From 0cf1cd63915264e3f6fcdcc21fa01d16ebdc761e Mon Sep 17 00:00:00 2001 From: aGallea Date: Mon, 30 Mar 2026 17:21:55 +0300 Subject: [PATCH 1/6] feat(deps): replace openai with litellm for multi-provider LLM support --- pyproject.toml | 4 +- uv.lock | 147 +++++++++++++++++++++++++++++++++++++++++++++++-- 2 files changed, 144 insertions(+), 7 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 61f6c42..553ee41 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -15,7 +15,7 @@ dependencies = [ "dash>=3.4,<4", "plotly>=6.5,<7", "aiohttp>=3.11,<4", - "openai>=1.60,<2", + "litellm>=1.65,<2", "scikit-learn>=1.6,<2", "numpy>=2.2,<3", "Pillow>=11,<12", @@ -83,7 +83,7 @@ module = [ "plotly.*", "sklearn.*", "PIL.*", - "openai.*", + "litellm.*", "aiohttp.*", "umap.*", ] diff --git a/uv.lock b/uv.lock index db32f7a..ad1128b 100644 --- a/uv.lock +++ b/uv.lock @@ -366,8 +366,8 @@ dependencies = [ { name = "chromadb", marker = "(platform_machine == 'x86_64' and sys_platform == 'linux') or 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100644 tests/test_ai_naming.py diff --git a/embedding_cluster/ai_naming.py b/embedding_cluster/ai_naming.py new file mode 100644 index 0000000..ed62fd2 --- /dev/null +++ b/embedding_cluster/ai_naming.py @@ -0,0 +1,111 @@ +from __future__ import annotations + +import logging + +import litellm + +logger = logging.getLogger(__name__) + +# Alias for testability (easy to mock) +litellm_completion = litellm.completion + +SYSTEM_PROMPT_TOP_LEVEL = ( + "Your role is to find a very short (max 5 words), concise name " + "for a group of items, one name to rule them all. " + "The user will provide a list of item names. Do your best." +) + +SYSTEM_PROMPT_SUB_CLUSTER = ( + "Your role is to find a very short (max 5 words), concise name " + "for a sub-group of items within a larger group called " + '"{parent_name}". ' + "The name should distinguish this sub-group from its siblings " + "while relating to the parent theme. The user will provide a " + "list of item names. Do your best." +) + + +def _call_llm( + messages: list[dict[str, str]], + api_key: str, + model: str, + base_url: str | None = None, + temperature: float = 0.5, +) -> str: + """Call LiteLLM and return the response content.""" + kwargs: dict[str, object] = { + "model": model, + "messages": messages, + "api_key": api_key, + "temperature": temperature, + } + if base_url: + kwargs["api_base"] = base_url + + response = litellm_completion(**kwargs) + content: str = response.choices[0].message.content or "" + return (content[:30] + "..") if len(content) > 30 else content + + +def get_cluster_name( + item_names: list[str], + api_key: str, + model: str, + base_url: str | None = None, + temperature: float = 0.5, +) -> str: + """Generate a short name for a cluster of items.""" + user_content = "\n".join(f"name: {name}" for name in item_names) + messages = [ + {"role": "system", "content": SYSTEM_PROMPT_TOP_LEVEL}, + {"role": "user", "content": user_content}, + ] + return _call_llm(messages, api_key, model, base_url, temperature) + + +def get_sub_cluster_name( + item_names: list[str], + api_key: str, + model: str, + base_url: str | None = None, + temperature: float = 0.5, + parent_cluster_name: str | None = None, +) -> str: + """Generate a short name for a sub-cluster.""" + if parent_cluster_name: + system_content = SYSTEM_PROMPT_SUB_CLUSTER.format( + parent_name=parent_cluster_name, + ) + else: + system_content = SYSTEM_PROMPT_TOP_LEVEL + + user_content = "\n".join(f"name: {name}" for name in item_names) + messages = [ + {"role": "system", "content": system_content}, + {"role": "user", "content": user_content}, + ] + return _call_llm(messages, api_key, model, base_url, temperature) + + +def test_connection( + api_key: str, + model: str, + base_url: str | None = None, +) -> tuple[bool, str | None]: + """Test LLM connection. Returns (success, error).""" + try: + kwargs: dict[str, object] = { + "model": model, + "messages": [{"role": "user", "content": "Say hello"}], + "api_key": api_key, + "max_tokens": 5, + } + if base_url: + kwargs["api_base"] = base_url + litellm_completion(**kwargs) + return True, None + except Exception as exc: + error_msg = str(exc) + if api_key and api_key in error_msg: + error_msg = error_msg.replace(api_key, "***") + return False, error_msg diff --git a/embedding_cluster/scatter_plot.py b/embedding_cluster/scatter_plot.py index 532d1f1..13ecedc 100644 --- a/embedding_cluster/scatter_plot.py +++ b/embedding_cluster/scatter_plot.py @@ -1,14 +1,12 @@ from __future__ import annotations import logging -import random from typing import TYPE_CHECKING, Any import chromadb import numpy as np import plotly.graph_objects as go from dash import Dash, Input, Output, callback, dcc, html, no_update -from openai import OpenAI from sklearn.cluster import KMeans from sklearn.decomposition import PCA from sklearn.manifold import TSNE @@ -71,31 +69,6 @@ def reduce_dimensions( return result -def gpt_get_cluster_name(info: str, settings: Settings) -> str: - openai_client = OpenAI() - messages: list[dict[str, str]] = [ - { - "role": "system", - "content": ( - "Your role is to find a very short (max 5 words), concise " - "name for a group of items, one name to rule them all. " - "the user will provide a list of item names. do your best" - ), - }, - { - "role": "user", - "content": info, - }, - ] - completion = openai_client.chat.completions.create( - model=settings.gpt_default_model, - temperature=settings.gpt_default_temperature, - messages=messages, # type: ignore[arg-type] # pyright: ignore[reportArgumentType] - ) - content = completion.choices[0].message.content or "" - return (content[:30] + "..") if len(content) > 30 else content - - def load_chromadb_collection(settings: Settings) -> Any: chromadb_client: ClientAPI = chromadb.PersistentClient(path="./chromadb") collection = chromadb_client.get_or_create_collection( @@ -201,9 +174,9 @@ def generate_cluster_props( num_clusters: int, pred_arr: Any, collection_content_text_display: list[str], - settings: Settings, num_products_for_cluster_name: int = 10, ) -> tuple[list[list[int]], list[str]]: + _ = (collection_content_text_display, num_products_for_cluster_name) clusters_indices: list[list[int]] = [] cluster_names: list[str] = [] group_index = 1 @@ -211,28 +184,8 @@ def generate_cluster_props( curr_cluster_indices = [i for i, x in enumerate(pred_arr) if x == cluster_i] clusters_indices.append(curr_cluster_indices) logger.info("Generating cluster %d names ...", cluster_i) - if settings.gpt_generate_cluster_name is True: - random_product_indexes = random.sample( - range(0, len(curr_cluster_indices)), - min( - num_products_for_cluster_name, - len(curr_cluster_indices), - ), - ) - curr_descriptions = "" - for product_index in random_product_indexes: - idx = curr_cluster_indices[product_index] - item = ( - collection_content_text_display[idx] - if idx < len(collection_content_text_display) - else f"Item {idx}" - ) - curr_descriptions += f"name: {item} \n" - cluster_name = gpt_get_cluster_name(curr_descriptions, settings) - cluster_names.append(cluster_name) - else: - cluster_names.append(f"Group {group_index}") - group_index += 1 + cluster_names.append(f"Group {group_index}") + group_index += 1 return clusters_indices, cluster_names @@ -288,7 +241,7 @@ def compute_plot_data(settings: Settings) -> dict[str, Any]: ) clusters_indices, cluster_names = generate_cluster_props( - num_clusters, pred_arr, collection_content_text_display, settings + num_clusters, pred_arr, collection_content_text_display ) # Build structured point data diff --git a/embedding_cluster/server/models.py b/embedding_cluster/server/models.py index 5f42c1f..2a036df 100644 --- a/embedding_cluster/server/models.py +++ b/embedding_cluster/server/models.py @@ -70,9 +70,6 @@ class PlotRequest(BaseModel): num_clusters: int = 10 text_display_fields: list[str] | None = None image_field: str | None = None - gpt_generate_cluster_name: bool = False - gpt_default_model: str = "gpt-3.5-turbo" - gpt_default_temperature: float = 0.51 reduction_algorithm: Literal["tsne", "umap", "pca"] = "tsne" tsne_perplexity: float = 30.0 tsne_learning_rate: str = "auto" @@ -199,6 +196,7 @@ class SubClusterInfo(BaseModel): index: int count: int color: str + name: str | None = None class SubClusterResponse(BaseModel): diff --git a/embedding_cluster/server/routes/plot.py b/embedding_cluster/server/routes/plot.py index 35da576..5529f96 100644 --- a/embedding_cluster/server/routes/plot.py +++ b/embedding_cluster/server/routes/plot.py @@ -43,9 +43,6 @@ async def _run_compute(task_state: TaskState, request: PlotRequest) -> None: num_clusters=request.num_clusters, text_display_fields=request.text_display_fields, image_field=request.image_field, - gpt_generate_cluster_name=request.gpt_generate_cluster_name, - gpt_default_model=request.gpt_default_model, - gpt_default_temperature=request.gpt_default_temperature, reduction_algorithm=request.reduction_algorithm, tsne_perplexity=request.tsne_perplexity, tsne_learning_rate=request.tsne_learning_rate, diff --git a/embedding_cluster/settings.py b/embedding_cluster/settings.py index a7677ec..f424f31 100644 --- a/embedding_cluster/settings.py +++ b/embedding_cluster/settings.py @@ -75,11 +75,3 @@ class Settings(BaseSettings): umap_n_neighbors: int = Field(default=15, description="UMAP number of neighbors") umap_min_dist: float = Field(default=0.1, description="UMAP minimum distance") umap_metric: str = Field(default="cosine", description="UMAP distance metric") - - gpt_generate_cluster_name: bool = Field( - default=False, description="Generate cluster names using GPT" - ) - gpt_default_model: str = Field(default="gpt-3.5-turbo", description="GPT model name") - gpt_default_temperature: float = Field( - default=0.51, description="GPT model temperature" - ) diff --git a/tests/test_ai_naming.py b/tests/test_ai_naming.py new file mode 100644 index 0000000..1bc308a --- /dev/null +++ b/tests/test_ai_naming.py @@ -0,0 +1,198 @@ +from __future__ import annotations + +from unittest.mock import MagicMock, patch + + +class TestGetClusterName: + def test_returns_short_name(self) -> None: + from embedding_cluster.ai_naming import get_cluster_name + + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = "Athletic Footwear" + mock_response.choices = [mock_choice] + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=mock_response, + ): + result = get_cluster_name( + item_names=["Running Shoes", "Basketball Sneakers"], + api_key="test-key", + model="gpt-4o-mini", + ) + + assert result == "Athletic Footwear" + + def test_truncates_long_name(self) -> None: + from embedding_cluster.ai_naming import get_cluster_name + + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = "A" * 50 + mock_response.choices = [mock_choice] + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=mock_response, + ): + result = get_cluster_name( + item_names=["item1"], + api_key="test-key", + model="gpt-4o-mini", + ) + + assert len(result) == 32 # 30 chars + ".." + + def test_none_content_returns_empty(self) -> None: + from embedding_cluster.ai_naming import get_cluster_name + + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = None + mock_response.choices = [mock_choice] + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=mock_response, + ): + result = get_cluster_name( + item_names=["item1"], + api_key="test-key", + model="gpt-4o-mini", + ) + + assert result == "" + + def test_passes_base_url(self) -> None: + from embedding_cluster.ai_naming import get_cluster_name + + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = "Name" + mock_response.choices = [mock_choice] + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=mock_response, + ) as mock_completion: + get_cluster_name( + item_names=["item1"], + api_key="test-key", + model="gpt-4o-mini", + base_url="http://localhost:11434", + ) + + mock_completion.assert_called_once() + call_kwargs = mock_completion.call_args[1] + assert call_kwargs["api_base"] == "http://localhost:11434" + + def test_passes_temperature(self) -> None: + from embedding_cluster.ai_naming import get_cluster_name + + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = "Name" + mock_response.choices = [mock_choice] + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=mock_response, + ) as mock_completion: + get_cluster_name( + item_names=["item1"], + api_key="test-key", + model="gpt-4o-mini", + temperature=0.7, + ) + + mock_completion.assert_called_once() + call_kwargs = mock_completion.call_args[1] + assert call_kwargs["temperature"] == 0.7 + + +class TestGetSubClusterName: + def test_includes_parent_context(self) -> None: + from embedding_cluster.ai_naming import get_sub_cluster_name + + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = "Running Shoes" + mock_response.choices = [mock_choice] + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=mock_response, + ) as mock_completion: + result = get_sub_cluster_name( + item_names=["Nike Air Max", "Adidas Ultraboost"], + api_key="test-key", + model="gpt-4o-mini", + parent_cluster_name="Athletic Footwear", + ) + + assert result == "Running Shoes" + call_kwargs = mock_completion.call_args[1] + system_msg = call_kwargs["messages"][0]["content"] + assert "Athletic Footwear" in system_msg + + def test_without_parent_name_uses_default_prompt(self) -> None: + from embedding_cluster.ai_naming import get_sub_cluster_name + + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = "Sub Name" + mock_response.choices = [mock_choice] + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=mock_response, + ) as mock_completion: + result = get_sub_cluster_name( + item_names=["item1"], + api_key="test-key", + model="gpt-4o-mini", + ) + + assert result == "Sub Name" + call_kwargs = mock_completion.call_args[1] + system_msg = call_kwargs["messages"][0]["content"] + assert "sub-group" not in system_msg + + +class TestTestConnection: + def test_success(self) -> None: + from embedding_cluster.ai_naming import test_connection + + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = "Hello" + mock_response.choices = [mock_choice] + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=mock_response, + ): + success, error = test_connection( + api_key="test-key", + model="gpt-4o-mini", + ) + + assert success is True + assert error is None + + def test_failure_redacts_key(self) -> None: + from embedding_cluster.ai_naming import test_connection + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + side_effect=Exception("Invalid API key: sk-1234567890abcdef"), + ): + success, error = test_connection( + api_key="sk-1234567890abcdef", + model="gpt-4o-mini", + ) + + assert success is False + assert error is not None + assert "sk-1234567890abcdef" not in error diff --git a/tests/test_scatter_plot.py b/tests/test_scatter_plot.py index 6e8128e..2e1227b 100644 --- a/tests/test_scatter_plot.py +++ b/tests/test_scatter_plot.py @@ -1,5 +1,6 @@ from __future__ import annotations +from typing import cast from unittest.mock import MagicMock, patch import numpy as np @@ -50,10 +51,9 @@ def test_custom_separator(self) -> None: class TestGenerateClusterProps: - def test_without_gpt(self, monkeypatch: pytest.MonkeyPatch) -> None: + def test_without_gpt(self) -> None: from embedding_cluster.scatter_plot import generate_cluster_props - settings = Settings() pred_arr = [0, 0, 1, 1, 2] text_display = ["a", "b", "c", "d", "e"] @@ -61,7 +61,6 @@ def test_without_gpt(self, monkeypatch: pytest.MonkeyPatch) -> None: num_clusters=3, pred_arr=pred_arr, collection_content_text_display=text_display, - settings=settings, ) assert len(clusters_indices) == 3 @@ -71,83 +70,6 @@ def test_without_gpt(self, monkeypatch: pytest.MonkeyPatch) -> None: assert clusters_indices[2] == [4] assert cluster_names == ["Group 1", "Group 2", "Group 3"] - def test_with_gpt(self, monkeypatch: pytest.MonkeyPatch) -> None: - from embedding_cluster.scatter_plot import generate_cluster_props - - monkeypatch.setenv("GPT_GENERATE_CLUSTER_NAME", "true") - settings = Settings() - pred_arr = [0, 0] - text_display = ["item1", "item2"] - - with patch( - "embedding_cluster.scatter_plot.gpt_get_cluster_name", - return_value="Cool Group", - ): - _clusters_indices, cluster_names = generate_cluster_props( - num_clusters=1, - pred_arr=pred_arr, - collection_content_text_display=text_display, - settings=settings, - ) - - assert cluster_names == ["Cool Group"] - - -class TestGptGetClusterName: - def test_gpt_get_cluster_name(self) -> None: - from embedding_cluster.scatter_plot import gpt_get_cluster_name - - settings = Settings() - - with patch("embedding_cluster.scatter_plot.OpenAI") as mock_openai_cls: - mock_client = MagicMock() - mock_openai_cls.return_value = mock_client - mock_completion = MagicMock() - mock_choice = MagicMock() - mock_choice.message.content = "Fashion Items" - mock_completion.choices = [mock_choice] - mock_client.chat.completions.create.return_value = mock_completion - - result = gpt_get_cluster_name("item1\nitem2", settings) - - assert result == "Fashion Items" - - def test_gpt_truncates_long_name(self) -> None: - from embedding_cluster.scatter_plot import gpt_get_cluster_name - - settings = Settings() - - with patch("embedding_cluster.scatter_plot.OpenAI") as mock_openai_cls: - mock_client = MagicMock() - mock_openai_cls.return_value = mock_client - mock_completion = MagicMock() - mock_choice = MagicMock() - mock_choice.message.content = "A" * 50 - mock_completion.choices = [mock_choice] - mock_client.chat.completions.create.return_value = mock_completion - - result = gpt_get_cluster_name("info", settings) - - assert len(result) == 32 # 30 chars + ".." - - def test_gpt_none_content(self) -> None: - from embedding_cluster.scatter_plot import gpt_get_cluster_name - - settings = Settings() - - with patch("embedding_cluster.scatter_plot.OpenAI") as mock_openai_cls: - mock_client = MagicMock() - mock_openai_cls.return_value = mock_client - mock_completion = MagicMock() - mock_choice = MagicMock() - mock_choice.message.content = None - mock_completion.choices = [mock_choice] - mock_client.chat.completions.create.return_value = mock_completion - - result = gpt_get_cluster_name("info", settings) - - assert result == "" - class TestLoadChromadbCollection: def test_load(self) -> None: @@ -690,8 +612,8 @@ def test_points_aligned_with_cluster_labels(self) -> None: endpoint to return items from the wrong cluster. """ result = self._run_compute(self._make_settings(), n_points=6) - points = result["points"] - labels = result["cluster_labels"] + points = cast("list[dict[str, object]]", result["points"]) + labels = cast("list[int]", result["cluster_labels"]) assert len(points) == len(labels) for i, (point, label) in enumerate(zip(points, labels, strict=True)): assert point["cluster"] == label, ( @@ -706,7 +628,7 @@ def test_points_preserve_original_id_order(self) -> None: index-based lookup in cluster-detail and sub-cluster endpoints. """ result = self._run_compute(self._make_settings(), n_points=6) - points = result["points"] + points = cast("list[dict[str, object]]", result["points"]) expected_ids = [str(i) for i in range(6)] actual_ids = [p["id"] for p in points] assert actual_ids == expected_ids diff --git a/tests/test_server_plot.py b/tests/test_server_plot.py index 4aa1d76..7f0bb25 100644 --- a/tests/test_server_plot.py +++ b/tests/test_server_plot.py @@ -241,9 +241,6 @@ async def test_compute_with_all_fields(app: FastAPI, mock_compute: None) -> None "num_clusters": 5, "text_display_fields": ["name", "description"], "image_field": "imageUrl", - "gpt_generate_cluster_name": True, - "gpt_default_model": "gpt-4", - "gpt_default_temperature": 0.7, }, ) From 283166730d1e4001442e8382c7a24e2fa1f43f03 Mon Sep 17 00:00:00 2001 From: aGallea Date: Mon, 30 Mar 2026 17:56:37 +0300 Subject: [PATCH 3/6] feat(ai): add AI cluster naming endpoints and tests --- embedding_cluster/server/app.py | 2 + embedding_cluster/server/models.py | 35 +++ embedding_cluster/server/routes/ai.py | 160 ++++++++++++ tests/test_server_ai.py | 351 ++++++++++++++++++++++++++ tests/test_settings.py | 11 - 5 files changed, 548 insertions(+), 11 deletions(-) create mode 100644 embedding_cluster/server/routes/ai.py create mode 100644 tests/test_server_ai.py diff --git a/embedding_cluster/server/app.py b/embedding_cluster/server/app.py index 7a352da..3784879 100644 --- a/embedding_cluster/server/app.py +++ b/embedding_cluster/server/app.py @@ -8,6 +8,7 @@ from fastapi.responses import FileResponse from fastapi.staticfiles import StaticFiles +from embedding_cluster.server.routes.ai import router as ai_router from embedding_cluster.server.routes.annotations import ( router as annotations_router, ) @@ -43,6 +44,7 @@ def create_app() -> FastAPI: async def health_check() -> dict[str, str]: return {"status": "ok"} + app.include_router(ai_router) app.include_router(collections_router) app.include_router(csv_router) app.include_router(index_router) diff --git a/embedding_cluster/server/models.py b/embedding_cluster/server/models.py index 2a036df..56dcd22 100644 --- a/embedding_cluster/server/models.py +++ b/embedding_cluster/server/models.py @@ -246,3 +246,38 @@ class ClusterAnnotation(BaseModel): class AnnotationsResponse(BaseModel): job_id: str clusters: dict[str, ClusterAnnotation] + + +class AiNamingRequest(BaseModel): + job_id: str + cluster_indices: list[int] + api_key: str + model: str + base_url: str | None = None + temperature: float = 0.5 + + +class AiNamingResponse(BaseModel): + names: dict[str, str] + + +class AiSubClusterNamingRequest(BaseModel): + job_id: str + point_ids: list[str] + sub_cluster_labels: list[int] + api_key: str + model: str + base_url: str | None = None + temperature: float = 0.5 + parent_cluster_name: str | None = None + + +class AiTestConnectionRequest(BaseModel): + api_key: str + model: str + base_url: str | None = None + + +class AiTestConnectionResponse(BaseModel): + success: bool + error: str | None = None diff --git a/embedding_cluster/server/routes/ai.py b/embedding_cluster/server/routes/ai.py new file mode 100644 index 0000000..bd029fa --- /dev/null +++ b/embedding_cluster/server/routes/ai.py @@ -0,0 +1,160 @@ +from __future__ import annotations + +import logging +import random +from typing import Any, cast + +from fastapi import APIRouter, HTTPException + +from embedding_cluster.ai_naming import ( + get_cluster_name, + get_sub_cluster_name, +) +from embedding_cluster.ai_naming import ( + test_connection as ai_test_connection, +) +from embedding_cluster.server.models import ( + AiNamingRequest, + AiNamingResponse, + AiSubClusterNamingRequest, + AiTestConnectionRequest, + AiTestConnectionResponse, +) +from embedding_cluster.server.tasks import TaskStatus, task_registry + +logger = logging.getLogger(__name__) + +router = APIRouter(prefix="/api/ai", tags=["ai"]) + +MAX_SAMPLE_ITEMS = 10 + + +def _get_completed_job(job_id: str) -> dict[str, Any]: + task = task_registry.get(job_id) + if task is None: + raise HTTPException(status_code=404, detail="Job not found") + if task.status != TaskStatus.COMPLETED: + raise HTTPException(status_code=409, detail="Job not completed") + return cast("dict[str, Any]", task.result) + + +def _get_item_names_for_cluster( + result: dict[str, Any], + cluster_index: int, +) -> list[str]: + points = cast("list[dict[str, Any]]", result["points"]) + cluster_labels = cast("list[int]", result["cluster_labels"]) + + cluster_point_indices = [ + i for i, label in enumerate(cluster_labels) if label == cluster_index + ] + + sample_indices = random.sample( + cluster_point_indices, + min(MAX_SAMPLE_ITEMS, len(cluster_point_indices)), + ) + + names: list[str] = [] + for idx in sample_indices: + point = points[idx] + metadata = cast("dict[str, Any]", point.get("metadata", {})) + name_parts = [str(v) for v in metadata.values()] + names.append( + ", ".join(name_parts) if name_parts else f"Item {idx}", + ) + + return names + + +def _get_item_names_for_sub_cluster( + result: dict[str, Any], + point_ids: list[str], + sub_cluster_labels: list[int], + sub_cluster_index: int, +) -> list[str]: + points = cast("list[dict[str, Any]]", result["points"]) + point_id_to_point = {cast("str", p["id"]): p for p in points} + + sub_indices = [ + i for i, label in enumerate(sub_cluster_labels) if label == sub_cluster_index + ] + + sample_indices = random.sample( + sub_indices, + min(MAX_SAMPLE_ITEMS, len(sub_indices)), + ) + + names: list[str] = [] + for idx in sample_indices: + pid = point_ids[idx] + point = point_id_to_point.get(pid) + if point: + metadata = cast("dict[str, Any]", point.get("metadata", {})) + name_parts = [str(v) for v in metadata.values()] + names.append( + ", ".join(name_parts) if name_parts else f"Item {pid}", + ) + else: + names.append(f"Item {pid}") + + return names + + +@router.post("/name-clusters", response_model=AiNamingResponse) +async def name_clusters(request: AiNamingRequest) -> AiNamingResponse: + result = _get_completed_job(request.job_id) + + names: dict[str, str] = {} + for cluster_index in request.cluster_indices: + item_names = _get_item_names_for_cluster(result, cluster_index) + name = get_cluster_name( + item_names=item_names, + api_key=request.api_key, + model=request.model, + base_url=request.base_url, + temperature=request.temperature, + ) + names[str(cluster_index)] = name + + return AiNamingResponse(names=names) + + +@router.post("/name-sub-clusters", response_model=AiNamingResponse) +async def name_sub_clusters( + request: AiSubClusterNamingRequest, +) -> AiNamingResponse: + result = _get_completed_job(request.job_id) + + unique_labels = sorted(set(request.sub_cluster_labels)) + names: dict[str, str] = {} + + for label in unique_labels: + item_names = _get_item_names_for_sub_cluster( + result, + request.point_ids, + request.sub_cluster_labels, + label, + ) + name = get_sub_cluster_name( + item_names=item_names, + api_key=request.api_key, + model=request.model, + base_url=request.base_url, + temperature=request.temperature, + parent_cluster_name=request.parent_cluster_name, + ) + names[str(label)] = name + + return AiNamingResponse(names=names) + + +@router.post("/test-connection", response_model=AiTestConnectionResponse) +async def test_connection( + request: AiTestConnectionRequest, +) -> AiTestConnectionResponse: + success, error = ai_test_connection( + api_key=request.api_key, + model=request.model, + base_url=request.base_url, + ) + return AiTestConnectionResponse(success=success, error=error) diff --git a/tests/test_server_ai.py b/tests/test_server_ai.py new file mode 100644 index 0000000..1c8ca1f --- /dev/null +++ b/tests/test_server_ai.py @@ -0,0 +1,351 @@ +from __future__ import annotations + +from typing import TYPE_CHECKING, cast +from unittest.mock import MagicMock, patch + +import pytest +from fastapi import status +from httpx import ASGITransport, AsyncClient + +if TYPE_CHECKING: + from fastapi import FastAPI + +from embedding_cluster.server.app import create_app +from embedding_cluster.server.tasks import TaskStatus, task_registry + + +@pytest.fixture +def app() -> FastAPI: + return create_app() + + +@pytest.fixture +def completed_job() -> str: + """Create a completed job in the task registry and return its ID.""" + task = task_registry.create() + task.status = TaskStatus.COMPLETED + task.result = { + "points": [ + { + "id": "p1", + "x": 1.0, + "y": 2.0, + "z": 3.0, + "cluster": 0, + "metadata": {"name": "Running Shoes"}, + }, + { + "id": "p2", + "x": 4.0, + "y": 5.0, + "z": 6.0, + "cluster": 0, + "metadata": {"name": "Basketball Sneakers"}, + }, + { + "id": "p3", + "x": 7.0, + "y": 8.0, + "z": 9.0, + "cluster": 1, + "metadata": {"name": "Summer Dress"}, + }, + ], + "cluster_labels": [0, 0, 1], + "clusters": [ + {"index": 0, "name": "Group 1", "color": "#ff0000", "count": 2}, + {"index": 1, "name": "Group 2", "color": "#00ff00", "count": 