diff --git a/.github/workflows/e2e_tests.yml b/.github/workflows/e2e_tests.yml index cb69e9ef6..8cd62910c 100644 --- a/.github/workflows/e2e_tests.yml +++ b/.github/workflows/e2e_tests.yml @@ -237,6 +237,31 @@ jobs: EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }} run: uv run python ./cognee/tests/test_dataset_database_handler.py + test-dataset-database-deletion: + name: Test dataset database deletion in Cognee + runs-on: ubuntu-22.04 + steps: + - name: Check out repository + uses: actions/checkout@v4 + + - name: Cognee Setup + uses: ./.github/actions/cognee_setup + with: + python-version: '3.11.x' + + - name: Run dataset databases deletion test + env: + ENV: 'dev' + LLM_MODEL: ${{ secrets.LLM_MODEL }} + LLM_ENDPOINT: ${{ secrets.LLM_ENDPOINT }} + LLM_API_KEY: ${{ secrets.LLM_API_KEY }} + LLM_API_VERSION: ${{ secrets.LLM_API_VERSION }} + EMBEDDING_MODEL: ${{ secrets.EMBEDDING_MODEL }} + EMBEDDING_ENDPOINT: ${{ secrets.EMBEDDING_ENDPOINT }} + EMBEDDING_API_KEY: ${{ secrets.EMBEDDING_API_KEY }} + EMBEDDING_API_VERSION: ${{ secrets.EMBEDDING_API_VERSION }} + run: uv run python ./cognee/tests/test_dataset_delete.py + test-permissions: name: Test permissions with different situations in Cognee runs-on: ubuntu-22.04 diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml new file mode 100644 index 000000000..ff2f809f3 --- /dev/null +++ b/.github/workflows/release.yml @@ -0,0 +1,154 @@ +name: release.yml +on: + workflow_dispatch: + inputs: + flavour: + required: true + default: dev + type: choice + options: + - dev + - main + description: Dev or Main release + test_mode: + required: true + type: boolean + description: Aka Dry Run. If true, it won't affect public indices or repositories + +jobs: + release-github: + name: Create GitHub Release from ${{ inputs.flavour }} + outputs: + tag: ${{ steps.create_tag.outputs.tag }} + version: ${{ steps.create_tag.outputs.version }} + permissions: + contents: write + runs-on: ubuntu-latest + + steps: + - name: Check out ${{ inputs.flavour }} + uses: actions/checkout@v4 + with: + ref: ${{ inputs.flavour }} + - name: Install uv + uses: astral-sh/setup-uv@v7 + + - name: Create and push git tag + id: create_tag + env: + TEST_MODE: ${{ inputs.test_mode }} + run: | + VERSION="$(uv version --short)" + TAG="v${VERSION}" + + echo "Tag to create: ${TAG}" + + git config user.name "github-actions[bot]" + git config user.email "41898282+github-actions[bot]@users.noreply.github.com" + + echo "tag=${TAG}" >> "$GITHUB_OUTPUT" + echo "version=${VERSION}" >> "$GITHUB_OUTPUT" + + if [ "$TEST_MODE" = "false" ]; then + git tag "${TAG}" + git push origin "${TAG}" + else + echo "Test mode is enabled. Skipping tag creation and push." + fi + + - name: Create GitHub Release + uses: softprops/action-gh-release@v2 + with: + tag_name: ${{ steps.create_tag.outputs.tag }} + generate_release_notes: true + env: + GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} + + release-pypi-package: + needs: release-github + name: Release PyPI Package from ${{ inputs.flavour }} + permissions: + contents: read + runs-on: ubuntu-latest + + steps: + - name: Check out ${{ inputs.flavour }} + uses: actions/checkout@v4 + with: + ref: ${{ inputs.flavour }} + + - name: Install uv + uses: astral-sh/setup-uv@v7 + + - name: Install Python + run: uv python install + + - name: Install dependencies + run: uv sync --locked --all-extras + + - name: Build distributions + run: uv build + + - name: Publish ${{ inputs.flavour }} release to TestPyPI + if: ${{ inputs.test_mode }} + env: + UV_PUBLISH_TOKEN: ${{ secrets.TEST_PYPI_TOKEN }} + run: uv publish --publish-url https://test.pypi.org/legacy/ + + - name: Publish ${{ inputs.flavour }} release to PyPI + if: ${{ !inputs.test_mode }} + env: + UV_PUBLISH_TOKEN: ${{ secrets.PYPI_TOKEN }} + run: uv publish + + release-docker-image: + needs: release-github + name: Release Docker Image from ${{ inputs.flavour }} + permissions: + contents: read + runs-on: ubuntu-latest + + steps: + - name: Check out ${{ inputs.flavour }} + uses: actions/checkout@v4 + with: + ref: ${{ inputs.flavour }} + + - name: Set up Docker Buildx + uses: docker/setup-buildx-action@v3 + + - name: Log in to Docker Hub + uses: docker/login-action@v3 + with: + username: ${{ secrets.DOCKER_USERNAME }} + password: ${{ secrets.DOCKER_PASSWORD }} + + - name: Build and push Dev Docker Image + if: ${{ inputs.flavour == 'dev' }} + uses: docker/build-push-action@v5 + with: + context: . + platforms: linux/amd64,linux/arm64 + push: ${{ !inputs.test_mode }} + tags: cognee/cognee:${{ needs.release-github.outputs.version }} + labels: | + version=${{ needs.release-github.outputs.version }} + flavour=${{ inputs.flavour }} + cache-from: type=registry,ref=cognee/cognee:buildcache + cache-to: type=registry,ref=cognee/cognee:buildcache,mode=max + + - name: Build and push Main Docker Image + if: ${{ inputs.flavour == 'main' }} + uses: docker/build-push-action@v5 + with: + context: . + platforms: linux/amd64,linux/arm64 + push: ${{ !inputs.test_mode }} + tags: | + cognee/cognee:${{ needs.release-github.outputs.version }} + cognee/cognee:latest + labels: | + version=${{ needs.release-github.outputs.version }} + flavour=${{ inputs.flavour }} + cache-from: type=registry,ref=cognee/cognee:buildcache + cache-to: type=registry,ref=cognee/cognee:buildcache,mode=max diff --git a/.github/workflows/search_db_tests.yml b/.github/workflows/search_db_tests.yml index 118c1c06c..f0c7817cd 100644 --- a/.github/workflows/search_db_tests.yml +++ b/.github/workflows/search_db_tests.yml @@ -11,12 +11,21 @@ on: type: string default: "all" description: "Which vector databases to test (comma-separated list or 'all')" + python-versions: + required: false + type: string + default: '["3.10", "3.11", "3.12", "3.13"]' + description: "Python versions to test (JSON array)" jobs: run-kuzu-lance-sqlite-search-tests: - name: Search test for Kuzu/LanceDB/Sqlite + name: Search test for Kuzu/LanceDB/Sqlite (Python ${{ matrix.python-version }}) runs-on: ubuntu-22.04 if: ${{ inputs.databases == 'all' || contains(inputs.databases, 'kuzu/lance/sqlite') }} + strategy: + matrix: + python-version: ${{ fromJSON(inputs.python-versions) }} + fail-fast: false steps: - name: Check out uses: actions/checkout@v4 @@ -26,7 +35,7 @@ jobs: - name: Cognee Setup uses: ./.github/actions/cognee_setup with: - python-version: ${{ inputs.python-version }} + python-version: ${{ matrix.python-version }} - name: Dependencies already installed run: echo "Dependencies already installed in setup" @@ -45,13 +54,16 @@ jobs: GRAPH_DATABASE_PROVIDER: 'kuzu' VECTOR_DB_PROVIDER: 'lancedb' DB_PROVIDER: 'sqlite' - run: uv run python ./cognee/tests/test_search_db.py + run: uv run pytest cognee/tests/test_search_db.py -v --log-level=INFO run-neo4j-lance-sqlite-search-tests: - name: Search test for Neo4j/LanceDB/Sqlite + name: Search test for Neo4j/LanceDB/Sqlite (Python ${{ matrix.python-version }}) runs-on: ubuntu-22.04 if: ${{ inputs.databases == 'all' || contains(inputs.databases, 'neo4j/lance/sqlite') }} - + strategy: + matrix: + python-version: ${{ fromJSON(inputs.python-versions) }} + fail-fast: false steps: - name: Check out uses: actions/checkout@v4 @@ -61,7 +73,7 @@ jobs: - name: Cognee Setup uses: ./.github/actions/cognee_setup with: - python-version: ${{ inputs.python-version }} + python-version: ${{ matrix.python-version }} - name: Setup Neo4j with GDS uses: ./.github/actions/setup_neo4j @@ -88,12 +100,16 @@ jobs: GRAPH_DATABASE_URL: ${{ steps.neo4j.outputs.neo4j-url }} GRAPH_DATABASE_USERNAME: ${{ steps.neo4j.outputs.neo4j-username }} GRAPH_DATABASE_PASSWORD: ${{ steps.neo4j.outputs.neo4j-password }} - run: uv run python ./cognee/tests/test_search_db.py + run: uv run pytest cognee/tests/test_search_db.py -v --log-level=INFO run-kuzu-pgvector-postgres-search-tests: - name: Search test for Kuzu/PGVector/Postgres + name: Search test for Kuzu/PGVector/Postgres (Python ${{ matrix.python-version }}) runs-on: ubuntu-22.04 if: ${{ inputs.databases == 'all' || contains(inputs.databases, 'kuzu/pgvector/postgres') }} + strategy: + matrix: + python-version: ${{ fromJSON(inputs.python-versions) }} + fail-fast: false services: postgres: image: pgvector/pgvector:pg17 @@ -117,7 +133,7 @@ jobs: - name: Cognee Setup uses: ./.github/actions/cognee_setup with: - python-version: ${{ inputs.python-version }} + python-version: ${{ matrix.python-version }} extra-dependencies: "postgres" - name: Dependencies already installed @@ -143,12 +159,16 @@ jobs: DB_PORT: 5432 DB_USERNAME: cognee DB_PASSWORD: cognee - run: uv run python ./cognee/tests/test_search_db.py + run: uv run pytest cognee/tests/test_search_db.py -v --log-level=INFO run-neo4j-pgvector-postgres-search-tests: - name: Search test for Neo4j/PGVector/Postgres + name: Search test for Neo4j/PGVector/Postgres (Python ${{ matrix.python-version }}) runs-on: ubuntu-22.04 if: ${{ inputs.databases == 'all' || contains(inputs.databases, 'neo4j/pgvector/postgres') }} + strategy: + matrix: + python-version: ${{ fromJSON(inputs.python-versions) }} + fail-fast: false services: postgres: image: pgvector/pgvector:pg17 @@ -172,7 +192,7 @@ jobs: - name: Cognee Setup uses: ./.github/actions/cognee_setup with: - python-version: ${{ inputs.python-version }} + python-version: ${{ matrix.python-version }} extra-dependencies: "postgres" - name: Setup Neo4j with GDS @@ -205,4 +225,4 @@ jobs: DB_PORT: 5432 DB_USERNAME: cognee DB_PASSWORD: cognee - run: uv run python ./cognee/tests/test_search_db.py + run: uv run pytest cognee/tests/test_search_db.py -v --log-level=INFO diff --git a/.github/workflows/test_llms.yml b/.github/workflows/test_llms.yml index 6b0221309..8f9d30d10 100644 --- a/.github/workflows/test_llms.yml +++ b/.github/workflows/test_llms.yml @@ -84,3 +84,93 @@ jobs: EMBEDDING_DIMENSIONS: "3072" EMBEDDING_MAX_TOKENS: "8191" run: uv run python ./examples/python/simple_example.py + + test-bedrock-api-key: + name: Run Bedrock API Key Test + runs-on: ubuntu-22.04 + steps: + - name: Check out repository + uses: actions/checkout@v4 + + - name: Cognee Setup + uses: ./.github/actions/cognee_setup + with: + python-version: '3.11.x' + extra-dependencies: "aws" + + - name: Run Bedrock API Key Simple Example + env: + LLM_PROVIDER: "bedrock" + LLM_API_KEY: ${{ secrets.BEDROCK_API_KEY }} + LLM_MODEL: "eu.anthropic.claude-sonnet-4-5-20250929-v1:0" + LLM_MAX_TOKENS: "16384" + AWS_REGION_NAME: "eu-west-1" + EMBEDDING_PROVIDER: "bedrock" + EMBEDDING_API_KEY: ${{ secrets.BEDROCK_API_KEY }} + EMBEDDING_MODEL: "amazon.titan-embed-text-v2:0" + EMBEDDING_DIMENSIONS: "1024" + EMBEDDING_MAX_TOKENS: "8191" + run: uv run python ./examples/python/simple_example.py + + test-bedrock-aws-credentials: + name: Run Bedrock AWS Credentials Test + runs-on: ubuntu-22.04 + steps: + - name: Check out repository + uses: actions/checkout@v4 + + - name: Cognee Setup + uses: ./.github/actions/cognee_setup + with: + python-version: '3.11.x' + extra-dependencies: "aws" + + - name: Run Bedrock AWS Credentials Simple Example + env: + LLM_PROVIDER: "bedrock" + LLM_MODEL: "eu.anthropic.claude-sonnet-4-5-20250929-v1:0" + LLM_MAX_TOKENS: "16384" + AWS_REGION_NAME: "eu-west-1" + AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} + AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }} + EMBEDDING_PROVIDER: "bedrock" + EMBEDDING_API_KEY: ${{ secrets.BEDROCK_API_KEY }} + EMBEDDING_MODEL: "amazon.titan-embed-text-v2:0" + EMBEDDING_DIMENSIONS: "1024" + EMBEDDING_MAX_TOKENS: "8191" + run: uv run python ./examples/python/simple_example.py + + test-bedrock-aws-profile: + name: Run Bedrock AWS Profile Test + runs-on: ubuntu-22.04 + steps: + - name: Check out repository + uses: actions/checkout@v4 + + - name: Cognee Setup + uses: ./.github/actions/cognee_setup + with: + python-version: '3.11.x' + extra-dependencies: "aws" + + - name: Configure AWS Profile + run: | + mkdir -p ~/.aws + cat > ~/.aws/credentials << EOF + [bedrock-test] + aws_access_key_id = ${{ secrets.AWS_ACCESS_KEY_ID }} + aws_secret_access_key = ${{ secrets.AWS_SECRET_ACCESS_KEY }} + EOF + + - name: Run Bedrock AWS Profile Simple Example + env: + LLM_PROVIDER: "bedrock" + LLM_MODEL: "eu.anthropic.claude-sonnet-4-5-20250929-v1:0" + LLM_MAX_TOKENS: "16384" + AWS_PROFILE_NAME: "bedrock-test" + AWS_REGION_NAME: "eu-west-1" + EMBEDDING_PROVIDER: "bedrock" + EMBEDDING_MODEL: "amazon.titan-embed-text-v2:0" + EMBEDDING_DIMENSIONS: "1024" + EMBEDDING_MAX_TOKENS: "8191" + run: uv run python ./examples/python/simple_example.py \ No newline at end of file diff --git a/cognee-mcp/src/test_client.py b/cognee-mcp/src/test_client.py index 23160d8b2..bce7f807f 100755 --- a/cognee-mcp/src/test_client.py +++ b/cognee-mcp/src/test_client.py @@ -3,7 +3,7 @@ Test client for Cognee MCP Server functionality. This script tests all the tools and functions available in the Cognee MCP server, -including cognify, codify, search, prune, status checks, and utility functions. +including cognify, search, prune, status checks, and utility functions. Usage: # Set your OpenAI API key first @@ -23,6 +23,7 @@ import tempfile import time from contextlib import asynccontextmanager from cognee.shared.logging_utils import setup_logging +from logging import ERROR, INFO from mcp import ClientSession, StdioServerParameters from mcp.client.stdio import stdio_client @@ -35,7 +36,7 @@ from src.server import ( load_class, ) -# Set timeout for cognify/codify to complete in +# Set timeout for cognify to complete in TIMEOUT = 5 * 60 # 5 min in seconds @@ -151,12 +152,9 @@ DEBUG = True expected_tools = { "cognify", - "codify", "search", "prune", "cognify_status", - "codify_status", - "cognee_add_developer_rules", "list_data", "delete", } @@ -247,106 +245,6 @@ DEBUG = True } print(f"โŒ {test_name} test failed: {e}") - async def test_codify(self): - """Test the codify functionality using MCP client.""" - print("\n๐Ÿงช Testing codify functionality...") - try: - async with self.mcp_server_session() as session: - codify_result = await session.call_tool( - "codify", arguments={"repo_path": self.test_repo_dir} - ) - - start = time.time() # mark the start - while True: - try: - # Wait a moment - await asyncio.sleep(5) - - # Check if codify processing is finished - status_result = await session.call_tool("codify_status", arguments={}) - if hasattr(status_result, "content") and status_result.content: - status_text = ( - status_result.content[0].text - if status_result.content - else str(status_result) - ) - else: - status_text = str(status_result) - - if str(PipelineRunStatus.DATASET_PROCESSING_COMPLETED) in status_text: - break - elif time.time() - start > TIMEOUT: - raise TimeoutError("Codify did not complete in 5min") - except DatabaseNotCreatedError: - if time.time() - start > TIMEOUT: - raise TimeoutError("Database was not created in 5min") - - self.test_results["codify"] = { - "status": "PASS", - "result": codify_result, - "message": "Codify executed successfully", - } - print("โœ… Codify test passed") - - except Exception as e: - self.test_results["codify"] = { - "status": "FAIL", - "error": str(e), - "message": "Codify test failed", - } - print(f"โŒ Codify test failed: {e}") - - async def test_cognee_add_developer_rules(self): - """Test the cognee_add_developer_rules functionality using MCP client.""" - print("\n๐Ÿงช Testing cognee_add_developer_rules functionality...") - try: - async with self.mcp_server_session() as session: - result = await session.call_tool( - "cognee_add_developer_rules", arguments={"base_path": self.test_data_dir} - ) - - start = time.time() # mark the start - while True: - try: - # Wait a moment - await asyncio.sleep(5) - - # Check if developer rule cognify processing is finished - status_result = await session.call_tool("cognify_status", arguments={}) - if hasattr(status_result, "content") and status_result.content: - status_text = ( - status_result.content[0].text - if status_result.content - else str(status_result) - ) - else: - status_text = str(status_result) - - if str(PipelineRunStatus.DATASET_PROCESSING_COMPLETED) in status_text: - break - elif time.time() - start > TIMEOUT: - raise TimeoutError( - "Cognify of developer rules did not complete in 5min" - ) - except DatabaseNotCreatedError: - if time.time() - start > TIMEOUT: - raise TimeoutError("Database was not created in 5min") - - self.test_results["cognee_add_developer_rules"] = { - "status": "PASS", - "result": result, - "message": "Developer rules addition executed successfully", - } - print("โœ… Developer rules test passed") - - except Exception as e: - self.test_results["cognee_add_developer_rules"] = { - "status": "FAIL", - "error": str(e), - "message": "Developer rules test failed", - } - print(f"โŒ Developer rules test failed: {e}") - async def test_search_functionality(self): """Test the search functionality with different search types using MCP client.""" print("\n๐Ÿงช Testing search functionality...") @@ -359,7 +257,11 @@ DEBUG = True # Go through all Cognee search types for search_type in SearchType: # Don't test these search types - if search_type in [SearchType.NATURAL_LANGUAGE, SearchType.CYPHER]: + if search_type in [ + SearchType.NATURAL_LANGUAGE, + SearchType.CYPHER, + SearchType.TRIPLET_COMPLETION, + ]: break try: async with self.mcp_server_session() as session: @@ -681,9 +583,6 @@ class TestModel: test_name="Cognify2", ) - await self.test_codify() - await self.test_cognee_add_developer_rules() - # Test list_data and delete functionality await self.test_list_data() await self.test_delete() @@ -739,7 +638,5 @@ async def main(): if __name__ == "__main__": - from logging import ERROR - logger = setup_logging(log_level=ERROR) asyncio.run(main()) diff --git a/cognee/api/v1/add/add.py b/cognee/api/v1/add/add.py index 1ea4caca4..90ea32ae7 100644 --- a/cognee/api/v1/add/add.py +++ b/cognee/api/v1/add/add.py @@ -155,7 +155,7 @@ async def add( - LLM_API_KEY: API key for your LLM provider (OpenAI, Anthropic, etc.) Optional: - - LLM_PROVIDER: "openai" (default), "anthropic", "gemini", "ollama", "mistral" + - LLM_PROVIDER: "openai" (default), "anthropic", "gemini", "ollama", "mistral", "bedrock" - LLM_MODEL: Model name (default: "gpt-5-mini") - DEFAULT_USER_EMAIL: Custom default user email - DEFAULT_USER_PASSWORD: Custom default user password diff --git a/cognee/api/v1/cognify/cognify.py b/cognee/api/v1/cognify/cognify.py index 9862edd49..ffc903d68 100644 --- a/cognee/api/v1/cognify/cognify.py +++ b/cognee/api/v1/cognify/cognify.py @@ -53,6 +53,7 @@ async def cognify( custom_prompt: Optional[str] = None, temporal_cognify: bool = False, data_per_batch: int = 20, + **kwargs, ): """ Transform ingested data into a structured knowledge graph. @@ -223,6 +224,7 @@ async def cognify( config=config, custom_prompt=custom_prompt, chunks_per_batch=chunks_per_batch, + **kwargs, ) # By calling get pipeline executor we get a function that will have the run_pipeline run in the background or a function that we will need to wait for @@ -251,6 +253,7 @@ async def get_default_tasks( # TODO: Find out a better way to do this (Boris's config: Config = None, custom_prompt: Optional[str] = None, chunks_per_batch: int = 100, + **kwargs, ) -> list[Task]: if config is None: ontology_config = get_ontology_env_config() @@ -288,6 +291,7 @@ async def get_default_tasks( # TODO: Find out a better way to do this (Boris's config=config, custom_prompt=custom_prompt, task_config={"batch_size": chunks_per_batch}, + **kwargs, ), # Generate knowledge graphs from the document chunks. Task( summarize_text, diff --git a/cognee/api/v1/cognify/routers/get_cognify_router.py b/cognee/api/v1/cognify/routers/get_cognify_router.py index 4f1497e3c..a499b3ca3 100644 --- a/cognee/api/v1/cognify/routers/get_cognify_router.py +++ b/cognee/api/v1/cognify/routers/get_cognify_router.py @@ -42,7 +42,9 @@ class CognifyPayloadDTO(InDTO): default="", description="Custom prompt for entity extraction and graph generation" ) ontology_key: Optional[List[str]] = Field( - default=None, description="Reference to one or more previously uploaded ontologies" + default=None, + examples=[[]], + description="Reference to one or more previously uploaded ontologies", ) diff --git a/cognee/api/v1/datasets/routers/get_datasets_router.py b/cognee/api/v1/datasets/routers/get_datasets_router.py index eff87b3af..ca738dfbe 100644 --- a/cognee/api/v1/datasets/routers/get_datasets_router.py +++ b/cognee/api/v1/datasets/routers/get_datasets_router.py @@ -208,14 +208,14 @@ def get_datasets_router() -> APIRouter: }, ) - from cognee.modules.data.methods import get_dataset, delete_dataset + from cognee.modules.data.methods import delete_dataset - dataset = await get_dataset(user.id, dataset_id) + dataset = await get_authorized_existing_datasets([dataset_id], "delete", user) if dataset is None: raise DatasetNotFoundError(message=f"Dataset ({str(dataset_id)}) not found.") - await delete_dataset(dataset) + await delete_dataset(dataset[0]) @router.delete( "/{dataset_id}/data/{data_id}", diff --git a/cognee/api/v1/ontologies/routers/get_ontology_router.py b/cognee/api/v1/ontologies/routers/get_ontology_router.py index ee31c683f..77667d88d 100644 --- a/cognee/api/v1/ontologies/routers/get_ontology_router.py +++ b/cognee/api/v1/ontologies/routers/get_ontology_router.py @@ -1,4 +1,4 @@ -from fastapi import APIRouter, File, Form, UploadFile, Depends, HTTPException +from fastapi import APIRouter, File, Form, UploadFile, Depends, Request from fastapi.responses import JSONResponse from typing import Optional, List @@ -15,28 +15,25 @@ def