:var(--md-default-bg-color)}.relationshipLine{stroke:var(--md-mermaid-edge-color)}defs .marker.oneOrMore.er *,defs .marker.onlyOne.er *,defs .marker.zeroOrMore.er *,defs .marker.zeroOrOne.er *{stroke:var(--md-mermaid-edge-color)!important}text:not([class]):last-child{fill:var(--md-mermaid-label-fg-color)}.actor{fill:var(--md-mermaid-sequence-actor-bg-color);stroke:var(--md-mermaid-sequence-actor-border-color)}text.actor>tspan{fill:var(--md-mermaid-sequence-actor-fg-color);font-family:var(--md-mermaid-font-family)}line{stroke:var(--md-mermaid-sequence-actor-line-color)}.actor-man circle,.actor-man 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l=[i,...M(":not(details) > [href], summary, details[open] [href]",s)],f=Math.max(0,(Math.max(0,l.indexOf(p))+l.length+(c.type==="ArrowUp"?-1:1))%l.length);l[f].focus()}c.claim();break;default:i!==Ne()&&i.focus()}}),r.pipe(g(({mode:c})=>c==="global")).subscribe(c=>{switch(c.type){case"f":case"s":case"/":i.focus(),i.select(),c.claim();break}});let a=Si(i,{worker$:n});return L(a,Oi(s,{worker$:n,query$:a})).pipe(Ve(...me("search-share",e).map(c=>Li(c,{query$:a})),...me("search-suggest",e).map(c=>Mi(c,{worker$:n,keyboard$:r}))))}catch(n){return e.hidden=!0,tt}}function Ai(e,{index$:t,location$:r}){return z([t,r.pipe(Q(we()),g(o=>!!o.searchParams.get("h")))]).pipe(m(([o,n])=>xi(o.config)(n.searchParams.get("h"))),m(o=>{var s;let n=new Map,i=document.createNodeIterator(e,NodeFilter.SHOW_TEXT);for(let a=i.nextNode();a;a=i.nextNode())if((s=a.parentElement)!=null&&s.offsetHeight){let c=a.textContent,p=o(c);p.length>c.length&&n.set(a,p)}for(let[a,c]of 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var hadFocusVisibleRecently = false;\n var hadFocusVisibleRecentlyTimeout = null;\n\n var inputTypesAllowlist = {\n text: true,\n search: true,\n url: true,\n tel: true,\n email: true,\n password: true,\n number: true,\n date: true,\n month: true,\n week: true,\n time: true,\n datetime: true,\n 'datetime-local': true\n };\n\n /**\n * Helper function for legacy browsers and iframes which sometimes focus\n * elements like document, body, and non-interactive SVG.\n * @param {Element} el\n */\n function isValidFocusTarget(el) {\n if (\n el &&\n el !== document &&\n el.nodeName !== 'HTML' &&\n el.nodeName !== 'BODY' &&\n 'classList' in el &&\n 'contains' in el.classList\n ) {\n return true;\n }\n return false;\n }\n\n /**\n * Computes whether the given element should automatically trigger the\n * `focus-visible` class being added, i.e. whether it should always match\n * `:focus-visible` when focused.\n * @param {Element} el\n * @return {boolean}\n */\n function focusTriggersKeyboardModality(el) {\n var type = el.type;\n var tagName = el.tagName;\n\n if (tagName === 'INPUT' && inputTypesAllowlist[type] && !el.readOnly) {\n return true;\n }\n\n if (tagName === 'TEXTAREA' && !el.readOnly) {\n return true;\n }\n\n if (el.isContentEditable) {\n return true;\n }\n\n return false;\n }\n\n /**\n * Add the `focus-visible` class to the given element if it was not added by\n * the author.\n * @param {Element} el\n */\n function addFocusVisibleClass(el) {\n if (el.classList.contains('focus-visible')) {\n return;\n }\n el.classList.add('focus-visible');\n el.setAttribute('data-focus-visible-added', '');\n }\n\n /**\n * Remove the `focus-visible` class from the given element if it was not\n * originally added by the author.\n * @param {Element} el\n */\n function removeFocusVisibleClass(el) {\n if (!el.hasAttribute('data-focus-visible-added')) {\n return;\n }\n el.classList.remove('focus-visible');\n el.removeAttribute('data-focus-visible-added');\n }\n\n /**\n * If the most recent user interaction was via the keyboard;\n * and the key press did not include a meta, alt/option, or control key;\n * then the modality is keyboard. Otherwise, the modality is not keyboard.\n * Apply `focus-visible` to any current active element and keep track\n * of our keyboard modality state with `hadKeyboardEvent`.\n * @param {KeyboardEvent} e\n */\n function onKeyDown(e) {\n if (e.metaKey || e.altKey || e.ctrlKey) {\n return;\n }\n\n if (isValidFocusTarget(scope.activeElement)) {\n addFocusVisibleClass(scope.activeElement);\n }\n\n hadKeyboardEvent = true;\n }\n\n /**\n * If at any point a user clicks with a pointing device, ensure that we change\n * the modality away from keyboard.\n * This avoids the situation where a user presses a key on an already focused\n * element, and then clicks on a different element, focusing it with a\n * pointing device, while we still think we're in keyboard modality.\n * @param {Event} e\n */\n function onPointerDown(e) {\n hadKeyboardEvent = false;\n }\n\n /**\n * On `focus`, add the `focus-visible` class to the target if:\n * - the target received focus as a result of keyboard navigation, or\n * - the event target is an element that will likely require interaction\n * via the keyboard (e.g. a text box)\n * @param {Event} e\n */\n function onFocus(e) {\n // Prevent IE from focusing the document or HTML element.\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (hadKeyboardEvent || focusTriggersKeyboardModality(e.target)) {\n addFocusVisibleClass(e.target);\n }\n }\n\n /**\n * On `blur`, remove the `focus-visible` class from the target.\n * @param {Event} e\n */\n function onBlur(e) {\n if (!isValidFocusTarget(e.target)) {\n return;\n }\n\n if (\n e.target.classList.contains('focus-visible') ||\n e.target.hasAttribute('data-focus-visible-added')\n ) {\n // To detect a tab/window switch, we look for a blur event followed\n // rapidly by a visibility change.\n // If we don't see a visibility change within 100ms, it's probably a\n // regular focus change.\n hadFocusVisibleRecently = true;\n window.clearTimeout(hadFocusVisibleRecentlyTimeout);\n hadFocusVisibleRecentlyTimeout = window.setTimeout(function() {\n hadFocusVisibleRecently = false;\n }, 100);\n removeFocusVisibleClass(e.target);\n }\n }\n\n /**\n * If the user changes tabs, keep track of whether or not the previously\n * focused element had .focus-visible.\n * @param {Event} e\n */\n function onVisibilityChange(e) {\n if (document.visibilityState === 'hidden') {\n // If the tab becomes active again, the browser will handle calling focus\n // on the element (Safari actually calls it twice).\n // If this tab change caused a blur on an element with focus-visible,\n // re-apply the class when the user switches back to the tab.\n if (hadFocusVisibleRecently) {\n hadKeyboardEvent = true;\n }\n addInitialPointerMoveListeners();\n }\n }\n\n /**\n * Add a group of listeners to detect usage of any pointing devices.\n * These listeners will be added when the polyfill first loads, and anytime\n * the window is blurred, so that they are active when the window regains\n * focus.\n */\n function addInitialPointerMoveListeners() {\n document.addEventListener('mousemove', onInitialPointerMove);\n document.addEventListener('mousedown', onInitialPointerMove);\n document.addEventListener('mouseup', onInitialPointerMove);\n document.addEventListener('pointermove', onInitialPointerMove);\n document.addEventListener('pointerdown', onInitialPointerMove);\n document.addEventListener('pointerup', onInitialPointerMove);\n document.addEventListener('touchmove', onInitialPointerMove);\n document.addEventListener('touchstart', onInitialPointerMove);\n document.addEventListener('touchend', onInitialPointerMove);\n }\n\n function removeInitialPointerMoveListeners() {\n document.removeEventListener('mousemove', onInitialPointerMove);\n document.removeEventListener('mousedown', onInitialPointerMove);\n document.removeEventListener('mouseup', onInitialPointerMove);\n document.removeEventListener('pointermove', onInitialPointerMove);\n document.removeEventListener('pointerdown', onInitialPointerMove);\n document.removeEventListener('pointerup', onInitialPointerMove);\n document.removeEventListener('touchmove', onInitialPointerMove);\n document.removeEventListener('touchstart', onInitialPointerMove);\n document.removeEventListener('touchend', onInitialPointerMove);\n }\n\n /**\n * When the polfyill first loads, assume the user is in keyboard modality.\n * If any event is received from a pointing device (e.g. mouse, pointer,\n * touch), turn off keyboard modality.\n * This accounts for situations where focus enters the page from the URL bar.\n * @param {Event} e\n */\n function onInitialPointerMove(e) {\n // Work around a Safari quirk that fires a mousemove on whenever the\n // window blurs, even if you're tabbing out of the page. \u00AF\\_(\u30C4)_/\u00AF\n if (e.target.nodeName && e.target.nodeName.toLowerCase() === 'html') {\n return;\n }\n\n hadKeyboardEvent = false;\n removeInitialPointerMoveListeners();\n }\n\n // For some kinds of state, we are interested in changes at the global scope\n // only. For example, global pointer input, global key presses and global\n // visibility change should affect the state at every scope:\n document.addEventListener('keydown', onKeyDown, true);\n document.addEventListener('mousedown', onPointerDown, true);\n document.addEventListener('pointerdown', onPointerDown, true);\n document.addEventListener('touchstart', onPointerDown, true);\n document.addEventListener('visibilitychange', onVisibilityChange, true);\n\n addInitialPointerMoveListeners();\n\n // For focus and blur, we specifically care about state changes in the local\n // scope. This is because focus / blur events that originate from within a\n // shadow root are not re-dispatched from the host element if it was already\n // the active element in its own scope:\n scope.addEventListener('focus', onFocus, true);\n scope.addEventListener('blur', onBlur, true);\n\n // We detect that a node is a ShadowRoot by ensuring that it is a\n // DocumentFragment and also has a host property. This check covers native\n // implementation and polyfill implementation transparently. If we only cared\n // about the native implementation, we could just check if the scope was\n // an instance of a ShadowRoot.\n if (scope.nodeType === Node.DOCUMENT_FRAGMENT_NODE && scope.host) {\n // Since a ShadowRoot is a special kind of DocumentFragment, it does not\n // have a root element to add a class to. So, we add this attribute to the\n // host element instead:\n scope.host.setAttribute('data-js-focus-visible', '');\n } else if (scope.nodeType === Node.DOCUMENT_NODE) {\n document.documentElement.classList.add('js-focus-visible');\n document.documentElement.setAttribute('data-js-focus-visible', '');\n }\n }\n\n // It is important to wrap all references to global window and document in\n // these checks to support server-side rendering use cases\n // @see https://github.com/WICG/focus-visible/issues/199\n if (typeof window !== 'undefined' && typeof document !== 'undefined') {\n // Make the polyfill helper globally available. This can be used as a signal\n // to interested libraries that wish to coordinate with the polyfill for e.g.,\n // applying the polyfill to a shadow root:\n window.applyFocusVisiblePolyfill = applyFocusVisiblePolyfill;\n\n // Notify interested libraries of the polyfill's presence, in case the\n // polyfill was loaded lazily:\n var event;\n\n try {\n event = new CustomEvent('focus-visible-polyfill-ready');\n } catch (error) {\n // IE11 does not support using CustomEvent as a constructor directly:\n event = document.createEvent('CustomEvent');\n event.initCustomEvent('focus-visible-polyfill-ready', false, false, {});\n }\n\n window.dispatchEvent(event);\n }\n\n if (typeof document !== 'undefined') {\n // Apply the polyfill to the global document, so that no JavaScript\n // coordination is required to use the polyfill in the top-level document:\n applyFocusVisiblePolyfill(document);\n }\n\n})));\n", "/*!\n * escape-html\n * Copyright(c) 2012-2013 TJ Holowaychuk\n * Copyright(c) 2015 Andreas Lubbe\n * Copyright(c) 2015 Tiancheng \"Timothy\" Gu\n * MIT Licensed\n */\n\n'use strict';\n\n/**\n * Module variables.\n * @private\n */\n\nvar matchHtmlRegExp = /[\"'&<>]/;\n\n/**\n * Module exports.\n * @public\n */\n\nmodule.exports = escapeHtml;\n\n/**\n * Escape special characters in the given string of html.\n *\n * @param {string} string The string to escape for inserting into HTML\n * @return {string}\n * @public\n */\n\nfunction escapeHtml(string) {\n var str = '' + string;\n var match = matchHtmlRegExp.exec(str);\n\n if (!match) {\n return str;\n }\n\n var escape;\n var html = '';\n var index = 0;\n var lastIndex = 0;\n\n for (index = match.index; index < str.length; index++) {\n switch (str.charCodeAt(index)) {\n case 34: // \"\n escape = '"';\n break;\n case 38: // &\n escape = '&';\n break;\n case 39: // '\n escape = ''';\n break;\n case 60: // <\n escape = '<';\n break;\n case 62: // >\n escape = '>';\n break;\n default:\n continue;\n }\n\n if (lastIndex !== index) {\n html += str.substring(lastIndex, index);\n }\n\n lastIndex = index + 1;\n html += escape;\n }\n\n return lastIndex !== index\n ? html + str.substring(lastIndex, index)\n : html;\n}\n", "/*!\n * clipboard.js v2.0.11\n * https://clipboardjs.com/\n *\n * Licensed MIT \u00A9 Zeno Rocha\n */\n(function webpackUniversalModuleDefinition(root, factory) {\n\tif(typeof exports === 'object' && typeof module === 'object')\n\t\tmodule.exports = factory();\n\telse if(typeof define === 'function' && define.amd)\n\t\tdefine([], factory);\n\telse if(typeof exports === 'object')\n\t\texports[\"ClipboardJS\"] = factory();\n\telse\n\t\troot[\"ClipboardJS\"] = factory();\n})(this, function() {\nreturn /******/ (function() { // webpackBootstrap\n/******/ \tvar __webpack_modules__ = ({\n\n/***/ 686:\n/***/ (function(__unused_webpack_module, __webpack_exports__, __webpack_require__) {\n\n\"use strict\";\n\n// EXPORTS\n__webpack_require__.d(__webpack_exports__, {\n \"default\": function() { return /* binding */ clipboard; }\n});\n\n// EXTERNAL MODULE: ./node_modules/tiny-emitter/index.js\nvar tiny_emitter = __webpack_require__(279);\nvar tiny_emitter_default = /*#__PURE__*/__webpack_require__.n(tiny_emitter);\n// EXTERNAL MODULE: ./node_modules/good-listener/src/listen.js\nvar listen = __webpack_require__(370);\nvar listen_default = /*#__PURE__*/__webpack_require__.n(listen);\n// EXTERNAL MODULE: ./node_modules/select/src/select.js\nvar src_select = __webpack_require__(817);\nvar select_default = /*#__PURE__*/__webpack_require__.n(src_select);\n;// CONCATENATED MODULE: ./src/common/command.js\n/**\n * Executes a given operation type.\n * @param {String} type\n * @return {Boolean}\n */\nfunction command(type) {\n try {\n return document.execCommand(type);\n } catch (err) {\n return false;\n }\n}\n;// CONCATENATED MODULE: ./src/actions/cut.js\n\n\n/**\n * Cut action wrapper.\n * @param {String|HTMLElement} target\n * @return {String}\n */\n\nvar ClipboardActionCut = function ClipboardActionCut(target) {\n var selectedText = select_default()(target);\n command('cut');\n return selectedText;\n};\n\n/* harmony default export */ var actions_cut = (ClipboardActionCut);\n;// CONCATENATED MODULE: ./src/common/create-fake-element.js\n/**\n * Creates a fake textarea element with a value.\n * @param {String} value\n * @return {HTMLElement}\n */\nfunction createFakeElement(value) {\n var isRTL = document.documentElement.getAttribute('dir') === 'rtl';\n var fakeElement = document.createElement('textarea'); // Prevent zooming on iOS\n\n fakeElement.style.fontSize = '12pt'; // Reset box model\n\n fakeElement.style.border = '0';\n fakeElement.style.padding = '0';\n fakeElement.style.margin = '0'; // Move element out of screen horizontally\n\n fakeElement.style.position = 'absolute';\n fakeElement.style[isRTL ? 'right' : 'left'] = '-9999px'; // Move element to the same position vertically\n\n var yPosition = window.pageYOffset || document.documentElement.scrollTop;\n fakeElement.style.top = \"\".concat(yPosition, \"px\");\n fakeElement.setAttribute('readonly', '');\n fakeElement.value = value;\n return fakeElement;\n}\n;// CONCATENATED MODULE: ./src/actions/copy.js\n\n\n\n/**\n * Create fake copy action wrapper using a fake element.\n * @param {String} target\n * @param {Object} options\n * @return {String}\n */\n\nvar fakeCopyAction = function fakeCopyAction(value, options) {\n var fakeElement = createFakeElement(value);\n options.container.appendChild(fakeElement);\n var selectedText = select_default()(fakeElement);\n command('copy');\n fakeElement.remove();\n return selectedText;\n};\n/**\n * Copy action wrapper.\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @return {String}\n */\n\n\nvar ClipboardActionCopy = function ClipboardActionCopy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n var selectedText = '';\n\n if (typeof target === 'string') {\n selectedText = fakeCopyAction(target, options);\n } else if (target instanceof HTMLInputElement && !['text', 'search', 'url', 'tel', 'password'].includes(target === null || target === void 0 ? void 0 : target.type)) {\n // If input type doesn't support `setSelectionRange`. Simulate it. https://developer.mozilla.org/en-US/docs/Web/API/HTMLInputElement/setSelectionRange\n selectedText = fakeCopyAction(target.value, options);\n } else {\n selectedText = select_default()(target);\n command('copy');\n }\n\n return selectedText;\n};\n\n/* harmony default export */ var actions_copy = (ClipboardActionCopy);\n;// CONCATENATED MODULE: ./src/actions/default.js\nfunction _typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { _typeof = function _typeof(obj) { return typeof obj; }; } else { _typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return _typeof(obj); }\n\n\n\n/**\n * Inner function which performs selection from either `text` or `target`\n * properties and then executes copy or cut operations.\n * @param {Object} options\n */\n\nvar ClipboardActionDefault = function ClipboardActionDefault() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n // Defines base properties passed from constructor.\n var _options$action = options.action,\n action = _options$action === void 0 ? 'copy' : _options$action,\n container = options.container,\n target = options.target,\n text = options.text; // Sets the `action` to be performed which can be either 'copy' or 'cut'.\n\n if (action !== 'copy' && action !== 'cut') {\n throw new Error('Invalid \"action\" value, use either \"copy\" or \"cut\"');\n } // Sets the `target` property using an element that will be have its content copied.\n\n\n if (target !== undefined) {\n if (target && _typeof(target) === 'object' && target.nodeType === 1) {\n if (action === 'copy' && target.hasAttribute('disabled')) {\n throw new Error('Invalid \"target\" attribute. Please use \"readonly\" instead of \"disabled\" attribute');\n }\n\n if (action === 'cut' && (target.hasAttribute('readonly') || target.hasAttribute('disabled'))) {\n throw new Error('Invalid \"target\" attribute. You can\\'t cut text from elements with \"readonly\" or \"disabled\" attributes');\n }\n } else {\n throw new Error('Invalid \"target\" value, use a valid Element');\n }\n } // Define selection strategy based on `text` property.