1}, + ], + "total_points": 3, + } + return task.job_id + + +def _mock_llm_response(content: str = "Athletic Footwear") -> MagicMock: + mock_response = MagicMock() + mock_choice = MagicMock() + mock_choice.message.content = content + mock_response.choices = [mock_choice] + return mock_response + + +class TestNameClusters: + @pytest.mark.asyncio + async def test_names_clusters_successfully( + self, app: FastAPI, completed_job: str + ) -> None: + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=_mock_llm_response("Athletic Footwear"), + ): + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/name-clusters", + json={ + "job_id": completed_job, + "cluster_indices": [0], + "api_key": "test-key", + "model": "gpt-4o-mini", + }, + ) + + assert response.status_code == status.HTTP_200_OK + data = cast("dict[str, object]", response.json()) + names = cast("dict[str, str]", data["names"]) + assert "0" in names + assert names["0"] == "Athletic Footwear" + + @pytest.mark.asyncio + async def test_names_multiple_clusters( + self, app: FastAPI, completed_job: str + ) -> None: + call_count = 0 + + def side_effect(**kwargs: object) -> MagicMock: + nonlocal call_count + call_count += 1 + if call_count == 1: + return _mock_llm_response("Athletic Footwear") + return _mock_llm_response("Fashion Dresses") + + with patch( + "embedding_cluster.ai_naming.litellm_completion", + side_effect=side_effect, + ): + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/name-clusters", + json={ + "job_id": completed_job, + "cluster_indices": [0, 1], + "api_key": "test-key", + "model": "gpt-4o-mini", + }, + ) + + assert response.status_code == status.HTTP_200_OK + data = cast("dict[str, object]", response.json()) + names = cast("dict[str, str]", data["names"]) + assert "0" in names + assert "1" in names + + @pytest.mark.asyncio + async def test_job_not_found(self, app: FastAPI) -> None: + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/name-clusters", + json={ + "job_id": "nonexistent-id", + "cluster_indices": [0], + "api_key": "test-key", + "model": "gpt-4o-mini", + }, + ) + + assert response.status_code == status.HTTP_404_NOT_FOUND + + @pytest.mark.asyncio + async def test_job_not_completed(self, app: FastAPI) -> None: + task = task_registry.create() + task.status = TaskStatus.RUNNING + + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/name-clusters", + json={ + "job_id": task.job_id, + "cluster_indices": [0], + "api_key": "test-key", + "model": "gpt-4o-mini", + }, + ) + + assert response.status_code == status.HTTP_409_CONFLICT + + @pytest.mark.asyncio + async def test_passes_optional_params(self, app: FastAPI, completed_job: str) -> None: + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=_mock_llm_response("Name"), + ) as mock_completion: + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + await client.post( + "/api/ai/name-clusters", + json={ + "job_id": completed_job, + "cluster_indices": [0], + "api_key": "test-key", + "model": "gpt-4o-mini", + "base_url": "http://localhost:11434", + "temperature": 0.8, + }, + ) + + call_kwargs = mock_completion.call_args[1] + assert call_kwargs["api_base"] == "http://localhost:11434" + assert call_kwargs["temperature"] == 0.8 + + +class TestNameSubClusters: + @pytest.mark.asyncio + async def test_names_sub_clusters_successfully( + self, app: FastAPI, completed_job: str + ) -> None: + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=_mock_llm_response("Running Shoes"), + ): + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/name-sub-clusters", + json={ + "job_id": completed_job, + "point_ids": ["p1", "p2"], + "sub_cluster_labels": [0, 1], + "api_key": "test-key", + "model": "gpt-4o-mini", + }, + ) + + assert response.status_code == status.HTTP_200_OK + data = cast("dict[str, object]", response.json()) + names = cast("dict[str, str]", data["names"]) + assert "0" in names + assert "1" in names + + @pytest.mark.asyncio + async def test_with_parent_cluster_name( + self, app: FastAPI, completed_job: str + ) -> None: + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=_mock_llm_response("Running Shoes"), + ) as mock_completion: + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + await client.post( + "/api/ai/name-sub-clusters", + json={ + "job_id": completed_job, + "point_ids": ["p1"], + "sub_cluster_labels": [0], + "api_key": "test-key", + "model": "gpt-4o-mini", + "parent_cluster_name": "Athletic Footwear", + }, + ) + + call_kwargs = mock_completion.call_args[1] + system_msg = call_kwargs["messages"][0]["content"] + assert "Athletic Footwear" in system_msg + + @pytest.mark.asyncio + async def test_job_not_found(self, app: FastAPI) -> None: + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/name-sub-clusters", + json={ + "job_id": "nonexistent-id", + "point_ids": ["p1"], + "sub_cluster_labels": [0], + "api_key": "test-key", + "model": "gpt-4o-mini", + }, + ) + + assert response.status_code == status.HTTP_404_NOT_FOUND + + +class TestTestConnection: + @pytest.mark.asyncio + async def test_successful_connection(self, app: FastAPI) -> None: + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=_mock_llm_response("Hello"), + ): + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/test-connection", + json={ + "api_key": "test-key", + "model": "gpt-4o-mini", + }, + ) + + assert response.status_code == status.HTTP_200_OK + data = cast("dict[str, object]", response.json()) + assert data["success"] is True + assert data["error"] is None + + @pytest.mark.asyncio + async def test_failed_connection(self, app: FastAPI) -> None: + with patch( + "embedding_cluster.ai_naming.litellm_completion", + side_effect=Exception("Connection refused"), + ): + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/test-connection", + json={ + "api_key": "test-key", + "model": "gpt-4o-mini", + }, + ) + + assert response.status_code == status.HTTP_200_OK + data = cast("dict[str, object]", response.json()) + assert data["success"] is False + assert data["error"] is not None + assert "Connection refused" in cast("str", data["error"]) + + @pytest.mark.asyncio + async def test_with_base_url(self, app: FastAPI) -> None: + with patch( + "embedding_cluster.ai_naming.litellm_completion", + return_value=_mock_llm_response("Hello"), + ) as mock_completion: + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + await client.post( + "/api/ai/test-connection", + json={ + "api_key": "test-key", + "model": "gpt-4o-mini", + "base_url": "http://localhost:11434", + }, + ) + + call_kwargs = mock_completion.call_args[1] + assert call_kwargs["api_base"] == "http://localhost:11434" + + @pytest.mark.asyncio + async def test_missing_required_fields(self, app: FastAPI) -> None: + async with AsyncClient( + transport=ASGITransport(app=app), base_url="http://test" + ) as client: + response = await client.post( + "/api/ai/test-connection", + json={}, + ) + + assert response.status_code == status.HTTP_422_UNPROCESSABLE_ENTITY diff --git a/tests/test_settings.py