docs: add Pydantic AI guide + Hermes standalone provider-plugin section

docs.json

@@ -223,7 +223,8 @@
                     "pages": [
                       "v3/integrations/openai-sdk-python",
                       "v3/integrations/openai-sdk-typescript",
-                      "v3/integrations/langchain"
+                      "v3/integrations/langchain",
+                      "v3/integrations/pydantic-ai"
                     ]
                   },
                   {

v3/integrations/hermes.mdx

@@ -15,7 +15,7 @@
   proficiencyLevel="Intermediate"
   keywords={["Eden AI", "AI API", "Hermes Agent", "Nous Research"]}
   datePublished="2026-06-19T00:00:00Z"
-  dateModified="2026-06-19T00:00:00Z"
+  dateModified="2026-07-16T00:00:00Z"
 />
 
 Connect [Hermes Agent](https://hermes-agent.nousresearch.com) to Eden AI and run the self-hosted, persistent agent on 500+ models with automatic fallbacks and a single API key.
@@ -66,7 +66,7 @@
 ```yaml config.yaml
 model:
   provider: custom
   base_url: https://api.edenai.run/v3
   default: anthropic/claude-sonnet-4-5
 ```
 </CodeGroup>
@@ -111,7 +111,7 @@
 | `anthropic/claude-opus-4-8` | Maximum capability |
 | `anthropic/claude-haiku-4-5` | Fast and cheap |
 | `openai/gpt-5` | OpenAI's frontier model |
 | `google/gemini-2.5-pro` | Long context, multimodal |
 
 Browse the full catalog at [app.edenai.run/models](https://app.edenai.run/models).
 