\n\n\n if (text) {\n return actions_copy(text, {\n container: container\n });\n } // Defines which selection strategy based on `target` property.\n\n\n if (target) {\n return action === 'cut' ? actions_cut(target) : actions_copy(target, {\n container: container\n });\n }\n};\n\n/* harmony default export */ var actions_default = (ClipboardActionDefault);\n;// CONCATENATED MODULE: ./src/clipboard.js\nfunction clipboard_typeof(obj) { \"@babel/helpers - typeof\"; if (typeof Symbol === \"function\" && typeof Symbol.iterator === \"symbol\") { clipboard_typeof = function _typeof(obj) { return typeof obj; }; } else { clipboard_typeof = function _typeof(obj) { return obj && typeof Symbol === \"function\" && obj.constructor === Symbol && obj !== Symbol.prototype ? \"symbol\" : typeof obj; }; } return clipboard_typeof(obj); }\n\nfunction _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError(\"Cannot call a class as a function\"); } }\n\nfunction _defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if (\"value\" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } }\n\nfunction _createClass(Constructor, protoProps, staticProps) { if (protoProps) _defineProperties(Constructor.prototype, protoProps); if (staticProps) _defineProperties(Constructor, staticProps); return Constructor; }\n\nfunction _inherits(subClass, superClass) { if (typeof superClass !== \"function\" && superClass !== null) { throw new TypeError(\"Super expression must either be null or a function\"); } subClass.prototype = Object.create(superClass && superClass.prototype, { constructor: { value: subClass, writable: true, configurable: true } }); if (superClass) _setPrototypeOf(subClass, superClass); }\n\nfunction _setPrototypeOf(o, p) { _setPrototypeOf = Object.setPrototypeOf || function _setPrototypeOf(o, p) { o.__proto__ = p; return o; }; return _setPrototypeOf(o, p); }\n\nfunction _createSuper(Derived) { var hasNativeReflectConstruct = _isNativeReflectConstruct(); return function _createSuperInternal() { var Super = _getPrototypeOf(Derived), result; if (hasNativeReflectConstruct) { var NewTarget = _getPrototypeOf(this).constructor; result = Reflect.construct(Super, arguments, NewTarget); } else { result = Super.apply(this, arguments); } return _possibleConstructorReturn(this, result); }; }\n\nfunction _possibleConstructorReturn(self, call) { if (call && (clipboard_typeof(call) === \"object\" || typeof call === \"function\")) { return call; } return _assertThisInitialized(self); }\n\nfunction _assertThisInitialized(self) { if (self === void 0) { throw new ReferenceError(\"this hasn't been initialised - super() hasn't been called\"); } return self; }\n\nfunction _isNativeReflectConstruct() { if (typeof Reflect === \"undefined\" || !Reflect.construct) return false; if (Reflect.construct.sham) return false; if (typeof Proxy === \"function\") return true; try { Date.prototype.toString.call(Reflect.construct(Date, [], function () {})); return true; } catch (e) { return false; } }\n\nfunction _getPrototypeOf(o) { _getPrototypeOf = Object.setPrototypeOf ? Object.getPrototypeOf : function _getPrototypeOf(o) { return o.__proto__ || Object.getPrototypeOf(o); }; return _getPrototypeOf(o); }\n\n\n\n\n\n\n/**\n * Helper function to retrieve attribute value.\n * @param {String} suffix\n * @param {Element} element\n */\n\nfunction getAttributeValue(suffix, element) {\n var attribute = \"data-clipboard-\".concat(suffix);\n\n if (!element.hasAttribute(attribute)) {\n return;\n }\n\n return element.getAttribute(attribute);\n}\n/**\n * Base class which takes one or more elements, adds event listeners to them,\n * and instantiates a new `ClipboardAction` on each click.\n */\n\n\nvar Clipboard = /*#__PURE__*/function (_Emitter) {\n _inherits(Clipboard, _Emitter);\n\n var _super = _createSuper(Clipboard);\n\n /**\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n * @param {Object} options\n */\n function Clipboard(trigger, options) {\n var _this;\n\n _classCallCheck(this, Clipboard);\n\n _this = _super.call(this);\n\n _this.resolveOptions(options);\n\n _this.listenClick(trigger);\n\n return _this;\n }\n /**\n * Defines if attributes would be resolved using internal setter functions\n * or custom functions that were passed in the constructor.\n * @param {Object} options\n */\n\n\n _createClass(Clipboard, [{\n key: \"resolveOptions\",\n value: function resolveOptions() {\n var options = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : {};\n this.action = typeof options.action === 'function' ? options.action : this.defaultAction;\n this.target = typeof options.target === 'function' ? options.target : this.defaultTarget;\n this.text = typeof options.text === 'function' ? options.text : this.defaultText;\n this.container = clipboard_typeof(options.container) === 'object' ? options.container : document.body;\n }\n /**\n * Adds a click event listener to the passed trigger.\n * @param {String|HTMLElement|HTMLCollection|NodeList} trigger\n */\n\n }, {\n key: \"listenClick\",\n value: function listenClick(trigger) {\n var _this2 = this;\n\n this.listener = listen_default()(trigger, 'click', function (e) {\n return _this2.onClick(e);\n });\n }\n /**\n * Defines a new `ClipboardAction` on each click event.\n * @param {Event} e\n */\n\n }, {\n key: \"onClick\",\n value: function onClick(e) {\n var trigger = e.delegateTarget || e.currentTarget;\n var action = this.action(trigger) || 'copy';\n var text = actions_default({\n action: action,\n container: this.container,\n target: this.target(trigger),\n text: this.text(trigger)\n }); // Fires an event based on the copy operation result.\n\n this.emit(text ? 'success' : 'error', {\n action: action,\n text: text,\n trigger: trigger,\n clearSelection: function clearSelection() {\n if (trigger) {\n trigger.focus();\n }\n\n window.getSelection().removeAllRanges();\n }\n });\n }\n /**\n * Default `action` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultAction\",\n value: function defaultAction(trigger) {\n return getAttributeValue('action', trigger);\n }\n /**\n * Default `target` lookup function.\n * @param {Element} trigger\n */\n\n }, {\n key: \"defaultTarget\",\n value: function defaultTarget(trigger) {\n var selector = getAttributeValue('target', trigger);\n\n if (selector) {\n return document.querySelector(selector);\n }\n }\n /**\n * Allow fire programmatically a copy action\n * @param {String|HTMLElement} target\n * @param {Object} options\n * @returns Text copied.\n */\n\n }, {\n key: \"defaultText\",\n\n /**\n * Default `text` lookup function.\n * @param {Element} trigger\n */\n value: function defaultText(trigger) {\n return getAttributeValue('text', trigger);\n }\n /**\n * Destroy lifecycle.\n */\n\n }, {\n key: \"destroy\",\n value: function destroy() {\n this.listener.destroy();\n }\n }], [{\n key: \"copy\",\n value: function copy(target) {\n var options = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : {\n container: document.body\n };\n return actions_copy(target, options);\n }\n /**\n * Allow fire programmatically a cut action\n * @param {String|HTMLElement} target\n * @returns Text cutted.\n */\n\n }, {\n key: \"cut\",\n value: function cut(target) {\n return actions_cut(target);\n }\n /**\n * Returns the support of the given action, or all actions if no action is\n * given.\n * @param {String} [action]\n */\n\n }, {\n key: \"isSupported\",\n value: function isSupported() {\n var action = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : ['copy', 'cut'];\n var actions = typeof action === 'string' ? [action] : action;\n var support = !!document.queryCommandSupported;\n actions.forEach(function (action) {\n support = support && !!document.queryCommandSupported(action);\n });\n return support;\n }\n }]);\n\n return Clipboard;\n}((tiny_emitter_default()));\n\n/* harmony default export */ var clipboard = (Clipboard);\n\n/***/ }),\n\n/***/ 828:\n/***/ (function(module) {\n\nvar DOCUMENT_NODE_TYPE = 9;\n\n/**\n * A polyfill for Element.matches()\n */\nif (typeof Element !== 'undefined' && !Element.prototype.matches) {\n var proto = Element.prototype;\n\n proto.matches = proto.matchesSelector ||\n proto.mozMatchesSelector ||\n proto.msMatchesSelector ||\n proto.oMatchesSelector ||\n proto.webkitMatchesSelector;\n}\n\n/**\n * Finds the closest parent that matches a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @return {Function}\n */\nfunction closest (element, selector) {\n while (element && element.nodeType !== DOCUMENT_NODE_TYPE) {\n if (typeof element.matches === 'function' &&\n element.matches(selector)) {\n return element;\n }\n element = element.parentNode;\n }\n}\n\nmodule.exports = closest;\n\n\n/***/ }),\n\n/***/ 438:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar closest = __webpack_require__(828);\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction _delegate(element, selector, type, callback, useCapture) {\n var listenerFn = listener.apply(this, arguments);\n\n element.addEventListener(type, listenerFn, useCapture);\n\n return {\n destroy: function() {\n element.removeEventListener(type, listenerFn, useCapture);\n }\n }\n}\n\n/**\n * Delegates event to a selector.\n *\n * @param {Element|String|Array} [elements]\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @param {Boolean} useCapture\n * @return {Object}\n */\nfunction delegate(elements, selector, type, callback, useCapture) {\n // Handle the regular Element usage\n if (typeof elements.addEventListener === 'function') {\n return _delegate.apply(null, arguments);\n }\n\n // Handle Element-less usage, it defaults to global delegation\n if (typeof type === 'function') {\n // Use `document` as the first parameter, then apply arguments\n // This is a short way to .unshift `arguments` without running into deoptimizations\n return _delegate.bind(null, document).apply(null, arguments);\n }\n\n // Handle Selector-based usage\n if (typeof elements === 'string') {\n elements = document.querySelectorAll(elements);\n }\n\n // Handle Array-like based usage\n return Array.prototype.map.call(elements, function (element) {\n return _delegate(element, selector, type, callback, useCapture);\n });\n}\n\n/**\n * Finds closest match and invokes callback.\n *\n * @param {Element} element\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Function}\n */\nfunction listener(element, selector, type, callback) {\n return function(e) {\n e.delegateTarget = closest(e.target, selector);\n\n if (e.delegateTarget) {\n callback.call(element, e);\n }\n }\n}\n\nmodule.exports = delegate;\n\n\n/***/ }),\n\n/***/ 879:\n/***/ (function(__unused_webpack_module, exports) {\n\n/**\n * Check if argument is a HTML element.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.node = function(value) {\n return value !== undefined\n && value instanceof HTMLElement\n && value.nodeType === 1;\n};\n\n/**\n * Check if argument is a list of HTML elements.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.nodeList = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return value !== undefined\n && (type === '[object NodeList]' || type === '[object HTMLCollection]')\n && ('length' in value)\n && (value.length === 0 || exports.node(value[0]));\n};\n\n/**\n * Check if argument is a string.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.string = function(value) {\n return typeof value === 'string'\n || value instanceof String;\n};\n\n/**\n * Check if argument is a function.\n *\n * @param {Object} value\n * @return {Boolean}\n */\nexports.fn = function(value) {\n var type = Object.prototype.toString.call(value);\n\n return type === '[object Function]';\n};\n\n\n/***/ }),\n\n/***/ 370:\n/***/ (function(module, __unused_webpack_exports, __webpack_require__) {\n\nvar is = __webpack_require__(879);\nvar delegate = __webpack_require__(438);\n\n/**\n * Validates all params and calls the right\n * listener function based on its target type.\n *\n * @param {String|HTMLElement|HTMLCollection|NodeList} target\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listen(target, type, callback) {\n if (!target && !type && !callback) {\n throw new Error('Missing required arguments');\n }\n\n if (!is.string(type)) {\n throw new TypeError('Second argument must be a String');\n }\n\n if (!is.fn(callback)) {\n throw new TypeError('Third argument must be a Function');\n }\n\n if (is.node(target)) {\n return listenNode(target, type, callback);\n }\n else if (is.nodeList(target)) {\n return listenNodeList(target, type, callback);\n }\n else if (is.string(target)) {\n return listenSelector(target, type, callback);\n }\n else {\n throw new TypeError('First argument must be a String, HTMLElement, HTMLCollection, or NodeList');\n }\n}\n\n/**\n * Adds an event listener to a HTML element\n * and returns a remove listener function.\n *\n * @param {HTMLElement} node\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNode(node, type, callback) {\n node.addEventListener(type, callback);\n\n return {\n destroy: function() {\n node.removeEventListener(type, callback);\n }\n }\n}\n\n/**\n * Add an event listener to a list of HTML elements\n * and returns a remove listener function.\n *\n * @param {NodeList|HTMLCollection} nodeList\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenNodeList(nodeList, type, callback) {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.addEventListener(type, callback);\n });\n\n return {\n destroy: function() {\n Array.prototype.forEach.call(nodeList, function(node) {\n node.removeEventListener(type, callback);\n });\n }\n }\n}\n\n/**\n * Add an event listener to a selector\n * and returns a remove listener function.\n *\n * @param {String} selector\n * @param {String} type\n * @param {Function} callback\n * @return {Object}\n */\nfunction listenSelector(selector, type, callback) {\n return delegate(document.body, selector, type, callback);\n}\n\nmodule.exports = listen;\n\n\n/***/ }),\n\n/***/ 817:\n/***/ (function(module) {\n\nfunction select(element) {\n var selectedText;\n\n if (element.nodeName === 'SELECT') {\n element.focus();\n\n selectedText = element.value;\n }\n else if (element.nodeName === 'INPUT' || element.nodeName === 'TEXTAREA') {\n var isReadOnly = element.hasAttribute('readonly');\n\n if (!isReadOnly) {\n element.setAttribute('readonly', '');\n }\n\n element.select();\n element.setSelectionRange(0, element.value.length);\n\n if (!isReadOnly) {\n element.removeAttribute('readonly');\n }\n\n selectedText = element.value;\n }\n else {\n if (element.hasAttribute('contenteditable')) {\n element.focus();\n }\n\n var selection = window.getSelection();\n var range = document.createRange();\n\n range.selectNodeContents(element);\n selection.removeAllRanges();\n selection.addRange(range);\n\n selectedText = selection.toString();\n }\n\n return selectedText;\n}\n\nmodule.exports = select;\n\n\n/***/ }),\n\n/***/ 279:\n/***/ (function(module) {\n\nfunction E () {\n // Keep this empty so it's easier to inherit from\n // (via https://github.com/lipsmack from https://github.com/scottcorgan/tiny-emitter/issues/3)\n}\n\nE.prototype = {\n on: function (name, callback, ctx) {\n var e = this.e || (this.e = {});\n\n (e[name] || (e[name] = [])).push({\n fn: callback,\n ctx: ctx\n });\n\n return this;\n },\n\n once: function (name, callback, ctx) {\n var self = this;\n function listener () {\n self.off(name, listener);\n callback.apply(ctx, arguments);\n };\n\n listener._ = callback\n return this.on(name, listener, ctx);\n },\n\n emit: function (name) {\n var data = [].slice.call(arguments, 1);\n var evtArr = ((this.e || (this.e = {}))[name] || []).slice();\n var i = 0;\n var len = evtArr.length;\n\n for (i; i < len; i++) {\n evtArr[i].fn.apply(evtArr[i].ctx, data);\n }\n\n return this;\n },\n\n off: function (name, callback) {\n var e = this.e || (this.e = {});\n var evts = e[name];\n var liveEvents = [];\n\n if (evts && callback) {\n for (var i = 0, len = evts.length; i < len; i++) {\n if (evts[i].fn !== callback && evts[i].fn._ !== callback)\n liveEvents.push(evts[i]);\n }\n }\n\n // Remove event from queue to prevent memory leak\n // Suggested by https://github.com/lazd\n // Ref: https://github.com/scottcorgan/tiny-emitter/commit/c6ebfaa9bc973b33d110a84a307742b7cf94c953#commitcomment-5024910\n\n (liveEvents.length)\n ? e[name] = liveEvents\n : delete e[name];\n\n return this;\n }\n};\n\nmodule.exports = E;\nmodule.exports.TinyEmitter = E;\n\n\n/***/ })\n\n/******/ \t});\n/************************************************************************/\n/******/ \t// The module cache\n/******/ \tvar __webpack_module_cache__ = {};\n/******/ \t\n/******/ \t// The require function\n/******/ \tfunction __webpack_require__(moduleId) {\n/******/ \t\t// Check if module is in cache\n/******/ \t\tif(__webpack_module_cache__[moduleId]) {\n/******/ \t\t\treturn __webpack_module_cache__[moduleId].exports;\n/******/ \t\t}\n/******/ \t\t// Create a new module (and put it into the cache)\n/******/ \t\tvar module = __webpack_module_cache__[moduleId] = {\n/******/ \t\t\t// no module.id needed\n/******/ \t\t\t// no module.loaded needed\n/******/ \t\t\texports: {}\n/******/ \t\t};\n/******/ \t\n/******/ \t\t// Execute the module function\n/******/ \t\t__webpack_modules__[moduleId](module, module.exports, __webpack_require__);\n/******/ \t\n/******/ \t\t// Return the exports of the module\n/******/ \t\treturn module.exports;\n/******/ \t}\n/******/ \t\n/************************************************************************/\n/******/ \t/* webpack/runtime/compat get default export */\n/******/ \t!function() {\n/******/ \t\t// getDefaultExport function for compatibility with non-harmony modules\n/******/ \t\t__webpack_require__.n = function(module) {\n/******/ \t\t\tvar getter = module && module.__esModule ?\n/******/ \t\t\t\tfunction() { return module['default']; } :\n/******/ \t\t\t\tfunction() { return module; };\n/******/ \t\t\t__webpack_require__.d(getter, { a: getter });\n/******/ \t\t\treturn getter;\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/define property getters */\n/******/ \t!function() {\n/******/ \t\t// define getter functions for harmony exports\n/******/ \t\t__webpack_require__.d = function(exports, definition) {\n/******/ \t\t\tfor(var key in definition) {\n/******/ \t\t\t\tif(__webpack_require__.o(definition, key) && !