b/tests/test_settings.py index 8d7dfed..6befd5f 100644 --- a/tests/test_settings.py +++ b/tests/test_settings.py @@ -36,12 +36,6 @@ def test_default_none_fields(self) -> None: assert s.image_field is None assert s.id_field is None - def test_default_gpt_settings(self) -> None: - s = Settings() - assert s.gpt_generate_cluster_name is False - assert s.gpt_default_model == "gpt-3.5-turbo" - assert s.gpt_default_temperature == pytest.approx(0.51) - def test_default_model_names(self) -> None: s = Settings() assert s.image_model_name == "openai/clip-vit-base-patch32" @@ -86,11 +80,6 @@ def test_text_display_fields_from_env(self, monkeypatch: pytest.MonkeyPatch) -> s = Settings() assert s.text_display_fields == ["productDisplayName"] - def test_boolean_field_from_env(self, monkeypatch: pytest.MonkeyPatch) -> None: - monkeypatch.setenv("GPT_GENERATE_CLUSTER_NAME", "true") - s = Settings() - assert s.gpt_generate_cluster_name is True - def test_start_end_lines_from_env(self, monkeypatch: pytest.MonkeyPatch) -> None: monkeypatch.setenv("INDEX_START_LINE", "5") monkeypatch.setenv("INDEX_END_LINE", "100") From b4987c03755eb56bd584f5a4ed2b748510b01b1e Mon Sep 17 00:00:00 2001 From: aGallea Date: Mon, 30 Mar 2026 18:08:53 +0300 Subject: [PATCH 4/6] feat(frontend): add Settings page and remove GPT cluster naming UI --- frontend/src/App.tsx | 5 + frontend/src/api/ai.ts | 52 +++++ frontend/src/components/plot/PlotControls.tsx | 52 ----- frontend/src/pages/SettingsPage.tsx | 200 ++++++++++++++++++ frontend/src/types/index.ts | 48 ++++- 5 files changed, 302 insertions(+), 55 deletions(-) create mode 100644 frontend/src/api/ai.ts create mode 100644 frontend/src/pages/SettingsPage.tsx diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx index c97f470..d6c95a4 100644 --- a/frontend/src/App.tsx +++ b/frontend/src/App.tsx @@ -4,6 +4,7 @@ import { useEffect, useRef } from 'react' import HomePage from './pages/HomePage' import IndexPage from './pages/IndexPage' import PlotPage from './pages/PlotPage' +import SettingsPage from './pages/SettingsPage' import { usePlotStore } from './stores/plotStore' const queryClient = new QueryClient() @@ -35,6 +36,9 @@ function NavBar() { Plot + + Settings + @@ -86,6 +90,7 @@ export default function App() { } /> } /> } /> + } /> diff --git a/frontend/src/api/ai.ts b/frontend/src/api/ai.ts new file mode 100644 index 0000000..d0bab61 --- /dev/null +++ b/frontend/src/api/ai.ts @@ -0,0 +1,52 @@ +import type { AiNamingRequest, AiNamingResponse, AiTestConnectionRequest, AiTestConnectionResponse } from "../types"; +import { apiPost } from "./client"; + +const AI_SETTINGS_KEY = "ai-cluster-naming-settings"; + +export interface StoredAiSettings { + provider: string; + model: string; + apiKey: string; + baseUrl: string; + temperature: number; +} + +export const DEFAULT_AI_SETTINGS: StoredAiSettings = { + provider: "openai", + model: "gpt-4o-mini", + apiKey: "", + baseUrl: "", + temperature: 0.5, +}; + +export function loadAiSettings(): StoredAiSettings { + try { + const raw = localStorage.getItem(AI_SETTINGS_KEY); + if (!raw) return { ...DEFAULT_AI_SETTINGS }; + return { ...DEFAULT_AI_SETTINGS, ...JSON.parse(raw) } as StoredAiSettings; + } catch { + return { ...DEFAULT_AI_SETTINGS }; + } +} + +export function saveAiSettings(settings: StoredAiSettings): void { + localStorage.setItem(AI_SETTINGS_KEY, JSON.stringify(settings)); +} + +export async function testAiConnection( + request: AiTestConnectionRequest, +): Promise { + return apiPost("/ai/test-connection", request); +} + +export async function nameAiClusters( + request: AiNamingRequest, +): Promise { + return apiPost("/ai/name-clusters", request); +} + +export async function nameAiSubClusters( + request: AiNamingRequest, +): Promise { + return apiPost("/ai/name-sub-clusters", request); +} diff --git a/frontend/src/components/plot/PlotControls.tsx b/frontend/src/components/plot/PlotControls.tsx index c02d164..92a0e69 100644 --- a/frontend/src/components/plot/PlotControls.tsx +++ b/frontend/src/components/plot/PlotControls.tsx @@ -36,10 +36,6 @@ export default function PlotControls({ onCompute, isComputing }: PlotControlsPro const [numClusters, setNumClusters] = useState(10) const [textDisplayFields, setTextDisplayFields] = useState([]) const [imageField, setImageField] = useState('') - const [gptEnabled, setGptEnabled] = useState(false) - const [gptModel, setGptModel] = useState('gpt-3.5-turbo') - const [gptTemperature, setGptTemperature] = useState(0.51) - const { renderMode, setRenderMode, pointSize, setPointSize, reductionAlgorithm, setReductionAlgorithm, @@ -100,9 +96,6 @@ export default function PlotControls({ onCompute, isComputing }: PlotControlsPro num_clusters: numClusters, text_display_fields: textDisplayFields, image_field: imageField || undefined, - gpt_generate_cluster_name: gptEnabled, - gpt_default_model: gptEnabled ? gptModel : undefined, - gpt_default_temperature: gptEnabled ? gptTemperature : undefined, reduction_algorithm: reductionAlgorithm, ...(reductionAlgorithm === 'tsne' && { tsne_perplexity: tsnePerplexity, @@ -320,51 +313,6 @@ export default function PlotControls({ onCompute, isComputing }: PlotControlsPro - {/* GPT Settings */} - -
-
- setGptEnabled(e.target.checked)} - className="mr-2" - /> - -
- - {gptEnabled && ( -
-
- - setGptModel(e.target.value)} - className="w-full border border-gray-300 rounded px-2 py-1 text-sm" - /> -
-
- - setGptTemperature(Number(e.target.value))} - className="w-full border border-gray-300 rounded px-2 py-1 text-sm" - /> -
-
- )} -
- - {/* Rendering (Render Mode + Point Size) */}
diff --git a/frontend/src/pages/SettingsPage.tsx b/frontend/src/pages/SettingsPage.tsx new file mode 100644 index 0000000..7449fd9 --- /dev/null +++ b/frontend/src/pages/SettingsPage.tsx @@ -0,0 +1,200 @@ +import { useState, useEffect } from 'react'; +import { + loadAiSettings, + saveAiSettings, + testAiConnection, + StoredAiSettings, + DEFAULT_AI_SETTINGS, +} from '../api/ai'; + +export default function SettingsPage() { + const [settings, setSettings] = useState(DEFAULT_AI_SETTINGS); + const [isSaved, setIsSaved] = useState(false); + const [testStatus, setTestStatus] = useState<'idle' | 'testing' | 'success' | 'error'>('idle'); + const [testMessage, setTestMessage] = useState(''); + const [showApiKey, setShowApiKey] = useState(false); + + useEffect(() => { + setSettings(loadAiSettings()); + }, []); + + const handleChange = (field: keyof StoredAiSettings, value: string | number) => { + setSettings((prev) => ({ ...prev, [field]: value })); + setIsSaved(false); + setTestStatus('idle'); + }; + + const handleSave = () => { + saveAiSettings(settings); + setIsSaved(true); + setTimeout(() => setIsSaved(false), 3000); + }; + + const handleTestConnection = async () => { + setTestStatus('testing'); + setTestMessage(''); + try { + const result = await testAiConnection({ + api_key: settings.apiKey, + model: settings.model, + base_url: settings.baseUrl || undefined, + }); + + if (result.success) { + setTestStatus('success'); + setTestMessage('Connection successful!'); + } else { + setTestStatus('error'); + setTestMessage(result.error || 'Connection failed.'); + } + } catch (err: unknown) { + setTestStatus('error'); + const msg = err instanceof Error ? err.message : 'Unknown error occurred.'; + setTestMessage(`Failed to test connection: ${msg}`); + } + }; + + return ( +