@@ -123,6 +123,51 @@
 hermes fallback add
 ```
 
+## First-class provider plugin (optional)
+
+The setup above uses Hermes' generic `custom` provider, which is the fastest way to get running. For a **native `--provider eden-ai` experience** — so Eden AI shows up in `hermes model`, `hermes doctor`, and the setup wizard — install Eden AI as a **standalone model-provider plugin**. Drop a directory under `$HERMES_HOME/plugins/model-providers/eden-ai/`, with no changes to the Hermes repo:
+
+<CodeGroup>
+{/* skip-test */}
+```python __init__.py
+from providers import register_provider
+from providers.base import ProviderProfile
+
+eden_ai = ProviderProfile(
+    name="eden-ai",
+    aliases=("edenai",),
+    display_name="Eden AI",
+    description="Eden AI — 500+ models via one OpenAI-compatible API (EU/GDPR)",
+    signup_url="https://app.edenai.run",
+    env_vars=("EDENAI_API_KEY",),
+    base_url="https://api.edenai.run/v3",
+    auth_type="api_key",
+    default_aux_model="mistral/mistral-small-2603",
+    fallback_models=(
+        "anthropic/claude-sonnet-5",
+        "openai/gpt-5.5",
+        "mistral/mistral-small-2603",
+    ),
+)
+
+register_provider(eden_ai)
+```
+
+```yaml plugin.yaml
+name: eden-ai
+kind: model-provider
+version: 1.0.0
+description: Eden AI — 500+ models via one OpenAI-compatible API (EU/GDPR)
+author: Eden AI
+```
+</CodeGroup>
+
+Hermes then auto-wires credential resolution, the `--provider eden-ai` flag, the `hermes model` picker (models fetched from `{base_url}/models`), and the `hermes doctor` health check. Select it with:
+
+```bash
+hermes chat --provider eden-ai
+```
+
 ## Troubleshooting
 
 ### `401` / `Custom token not found`

v3/integrations/pydantic-ai.mdx

@@ -0,0 +1,205 @@
+---
+title: "Pydantic AI"
+icon: "/integration-logo/pydantic-ai-icondoc.svg"
+description: "Use Pydantic AI with Eden AI to build type-safe agents on 500+ AI models through one API."
+---
+
+import { TechArticleSchema } from "/snippets/TechArticleSchema.mdx";
+
+<TechArticleSchema
+  title={"Pydantic AI"}
+  description={"Use Pydantic AI with Eden AI to build type-safe agents on 500+ AI models through one API."}
+  path="v3/integrations/pydantic-ai"
+  articleSection="AI Frameworks"
+  about={"LLM Framework Integration"}
+  proficiencyLevel="Intermediate"
+  keywords={["Eden AI", "AI API", "Pydantic AI", "Python", "Agents"]}
+  datePublished="2026-07-16T00:00:00Z"
+  dateModified="2026-07-16T00:00:00Z"
+/>
+
+Use Pydantic AI with Eden AI to build type-safe agents on 500+ AI models through one API.
+
+## Overview
+
+Pydantic AI is a type-safe, structured-output agent framework for Python. It works with any OpenAI-compatible endpoint through `OpenAIChatModel` + `OpenAIProvider`, so you can point it at Eden AI's V3 API and access models from OpenAI, Anthropic, Google, Cohere, Meta, and more — behind one key, with EU-based, GDPR-aligned inference.
+
+## Installation
+
+<CodeGroup>
+```bash pip
+pip install pydantic-ai
+```
+
+```bash poetry
+poetry add pydantic-ai
+```
+
+</CodeGroup>
+
+## Quick Start
+
+Point Pydantic AI's OpenAI model at Eden AI:
+
+<CodeGroup>
+{/* skip-test */}
+```python Python
+from pydantic_ai import Agent
+from pydantic_ai.models.openai import OpenAIChatModel
+from pydantic_ai.providers.openai import OpenAIProvider
+
+model = OpenAIChatModel(
+    "openai/gpt-5.5",
+    provider=OpenAIProvider(
+        api_key="YOUR_EDEN_AI_API_KEY",  # Get from https://app.edenai.run
+        base_url="https://api.edenai.run/v3",
+    ),
+)
+
+agent = Agent(model)
+result = agent.run_sync("Hello! How are you?")
+print(result.output)
+```
+</CodeGroup>
+
+## Available Models
+
+Access models from multiple providers using the `provider/model` format:
+
+**OpenAI**
+- `openai/gpt-5.5`
+- `openai/gpt-5-mini`
+
+**Anthropic**
+- `anthropic/claude-sonnet-5`
+- `anthropic/claude-opus-4-8`
+- `anthropic/claude-haiku-4-5`
+
+**Google**
+- `google/gemini-2.5-pro`
+- `google/gemini-3.5-flash`
+
+**Mistral**
+- `mistral/mistral-large-2512`
+- `mistral/mistral-small-2603`
+
+## Structured Output
+
+Pydantic AI's signature feature works unchanged — define a Pydantic `output_type` and the agent returns a validated object, whichever Eden AI model you choose:
+
+<CodeGroup>
+{/* skip-test */}
+```python Python
+from pydantic import BaseModel
+from pydantic_ai import Agent
+from pydantic_ai.models.openai import OpenAIChatModel
+from pydantic_ai.providers.openai import OpenAIProvider
+
+class City(BaseModel):
+    name: str
+    country: str
+    population: int
+
+model = OpenAIChatModel(
+    "anthropic/claude-sonnet-5",
+    provider=OpenAIProvider(
+        api_key="YOUR_EDEN_AI_API_KEY",
+        base_url="https://api.edenai.run/v3",
+    ),
+)
+
+agent = Agent(model, output_type=City)
+result = agent.run_sync("Tell me about the capital of France.")
+print(result.output)  # City(name='Paris', country='France', population=...)
+```
+</CodeGroup>
+
+## Multi-Turn Conversations
+
+Keep conversation history across runs with `message_history`:
+
+<CodeGroup>
+{/* skip-test */}
+```python Python
+from pydantic_ai import Agent
+from pydantic_ai.models.openai import OpenAIChatModel
+from pydantic_ai.providers.openai import OpenAIProvider
+
+model = OpenAIChatModel(
+    "anthropic/claude-sonnet-5",
+    provider=OpenAIProvider(
+        api_key="YOUR_EDEN_AI_API_KEY",
+        base_url="https://api.edenai.run/v3",
+    ),
+)
+agent = Agent(model, system_prompt="You are a helpful assistant.")
+
+result = agent.run_sync("What is the capital of France?")
+print(result.output)
+
+# Continue the conversation with prior context
+result = agent.run_sync(
+    "What's its population?",
+    message_history=result.all_messages(),
+)
+print(result.output)
+```
+</CodeGroup>
+
+## Error Handling
+
+<CodeGroup>
+{/* skip-test */}
+```python Python
+from pydantic_ai import Agent
+from pydantic_ai.models.openai import OpenAIChatModel
+from pydantic_ai.providers.openai import OpenAIProvider
+from pydantic_ai.exceptions import ModelHTTPError, UnexpectedModelBehavior
+
+model = OpenAIChatModel(
+    "openai/gpt-5.5",
+    provider=OpenAIProvider(
+        api_key="YOUR_EDEN_AI_API_KEY",
+        base_url="https://api.edenai.run/v3",
+    ),
+)
+agent = Agent(model)
+
+try:
+    result = agent.run_sync("Hello!")
+    print(result.output)
+except ModelHTTPError as e:
+    print(f"Model HTTP error (auth, rate limit, bad request): {e}")
+except UnexpectedModelBehavior as e:
+    print(f"Unexpected model behavior: {e}")
+```
+</CodeGroup>
+
+## Environment Variables
+
+<CodeGroup>
+```bash .env
+EDEN_AI_API_KEY=your_api_key_here
+```
+
+{/* skip-test */}
+```python Python
+import os
+from pydantic_ai.models.openai import OpenAIChatModel
+from pydantic_ai.providers.openai import OpenAIProvider
+
+model = OpenAIChatModel(
+    "openai/gpt-5.5",
+    provider=OpenAIProvider(
+        api_key=os.getenv("EDEN_AI_API_KEY"),
+        base_url="https://api.edenai.run/v3",
+    ),
+)
+```
+</CodeGroup>
+
+## Next Steps
+
+- [Chat Completions](/v3/llms/chat-completions) - Core LLM endpoint
+- [List LLM Models](/v3/llms/listing-models) - Browse available providers and models
+- [OpenAI SDK (Python)](/v3/integrations/openai-sdk-python) - Direct SDK usage