__webpack_require__.o(exports, key)) {\n/******/ \t\t\t\t\tObject.defineProperty(exports, key, { enumerable: true, get: definition[key] });\n/******/ \t\t\t\t}\n/******/ \t\t\t}\n/******/ \t\t};\n/******/ \t}();\n/******/ \t\n/******/ \t/* webpack/runtime/hasOwnProperty shorthand */\n/******/ \t!function() {\n/******/ \t\t__webpack_require__.o = function(obj, prop) { return Object.prototype.hasOwnProperty.call(obj, prop); }\n/******/ \t}();\n/******/ \t\n/************************************************************************/\n/******/ \t// module exports must be returned from runtime so entry inlining is disabled\n/******/ \t// startup\n/******/ \t// Load entry module and return exports\n/******/ \treturn __webpack_require__(686);\n/******/ })()\n.default;\n});", "/*\n * Copyright (c) 2016-2025 Martin Donath \n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the \"Software\"), to\n * deal in the Software without restriction, including without limitation the\n * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or\n * sell copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE\n * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING\n * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS\n * IN THE SOFTWARE.\n */\n\nimport \"focus-visible\"\n\nimport {\n EMPTY,\n NEVER,\n Observable,\n Subject,\n defer,\n delay,\n filter,\n map,\n merge,\n mergeWith,\n shareReplay,\n switchMap\n} from \"rxjs\"\n\nimport { configuration, feature } from \"./_\"\nimport {\n at,\n getActiveElement,\n getOptionalElement,\n requestJSON,\n setLocation,\n setToggle,\n watchDocument,\n watchKeyboard,\n watchLocation,\n watchLocationTarget,\n watchMedia,\n watchPrint,\n watchScript,\n watchViewport\n} from \"./browser\"\nimport {\n getComponentElement,\n getComponentElements,\n mountAnnounce,\n mountBackToTop,\n mountConsent,\n mountContent,\n mountDialog,\n mountHeader,\n mountHeaderTitle,\n mountPalette,\n mountProgress,\n mountSearch,\n mountSearchHiglight,\n mountSidebar,\n mountSource,\n mountTableOfContents,\n mountTabs,\n watchHeader,\n watchMain\n} from \"./components\"\nimport {\n SearchIndex,\n fetchSitemap,\n setupAlternate,\n setupClipboardJS,\n setupInstantNavigation,\n setupVersionSelector\n} from \"./integrations\"\nimport {\n patchEllipsis,\n patchIndeterminate,\n patchScrollfix,\n patchScrolllock\n} from \"./patches\"\nimport \"./polyfills\"\n\n/* ----------------------------------------------------------------------------\n * Functions - @todo refactor\n * ------------------------------------------------------------------------- */\n\n/**\n * Fetch search index\n *\n * @returns Search index observable\n */\nfunction fetchSearchIndex(): Observable {\n if (location.protocol === \"file:\") {\n return watchScript(\n `${new URL(\"search/search_index.js\", config.base)}`\n )\n .pipe(\n // @ts-ignore - @todo fix typings\n map(() => __index),\n shareReplay(1)\n )\n } else {\n return requestJSON(\n new URL(\"search/search_index.json\", config.base)\n )\n }\n}\n\n/* ----------------------------------------------------------------------------\n * Application\n * ------------------------------------------------------------------------- */\n\n/* Yay, JavaScript is available */\ndocument.documentElement.classList.remove(\"no-js\")\ndocument.documentElement.classList.add(\"js\")\n\n/* Set up navigation observables and subjects */\nconst document$ = watchDocument()\nconst location$ = watchLocation()\nconst target$ = watchLocationTarget(location$)\nconst keyboard$ = watchKeyboard()\n\n/* Set up media observables */\nconst viewport$ = watchViewport()\nconst tablet$ = watchMedia(\"(min-width: 60em)\")\nconst screen$ = watchMedia(\"(min-width: 76.25em)\")\nconst print$ = watchPrint()\n\n/* Retrieve search index, if search is enabled */\nconst config = configuration()\nconst index$ = document.forms.namedItem(\"search\")\n ? fetchSearchIndex()\n : NEVER\n\n/* Set up Clipboard.js integration */\nconst alert$ = new Subject()\nsetupClipboardJS({ alert$ })\n\n/* Set up language selector */\nsetupAlternate({ document$ })\n\n/* Set up progress indicator */\nconst progress$ = new Subject()\n\n/* Set up sitemap for instant navigation and previews */\nconst sitemap$ = fetchSitemap(config.base)\n\n/* Set up instant navigation, if enabled */\nif (feature(\"navigation.instant\"))\n setupInstantNavigation({ sitemap$, location$, viewport$, progress$ })\n .subscribe(document$)\n\n/* Set up version selector */\nif (config.version?.provider === \"mike\")\n setupVersionSelector({ document$ })\n\n/* Always close drawer and search on navigation */\nmerge(location$, target$)\n .pipe(\n delay(125)\n )\n .subscribe(() => {\n setToggle(\"drawer\", false)\n setToggle(\"search\", false)\n })\n\n/* Set up global keyboard handlers */\nkeyboard$\n .pipe(\n filter(({ mode }) => mode === \"global\")\n )\n .subscribe(key => {\n switch (key.type) {\n\n /* Go to previous page */\n case \"p\":\n case \",\":\n const prev = getOptionalElement(\"link[rel=prev]\")\n if (typeof prev !== \"undefined\")\n setLocation(prev)\n break\n\n /* Go to next page */\n case \"n\":\n case \".\":\n const next = getOptionalElement(\"link[rel=next]\")\n if (typeof next !== \"undefined\")\n setLocation(next)\n break\n\n /* Expand navigation, see https://bit.ly/3ZjG5io */\n case \"Enter\":\n const active = getActiveElement()\n if (active instanceof HTMLLabelElement)\n active.click()\n }\n })\n\n/* Set up patches */\npatchEllipsis({ viewport$, document$ })\npatchIndeterminate({ document$, tablet$ })\npatchScrollfix({ document$ })\npatchScrolllock({ viewport$, tablet$ })\n\n/* Set up header and main area observable */\nconst header$ = watchHeader(getComponentElement(\"header\"), { viewport$ })\nconst main$ = document$\n .pipe(\n map(() => getComponentElement(\"main\")),\n switchMap(el => watchMain(el, { viewport$, header$ })),\n shareReplay(1)\n )\n\n/* Set up control component observables */\nconst control$ = merge(\n\n /* Consent */\n ...getComponentElements(\"consent\")\n .map(el => mountConsent(el, { target$ })),\n\n /* Dialog */\n ...getComponentElements(\"dialog\")\n .map(el => mountDialog(el, { alert$ })),\n\n /* Color palette */\n ...getComponentElements(\"palette\")\n .map(el => mountPalette(el)),\n\n /* Progress bar */\n ...getComponentElements(\"progress\")\n .map(el => mountProgress(el, { progress$ })),\n\n /* Search */\n ...getComponentElements(\"search\")\n .map(el => mountSearch(el, { index$, keyboard$ })),\n\n /* Repository information */\n ...getComponentElements(\"source\")\n .map(el => mountSource(el))\n)\n\n/* Set up content component observables */\nconst content$ = defer(() => merge(\n\n /* Announcement bar */\n ...getComponentElements(\"announce\")\n .map(el => mountAnnounce(el)),\n\n /* Content */\n ...getComponentElements(\"content\")\n .map(el => mountContent(el, { sitemap$, viewport$, target$, print$ })),\n\n /* Search highlighting */\n ...getComponentElements(\"content\")\n .map(el => feature(\"search.highlight\")\n ? mountSearchHiglight(el, { index$, location$ })\n : EMPTY\n ),\n\n /* Header */\n ...getComponentElements(\"header\")\n .map(el => mountHeader(el, { viewport$, header$, main$ })),\n\n /* Header title */\n ...getComponentElements(\"header-title\")\n .map(el => mountHeaderTitle(el, { viewport$, header$ })),\n\n /* Sidebar */\n ...getComponentElements(\"sidebar\")\n .map(el => el.getAttribute(\"data-md-type\") === \"navigation\"\n ? at(screen$, () => mountSidebar(el, { viewport$, header$, main$ }))\n : at(tablet$, () => mountSidebar(el, { viewport$, header$, main$ }))\n ),\n\n /* Navigation tabs */\n ...getComponentElements(\"tabs\")\n .map(el => mountTabs(el, { viewport$, header$ })),\n\n /* Table of contents */\n ...getComponentElements(\"toc\")\n .map(el => mountTableOfContents(el, {\n viewport$, header$, main$, target$\n })),\n\n /* Back-to-top button */\n ...getComponentElements(\"top\")\n .map(el => mountBackToTop(el, { viewport$, header$, main$, target$ }))\n))\n\n/* Set up component observables */\nconst component$ = document$\n .pipe(\n switchMap(() => content$),\n mergeWith(control$),\n shareReplay(1)\n )\n\n/* Subscribe to all components */\ncomponent$.subscribe()\n\n/* ----------------------------------------------------------------------------\n * Exports\n * ------------------------------------------------------------------------- */\n\nwindow.document$ = document$ /* Document observable */\nwindow.location$ = location$ /* Location subject */\nwindow.target$ = target$ /* Location target observable */\nwindow.keyboard$ = keyboard$ /* Keyboard observable */\nwindow.viewport$ = viewport$ /* Viewport observable */\nwindow.tablet$ = tablet$ /* Media tablet observable */\nwindow.screen$ = screen$ /* Media screen observable */\nwindow.print$ = print$ /* Media print observable */\nwindow.alert$ = alert$ /* Alert subject */\nwindow.progress$ = progress$ /* Progress indicator subject */\nwindow.component$ = component$ /* Component observable */\n", "/******************************************************************************\nCopyright (c) Microsoft Corporation.\n\nPermission to use, copy, modify, and/or distribute this software for any\npurpose with or without fee is hereby granted.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH\nREGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY\nAND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,\nINDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM\nLOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR\nOTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR\nPERFORMANCE OF THIS SOFTWARE.\n***************************************************************************** */\n/* global Reflect, Promise, SuppressedError, Symbol, Iterator */\n\nvar extendStatics = function(d, b) {\n extendStatics = Object.setPrototypeOf ||\n ({ __proto__: [] } instanceof Array && function (d, b) { d.__proto__ = b; }) ||\n function (d, b) { for (var p in b) if (Object.prototype.hasOwnProperty.call(b, p)) d[p] = b[p]; };\n return extendStatics(d, b);\n};\n\nexport function __extends(d, b) {\n if (typeof b !== \"function\" && b !== null)\n throw new TypeError(\"Class extends value \" + String(b) + \" is not a constructor or null\");\n extendStatics(d, b);\n function __() { this.constructor = d; }\n d.prototype = b === null ? Object.create(b) : (__.prototype = b.prototype, new __());\n}\n\nexport var __assign = function() {\n __assign = Object.assign || function __assign(t) {\n for (var s, i = 1, n = arguments.length; i < n; i++) {\n s = arguments[i];\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p)) t[p] = s[p];\n }\n return t;\n }\n return __assign.apply(this, arguments);\n}\n\nexport function __rest(s, e) {\n var t = {};\n for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)\n t[p] = s[p];\n if (s != null && typeof Object.getOwnPropertySymbols === \"function\")\n for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {\n if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))\n t[p[i]] = s[p[i]];\n }\n return t;\n}\n\nexport function __decorate(decorators, target, key, desc) {\n var c = arguments.length, r = c < 3 ? target : desc === null ? desc = Object.getOwnPropertyDescriptor(target, key) : desc, d;\n if (typeof Reflect === \"object\" && typeof Reflect.decorate === \"function\") r = Reflect.decorate(decorators, target, key, desc);\n else for (var i = decorators.length - 1; i >= 0; i--) if (d = decorators[i]) r = (c < 3 ? d(r) : c > 3 ? d(target, key, r) : d(target, key)) || r;\n return c > 3 && r && Object.defineProperty(target, key, r), r;\n}\n\nexport function __param(paramIndex, decorator) {\n return function (target, key) { decorator(target, key, paramIndex); }\n}\n\nexport function __esDecorate(ctor, descriptorIn, decorators, contextIn, initializers, extraInitializers) {\n function accept(f) { if (f !== void 0 && typeof f !== \"function\") throw new TypeError(\"Function expected\"); return f; }\n var kind = contextIn.kind, key = kind === \"getter\" ? \"get\" : kind === \"setter\" ? \"set\" : \"value\";\n var target = !descriptorIn && ctor ? contextIn[\"static\"] ? ctor : ctor.prototype : null;\n var descriptor = descriptorIn || (target ? Object.getOwnPropertyDescriptor(target, contextIn.name) : {});\n var _, done = false;\n for (var i = decorators.length - 1; i >= 0; i--) {\n var context = {};\n for (var p in contextIn) context[p] = p === \"access\" ? {} : contextIn[p];\n for (var p in contextIn.access) context.access[p] = contextIn.access[p];\n context.addInitializer = function (f) { if (done) throw new TypeError(\"Cannot add initializers after decoration has completed\"); extraInitializers.push(accept(f || null)); };\n var result = (0, decorators[i])(kind === \"accessor\" ? { get: descriptor.get, set: descriptor.set } : descriptor[key], context);\n if (kind === \"accessor\") {\n if (result === void 0) continue;\n if (result === null || typeof result !== \"object\") throw new TypeError(\"Object expected\");\n if (_ = accept(result.get)) descriptor.get = _;\n if (_ = accept(result.set)) descriptor.set = _;\n if (_ = accept(result.init)) initializers.unshift(_);\n }\n else if (_ = accept(result)) {\n if (kind === \"field\") initializers.unshift(_);\n else descriptor[key] = _;\n }\n }\n if (target) Object.defineProperty(target, contextIn.name, descriptor);\n done = true;\n};\n\nexport function __runInitializers(thisArg, initializers, value) {\n var useValue = arguments.length > 2;\n for (var i = 0; i < initializers.length; i++) {\n value = useValue ? initializers[i].call(thisArg, value) : initializers[i].call(thisArg);\n }\n return useValue ? value : void 0;\n};\n\nexport function __propKey(x) {\n return typeof x === \"symbol\" ? x : \"\".concat(x);\n};\n\nexport function __setFunctionName(f, name, prefix) {\n if (typeof name === \"symbol\") name = name.description ? \"[\".concat(name.description, \"]\") : \"\";\n return Object.defineProperty(f, \"name\", { configurable: true, value: prefix ? \"\".concat(prefix, \" \", name) : name });\n};\n\nexport function __metadata(metadataKey, metadataValue) {\n if (typeof Reflect === \"object\" && typeof Reflect.metadata === \"function\") return Reflect.metadata(metadataKey, metadataValue);\n}\n\nexport function __awaiter(thisArg, _arguments, P, generator) {\n function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }\n return new (P || (P = Promise))(function (resolve, reject) {\n function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }\n function rejected(value) { try { step(generator[\"throw\"](value)); } catch (e) { reject(e); } }\n function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }\n step((generator = generator.apply(thisArg, _arguments || [])).next());\n });\n}\n\nexport function __generator(thisArg, body) {\n var _ = { label: 0, sent: function() { if (t[0] & 1) throw t[1]; return t[1]; }, trys: [], ops: [] }, f, y, t, g = Object.create((typeof Iterator === \"function\" ? Iterator : Object).prototype);\n return g.next = verb(0), g[\"throw\"] = verb(1), g[\"return\"] = verb(2), typeof Symbol === \"function\" && (g[Symbol.iterator] = function() { return this; }), g;\n function verb(n) { return function (v) { return step([n, v]); }; }\n function step(op) {\n if (f) throw new TypeError(\"Generator is already executing.\");\n while (g && (g = 0, op[0] && (_ = 0)), _) try {\n if (f = 1, y && (t = op[0] & 2 ? y[\"return\"] : op[0] ? y[\"throw\"] || ((t = y[\"return\"]) && t.call(y), 0) : y.next) && !(t = t.call(y, op[1])).done) return t;\n if (y = 0, t) op = [op[0] & 2, t.value];\n switch (op[0]) {\n case 0: case 1: t = op; break;\n case 4: _.label++; return { value: op[1], done: false };\n case 5: _.label++; y = op[1]; op = [0]; continue;\n case 7: op = _.ops.pop(); _.trys.pop(); continue;\n default:\n if (!(t = _.trys, t = t.length > 0 && t[t.length - 1]) && (op[0] === 6 || op[0] === 2)) { _ = 0; continue; }\n if (op[0] === 3 && (!t || (op[1] > t[0] && op[1] < t[3]))) { _.label = op[1]; break; }\n if (op[0] === 6 && _.label < t[1]) { _.label = t[1]; t = op; break; }\n if (t && _.label < t[2]) { _.label = t[2]; _.ops.push(op); break; }\n if (t[2]) _.ops.pop();\n _.trys.pop(); continue;\n }\n op = body.call(thisArg, _);\n } catch (e) { op = [6, e]; y = 0; } finally { f = t = 0; }\n if (op[0] & 5) throw op[1]; return { value: op[0] ? op[1] : void 0, done: true };\n }\n}\n\nexport var __createBinding = Object.create ? (function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n var desc = Object.getOwnPropertyDescriptor(m, k);\n if (!desc || (\"get\" in desc ? !m.__esModule : desc.writable || desc.configurable)) {\n desc = { enumerable: true, get: function() { return m[k]; } };\n }\n Object.defineProperty(o, k2, desc);\n}) : (function(o, m, k, k2) {\n if (k2 === undefined) k2 = k;\n o[k2] = m[k];\n});\n\nexport function __exportStar(m, o) {\n for (var p in m) if (p !== \"default\" && !Object.prototype.hasOwnProperty.call(o, p)) __createBinding(o, m, p);\n}\n\nexport function __values(o) {\n var s = typeof Symbol === \"function\" && Symbol.iterator, m = s && o[s], i = 0;\n if (m) return m.call(o);\n if (o && typeof o.length === \"number\") return {\n next: function () {\n if (o && i >= o.length) o = void 0;\n return { value: o && o[i++], done: !o };\n }\n };\n throw new TypeError(s ? \"Object is not iterable.\" : \"Symbol.iterator is not defined.\");\n}\n\nexport function __read(o, n) {\n var m = typeof Symbol === \"function\" && o[Symbol.iterator];\n if (!m) return o;\n var i = m.call(o), r, ar = [], e;\n try {\n while ((n === void 0 || n-- > 0) && !(r = i.next()).done) ar.push(r.value);\n }\n catch (error) { e = { error: error }; }\n finally {\n try {\n if (r && !r.done && (m = i[\"return\"])) m.call(i);\n }\n finally { if (e) throw e.error; }\n }\n return ar;\n}\n\n/** @deprecated */\nexport function __spread() {\n for (var ar = [], i = 0; i < arguments.length; i++)\n ar = ar.concat(__read(arguments[i]));\n return ar;\n}\n\n/** @deprecated */\nexport function __spreadArrays() {\n for (var s = 0, i = 0, il = arguments.length; i < il; i++) s += arguments[i].length;\n for (var r = Array(s), k = 0, i = 0; i < il; i++)\n for (var a = arguments[i], j = 0, jl = a.length; j < jl; j++, k++)\n r[k] = a[j];\n return r;\n}\n\nexport function __spreadArray(to, from, pack) {\n if (pack || arguments.length === 2) for (var i = 0, l = from.length, ar; i < l; i++) {\n if (ar || !