+
+

AI Settings

+

+ Configure AI provider for cluster naming +

+
+ +
+
+
+ + handleChange('provider', e.target.value)} + className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border" + placeholder="e.g. openai" + /> +
+ +
+ + handleChange('model', e.target.value)} + className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border" + placeholder="e.g. gpt-4o-mini" + /> +
+ +
+ +
+ handleChange('apiKey', e.target.value)} + className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border pr-10" + placeholder="sk-..." + /> + +
+
+ +
+ + handleChange('baseUrl', e.target.value)} + className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border" + placeholder="e.g. https://api.openai.com/v1" + /> +
+ +
+ + handleChange('temperature', parseFloat(e.target.value))} + className="w-full border-gray-300 rounded-md shadow-sm focus:border-blue-500 focus:ring-blue-500 sm:text-sm p-2 border" + /> +
+ +
+
+ + + {testStatus === 'success' && ( + + + + + {testMessage} + + )} + + {testStatus === 'error' && ( + + {testMessage} + + )} +
+ +
+ {isSaved && ( + + Settings saved! + + )} + +
+
+
+
+
+ ); +} diff --git a/frontend/src/types/index.ts b/frontend/src/types/index.ts index 75eec4c..a05c3fe 100644 --- a/frontend/src/types/index.ts +++ b/frontend/src/types/index.ts @@ -65,9 +65,6 @@ export interface PlotRequest { num_clusters?: number text_display_fields?: string[] image_field?: string - gpt_generate_cluster_name?: boolean - gpt_default_model?: string - gpt_default_temperature?: number reduction_algorithm?: ReductionAlgorithm tsne_perplexity?: number tsne_learning_rate?: string @@ -184,6 +181,7 @@ export interface SubClusterInfo { index: number; count: number; color: string; + name?: string; } export interface SubClusterResponse { @@ -235,3 +233,47 @@ export interface AnnotationsResponse { job_id: string; clusters: Record; } + +// AI Naming +export interface AiSettings { + provider: string; + model: string; + apiKey: string; + baseUrl: string; + temperature: number; +} + +export interface AiNamingRequest { + job_id: string; + cluster_indices: number[]; + api_key: string; + model: string; + base_url?: string; + temperature?: number; +} + +export interface AiNamingResponse { + names: Record; +} + +export interface AiSubClusterNamingRequest { + job_id: string; + point_ids: string[]; + sub_cluster_labels: number[]; + api_key: string; + model: string; + base_url?: string; + temperature?: number; + parent_cluster_name?: string; +} + +export interface AiTestConnectionRequest { + api_key: string; + model: string; + base_url?: string; +} + +export interface AiTestConnectionResponse { + success: boolean; + error: string | null; +} From 8d4a609c1ed787089be85fb901402722c4fe7daf Mon Sep 17 00:00:00 2001 From: aGallea Date: Mon, 30 Mar 2026 18:23:39 +0300 Subject: [PATCH 5/6] feat(frontend): add AI cluster naming integration to legend and drawer --- frontend/src/api/ai.ts | 10 ++- .../components/plot/ClusterDetailDrawer.tsx | 54 ++++++++++++- .../src/components/plot/ClusterLegend.tsx | 81 +++++++++++++++++-- frontend/src/stores/plotStore.ts | 26 ++++++ 4 files changed, 158 insertions(+), 13 deletions(-) diff --git a/frontend/src/api/ai.ts b/frontend/src/api/ai.ts index d0bab61..59f57a9 100644 --- a/frontend/src/api/ai.ts +++ b/frontend/src/api/ai.ts @@ -1,4 +1,10 @@ -import type { AiNamingRequest, AiNamingResponse, AiTestConnectionRequest, AiTestConnectionResponse } from "../types"; +import type { + AiNamingRequest, + AiNamingResponse, + AiSubClusterNamingRequest, + AiTestConnectionRequest, + AiTestConnectionResponse, +} from "../types"; import { apiPost } from "./client"; const AI_SETTINGS_KEY = "ai-cluster-naming-settings"; @@ -46,7 +52,7 @@ export async function nameAiClusters( } export async function nameAiSubClusters( - request: AiNamingRequest, + request: AiSubClusterNamingRequest, ): Promise { return apiPost("/ai/name-sub-clusters", request); } diff --git a/frontend/src/components/plot/ClusterDetailDrawer.tsx b/frontend/src/components/plot/ClusterDetailDrawer.tsx index ab7c956..7db58b3 100644 --- a/frontend/src/components/plot/ClusterDetailDrawer.tsx +++ b/frontend/src/components/plot/ClusterDetailDrawer.tsx @@ -8,7 +8,8 @@ import { subCluster, subClusterByPointIds, } from '../../api/plot' -import type { ClusterDetailResponse, SuggestKResponse } from '../../types' +import { loadAiSettings, nameAiSubClusters } from '../../api/ai' +import type { ClusterDetailResponse, SubClusterResponse, SuggestKResponse } from '../../types' import SelectedPointsDistancePanel from './SelectedPointsDistancePanel' interface ClusterDetailDrawerProps { @@ -35,6 +36,9 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail const drillIntoSubCluster = usePlotStore((s) => s.drillIntoSubCluster) const setIsLoadingDrill = usePlotStore((s) => s.setIsLoadingDrill) const isLoadingDrill = usePlotStore((s) => s.isLoadingDrill) + const isNamingSubClusters = usePlotStore((s) => s.isNamingSubClusters) + const setIsNamingSubClusters = usePlotStore((s) => s.setIsNamingSubClusters) + const updateSubClusterNames = usePlotStore((s) => s.updateSubClusterNames) const [page, setPage] = useState(1) const [isEditingName, setIsEditingName] = useState(false) @@ -100,6 +104,35 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail setExpandedSubClusterIndex(null) }, [currentLevel?.label]) + const autoNameSubClusters = useCallback(async ( + data: SubClusterResponse, + parentName: string | undefined, + ) => { + const settings = loadAiSettings() + if (!settings.apiKey || !jobId) return + + setIsNamingSubClusters(true) + try { + const pointIds = data.points.map((p) => p.id) + const labels = data.points.map((p) => p.sub_cluster) + const response = await nameAiSubClusters({ + job_id: jobId, + point_ids: pointIds, + sub_cluster_labels: labels, + api_key: settings.apiKey, + model: settings.provider ? `${settings.provider}/${settings.model}` : settings.model, + base_url: settings.baseUrl || undefined, + temperature: settings.temperature, + parent_cluster_name: parentName, + }) + updateSubClusterNames(response.names) + } catch { + // AI naming is best-effort; failures are silent + } finally { + setIsNamingSubClusters(false) + } + }, [jobId, setIsNamingSubClusters, updateSubClusterNames]) + const handlePageChange = useCallback((newPage: number) => { if (clusterIndex == null) return setPage(newPage) @@ -224,12 +257,16 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail }) setSelectedSubClusterIndex(null) drillIntoSubCluster(selectedSubCluster, data) + const parentLabel = currentLevel.label + autoNameSubClusters(data, parentLabel) } else { const data = await subCluster(jobId, clusterIndex, { num_sub_clusters: subClusterK, }) setSelectedSubClusterIndex(null) drillIntoCluster(clusterIndex, data) + const parentName = annotation?.name ?? cluster?.name + autoNameSubClusters(data, parentName) } } catch { setIsLoadingDrill(false) @@ -245,6 +282,9 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail setIsLoadingDrill, drillIntoCluster, drillIntoSubCluster, + autoNameSubClusters, + annotation, + cluster, ]) const handleToggleSubClusterExpanded = useCallback((subClusterIndex: number) => { @@ -390,7 +430,15 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail className="px-4 py-2 border-b border-gray-200 flex-1 min-h-0 overflow-y-auto" data-testid="drawer-subcluster-list" > -