(i in from)) {\n if (!ar) ar = Array.prototype.slice.call(from, 0, i);\n ar[i] = from[i];\n }\n }\n return to.concat(ar || Array.prototype.slice.call(from));\n}\n\nexport function __await(v) {\n return this instanceof __await ? (this.v = v, this) : new __await(v);\n}\n\nexport function __asyncGenerator(thisArg, _arguments, generator) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var g = generator.apply(thisArg, _arguments || []), i, q = [];\n return i = Object.create((typeof AsyncIterator === \"function\" ? AsyncIterator : Object).prototype), verb(\"next\"), verb(\"throw\"), verb(\"return\", awaitReturn), i[Symbol.asyncIterator] = function () { return this; }, i;\n function awaitReturn(f) { return function (v) { return Promise.resolve(v).then(f, reject); }; }\n function verb(n, f) { if (g[n]) { i[n] = function (v) { return new Promise(function (a, b) { q.push([n, v, a, b]) > 1 || resume(n, v); }); }; if (f) i[n] = f(i[n]); } }\n function resume(n, v) { try { step(g[n](v)); } catch (e) { settle(q[0][3], e); } }\n function step(r) { r.value instanceof __await ? Promise.resolve(r.value.v).then(fulfill, reject) : settle(q[0][2], r); }\n function fulfill(value) { resume(\"next\", value); }\n function reject(value) { resume(\"throw\", value); }\n function settle(f, v) { if (f(v), q.shift(), q.length) resume(q[0][0], q[0][1]); }\n}\n\nexport function __asyncDelegator(o) {\n var i, p;\n return i = {}, verb(\"next\"), verb(\"throw\", function (e) { throw e; }), verb(\"return\"), i[Symbol.iterator] = function () { return this; }, i;\n function verb(n, f) { i[n] = o[n] ? function (v) { return (p = !p) ? { value: __await(o[n](v)), done: false } : f ? f(v) : v; } : f; }\n}\n\nexport function __asyncValues(o) {\n if (!Symbol.asyncIterator) throw new TypeError(\"Symbol.asyncIterator is not defined.\");\n var m = o[Symbol.asyncIterator], i;\n return m ? m.call(o) : (o = typeof __values === \"function\" ? __values(o) : o[Symbol.iterator](), i = {}, verb(\"next\"), verb(\"throw\"), verb(\"return\"), i[Symbol.asyncIterator] = function () { return this; }, i);\n function verb(n) { i[n] = o[n] && function (v) { return new Promise(function (resolve, reject) { v = o[n](v), settle(resolve, reject, v.done, v.value); }); }; }\n function settle(resolve, reject, d, v) { Promise.resolve(v).then(function(v) { resolve({ value: v, done: d }); }, reject); }\n}\n\nexport function __makeTemplateObject(cooked, raw) {\n if (Object.defineProperty) { Object.defineProperty(cooked, \"raw\", { value: raw }); } else { cooked.raw = raw; }\n return cooked;\n};\n\nvar __setModuleDefault = Object.create ? (function(o, v) {\n Object.defineProperty(o, \"default\", { enumerable: true, value: v });\n}) : function(o, v) {\n o[\"default\"] = v;\n};\n\nexport function __importStar(mod) {\n if (mod && mod.__esModule) return mod;\n var result = {};\n if (mod != null) for (var k in mod) if (k !== \"default\" && Object.prototype.hasOwnProperty.call(mod, k)) __createBinding(result, mod, k);\n __setModuleDefault(result, mod);\n return result;\n}\n\nexport function __importDefault(mod) {\n return (mod && mod.__esModule) ? mod : { default: mod };\n}\n\nexport function __classPrivateFieldGet(receiver, state, kind, f) {\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a getter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot read private member from an object whose class did not declare it\");\n return kind === \"m\" ? f : kind === \"a\" ? f.call(receiver) : f ? f.value : state.get(receiver);\n}\n\nexport function __classPrivateFieldSet(receiver, state, value, kind, f) {\n if (kind === \"m\") throw new TypeError(\"Private method is not writable\");\n if (kind === \"a\" && !f) throw new TypeError(\"Private accessor was defined without a setter\");\n if (typeof state === \"function\" ? receiver !== state || !f : !state.has(receiver)) throw new TypeError(\"Cannot write private member to an object whose class did not declare it\");\n return (kind === \"a\" ? f.call(receiver, value) : f ? f.value = value : state.set(receiver, value)), value;\n}\n\nexport function __classPrivateFieldIn(state, receiver) {\n if (receiver === null || (typeof receiver !== \"object\" && typeof receiver !== \"function\")) throw new TypeError(\"Cannot use 'in' operator on non-object\");\n return typeof state === \"function\" ? receiver === state : state.has(receiver);\n}\n\nexport function __addDisposableResource(env, value, async) {\n if (value !== null && value !== void 0) {\n if (typeof value !== \"object\" && typeof value !== \"function\") throw new TypeError(\"Object expected.\");\n var dispose, inner;\n if (async) {\n if (!Symbol.asyncDispose) throw new TypeError(\"Symbol.asyncDispose is not defined.\");\n dispose = value[Symbol.asyncDispose];\n }\n if (dispose === void 0) {\n if (!Symbol.dispose) throw new TypeError(\"Symbol.dispose is not defined.\");\n dispose = value[Symbol.dispose];\n if (async) inner = dispose;\n }\n if (typeof dispose !== \"function\") throw new TypeError(\"Object not disposable.\");\n if (inner) dispose = function() { try { inner.call(this); } catch (e) { return Promise.reject(e); } };\n env.stack.push({ value: value, dispose: dispose, async: async });\n }\n else if (async) {\n env.stack.push({ async: true });\n }\n return value;\n}\n\nvar _SuppressedError = typeof SuppressedError === \"function\" ? SuppressedError : function (error, suppressed, message) {\n var e = new Error(message);\n return e.name = \"SuppressedError\", e.error = error, e.suppressed = suppressed, e;\n};\n\nexport function __disposeResources(env) {\n function fail(e) {\n env.error = env.hasError ? new _SuppressedError(e, env.error, \"An error was suppressed during disposal.\") : e;\n env.hasError = true;\n }\n var r, s = 0;\n function next() {\n while (r = env.stack.pop()) {\n try {\n if (!r.async && s === 1) return s = 0, env.stack.push(r), Promise.resolve().then(next);\n if (r.dispose) {\n var result = r.dispose.call(r.value);\n if (r.async) return s |= 2, Promise.resolve(result).then(next, function(e) { fail(e); return next(); });\n }\n else s |= 1;\n }\n catch (e) {\n fail(e);\n }\n }\n if (s === 1) return env.hasError ? Promise.reject(env.error) : Promise.resolve();\n if (env.hasError) throw env.error;\n }\n return next();\n}\n\nexport default {\n __extends,\n __assign,\n __rest,\n __decorate,\n __param,\n __metadata,\n __awaiter,\n __generator,\n __createBinding,\n __exportStar,\n __values,\n __read,\n __spread,\n __spreadArrays,\n __spreadArray,\n __await,\n __asyncGenerator,\n __asyncDelegator,\n __asyncValues,\n __makeTemplateObject,\n __importStar,\n __importDefault,\n __classPrivateFieldGet,\n __classPrivateFieldSet,\n __classPrivateFieldIn,\n __addDisposableResource,\n __disposeResources,\n};\n", "/**\n * Returns true if the object is a function.\n * @param value The value to check\n */\nexport function isFunction(value: any): value is (...args: any[]) => any {\n return typeof value === 'function';\n}\n", "/**\n * Used to create Error subclasses until the community moves away from ES5.\n *\n * This is because compiling from TypeScript down to ES5 has issues with subclassing Errors\n * as well as other built-in types: https://github.com/Microsoft/TypeScript/issues/12123\n *\n * @param createImpl A factory function to create the actual constructor implementation. The returned\n * function should be a named function that calls `_super` internally.\n */\nexport function createErrorClass(createImpl: (_super: any) => any): T {\n const _super = (instance: any) => {\n Error.call(instance);\n instance.stack = new Error().stack;\n };\n\n const ctorFunc = createImpl(_super);\n ctorFunc.prototype = Object.create(Error.prototype);\n ctorFunc.prototype.constructor = ctorFunc;\n return ctorFunc;\n}\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface UnsubscriptionError extends Error {\n readonly errors: any[];\n}\n\nexport interface UnsubscriptionErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (errors: any[]): UnsubscriptionError;\n}\n\n/**\n * An error thrown when one or more errors have occurred during the\n * `unsubscribe` of a {@link Subscription}.\n */\nexport const UnsubscriptionError: UnsubscriptionErrorCtor = createErrorClass(\n (_super) =>\n function UnsubscriptionErrorImpl(this: any, errors: (Error | string)[]) {\n _super(this);\n this.message = errors\n ? `${errors.length} errors occurred during unsubscription:\n${errors.map((err, i) => `${i + 1}) ${err.toString()}`).join('\\n ')}`\n : '';\n this.name = 'UnsubscriptionError';\n this.errors = errors;\n }\n);\n", "/**\n * Removes an item from an array, mutating it.\n * @param arr The array to remove the item from\n * @param item The item to remove\n */\nexport function arrRemove(arr: T[] | undefined | null, item: T) {\n if (arr) {\n const index = arr.indexOf(item);\n 0 <= index && arr.splice(index, 1);\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { UnsubscriptionError } from './util/UnsubscriptionError';\nimport { SubscriptionLike, TeardownLogic, Unsubscribable } from './types';\nimport { arrRemove } from './util/arrRemove';\n\n/**\n * Represents a disposable resource, such as the execution of an Observable. A\n * Subscription has one important method, `unsubscribe`, that takes no argument\n * and just disposes the resource held by the subscription.\n *\n * Additionally, subscriptions may be grouped together through the `add()`\n * method, which will attach a child Subscription to the current Subscription.\n * When a Subscription is unsubscribed, all its children (and its grandchildren)\n * will be unsubscribed as well.\n */\nexport class Subscription implements SubscriptionLike {\n public static EMPTY = (() => {\n const empty = new Subscription();\n empty.closed = true;\n return empty;\n })();\n\n /**\n * A flag to indicate whether this Subscription has already been unsubscribed.\n */\n public closed = false;\n\n private _parentage: Subscription[] | Subscription | null = null;\n\n /**\n * The list of registered finalizers to execute upon unsubscription. Adding and removing from this\n * list occurs in the {@link #add} and {@link #remove} methods.\n */\n private _finalizers: Exclude[] | null = null;\n\n /**\n * @param initialTeardown A function executed first as part of the finalization\n * process that is kicked off when {@link #unsubscribe} is called.\n */\n constructor(private initialTeardown?: () => void) {}\n\n /**\n * Disposes the resources held by the subscription. May, for instance, cancel\n * an ongoing Observable execution or cancel any other type of work that\n * started when the Subscription was created.\n */\n unsubscribe(): void {\n let errors: any[] | undefined;\n\n if (!this.closed) {\n this.closed = true;\n\n // Remove this from it's parents.\n const { _parentage } = this;\n if (_parentage) {\n this._parentage = null;\n if (Array.isArray(_parentage)) {\n for (const parent of _parentage) {\n parent.remove(this);\n }\n } else {\n _parentage.remove(this);\n }\n }\n\n const { initialTeardown: initialFinalizer } = this;\n if (isFunction(initialFinalizer)) {\n try {\n initialFinalizer();\n } catch (e) {\n errors = e instanceof UnsubscriptionError ? e.errors : [e];\n }\n }\n\n const { _finalizers } = this;\n if (_finalizers) {\n this._finalizers = null;\n for (const finalizer of _finalizers) {\n try {\n execFinalizer(finalizer);\n } catch (err) {\n errors = errors ?? [];\n if (err instanceof UnsubscriptionError) {\n errors = [...errors, ...err.errors];\n } else {\n errors.push(err);\n }\n }\n }\n }\n\n if (errors) {\n throw new UnsubscriptionError(errors);\n }\n }\n }\n\n /**\n * Adds a finalizer to this subscription, so that finalization will be unsubscribed/called\n * when this subscription is unsubscribed. If this subscription is already {@link #closed},\n * because it has already been unsubscribed, then whatever finalizer is passed to it\n * will automatically be executed (unless the finalizer itself is also a closed subscription).\n *\n * Closed Subscriptions cannot be added as finalizers to any subscription. Adding a closed\n * subscription to a any subscription will result in no operation. (A noop).\n *\n * Adding a subscription to itself, or adding `null` or `undefined` will not perform any\n * operation at all. (A noop).\n *\n * `Subscription` instances that are added to this instance will automatically remove themselves\n * if they are unsubscribed. Functions and {@link Unsubscribable} objects that you wish to remove\n * will need to be removed manually with {@link #remove}\n *\n * @param teardown The finalization logic to add to this subscription.\n */\n add(teardown: TeardownLogic): void {\n // Only add the finalizer if it's not undefined\n // and don't add a subscription to itself.\n if (teardown && teardown !== this) {\n if (this.closed) {\n // If this subscription is already closed,\n // execute whatever finalizer is handed to it automatically.\n execFinalizer(teardown);\n } else {\n if (teardown instanceof Subscription) {\n // We don't add closed subscriptions, and we don't add the same subscription\n // twice. Subscription unsubscribe is idempotent.\n if (teardown.closed || teardown._hasParent(this)) {\n return;\n }\n teardown._addParent(this);\n }\n (this._finalizers = this._finalizers ?? []).push(teardown);\n }\n }\n }\n\n /**\n * Checks to see if a this subscription already has a particular parent.\n * This will signal that this subscription has already been added to the parent in question.\n * @param parent the parent to check for\n */\n private _hasParent(parent: Subscription) {\n const { _parentage } = this;\n return _parentage === parent || (Array.isArray(_parentage) && _parentage.includes(parent));\n }\n\n /**\n * Adds a parent to this subscription so it can be removed from the parent if it\n * unsubscribes on it's own.\n *\n * NOTE: THIS ASSUMES THAT {@link _hasParent} HAS ALREADY BEEN CHECKED.\n * @param parent The parent subscription to add\n */\n private _addParent(parent: Subscription) {\n const { _parentage } = this;\n this._parentage = Array.isArray(_parentage) ? (_parentage.push(parent), _parentage) : _parentage ? [_parentage, parent] : parent;\n }\n\n /**\n * Called on a child when it is removed via {@link #remove}.\n * @param parent The parent to remove\n */\n private _removeParent(parent: Subscription) {\n const { _parentage } = this;\n if (_parentage === parent) {\n this._parentage = null;\n } else if (Array.isArray(_parentage)) {\n arrRemove(_parentage, parent);\n }\n }\n\n /**\n * Removes a finalizer from this subscription that was previously added with the {@link #add} method.\n *\n * Note that `Subscription` instances, when unsubscribed, will automatically remove themselves\n * from every other `Subscription` they have been added to. This means that using the `remove` method\n * is not a common thing and should be used thoughtfully.\n *\n * If you add the same finalizer instance of a function or an unsubscribable object to a `Subscription` instance\n * more than once, you will need to call `remove` the same number of times to remove all instances.\n *\n * All finalizer instances are removed to free up memory upon unsubscription.\n *\n * @param teardown The finalizer to remove from this subscription\n */\n remove(teardown: Exclude): void {\n const { _finalizers } = this;\n _finalizers && arrRemove(_finalizers, teardown);\n\n if (teardown instanceof Subscription) {\n teardown._removeParent(this);\n }\n }\n}\n\nexport const EMPTY_SUBSCRIPTION = Subscription.EMPTY;\n\nexport function isSubscription(value: any): value is Subscription {\n return (\n value instanceof Subscription ||\n (value && 'closed' in value && isFunction(value.remove) && isFunction(value.add) && isFunction(value.unsubscribe))\n );\n}\n\nfunction execFinalizer(finalizer: Unsubscribable | (() => void)) {\n if (isFunction(finalizer)) {\n finalizer();\n } else {\n finalizer.unsubscribe();\n }\n}\n", "import { Subscriber } from './Subscriber';\nimport { ObservableNotification } from './types';\n\n/**\n * The {@link GlobalConfig} object for RxJS. It is used to configure things\n * like how to react on unhandled errors.\n */\nexport const config: GlobalConfig = {\n onUnhandledError: null,\n onStoppedNotification: null,\n Promise: undefined,\n useDeprecatedSynchronousErrorHandling: false,\n useDeprecatedNextContext: false,\n};\n\n/**\n * The global configuration object for RxJS, used to configure things\n * like how to react on unhandled errors. Accessible via {@link config}\n * object.\n */\nexport interface GlobalConfig {\n /**\n * A registration point for unhandled errors from RxJS. These are errors that\n * cannot were not handled by consuming code in the usual subscription path. For\n * example, if you have this configured, and you subscribe to an observable without\n * providing an error handler, errors from that subscription will end up here. This\n * will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onUnhandledError: ((err: any) => void) | null;\n\n /**\n * A registration point for notifications that cannot be sent to subscribers because they\n * have completed, errored or have been explicitly unsubscribed. By default, next, complete\n * and error notifications sent to stopped subscribers are noops. However, sometimes callers\n * might want a different behavior. For example, with sources that attempt to report errors\n * to stopped subscribers, a caller can configure RxJS to throw an unhandled error instead.\n * This will _always_ be called asynchronously on another job in the runtime. This is because\n * we do not want errors thrown in this user-configured handler to interfere with the\n * behavior of the library.\n */\n onStoppedNotification: ((notification: ObservableNotification, subscriber: Subscriber) => void) | null;\n\n /**\n * The promise constructor used by default for {@link Observable#toPromise toPromise} and {@link Observable#forEach forEach}\n * methods.\n *\n * @deprecated As of version 8, RxJS will no longer support this sort of injection of a\n * Promise constructor. If you need a Promise implementation other than native promises,\n * please polyfill/patch Promise as you see appropriate. Will be removed in v8.\n */\n Promise?: PromiseConstructorLike;\n\n /**\n * If true, turns on synchronous error rethrowing, which is a deprecated behavior\n * in v6 and higher. This behavior enables bad patterns like wrapping a subscribe\n * call in a try/catch block. It also enables producer interference, a nasty bug\n * where a multicast can be broken for all observers by a downstream consumer with\n * an unhandled error. DO NOT USE THIS FLAG UNLESS IT'S NEEDED TO BUY TIME\n * FOR MIGRATION REASONS.\n *\n * @deprecated As of version 8, RxJS will no longer support synchronous throwing\n * of unhandled errors. All errors will be thrown on a separate call stack to prevent bad\n * behaviors described above. Will be removed in v8.\n */\n useDeprecatedSynchronousErrorHandling: boolean;\n\n /**\n * If true, enables an as-of-yet undocumented feature from v5: The ability to access\n * `unsubscribe()` via `this` context in `next` functions created in observers passed\n * to `subscribe`.\n *\n * This is being removed because the performance was severely problematic, and it could also cause\n * issues when types other than POJOs are passed to subscribe as subscribers, as they will likely have\n * their `this` context overwritten.\n *\n * @deprecated As of version 8, RxJS will no longer support altering the\n * context of next functions provided as part of an observer to Subscribe. Instead,\n * you will have access to a subscription or a signal or token that will allow you to do things like\n * unsubscribe and test closed status. Will be removed in v8.\n */\n useDeprecatedNextContext: boolean;\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetTimeoutFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearTimeoutFunction = (handle: TimerHandle) => void;\n\ninterface TimeoutProvider {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n delegate:\n | {\n setTimeout: SetTimeoutFunction;\n clearTimeout: ClearTimeoutFunction;\n }\n | undefined;\n}\n\nexport const timeoutProvider: TimeoutProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setTimeout(handler: () => void, timeout?: number, ...args) {\n const { delegate } = timeoutProvider;\n if (delegate?.setTimeout) {\n return delegate.setTimeout(handler, timeout, ...args);\n }\n return setTimeout(handler, timeout, ...args);\n },\n clearTimeout(handle) {\n const { delegate } = timeoutProvider;\n return (delegate?.clearTimeout || clearTimeout)(handle as any);\n },\n delegate: undefined,\n};\n", "import { config } from '../config';\nimport { timeoutProvider } from '../scheduler/timeoutProvider';\n\n/**\n * Handles an error on another job either with the user-configured {@link onUnhandledError},\n * or by throwing it on that new job so it can be picked up by `window.onerror`, `process.on('error')`, etc.\n *\n * This should be called whenever there is an error that is out-of-band with the subscription\n * or when an error hits a terminal boundary of the subscription and no error handler was provided.\n *\n * @param err the error to report\n */\nexport function reportUnhandledError(err: any) {\n timeoutProvider.setTimeout(() => {\n const { onUnhandledError } = config;\n if (onUnhandledError) {\n // Execute the user-configured error handler.\n onUnhandledError(err);\n } else {\n // Throw so it is picked up by the runtime's uncaught error mechanism.\n throw err;\n }\n });\n}\n", "/* tslint:disable:no-empty */\nexport function noop() { }\n", "import { CompleteNotification, NextNotification, ErrorNotification } from './types';\n\n/**\n * A completion object optimized for memory use and created to be the\n * same \"shape\" as other notifications in v8.\n * @internal\n */\nexport const COMPLETE_NOTIFICATION = (() => createNotification('C', undefined, undefined) as CompleteNotification)();\n\n/**\n * Internal use only. Creates an optimized error notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function errorNotification(error: any): ErrorNotification {\n return createNotification('E', undefined, error) as any;\n}\n\n/**\n * Internal use only. Creates an optimized next notification that is the same \"shape\"\n * as other notifications.\n * @internal\n */\nexport function nextNotification(value: T) {\n return createNotification('N', value, undefined) as NextNotification;\n}\n\n/**\n * Ensures that all notifications created internally have the same \"shape\" in v8.\n *\n * TODO: This is only exported to support a crazy legacy test in `groupBy`.\n * @internal\n */\nexport function createNotification(kind: 'N' | 'E' | 'C', value: any, error: any) {\n return {\n kind,\n value,\n error,\n };\n}\n", "import { config } from '../config';\n\nlet context: { errorThrown: boolean; error: any } | null = null;\n\n/**\n * Handles dealing with errors for super-gross mode. Creates a context, in which\n * any synchronously thrown errors will be passed to {@link captureError}. Which\n * will record the error such that it will be rethrown after the call back is complete.\n * TODO: Remove in v8\n * @param cb An immediately executed function.\n */\nexport function errorContext(cb: () => void) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n const isRoot = !context;\n if (isRoot) {\n context = { errorThrown: false, error: null };\n }\n cb();\n if (isRoot) {\n const { errorThrown, error } = context!;\n context = null;\n if (errorThrown) {\n throw error;\n }\n }\n } else {\n // This is the general non-deprecated path for everyone that\n // isn't crazy enough to use super-gross mode (useDeprecatedSynchronousErrorHandling)\n cb();\n }\n}\n\n/**\n * Captures errors only in super-gross mode.\n * @param err the error to capture\n */\nexport function captureError(err: any) {\n if (config.useDeprecatedSynchronousErrorHandling && context) {\n context.errorThrown = true;\n context.error = err;\n }\n}\n", "import { isFunction } from './util/isFunction';\nimport { Observer, ObservableNotification } from './types';\nimport { isSubscription, Subscription } from './Subscription';\nimport { config } from './config';\nimport { reportUnhandledError } from './util/reportUnhandledError';\nimport { noop } from './util/noop';\nimport { nextNotification, errorNotification, COMPLETE_NOTIFICATION } from './NotificationFactories';\nimport { timeoutProvider } from './scheduler/timeoutProvider';\nimport { captureError } from './util/errorContext';\n\n/**\n * Implements the {@link Observer} interface and extends the\n * {@link Subscription} class. While the {@link Observer} is the public API for\n * consuming the values of an {@link Observable}, all Observers get converted to\n * a Subscriber, in order to provide Subscription-like capabilities such as\n * `unsubscribe`. Subscriber is a common type in RxJS, and crucial for\n * implementing operators, but it is rarely used as a public API.\n */\nexport class Subscriber extends Subscription implements Observer {\n /**\n * A static factory for a Subscriber, given a (potentially partial) definition\n * of an Observer.\n * @param next The `next` callback of an Observer.\n * @param error The `error` callback of an\n * Observer.\n * @param complete The `complete` callback of an\n * Observer.\n * @return A Subscriber wrapping the (partially defined)\n * Observer represented by the given arguments.\n * @deprecated Do not use. Will be removed in v8. There is no replacement for this\n * method, and there is no reason to be creating instances of `Subscriber` directly.\n * If you have a specific use case, please file an issue.\n */\n static create(next?: (x?: T) => void, error?: (e?: any) => void, complete?: () => void): Subscriber {\n return new SafeSubscriber(next, error, complete);\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected isStopped: boolean = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n protected destination: Subscriber | Observer; // this `any` is the escape hatch to erase extra type param (e.g. R)\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * There is no reason to directly create an instance of Subscriber. This type is exported for typings reasons.\n */\n constructor(destination?: Subscriber | Observer) {\n super();\n if (destination) {\n this.destination = destination;\n // Automatically chain subscriptions together here.\n // if destination is a Subscription, then it is a Subscriber.\n if (isSubscription(destination)) {\n destination.add(this);\n }\n } else {\n this.destination = EMPTY_OBSERVER;\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `next` from\n * the Observable, with a value. The Observable may call this method 0 or more\n * times.\n * @param value The `next` value.\n */\n next(value: T): void {\n if (this.isStopped) {\n handleStoppedNotification(nextNotification(value), this);\n } else {\n this._next(value!);\n }\n }\n\n /**\n * The {@link Observer} callback to receive notifications of type `error` from\n * the Observable, with an attached `Error`. Notifies the Observer that\n * the Observable has experienced an error condition.\n * @param err The `error` exception.\n */\n error(err?: any): void {\n if (this.isStopped) {\n handleStoppedNotification(errorNotification(err), this);\n } else {\n this.isStopped = true;\n this._error(err);\n }\n }\n\n /**\n * The {@link Observer} callback to receive a valueless notification of type\n * `complete` from the Observable. Notifies the Observer that the Observable\n * has finished sending push-based notifications.\n */\n complete(): void {\n if (this.isStopped) {\n handleStoppedNotification(COMPLETE_NOTIFICATION, this);\n } else {\n this.isStopped = true;\n this._complete();\n }\n }\n\n unsubscribe(): void {\n if (!this.closed) {\n this.isStopped = true;\n super.unsubscribe();\n this.destination = null!;\n }\n }\n\n protected _next(value: T): void {\n this.destination.next(value);\n }\n\n protected _error(err: any): void {\n try {\n this.destination.error(err);\n } finally {\n this.unsubscribe();\n }\n }\n\n protected _complete(): void {\n try {\n this.destination.complete();\n } finally {\n this.unsubscribe();\n }\n }\n}\n\n/**\n * This bind is captured here because we want to be able to have\n * compatibility with monoid libraries that tend to use a method named\n * `bind`. In particular, a library called Monio requires this.\n */\nconst _bind = Function.prototype.bind;\n\nfunction bind any>(fn: Fn, thisArg: any): Fn {\n return _bind.call(fn, thisArg);\n}\n\n/**\n * Internal optimization only, DO NOT EXPOSE.\n * @internal\n */\nclass ConsumerObserver implements Observer {\n constructor(private partialObserver: Partial>) {}\n\n next(value: T): void {\n const { partialObserver } = this;\n if (partialObserver.next) {\n try {\n partialObserver.next(value);\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n\n error(err: any): void {\n const { partialObserver } = this;\n if (partialObserver.error) {\n try {\n partialObserver.error(err);\n } catch (error) {\n handleUnhandledError(error);\n }\n } else {\n handleUnhandledError(err);\n }\n }\n\n complete(): void {\n const { partialObserver } = this;\n if (partialObserver.complete) {\n try {\n partialObserver.complete();\n } catch (error) {\n handleUnhandledError(error);\n }\n }\n }\n}\n\nexport class SafeSubscriber extends Subscriber {\n constructor(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((e?: any) => void) | null,\n complete?: (() => void) | null\n ) {\n super();\n\n let partialObserver: Partial>;\n if (isFunction(observerOrNext) || !observerOrNext) {\n // The first argument is a function, not an observer. The next\n // two arguments *could* be observers, or they could be empty.\n partialObserver = {\n next: (observerOrNext ?? undefined) as ((value: T) => void) | undefined,\n error: error ?? undefined,\n complete: complete ?? undefined,\n };\n } else {\n // The first argument is a partial observer.\n let context: any;\n if (this && config.useDeprecatedNextContext) {\n // This is a deprecated path that made `this.unsubscribe()` available in\n // next handler functions passed to subscribe. This only exists behind a flag\n // now, as it is *very* slow.\n context = Object.create(observerOrNext);\n context.unsubscribe = () => this.unsubscribe();\n partialObserver = {\n next: observerOrNext.next && bind(observerOrNext.next, context),\n error: observerOrNext.error && bind(observerOrNext.error, context),\n complete: observerOrNext.complete && bind(observerOrNext.complete, context),\n };\n } else {\n // The \"normal\" path. Just use the partial observer directly.\n partialObserver = observerOrNext;\n }\n }\n\n // Wrap the partial observer to ensure it's a full observer, and\n // make sure proper error handling is accounted for.\n this.destination = new ConsumerObserver(partialObserver);\n }\n}\n\nfunction handleUnhandledError(error: any) {\n if (config.useDeprecatedSynchronousErrorHandling) {\n captureError(error);\n } else {\n // Ideal path, we report this as an unhandled error,\n // which is thrown on a new call stack.\n reportUnhandledError(error);\n }\n}\n\n/**\n * An error handler used when no error handler was supplied\n * to the SafeSubscriber -- meaning no error handler was supplied\n * do the `subscribe` call on our observable.\n * @param err The error to handle\n */\nfunction defaultErrorHandler(err: any) {\n throw err;\n}\n\n/**\n * A handler for notifications that cannot be sent to a stopped subscriber.\n * @param notification The notification being sent.\n * @param subscriber The stopped subscriber.\n */\nfunction handleStoppedNotification(notification: ObservableNotification, subscriber: Subscriber) {\n const { onStoppedNotification } = config;\n onStoppedNotification && timeoutProvider.setTimeout(() => onStoppedNotification(notification, subscriber));\n}\n\n/**\n * The observer used as a stub for subscriptions where the user did not\n * pass any arguments to `subscribe`. Comes with the default error handling\n * behavior.\n */\nexport const EMPTY_OBSERVER: Readonly> & { closed: true } = {\n closed: true,\n next: noop,\n error: defaultErrorHandler,\n complete: noop,\n};\n", "/**\n * Symbol.observable or a string \"@@observable\". Used for interop\n *\n * @deprecated We will no longer be exporting this symbol in upcoming versions of RxJS.\n * Instead polyfill and use Symbol.observable directly *or* use https://www.npmjs.com/package/symbol-observable\n */\nexport const observable: string | symbol = (() => (typeof Symbol === 'function' && Symbol.observable) || '@@observable')();\n", "/**\n * This function takes one parameter and just returns it. Simply put,\n * this is like `(x: T): T => x`.\n *\n * ## Examples\n *\n * This is useful in some cases when using things like `mergeMap`\n *\n * ```ts\n * import { interval, take, map, range, mergeMap, identity } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(5));\n *\n * const result$ = source$.pipe(\n * map(i => range(i)),\n * mergeMap(identity) // same as mergeMap(x => x)\n * );\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * Or when you want to selectively apply an operator\n *\n * ```ts\n * import { interval, take, identity } from 'rxjs';\n *\n * const shouldLimit = () => Math.random() < 0.5;\n *\n * const source$ = interval(1000);\n *\n * const result$ = source$.pipe(shouldLimit() ? take(5) : identity);\n *\n * result$.subscribe({\n * next: console.log\n * });\n * ```\n *\n * @param x Any value that is returned by this function\n * @returns The value passed as the first parameter to this function\n */\nexport function identity(x: T): T {\n return x;\n}\n", "import { identity } from './identity';\nimport { UnaryFunction } from '../types';\n\nexport function pipe(): typeof identity;\nexport function pipe(fn1: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction): UnaryFunction;\nexport function pipe(fn1: UnaryFunction, fn2: UnaryFunction, fn3: UnaryFunction): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction\n): UnaryFunction;\nexport function pipe(\n fn1: UnaryFunction,\n fn2: UnaryFunction,\n fn3: UnaryFunction,\n fn4: UnaryFunction,\n fn5: UnaryFunction,\n fn6: UnaryFunction,\n fn7: UnaryFunction,\n fn8: UnaryFunction,\n fn9: UnaryFunction,\n ...fns: UnaryFunction[]\n): UnaryFunction;\n\n/**\n * pipe() can be called on one or more functions, each of which can take one argument (\"UnaryFunction\")\n * and uses it to return a value.\n * It returns a function that takes one argument, passes it to the first UnaryFunction, and then\n * passes the result to the next one, passes that result to the next one, and so on. \n */\nexport function pipe(...fns: Array>): UnaryFunction {\n return pipeFromArray(fns);\n}\n\n/** @internal */\nexport function pipeFromArray(fns: Array>): UnaryFunction {\n if (fns.length === 0) {\n return identity as UnaryFunction;\n }\n\n if (fns.length === 1) {\n return fns[0];\n }\n\n return function piped(input: T): R {\n return fns.reduce((prev: any, fn: UnaryFunction) => fn(prev), input as any);\n };\n}\n", "import { Operator } from './Operator';\nimport { SafeSubscriber, Subscriber } from './Subscriber';\nimport { isSubscription, Subscription } from './Subscription';\nimport { TeardownLogic, OperatorFunction, Subscribable, Observer } from './types';\nimport { observable as Symbol_observable } from './symbol/observable';\nimport { pipeFromArray } from './util/pipe';\nimport { config } from './config';\nimport { isFunction } from './util/isFunction';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A representation of any set of values over any amount of time. This is the most basic building block\n * of RxJS.\n */\nexport class Observable implements Subscribable {\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n source: Observable | undefined;\n\n /**\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n */\n operator: Operator | undefined;\n\n /**\n * @param subscribe The function that is called when the Observable is\n * initially subscribed to. This function is given a Subscriber, to which new values\n * can be `next`ed, or an `error` method can be called to raise an error, or\n * `complete` can be called to notify of a successful completion.\n */\n constructor(subscribe?: (this: Observable, subscriber: Subscriber) => TeardownLogic) {\n if (subscribe) {\n this._subscribe = subscribe;\n }\n }\n\n // HACK: Since TypeScript inherits static properties too, we have to\n // fight against TypeScript here so Subject can have a different static create signature\n /**\n * Creates a new Observable by calling the Observable constructor\n * @param subscribe the subscriber function to be passed to the Observable constructor\n * @return A new observable.\n * @deprecated Use `new Observable()` instead. Will be removed in v8.\n */\n static create: (...args: any[]) => any = (subscribe?: (subscriber: Subscriber) => TeardownLogic) => {\n return new Observable(subscribe);\n };\n\n /**\n * Creates a new Observable, with this Observable instance as the source, and the passed\n * operator defined as the new observable's operator.\n * @param operator the operator defining the operation to take on the observable\n * @return A new observable with the Operator applied.\n * @deprecated Internal implementation detail, do not use directly. Will be made internal in v8.\n * If you have implemented an operator using `lift`, it is recommended that you create an\n * operator by simply returning `new Observable()` directly. See \"Creating new operators from\n * scratch\" section here: https://rxjs.dev/guide/operators\n */\n lift(operator?: Operator): Observable {\n const observable = new Observable();\n observable.source = this;\n observable.operator = operator;\n return observable;\n }\n\n subscribe(observerOrNext?: Partial> | ((value: T) => void)): Subscription;\n /** @deprecated Instead of passing separate callback arguments, use an observer argument. Signatures taking separate callback arguments will be removed in v8. Details: https://rxjs.dev/deprecations/subscribe-arguments */\n subscribe(next?: ((value: T) => void) | null, error?: ((error: any) => void) | null, complete?: (() => void) | null): Subscription;\n /**\n * Invokes an execution of an Observable and registers Observer handlers for notifications it will emit.\n *\n * Use it when you have all these Observables, but still nothing is happening.\n *\n * `subscribe` is not a regular operator, but a method that calls Observable's internal `subscribe` function. It\n * might be for example a function that you passed to Observable's constructor, but most of the time it is\n * a library implementation, which defines what will be emitted by an Observable, and when it be will emitted. This means\n * that calling `subscribe` is actually the moment when Observable starts its work, not when it is created, as it is often\n * the thought.