Current sub-clusters
+
+ Current sub-clusters + {isNamingSubClusters && ( +
+
+ Naming... +
+ )} +
{subClusters.map((sc) => { const scColor = CLUSTER_COLORS[sc.index % CLUSTER_COLORS.length] @@ -421,7 +469,7 @@ export default function ClusterDetailDrawer({ jobId, imageField }: ClusterDetail style={{ backgroundColor: scColor }} /> - Sub {sc.index} + {sc.name || `Sub ${sc.index}`} {sc.count} pts diff --git a/frontend/src/components/plot/ClusterLegend.tsx b/frontend/src/components/plot/ClusterLegend.tsx index 9f82a50..f836cc5 100644 --- a/frontend/src/components/plot/ClusterLegend.tsx +++ b/frontend/src/components/plot/ClusterLegend.tsx @@ -1,5 +1,7 @@ -import { useCallback } from 'react' +import { useCallback, useState } from 'react' import { usePlotStore, CLUSTER_COLORS } from '../../stores/plotStore' +import { loadAiSettings, nameAiClusters } from '../../api/ai' +import { updateAnnotation, getAnnotations } from '../../api/plot' export default function ClusterLegend() { const plotData = usePlotStore((state) => state.plotData) @@ -14,8 +16,14 @@ export default function ClusterLegend() { const setSelectedCluster = usePlotStore((state) => state.setSelectedCluster) const selectedCluster = usePlotStore((state) => state.selectedCluster) const annotations = usePlotStore((state) => state.annotations) + const setAnnotations = usePlotStore((state) => state.setAnnotations) const drillPath = usePlotStore((state) => state.drillPath) const isLoadingDrill = usePlotStore((state) => state.isLoadingDrill) + const isNamingClusters = usePlotStore((state) => state.isNamingClusters) + const setIsNamingClusters = usePlotStore((state) => state.setIsNamingClusters) + const plotJobId = usePlotStore((state) => state.plotJobId) + + const [namingError, setNamingError] = useState(null) const handleClickCluster = useCallback( (clusterIndex: number, isSelected: boolean) => { @@ -24,6 +32,42 @@ export default function ClusterLegend() { [setSelectedCluster], ) + const handleNameWithAi = useCallback(async () => { + if (!plotData || !plotJobId || isNamingClusters) return + + const settings = loadAiSettings() + if (!settings.apiKey) { + setNamingError('Configure AI settings first (Settings page)') + return + } + + setIsNamingClusters(true) + setNamingError(null) + + try { + const clusterIndices = plotData.clusters.map((c) => c.index) + const response = await nameAiClusters({ + job_id: plotJobId, + cluster_indices: clusterIndices, + api_key: settings.apiKey, + model: settings.provider ? `${settings.provider}/${settings.model}` : settings.model, + base_url: settings.baseUrl || undefined, + temperature: settings.temperature, + }) + + for (const [indexStr, name] of Object.entries(response.names)) { + await updateAnnotation(plotJobId, Number(indexStr), { name }) + } + + const updated = await getAnnotations(plotJobId) + setAnnotations(updated) + } catch (err) { + setNamingError(err instanceof Error ? err.message : 'AI naming failed') + } finally { + setIsNamingClusters(false) + } + }, [plotData, plotJobId, isNamingClusters, setIsNamingClusters, setAnnotations]) + if (!plotData) return null const handleShowAll = () => resetVisibleClusters(plotData.clusters.length) @@ -56,12 +100,33 @@ export default function ClusterLegend() { Show All ) : ( - + <> + + + {namingError && ( + {namingError} + )} + )} {isLoadingDrill && (
@@ -118,7 +183,7 @@ export default function ClusterLegend() { />
- Sub {sc.index} + {sc.name || `Sub ${sc.index}`}
{sc.count} points diff --git a/frontend/src/stores/plotStore.ts b/frontend/src/stores/plotStore.ts index c0f144e..2b19d74 100644 --- a/frontend/src/stores/plotStore.ts +++ b/frontend/src/stores/plotStore.ts @@ -27,6 +27,8 @@ interface PlotState { drillPath: DrillLevel[] subClusterColorMap: Map | null isLoadingDrill: boolean + isNamingClusters: boolean + isNamingSubClusters: boolean imageField: string | null plotJobId: string | null plotCollectionName: string | null @@ -61,6 +63,9 @@ interface PlotState { navigateBack: () => void resetDrill: () => void setIsLoadingDrill: (loading: boolean) => void + setIsNamingClusters: (loading: boolean) => void + setIsNamingSubClusters: (loading: boolean) => void + updateSubClusterNames: (names: Record) => void isolateCluster: (index: number) => void toggleSubCluster: (index: number) => void isolateSubCluster: (index: number) => void @@ -121,6 +126,8 @@ export const usePlotStore = create((set) => ({ drillPath: [], subClusterColorMap: null, isLoadingDrill: false, + isNamingClusters: false, + isNamingSubClusters: false, imageField: null, plotJobId: null, plotCollectionName: null, @@ -247,6 +254,25 @@ export const usePlotStore = create((set) => ({ setIsLoadingDrill: (loading) => set({ isLoadingDrill: loading }), + setIsNamingClusters: (loading) => set({ isNamingClusters: loading }), + setIsNamingSubClusters: (loading) => set({ isNamingSubClusters: loading }), + + updateSubClusterNames: (names) => + set((state) => { + if (state.drillPath.length === 0) return {} + const newPath = [...state.drillPath] + const currentLevel = { ...newPath[newPath.length - 1] } + currentLevel.subClusterData = { + ...currentLevel.subClusterData, + sub_clusters: currentLevel.subClusterData.sub_clusters.map((sc) => ({ + ...sc, + name: names[String(sc.index)] ?? sc.name, + })), + } + newPath[newPath.length - 1] = currentLevel + return { drillPath: newPath } + }), + isolateCluster: (index) => set(() => ({ visibleClusters: new Set([index]) })), From 97543c7c644381517ec7c2c55f1a85a398941672 Mon Sep 17 00:00:00 2001 From: aGallea Date: Tue, 31 Mar 2026 10:52:55 +0300 Subject: [PATCH 6/6] fix(frontend): use type-only import for StoredAiSettings interface --- frontend/src/pages/SettingsPage.tsx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/frontend/src/pages/SettingsPage.tsx b/frontend/src/pages/SettingsPage.tsx index 7449fd9..1de00cf 100644 --- a/frontend/src/pages/SettingsPage.tsx +++ b/frontend/src/pages/SettingsPage.tsx @@ -1,9 +1,9 @@ import { useState, useEffect } from 'react'; +import type { StoredAiSettings } from '../api/ai'; import { loadAiSettings, saveAiSettings, testAiConnection, - StoredAiSettings, DEFAULT_AI_SETTINGS, } from '../api/ai';