\n *\n * Apart from starting the execution of an Observable, this method allows you to listen for values\n * that an Observable emits, as well as for when it completes or errors. You can achieve this in two\n * of the following ways.\n *\n * The first way is creating an object that implements {@link Observer} interface. It should have methods\n * defined by that interface, but note that it should be just a regular JavaScript object, which you can create\n * yourself in any way you want (ES6 class, classic function constructor, object literal etc.). In particular, do\n * not attempt to use any RxJS implementation details to create Observers - you don't need them. Remember also\n * that your object does not have to implement all methods. If you find yourself creating a method that doesn't\n * do anything, you can simply omit it. Note however, if the `error` method is not provided and an error happens,\n * it will be thrown asynchronously. Errors thrown asynchronously cannot be caught using `try`/`catch`. Instead,\n * use the {@link onUnhandledError} configuration option or use a runtime handler (like `window.onerror` or\n * `process.on('error)`) to be notified of unhandled errors. Because of this, it's recommended that you provide\n * an `error` method to avoid missing thrown errors.\n *\n * The second way is to give up on Observer object altogether and simply provide callback functions in place of its methods.\n * This means you can provide three functions as arguments to `subscribe`, where the first function is equivalent\n * of a `next` method, the second of an `error` method and the third of a `complete` method. Just as in case of an Observer,\n * if you do not need to listen for something, you can omit a function by passing `undefined` or `null`,\n * since `subscribe` recognizes these functions by where they were placed in function call. When it comes\n * to the `error` function, as with an Observer, if not provided, errors emitted by an Observable will be thrown asynchronously.\n *\n * You can, however, subscribe with no parameters at all. This may be the case where you're not interested in terminal events\n * and you also handled emissions internally by using operators (e.g. using `tap`).\n *\n * Whichever style of calling `subscribe` you use, in both cases it returns a Subscription object.\n * This object allows you to call `unsubscribe` on it, which in turn will stop the work that an Observable does and will clean\n * up all resources that an Observable used. Note that cancelling a subscription will not call `complete` callback\n * provided to `subscribe` function, which is reserved for a regular completion signal that comes from an Observable.\n *\n * Remember that callbacks provided to `subscribe` are not guaranteed to be called asynchronously.\n * It is an Observable itself that decides when these functions will be called. For example {@link of}\n * by default emits all its values synchronously. Always check documentation for how given Observable\n * will behave when subscribed and if its default behavior can be modified with a `scheduler`.\n *\n * #### Examples\n *\n * Subscribe with an {@link guide/observer Observer}\n *\n * ```ts\n * import { of } from 'rxjs';\n *\n * const sumObserver = {\n * sum: 0,\n * next(value) {\n * console.log('Adding: ' + value);\n * this.sum = this.sum + value;\n * },\n * error() {\n * // We actually could just remove this method,\n * // since we do not really care about errors right now.\n * },\n * complete() {\n * console.log('Sum equals: ' + this.sum);\n * }\n * };\n *\n * of(1, 2, 3) // Synchronously emits 1, 2, 3 and then completes.\n * .subscribe(sumObserver);\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Subscribe with functions ({@link deprecations/subscribe-arguments deprecated})\n *\n * ```ts\n * import { of } from 'rxjs'\n *\n * let sum = 0;\n *\n * of(1, 2, 3).subscribe(\n * value => {\n * console.log('Adding: ' + value);\n * sum = sum + value;\n * },\n * undefined,\n * () => console.log('Sum equals: ' + sum)\n * );\n *\n * // Logs:\n * // 'Adding: 1'\n * // 'Adding: 2'\n * // 'Adding: 3'\n * // 'Sum equals: 6'\n * ```\n *\n * Cancel a subscription\n *\n * ```ts\n * import { interval } from 'rxjs';\n *\n * const subscription = interval(1000).subscribe({\n * next(num) {\n * console.log(num)\n * },\n * complete() {\n * // Will not be called, even when cancelling subscription.\n * console.log('completed!');\n * }\n * });\n *\n * setTimeout(() => {\n * subscription.unsubscribe();\n * console.log('unsubscribed!');\n * }, 2500);\n *\n * // Logs:\n * // 0 after 1s\n * // 1 after 2s\n * // 'unsubscribed!' after 2.5s\n * ```\n *\n * @param observerOrNext Either an {@link Observer} with some or all callback methods,\n * or the `next` handler that is called for each value emitted from the subscribed Observable.\n * @param error A handler for a terminal event resulting from an error. If no error handler is provided,\n * the error will be thrown asynchronously as unhandled.\n * @param complete A handler for a terminal event resulting from successful completion.\n * @return A subscription reference to the registered handlers.\n */\n subscribe(\n observerOrNext?: Partial> | ((value: T) => void) | null,\n error?: ((error: any) => void) | null,\n complete?: (() => void) | null\n ): Subscription {\n const subscriber = isSubscriber(observerOrNext) ? observerOrNext : new SafeSubscriber(observerOrNext, error, complete);\n\n errorContext(() => {\n const { operator, source } = this;\n subscriber.add(\n operator\n ? // We're dealing with a subscription in the\n // operator chain to one of our lifted operators.\n operator.call(subscriber, source)\n : source\n ? // If `source` has a value, but `operator` does not, something that\n // had intimate knowledge of our API, like our `Subject`, must have\n // set it. We're going to just call `_subscribe` directly.\n this._subscribe(subscriber)\n : // In all other cases, we're likely wrapping a user-provided initializer\n // function, so we need to catch errors and handle them appropriately.\n this._trySubscribe(subscriber)\n );\n });\n\n return subscriber;\n }\n\n /** @internal */\n protected _trySubscribe(sink: Subscriber): TeardownLogic {\n try {\n return this._subscribe(sink);\n } catch (err) {\n // We don't need to return anything in this case,\n // because it's just going to try to `add()` to a subscription\n // above.\n sink.error(err);\n }\n }\n\n /**\n * Used as a NON-CANCELLABLE means of subscribing to an observable, for use with\n * APIs that expect promises, like `async/await`. You cannot unsubscribe from this.\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * #### Example\n *\n * ```ts\n * import { interval, take } from 'rxjs';\n *\n * const source$ = interval(1000).pipe(take(4));\n *\n * async function getTotal() {\n * let total = 0;\n *\n * await source$.forEach(value => {\n * total += value;\n * console.log('observable -> ' + value);\n * });\n *\n * return total;\n * }\n *\n * getTotal().then(\n * total => console.log('Total: ' + total)\n * );\n *\n * // Expected:\n * // 'observable -> 0'\n * // 'observable -> 1'\n * // 'observable -> 2'\n * // 'observable -> 3'\n * // 'Total: 6'\n * ```\n *\n * @param next A handler for each value emitted by the observable.\n * @return A promise that either resolves on observable completion or\n * rejects with the handled error.\n */\n forEach(next: (value: T) => void): Promise;\n\n /**\n * @param next a handler for each value emitted by the observable\n * @param promiseCtor a constructor function used to instantiate the Promise\n * @return a promise that either resolves on observable completion or\n * rejects with the handled error\n * @deprecated Passing a Promise constructor will no longer be available\n * in upcoming versions of RxJS. This is because it adds weight to the library, for very\n * little benefit. If you need this functionality, it is recommended that you either\n * polyfill Promise, or you create an adapter to convert the returned native promise\n * to whatever promise implementation you wanted. Will be removed in v8.\n */\n forEach(next: (value: T) => void, promiseCtor: PromiseConstructorLike): Promise;\n\n forEach(next: (value: T) => void, promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n const subscriber = new SafeSubscriber({\n next: (value) => {\n try {\n next(value);\n } catch (err) {\n reject(err);\n subscriber.unsubscribe();\n }\n },\n error: reject,\n complete: resolve,\n });\n this.subscribe(subscriber);\n }) as Promise;\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): TeardownLogic {\n return this.source?.subscribe(subscriber);\n }\n\n /**\n * An interop point defined by the es7-observable spec https://github.com/zenparsing/es-observable\n * @return This instance of the observable.\n */\n [Symbol_observable]() {\n return this;\n }\n\n /* tslint:disable:max-line-length */\n pipe(): Observable;\n pipe(op1: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction): Observable;\n pipe(op1: OperatorFunction, op2: OperatorFunction, op3: OperatorFunction): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction\n ): Observable;\n pipe(\n op1: OperatorFunction,\n op2: OperatorFunction,\n op3: OperatorFunction,\n op4: OperatorFunction,\n op5: OperatorFunction,\n op6: OperatorFunction,\n op7: OperatorFunction,\n op8: OperatorFunction,\n op9: OperatorFunction,\n ...operations: OperatorFunction[]\n ): Observable;\n /* tslint:enable:max-line-length */\n\n /**\n * Used to stitch together functional operators into a chain.\n *\n * ## Example\n *\n * ```ts\n * import { interval, filter, map, scan } from 'rxjs';\n *\n * interval(1000)\n * .pipe(\n * filter(x => x % 2 === 0),\n * map(x => x + x),\n * scan((acc, x) => acc + x)\n * )\n * .subscribe(x => console.log(x));\n * ```\n *\n * @return The Observable result of all the operators having been called\n * in the order they were passed in.\n */\n pipe(...operations: OperatorFunction[]): Observable {\n return pipeFromArray(operations)(this);\n }\n\n /* tslint:disable:max-line-length */\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: typeof Promise): Promise;\n /** @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise */\n toPromise(PromiseCtor: PromiseConstructorLike): Promise;\n /* tslint:enable:max-line-length */\n\n /**\n * Subscribe to this Observable and get a Promise resolving on\n * `complete` with the last emission (if any).\n *\n * **WARNING**: Only use this with observables you *know* will complete. If the source\n * observable does not complete, you will end up with a promise that is hung up, and\n * potentially all of the state of an async function hanging out in memory. To avoid\n * this situation, look into adding something like {@link timeout}, {@link take},\n * {@link takeWhile}, or {@link takeUntil} amongst others.\n *\n * @param [promiseCtor] a constructor function used to instantiate\n * the Promise\n * @return A Promise that resolves with the last value emit, or\n * rejects on an error. If there were no emissions, Promise\n * resolves with undefined.\n * @deprecated Replaced with {@link firstValueFrom} and {@link lastValueFrom}. Will be removed in v8. Details: https://rxjs.dev/deprecations/to-promise\n */\n toPromise(promiseCtor?: PromiseConstructorLike): Promise {\n promiseCtor = getPromiseCtor(promiseCtor);\n\n return new promiseCtor((resolve, reject) => {\n let value: T | undefined;\n this.subscribe(\n (x: T) => (value = x),\n (err: any) => reject(err),\n () => resolve(value)\n );\n }) as Promise;\n }\n}\n\n/**\n * Decides between a passed promise constructor from consuming code,\n * A default configured promise constructor, and the native promise\n * constructor and returns it. If nothing can be found, it will throw\n * an error.\n * @param promiseCtor The optional promise constructor to passed by consuming code\n */\nfunction getPromiseCtor(promiseCtor: PromiseConstructorLike | undefined) {\n return promiseCtor ?? config.Promise ?? Promise;\n}\n\nfunction isObserver(value: any): value is Observer {\n return value && isFunction(value.next) && isFunction(value.error) && isFunction(value.complete);\n}\n\nfunction isSubscriber(value: any): value is Subscriber {\n return (value && value instanceof Subscriber) || (isObserver(value) && isSubscription(value));\n}\n", "import { Observable } from '../Observable';\nimport { Subscriber } from '../Subscriber';\nimport { OperatorFunction } from '../types';\nimport { isFunction } from './isFunction';\n\n/**\n * Used to determine if an object is an Observable with a lift function.\n */\nexport function hasLift(source: any): source is { lift: InstanceType['lift'] } {\n return isFunction(source?.lift);\n}\n\n/**\n * Creates an `OperatorFunction`. Used to define operators throughout the library in a concise way.\n * @param init The logic to connect the liftedSource to the subscriber at the moment of subscription.\n */\nexport function operate(\n init: (liftedSource: Observable, subscriber: Subscriber) => (() => void) | void\n): OperatorFunction {\n return (source: Observable) => {\n if (hasLift(source)) {\n return source.lift(function (this: Subscriber, liftedSource: Observable) {\n try {\n return init(liftedSource, this);\n } catch (err) {\n this.error(err);\n }\n });\n }\n throw new TypeError('Unable to lift unknown Observable type');\n };\n}\n", "import { Subscriber } from '../Subscriber';\n\n/**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional teardown logic here. This will only be called on teardown if the\n * subscriber itself is not already closed. This is called after all other teardown logic is executed.\n */\nexport function createOperatorSubscriber(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n onFinalize?: () => void\n): Subscriber {\n return new OperatorSubscriber(destination, onNext, onComplete, onError, onFinalize);\n}\n\n/**\n * A generic helper for allowing operators to be created with a Subscriber and\n * use closures to capture necessary state from the operator function itself.\n */\nexport class OperatorSubscriber extends Subscriber {\n /**\n * Creates an instance of an `OperatorSubscriber`.\n * @param destination The downstream subscriber.\n * @param onNext Handles next values, only called if this subscriber is not stopped or closed. Any\n * error that occurs in this function is caught and sent to the `error` method of this subscriber.\n * @param onError Handles errors from the subscription, any errors that occur in this handler are caught\n * and send to the `destination` error handler.\n * @param onComplete Handles completion notification from the subscription. Any errors that occur in\n * this handler are sent to the `destination` error handler.\n * @param onFinalize Additional finalization logic here. This will only be called on finalization if the\n * subscriber itself is not already closed. This is called after all other finalization logic is executed.\n * @param shouldUnsubscribe An optional check to see if an unsubscribe call should truly unsubscribe.\n * NOTE: This currently **ONLY** exists to support the strange behavior of {@link groupBy}, where unsubscription\n * to the resulting observable does not actually disconnect from the source if there are active subscriptions\n * to any grouped observable. (DO NOT EXPOSE OR USE EXTERNALLY!!!)\n */\n constructor(\n destination: Subscriber,\n onNext?: (value: T) => void,\n onComplete?: () => void,\n onError?: (err: any) => void,\n private onFinalize?: () => void,\n private shouldUnsubscribe?: () => boolean\n ) {\n // It's important - for performance reasons - that all of this class's\n // members are initialized and that they are always initialized in the same\n // order. This will ensure that all OperatorSubscriber instances have the\n // same hidden class in V8. This, in turn, will help keep the number of\n // hidden classes involved in property accesses within the base class as\n // low as possible. If the number of hidden classes involved exceeds four,\n // the property accesses will become megamorphic and performance penalties\n // will be incurred - i.e. inline caches won't be used.\n //\n // The reasons for ensuring all instances have the same hidden class are\n // further discussed in this blog post from Benedikt Meurer:\n // https://benediktmeurer.de/2018/03/23/impact-of-polymorphism-on-component-based-frameworks-like-react/\n super(destination);\n this._next = onNext\n ? function (this: OperatorSubscriber, value: T) {\n try {\n onNext(value);\n } catch (err) {\n destination.error(err);\n }\n }\n : super._next;\n this._error = onError\n ? function (this: OperatorSubscriber, err: any) {\n try {\n onError(err);\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._error;\n this._complete = onComplete\n ? function (this: OperatorSubscriber) {\n try {\n onComplete();\n } catch (err) {\n // Send any errors that occur down stream.\n destination.error(err);\n } finally {\n // Ensure finalization.\n this.unsubscribe();\n }\n }\n : super._complete;\n }\n\n unsubscribe() {\n if (!this.shouldUnsubscribe || this.shouldUnsubscribe()) {\n const { closed } = this;\n super.unsubscribe();\n // Execute additional teardown if we have any and we didn't already do so.\n !closed && this.onFinalize?.();\n }\n }\n}\n", "import { Subscription } from '../Subscription';\n\ninterface AnimationFrameProvider {\n schedule(callback: FrameRequestCallback): Subscription;\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n delegate:\n | {\n requestAnimationFrame: typeof requestAnimationFrame;\n cancelAnimationFrame: typeof cancelAnimationFrame;\n }\n | undefined;\n}\n\nexport const animationFrameProvider: AnimationFrameProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n schedule(callback) {\n let request = requestAnimationFrame;\n let cancel: typeof cancelAnimationFrame | undefined = cancelAnimationFrame;\n const { delegate } = animationFrameProvider;\n if (delegate) {\n request = delegate.requestAnimationFrame;\n cancel = delegate.cancelAnimationFrame;\n }\n const handle = request((timestamp) => {\n // Clear the cancel function. The request has been fulfilled, so\n // attempting to cancel the request upon unsubscription would be\n // pointless.\n cancel = undefined;\n callback(timestamp);\n });\n return new Subscription(() => cancel?.(handle));\n },\n requestAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.requestAnimationFrame || requestAnimationFrame)(...args);\n },\n cancelAnimationFrame(...args) {\n const { delegate } = animationFrameProvider;\n return (delegate?.cancelAnimationFrame || cancelAnimationFrame)(...args);\n },\n delegate: undefined,\n};\n", "import { createErrorClass } from './createErrorClass';\n\nexport interface ObjectUnsubscribedError extends Error {}\n\nexport interface ObjectUnsubscribedErrorCtor {\n /**\n * @deprecated Internal implementation detail. Do not construct error instances.\n * Cannot be tagged as internal: https://github.com/ReactiveX/rxjs/issues/6269\n */\n new (): ObjectUnsubscribedError;\n}\n\n/**\n * An error thrown when an action is invalid because the object has been\n * unsubscribed.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n *\n * @class ObjectUnsubscribedError\n */\nexport const ObjectUnsubscribedError: ObjectUnsubscribedErrorCtor = createErrorClass(\n (_super) =>\n function ObjectUnsubscribedErrorImpl(this: any) {\n _super(this);\n this.name = 'ObjectUnsubscribedError';\n this.message = 'object unsubscribed';\n }\n);\n", "import { Operator } from './Operator';\nimport { Observable } from './Observable';\nimport { Subscriber } from './Subscriber';\nimport { Subscription, EMPTY_SUBSCRIPTION } from './Subscription';\nimport { Observer, SubscriptionLike, TeardownLogic } from './types';\nimport { ObjectUnsubscribedError } from './util/ObjectUnsubscribedError';\nimport { arrRemove } from './util/arrRemove';\nimport { errorContext } from './util/errorContext';\n\n/**\n * A Subject is a special type of Observable that allows values to be\n * multicasted to many Observers. Subjects are like EventEmitters.\n *\n * Every Subject is an Observable and an Observer. You can subscribe to a\n * Subject, and you can call next to feed values as well as error and complete.\n */\nexport class Subject extends Observable implements SubscriptionLike {\n closed = false;\n\n private currentObservers: Observer[] | null = null;\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n observers: Observer[] = [];\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n isStopped = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n hasError = false;\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n thrownError: any = null;\n\n /**\n * Creates a \"subject\" by basically gluing an observer to an observable.\n *\n * @deprecated Recommended you do not use. Will be removed at some point in the future. Plans for replacement still under discussion.\n */\n static create: (...args: any[]) => any = (destination: Observer, source: Observable): AnonymousSubject => {\n return new AnonymousSubject(destination, source);\n };\n\n constructor() {\n // NOTE: This must be here to obscure Observable's constructor.\n super();\n }\n\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n lift(operator: Operator): Observable {\n const subject = new AnonymousSubject(this, this);\n subject.operator = operator as any;\n return subject as any;\n }\n\n /** @internal */\n protected _throwIfClosed() {\n if (this.closed) {\n throw new ObjectUnsubscribedError();\n }\n }\n\n next(value: T) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n if (!this.currentObservers) {\n this.currentObservers = Array.from(this.observers);\n }\n for (const observer of this.currentObservers) {\n observer.next(value);\n }\n }\n });\n }\n\n error(err: any) {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.hasError = this.isStopped = true;\n this.thrownError = err;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.error(err);\n }\n }\n });\n }\n\n complete() {\n errorContext(() => {\n this._throwIfClosed();\n if (!this.isStopped) {\n this.isStopped = true;\n const { observers } = this;\n while (observers.length) {\n observers.shift()!.complete();\n }\n }\n });\n }\n\n unsubscribe() {\n this.isStopped = this.closed = true;\n this.observers = this.currentObservers = null!;\n }\n\n get observed() {\n return this.observers?.length > 0;\n }\n\n /** @internal */\n protected _trySubscribe(subscriber: Subscriber): TeardownLogic {\n this._throwIfClosed();\n return super._trySubscribe(subscriber);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._checkFinalizedStatuses(subscriber);\n return this._innerSubscribe(subscriber);\n }\n\n /** @internal */\n protected _innerSubscribe(subscriber: Subscriber) {\n const { hasError, isStopped, observers } = this;\n if (hasError || isStopped) {\n return EMPTY_SUBSCRIPTION;\n }\n this.currentObservers = null;\n observers.push(subscriber);\n return new Subscription(() => {\n this.currentObservers = null;\n arrRemove(observers, subscriber);\n });\n }\n\n /** @internal */\n protected _checkFinalizedStatuses(subscriber: Subscriber) {\n const { hasError, thrownError, isStopped } = this;\n if (hasError) {\n subscriber.error(thrownError);\n } else if (isStopped) {\n subscriber.complete();\n }\n }\n\n /**\n * Creates a new Observable with this Subject as the source. You can do this\n * to create custom Observer-side logic of the Subject and conceal it from\n * code that uses the Observable.\n * @return Observable that this Subject casts to.\n */\n asObservable(): Observable {\n const observable: any = new Observable();\n observable.source = this;\n return observable;\n }\n}\n\nexport class AnonymousSubject extends Subject {\n constructor(\n /** @deprecated Internal implementation detail, do not use directly. Will be made internal in v8. */\n public destination?: Observer,\n source?: Observable\n ) {\n super();\n this.source = source;\n }\n\n next(value: T) {\n this.destination?.next?.(value);\n }\n\n error(err: any) {\n this.destination?.error?.(err);\n }\n\n complete() {\n this.destination?.complete?.();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n return this.source?.subscribe(subscriber) ?? EMPTY_SUBSCRIPTION;\n }\n}\n", "import { Subject } from './Subject';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\n\n/**\n * A variant of Subject that requires an initial value and emits its current\n * value whenever it is subscribed to.\n */\nexport class BehaviorSubject extends Subject {\n constructor(private _value: T) {\n super();\n }\n\n get value(): T {\n return this.getValue();\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n const subscription = super._subscribe(subscriber);\n !subscription.closed && subscriber.next(this._value);\n return subscription;\n }\n\n getValue(): T {\n const { hasError, thrownError, _value } = this;\n if (hasError) {\n throw thrownError;\n }\n this._throwIfClosed();\n return _value;\n }\n\n next(value: T): void {\n super.next((this._value = value));\n }\n}\n", "import { TimestampProvider } from '../types';\n\ninterface DateTimestampProvider extends TimestampProvider {\n delegate: TimestampProvider | undefined;\n}\n\nexport const dateTimestampProvider: DateTimestampProvider = {\n now() {\n // Use the variable rather than `this` so that the function can be called\n // without being bound to the provider.\n return (dateTimestampProvider.delegate || Date).now();\n },\n delegate: undefined,\n};\n", "import { Subject } from './Subject';\nimport { TimestampProvider } from './types';\nimport { Subscriber } from './Subscriber';\nimport { Subscription } from './Subscription';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * A variant of {@link Subject} that \"replays\" old values to new subscribers by emitting them when they first subscribe.\n *\n * `ReplaySubject` has an internal buffer that will store a specified number of values that it has observed. Like `Subject`,\n * `ReplaySubject` \"observes\" values by having them passed to its `next` method. When it observes a value, it will store that\n * value for a time determined by the configuration of the `ReplaySubject`, as passed to its constructor.\n *\n * When a new subscriber subscribes to the `ReplaySubject` instance, it will synchronously emit all values in its buffer in\n * a First-In-First-Out (FIFO) manner. The `ReplaySubject` will also complete, if it has observed completion; and it will\n * error if it has observed an error.\n *\n * There are two main configuration items to be concerned with:\n *\n * 1. `bufferSize` - This will determine how many items are stored in the buffer, defaults to infinite.\n * 2. `windowTime` - The amount of time to hold a value in the buffer before removing it from the buffer.\n *\n * Both configurations may exist simultaneously. So if you would like to buffer a maximum of 3 values, as long as the values\n * are less than 2 seconds old, you could do so with a `new ReplaySubject(3, 2000)`.\n *\n * ### Differences with BehaviorSubject\n *\n * `BehaviorSubject` is similar to `new ReplaySubject(1)`, with a couple of exceptions:\n *\n * 1. `BehaviorSubject` comes \"primed\" with a single value upon construction.\n * 2. `ReplaySubject` will replay values, even after observing an error, where `BehaviorSubject` will not.\n *\n * @see {@link Subject}\n * @see {@link BehaviorSubject}\n * @see {@link shareReplay}\n */\nexport class ReplaySubject extends Subject {\n private _buffer: (T | number)[] = [];\n private _infiniteTimeWindow = true;\n\n /**\n * @param _bufferSize The size of the buffer to replay on subscription\n * @param _windowTime The amount of time the buffered items will stay buffered\n * @param _timestampProvider An object with a `now()` method that provides the current timestamp. This is used to\n * calculate the amount of time something has been buffered.\n */\n constructor(\n private _bufferSize = Infinity,\n private _windowTime = Infinity,\n private _timestampProvider: TimestampProvider = dateTimestampProvider\n ) {\n super();\n this._infiniteTimeWindow = _windowTime === Infinity;\n this._bufferSize = Math.max(1, _bufferSize);\n this._windowTime = Math.max(1, _windowTime);\n }\n\n next(value: T): void {\n const { isStopped, _buffer, _infiniteTimeWindow, _timestampProvider, _windowTime } = this;\n if (!isStopped) {\n _buffer.push(value);\n !_infiniteTimeWindow && _buffer.push(_timestampProvider.now() + _windowTime);\n }\n this._trimBuffer();\n super.next(value);\n }\n\n /** @internal */\n protected _subscribe(subscriber: Subscriber): Subscription {\n this._throwIfClosed();\n this._trimBuffer();\n\n const subscription = this._innerSubscribe(subscriber);\n\n const { _infiniteTimeWindow, _buffer } = this;\n // We use a copy here, so reentrant code does not mutate our array while we're\n // emitting it to a new subscriber.\n const copy = _buffer.slice();\n for (let i = 0; i < copy.length && !subscriber.closed; i += _infiniteTimeWindow ? 1 : 2) {\n subscriber.next(copy[i] as T);\n }\n\n this._checkFinalizedStatuses(subscriber);\n\n return subscription;\n }\n\n private _trimBuffer() {\n const { _bufferSize, _timestampProvider, _buffer, _infiniteTimeWindow } = this;\n // If we don't have an infinite buffer size, and we're over the length,\n // use splice to truncate the old buffer values off. Note that we have to\n // double the size for instances where we're not using an infinite time window\n // because we're storing the values and the timestamps in the same array.\n const adjustedBufferSize = (_infiniteTimeWindow ? 1 : 2) * _bufferSize;\n _bufferSize < Infinity && adjustedBufferSize < _buffer.length && _buffer.splice(0, _buffer.length - adjustedBufferSize);\n\n // Now, if we're not in an infinite time window, remove all values where the time is\n // older than what is allowed.\n if (!_infiniteTimeWindow) {\n const now = _timestampProvider.now();\n let last = 0;\n // Search the array for the first timestamp that isn't expired and\n // truncate the buffer up to that point.\n for (let i = 1; i < _buffer.length && (_buffer[i] as number) <= now; i += 2) {\n last = i;\n }\n last && _buffer.splice(0, last + 1);\n }\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Subscription } from '../Subscription';\nimport { SchedulerAction } from '../types';\n\n/**\n * A unit of work to be executed in a `scheduler`. An action is typically\n * created from within a {@link SchedulerLike} and an RxJS user does not need to concern\n * themselves about creating and manipulating an Action.\n *\n * ```ts\n * class Action extends Subscription {\n * new (scheduler: Scheduler, work: (state?: T) => void);\n * schedule(state?: T, delay: number = 0): Subscription;\n * }\n * ```\n */\nexport class Action extends Subscription {\n constructor(scheduler: Scheduler, work: (this: SchedulerAction, state?: T) => void) {\n super();\n }\n /**\n * Schedules this action on its parent {@link SchedulerLike} for execution. May be passed\n * some context object, `state`. May happen at some point in the future,\n * according to the `delay` parameter, if specified.\n * @param state Some contextual data that the `work` function uses when called by the\n * Scheduler.\n * @param delay Time to wait before executing the work, where the time unit is implicit\n * and defined by the Scheduler.\n * @return A subscription in order to be able to unsubscribe the scheduled work.\n */\n public schedule(state?: T, delay: number = 0): Subscription {\n return this;\n }\n}\n", "import type { TimerHandle } from './timerHandle';\ntype SetIntervalFunction = (handler: () => void, timeout?: number, ...args: any[]) => TimerHandle;\ntype ClearIntervalFunction = (handle: TimerHandle) => void;\n\ninterface IntervalProvider {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n delegate:\n | {\n setInterval: SetIntervalFunction;\n clearInterval: ClearIntervalFunction;\n }\n | undefined;\n}\n\nexport const intervalProvider: IntervalProvider = {\n // When accessing the delegate, use the variable rather than `this` so that\n // the functions can be called without being bound to the provider.\n setInterval(handler: () => void, timeout?: number, ...args) {\n const { delegate } = intervalProvider;\n if (delegate?.setInterval) {\n return delegate.setInterval(handler, timeout, ...args);\n }\n return setInterval(handler, timeout, ...args);\n },\n clearInterval(handle) {\n const { delegate } = intervalProvider;\n return (delegate?.clearInterval || clearInterval)(handle as any);\n },\n delegate: undefined,\n};\n", "import { Action } from './Action';\nimport { SchedulerAction } from '../types';\nimport { Subscription } from '../Subscription';\nimport { AsyncScheduler } from './AsyncScheduler';\nimport { intervalProvider } from './intervalProvider';\nimport { arrRemove } from '../util/arrRemove';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncAction extends Action {\n public id: TimerHandle | undefined;\n public state?: T;\n // @ts-ignore: Property has no initializer and is not definitely assigned\n public delay: number;\n protected pending: boolean = false;\n\n constructor(protected scheduler: AsyncScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (this.closed) {\n return this;\n }\n\n // Always replace the current state with the new state.\n this.state = state;\n\n const id = this.id;\n const scheduler = this.scheduler;\n\n //\n // Important implementation note:\n //\n // Actions only execute once by default, unless rescheduled from within the\n // scheduled callback. This allows us to implement single and repeat\n // actions via the same code path, without adding API surface area, as well\n // as mimic traditional recursion but across asynchronous boundaries.\n //\n // However, JS runtimes and timers distinguish between intervals achieved by\n // serial `setTimeout` calls vs. a single `setInterval` call. An interval of\n // serial `setTimeout` calls can be individually delayed, which delays\n // scheduling the next `setTimeout`, and so on. `setInterval` attempts to\n // guarantee the interval callback will be invoked more precisely to the\n // interval period, regardless of load.\n //\n // Therefore, we use `setInterval` to schedule single and repeat actions.\n // If the action reschedules itself with the same delay, the interval is not\n // canceled. If the action doesn't reschedule, or reschedules with a\n // different delay, the interval will be canceled after scheduled callback\n // execution.\n //\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, delay);\n }\n\n // Set the pending flag indicating that this action has been scheduled, or\n // has recursively rescheduled itself.\n this.pending = true;\n\n this.delay = delay;\n // If this action has already an async Id, don't request a new one.\n this.id = this.id ?? this.requestAsyncId(scheduler, this.id, delay);\n\n return this;\n }\n\n protected requestAsyncId(scheduler: AsyncScheduler, _id?: TimerHandle, delay: number = 0): TimerHandle {\n return intervalProvider.setInterval(scheduler.flush.bind(scheduler, this), delay);\n }\n\n protected recycleAsyncId(_scheduler: AsyncScheduler, id?: TimerHandle, delay: number | null = 0): TimerHandle | undefined {\n // If this action is rescheduled with the same delay time, don't clear the interval id.\n if (delay != null && this.delay === delay && this.pending === false) {\n return id;\n }\n // Otherwise, if the action's delay time is different from the current delay,\n // or the action has been rescheduled before it's executed, clear the interval id\n if (id != null) {\n intervalProvider.clearInterval(id);\n }\n\n return undefined;\n }\n\n /**\n * Immediately executes this action and the `work` it contains.\n */\n public execute(state: T, delay: number): any {\n if (this.closed) {\n return new Error('executing a cancelled action');\n }\n\n this.pending = false;\n const error = this._execute(state, delay);\n if (error) {\n return error;\n } else if (this.pending === false && this.id != null) {\n // Dequeue if the action didn't reschedule itself. Don't call\n // unsubscribe(), because the action could reschedule later.\n // For example:\n // ```\n // scheduler.schedule(function doWork(counter) {\n // /* ... I'm a busy worker bee ... */\n // var originalAction = this;\n // /* wait 100ms before rescheduling the action */\n // setTimeout(function () {\n // originalAction.schedule(counter + 1);\n // }, 100);\n // }, 1000);\n // ```\n this.id = this.recycleAsyncId(this.scheduler, this.id, null);\n }\n }\n\n protected _execute(state: T, _delay: number): any {\n let errored: boolean = false;\n let errorValue: any;\n try {\n this.work(state);\n } catch (e) {\n errored = true;\n // HACK: Since code elsewhere is relying on the \"truthiness\" of the\n // return here, we can't have it return \"\" or 0 or false.\n // TODO: Clean this up when we refactor schedulers mid-version-8 or so.\n errorValue = e ? e : new Error('Scheduled action threw falsy error');\n }\n if (errored) {\n this.unsubscribe();\n return errorValue;\n }\n }\n\n unsubscribe() {\n if (!this.closed) {\n const { id, scheduler } = this;\n const { actions } = scheduler;\n\n this.work = this.state = this.scheduler = null!;\n this.pending = false;\n\n arrRemove(actions, this);\n if (id != null) {\n this.id = this.recycleAsyncId(scheduler, id, null);\n }\n\n this.delay = null!;\n super.unsubscribe();\n }\n }\n}\n", "import { Action } from './scheduler/Action';\nimport { Subscription } from './Subscription';\nimport { SchedulerLike, SchedulerAction } from './types';\nimport { dateTimestampProvider } from './scheduler/dateTimestampProvider';\n\n/**\n * An execution context and a data structure to order tasks and schedule their\n * execution. Provides a notion of (potentially virtual) time, through the\n * `now()` getter method.\n *\n * Each unit of work in a Scheduler is called an `Action`.\n *\n * ```ts\n * class Scheduler {\n * now(): number;\n * schedule(work, delay?, state?): Subscription;\n * }\n * ```\n *\n * @deprecated Scheduler is an internal implementation detail of RxJS, and\n * should not be used directly. Rather, create your own class and implement\n * {@link SchedulerLike}. Will be made internal in v8.\n */\nexport class Scheduler implements SchedulerLike {\n public static now: () => number = dateTimestampProvider.now;\n\n constructor(private schedulerActionCtor: typeof Action, now: () => number = Scheduler.now) {\n this.now = now;\n }\n\n /**\n * A getter method that returns a number representing the current time\n * (at the time this function was called) according to the scheduler's own\n * internal clock.\n * @return A number that represents the current time. May or may not\n * have a relation to wall-clock time. May or may not refer to a time unit\n * (e.g. milliseconds).\n */\n public now: () => number;\n\n /**\n * Schedules a function, `work`, for execution. May happen at some point in\n * the future, according to the `delay` parameter, if specified. May be passed\n * some context object, `state`, which will be passed to the `work` function.\n *\n * The given arguments will be processed an stored as an Action object in a\n * queue of actions.\n *\n * @param work A function representing a task, or some unit of work to be\n * executed by the Scheduler.\n * @param delay Time to wait before executing the work, where the time unit is\n * implicit and defined by the Scheduler itself.\n * @param state Some contextual data that the `work` function uses when called\n * by the Scheduler.\n * @return A subscription in order to be able to unsubscribe the scheduled work.\n */\n public schedule(work: (this: SchedulerAction, state?: T) => void, delay: number = 0, state?: T): Subscription {\n return new this.schedulerActionCtor(this, work).schedule(state, delay);\n }\n}\n", "import { Scheduler } from '../Scheduler';\nimport { Action } from './Action';\nimport { AsyncAction } from './AsyncAction';\nimport { TimerHandle } from './timerHandle';\n\nexport class AsyncScheduler extends Scheduler {\n public actions: Array> = [];\n /**\n * A flag to indicate whether the Scheduler is currently executing a batch of\n * queued actions.\n * @internal\n */\n public _active: boolean = false;\n /**\n * An internal ID used to track the latest asynchronous task such as those\n * coming from `setTimeout`, `setInterval`, `requestAnimationFrame`, and\n * others.\n * @internal\n */\n public _scheduled: TimerHandle | undefined;\n\n constructor(SchedulerAction: typeof Action, now: () => number = Scheduler.now) {\n super(SchedulerAction, now);\n }\n\n public flush(action: AsyncAction): void {\n const { actions } = this;\n\n if (this._active) {\n actions.push(action);\n return;\n }\n\n let error: any;\n this._active = true;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions.shift()!)); // exhaust the scheduler queue\n\n this._active = false;\n\n if (error) {\n while ((action = actions.shift()!)) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\n/**\n *\n * Async Scheduler\n *\n * Schedule task as if you used setTimeout(task, duration)\n *\n * `async` scheduler schedules tasks asynchronously, by putting them on the JavaScript\n * event loop queue. It is best used to delay tasks in time or to schedule tasks repeating\n * in intervals.\n *\n * If you just want to \"defer\" task, that is to perform it right after currently\n * executing synchronous code ends (commonly achieved by `setTimeout(deferredTask, 0)`),\n * better choice will be the {@link asapScheduler} scheduler.\n *\n * ## Examples\n * Use async scheduler to delay task\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * const task = () => console.log('it works!');\n *\n * asyncScheduler.schedule(task, 2000);\n *\n * // After 2 seconds logs:\n * // \"it works!\"\n * ```\n *\n * Use async scheduler to repeat task in intervals\n * ```ts\n * import { asyncScheduler } from 'rxjs';\n *\n * function task(state) {\n * console.log(state);\n * this.schedule(state + 1, 1000); // `this` references currently executing Action,\n * // which we reschedule with new state and delay\n * }\n *\n * asyncScheduler.schedule(task, 3000, 0);\n *\n * // Logs:\n * // 0 after 3s\n * // 1 after 4s\n * // 2 after 5s\n * // 3 after 6s\n * ```\n */\n\nexport const asyncScheduler = new AsyncScheduler(AsyncAction);\n\n/**\n * @deprecated Renamed to {@link asyncScheduler}. Will be removed in v8.\n */\nexport const async = asyncScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { Subscription } from '../Subscription';\nimport { QueueScheduler } from './QueueScheduler';\nimport { SchedulerAction } from '../types';\nimport { TimerHandle } from './timerHandle';\n\nexport class QueueAction extends AsyncAction {\n constructor(protected scheduler: QueueScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n public schedule(state?: T, delay: number = 0): Subscription {\n if (delay > 0) {\n return super.schedule(state, delay);\n }\n this.delay = delay;\n this.state = state;\n this.scheduler.flush(this);\n return this;\n }\n\n public execute(state: T, delay: number): any {\n return delay > 0 || this.closed ? super.execute(state, delay) : this._execute(state, delay);\n }\n\n protected requestAsyncId(scheduler: QueueScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n\n if ((delay != null && delay > 0) || (delay == null && this.delay > 0)) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n\n // Otherwise flush the scheduler starting with this action.\n scheduler.flush(this);\n\n // HACK: In the past, this was returning `void`. However, `void` isn't a valid\n // `TimerHandle`, and generally the return value here isn't really used. So the\n // compromise is to return `0` which is both \"falsy\" and a valid `TimerHandle`,\n // as opposed to refactoring every other instanceo of `requestAsyncId`.\n return 0;\n }\n}\n", "import { AsyncScheduler } from './AsyncScheduler';\n\nexport class QueueScheduler extends AsyncScheduler {\n}\n", "import { QueueAction } from './QueueAction';\nimport { QueueScheduler } from './QueueScheduler';\n\n/**\n *\n * Queue Scheduler\n *\n * Put every next task on a queue, instead of executing it immediately\n *\n * `queue` scheduler, when used with delay, behaves the same as {@link asyncScheduler} scheduler.\n *\n * When used without delay, it schedules given task synchronously - executes it right when\n * it is scheduled. However when called recursively, that is when inside the scheduled task,\n * another task is scheduled with queue scheduler, instead of executing immediately as well,\n * that task will be put on a queue and wait for current one to finish.\n *\n * This means that when you execute task with `queue` scheduler, you are sure it will end\n * before any other task scheduled with that scheduler will start.\n *\n * ## Examples\n * Schedule recursively first, then do something\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(() => {\n * queueScheduler.schedule(() => console.log('second')); // will not happen now, but will be put on a queue\n *\n * console.log('first');\n * });\n *\n * // Logs:\n * // \"first\"\n * // \"second\"\n * ```\n *\n * Reschedule itself recursively\n * ```ts\n * import { queueScheduler } from 'rxjs';\n *\n * queueScheduler.schedule(function(state) {\n * if (state !== 0) {\n * console.log('before', state);\n * this.schedule(state - 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * console.log('after', state);\n * }\n * }, 0, 3);\n *\n * // In scheduler that runs recursively, you would expect:\n * // \"before\", 3\n * // \"before\", 2\n * // \"before\", 1\n * // \"after\", 1\n * // \"after\", 2\n * // \"after\", 3\n *\n * // But with queue it logs:\n * // \"before\", 3\n * // \"after\", 3\n * // \"before\", 2\n * // \"after\", 2\n * // \"before\", 1\n * // \"after\", 1\n * ```\n */\n\nexport const queueScheduler = new QueueScheduler(QueueAction);\n\n/**\n * @deprecated Renamed to {@link queueScheduler}. Will be removed in v8.\n */\nexport const queue = queueScheduler;\n", "import { AsyncAction } from './AsyncAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\nimport { SchedulerAction } from '../types';\nimport { animationFrameProvider } from './animationFrameProvider';\nimport { TimerHandle } from './timerHandle';\n\nexport class AnimationFrameAction extends AsyncAction {\n constructor(protected scheduler: AnimationFrameScheduler, protected work: (this: SchedulerAction, state?: T) => void) {\n super(scheduler, work);\n }\n\n protected requestAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle {\n // If delay is greater than 0, request as an async action.\n if (delay !== null && delay > 0) {\n return super.requestAsyncId(scheduler, id, delay);\n }\n // Push the action to the end of the scheduler queue.\n scheduler.actions.push(this);\n // If an animation frame has already been requested, don't request another\n // one. If an animation frame hasn't been requested yet, request one. Return\n // the current animation frame request id.\n return scheduler._scheduled || (scheduler._scheduled = animationFrameProvider.requestAnimationFrame(() => scheduler.flush(undefined)));\n }\n\n protected recycleAsyncId(scheduler: AnimationFrameScheduler, id?: TimerHandle, delay: number = 0): TimerHandle | undefined {\n // If delay exists and is greater than 0, or if the delay is null (the\n // action wasn't rescheduled) but was originally scheduled as an async\n // action, then recycle as an async action.\n if (delay != null ? delay > 0 : this.delay > 0) {\n return super.recycleAsyncId(scheduler, id, delay);\n }\n // If the scheduler queue has no remaining actions with the same async id,\n // cancel the requested animation frame and set the scheduled flag to\n // undefined so the next AnimationFrameAction will request its own.\n const { actions } = scheduler;\n if (id != null && id === scheduler._scheduled && actions[actions.length - 1]?.id !== id) {\n animationFrameProvider.cancelAnimationFrame(id as number);\n scheduler._scheduled = undefined;\n }\n // Return undefined so the action knows to request a new async id if it's rescheduled.\n return undefined;\n }\n}\n", "import { AsyncAction } from './AsyncAction';\nimport { AsyncScheduler } from './AsyncScheduler';\n\nexport class AnimationFrameScheduler extends AsyncScheduler {\n public flush(action?: AsyncAction): void {\n this._active = true;\n // The async id that effects a call to flush is stored in _scheduled.\n // Before executing an action, it's necessary to check the action's async\n // id to determine whether it's supposed to be executed in the current\n // flush.\n // Previous implementations of this method used a count to determine this,\n // but that was unsound, as actions that are unsubscribed - i.e. cancelled -\n // are removed from the actions array and that can shift actions that are\n // scheduled to be executed in a subsequent flush into positions at which\n // they are executed within the current flush.\n let flushId;\n if (action) {\n flushId = action.id;\n } else {\n flushId = this._scheduled;\n this._scheduled = undefined;\n }\n\n const { actions } = this;\n let error: any;\n action = action || actions.shift()!;\n\n do {\n if ((error = action.execute(action.state, action.delay))) {\n break;\n }\n } while ((action = actions[0]) && action.id === flushId && actions.shift());\n\n this._active = false;\n\n if (error) {\n while ((action = actions[0]) && action.id === flushId && actions.shift()) {\n action.unsubscribe();\n }\n throw error;\n }\n }\n}\n", "import { AnimationFrameAction } from './AnimationFrameAction';\nimport { AnimationFrameScheduler } from './AnimationFrameScheduler';\n\n/**\n *\n * Animation Frame Scheduler\n *\n * Perform task when `window.requestAnimationFrame` would fire\n *\n * When `animationFrame` scheduler is used with delay, it will fall back to {@link asyncScheduler} scheduler\n * behaviour.\n *\n * Without delay, `animationFrame` scheduler can be used to create smooth browser animations.\n * It makes sure scheduled task will happen just before next browser content repaint,\n * thus performing animations as efficiently as possible.\n *\n * ## Example\n * Schedule div height animation\n * ```ts\n * // html:
\n * import { animationFrameScheduler } from 'rxjs';\n *\n * const div = document.querySelector('div');\n *\n * animationFrameScheduler.schedule(function(height) {\n * div.style.height = height + \"px\";\n *\n * this.schedule(height + 1); // `this` references currently executing Action,\n * // which we reschedule with new state\n * }, 0, 0);\n *\n * // You will see a div element growing in height\n * ```\n */\n\nexport const animationFrameScheduler = new AnimationFrameScheduler(AnimationFrameAction);\n\n/**\n * @deprecated Renamed to {@link animationFrameScheduler}. Will be removed in v8.\n */\nexport const animationFrame = animationFrameScheduler;\n", "import { Observable } from '../Observable';\nimport { SchedulerLike } from '../types';\n\n/**\n * A simple Observable that emits no items to the Observer and immediately\n * emits a complete notification.\n *\n * Just emits 'complete', and nothing else.\n *\n * ![](empty.png)\n *\n * A simple Observable that only emits the complete notification. It can be used\n * for composing with other Observables, such as in a {@link mergeMap}.\n *\n * ## Examples\n *\n * Log complete notification\n *\n * ```ts\n * import { EMPTY } from 'rxjs';\n *\n * EMPTY.subscribe({\n * next: () => console.log('Next'),\n * complete: () => console.log('Complete!')\n * });\n *\n * // Outputs\n * // Complete!\n * ```\n *\n * Emit the number 7, then complete\n *\n * ```ts\n * import { EMPTY, startWith } from 'rxjs';\n *\n * const result = EMPTY.pipe(startWith(7));\n * result.subscribe(x => console.log(x));\n *\n * // Outputs\n * // 7\n * ```\n *\n * Map and flatten only odd numbers to the sequence `'a'`, `'b'`, `'c'`\n *\n * ```ts\n * import { interval, mergeMap, of, EMPTY } from 'rxjs';\n *\n * const interval$ = interval(1000);\n * const result = interval$.pipe(\n * mergeMap(x => x % 2 === 1 ? of('a', 'b', 'c') : EMPTY),\n * );\n * result.subscribe(x => console.log(x));\n *\n * // Results in the following to the console:\n * // x is equal to the count on the interval, e.g. (0, 1, 2, 3, ...)\n * // x will occur every 1000ms\n * // if x % 2 is equal to 1, print a, b, c (each on its own)\n * // if x % 2 is not equal to 1, nothing will be output\n * ```\n *\n * @see {@link Observable}\n * @see {@link NEVER}\n * @see {@link of}\n * @see {@link throwError}\n */\nexport const EMPTY = new Observable((subscriber) => subscriber.complete());\n\n/**\n * @param scheduler A {@link SchedulerLike} to use for scheduling\n * the emission of the complete notification.\n * @deprecated Replaced with the {@link EMPTY} constant or {@link scheduled} (e.g. `scheduled([], scheduler)`). Will be removed in v8.\n */\nexport function empty(scheduler?: SchedulerLike) {\n return scheduler ? emptyScheduled(scheduler) : EMPTY;\n}\n\nfunction emptyScheduled(scheduler: SchedulerLike) {\n return new Observable((subscriber) => scheduler.schedule(() => subscriber.complete()));\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport function isScheduler(value: any): value is SchedulerLike {\n return value && isFunction(value.schedule);\n}\n", "import { SchedulerLike } from '../types';\nimport { isFunction } from './isFunction';\nimport { isScheduler } from './isScheduler';\n\nfunction last(arr: T[]): T | undefined {\n return arr[arr.length - 1];\n}\n\nexport function popResultSelector(args: any[]): ((...args: unknown[]) => unknown) | undefined {\n return isFunction(last(args)) ? args.pop() : undefined;\n}\n\nexport function popScheduler(args: any[]): SchedulerLike | undefined {\n return isScheduler(last(args)) ? args.pop() : undefined;\n}\n\nexport function popNumber(args: any[], defaultValue: number): number {\n return typeof last(args) === 'number' ? args.pop()! : defaultValue;\n}\n", "export const isArrayLike = ((x: any): x is ArrayLike => x && typeof x.length === 'number' && typeof x !== 'function');", "import { isFunction } from \"./isFunction\";\n\n/**\n * Tests to see if the object is \"thennable\".\n * @param value the object to test\n */\nexport function isPromise(value: any): value is PromiseLike {\n return isFunction(value?.then);\n}\n", "import { InteropObservable } from '../types';\nimport { observable as Symbol_observable } from '../symbol/observable';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being Observable (but not necessary an Rx Observable) */\nexport function isInteropObservable(input: any): input is InteropObservable {\n return isFunction(input[Symbol_observable]);\n}\n", "import { isFunction } from './isFunction';\n\nexport function isAsyncIterable(obj: any): obj is AsyncIterable {\n return Symbol.asyncIterator && isFunction(obj?.[Symbol.asyncIterator]);\n}\n", "/**\n * Creates the TypeError to throw if an invalid object is passed to `from` or `scheduled`.\n * @param input The object that was passed.\n */\nexport function createInvalidObservableTypeError(input: any) {\n // TODO: We should create error codes that can be looked up, so this can be less verbose.\n return new TypeError(\n `You provided ${\n input !== null && typeof input === 'object' ? 'an invalid object' : `'${input}'`\n } where a stream was expected. You can provide an Observable, Promise, ReadableStream, Array, AsyncIterable, or Iterable.`\n );\n}\n", "export function getSymbolIterator(): symbol {\n if (typeof Symbol !== 'function' || !Symbol.iterator) {\n return '@@iterator' as any;\n }\n\n return Symbol.iterator;\n}\n\nexport const iterator = getSymbolIterator();\n", "import { iterator as Symbol_iterator } from '../symbol/iterator';\nimport { isFunction } from './isFunction';\n\n/** Identifies an input as being an Iterable */\nexport function isIterable(input: any): input is Iterable {\n return isFunction(input?.[Symbol_iterator]);\n}\n", "import { ReadableStreamLike } from '../types';\nimport { isFunction } from './isFunction';\n\nexport async function* readableStreamLikeToAsyncGenerator(readableStream: ReadableStreamLike): AsyncGenerator {\n const reader = readableStream.getReader();\n try {\n while (true) {\n const { value, done } = await reader.read();\n if (done) {\n return;\n }\n yield value!;\n }\n } finally {\n reader.releaseLock();\n }\n}\n\nexport function isReadableStreamLike(obj: any): obj is ReadableStreamLike {\n // We don't want to use instanceof checks because they would return\n // false for instances from another Realm, like an