get_ontology_router() -> APIRouter: @router.post("", response_model=dict) async def upload_ontology( + request: Request, ontology_key: str = Form(...), - ontology_file: List[UploadFile] = File(...), - descriptions: Optional[str] = Form(None), + ontology_file: UploadFile = File(...), + description: Optional[str] = Form(None), user: User = Depends(get_authenticated_user), ): """ - Upload ontology files with their respective keys for later use in cognify operations. - - Supports both single and multiple file uploads: - - Single file: ontology_key=["key"], ontology_file=[file] - - Multiple files: ontology_key=["key1", "key2"], ontology_file=[file1, file2] + Upload a single ontology file for later use in cognify operations. ## Request Parameters - - **ontology_key** (str): JSON array string of user-defined identifiers for the ontologies - - **ontology_file** (List[UploadFile]): OWL format ontology files - - **descriptions** (Optional[str]): JSON array string of optional descriptions + - **ontology_key** (str): User-defined identifier for the ontology. + - **ontology_file** (UploadFile): Single OWL format ontology file + - **description** (Optional[str]): Optional description for the ontology. ## Response - Returns metadata about uploaded ontologies including keys, filenames, sizes, and upload timestamps. + Returns metadata about the uploaded ontology including key, filename, size, and upload timestamp. ## Error Codes - - **400 Bad Request**: Invalid file format, duplicate keys, array length mismatches, file size exceeded + - **400 Bad Request**: Invalid file format, duplicate key, multiple files uploaded - **500 Internal Server Error**: File system or processing errors """ send_telemetry( @@ -49,16 +46,22 @@ def get_ontology_router() -> APIRouter: ) try: - import json + # Enforce: exactly one uploaded file for "ontology_file" + form = await request.form() + uploaded_files = form.getlist("ontology_file") + if len(uploaded_files) != 1: + raise ValueError("Only one ontology_file is allowed") - ontology_keys = json.loads(ontology_key) - description_list = json.loads(descriptions) if descriptions else None + if ontology_key.strip().startswith(("[", "{")): + raise ValueError("ontology_key must be a string") + if description is not None and description.strip().startswith(("[", "{")): + raise ValueError("description must be a string") - if not isinstance(ontology_keys, list): - raise ValueError("ontology_key must be a JSON array") - - results = await ontology_service.upload_ontologies( - ontology_keys, ontology_file, user, description_list + result = await ontology_service.upload_ontology( + ontology_key=ontology_key, + file=ontology_file, + user=user, + description=description, ) return { @@ -70,10 +73,9 @@ def get_ontology_router() -> APIRouter: "uploaded_at": result.uploaded_at, "description": result.description, } - for result in results ] } - except (json.JSONDecodeError, ValueError) as e: + except ValueError as e: return JSONResponse(status_code=400, content={"error": str(e)}) except Exception as e: return JSONResponse(status_code=500, content={"error": str(e)}) diff --git a/cognee/infrastructure/databases/utils/__init__.py b/cognee/infrastructure/databases/utils/__init__.py index f31d1e0dc..3907b4325 100644 --- a/cognee/infrastructure/databases/utils/__init__.py +++ b/cognee/infrastructure/databases/utils/__init__.py @@ -1,2 +1,4 @@ from .get_or_create_dataset_database import get_or_create_dataset_database from .resolve_dataset_database_connection_info import resolve_dataset_database_connection_info +from .get_graph_dataset_database_handler import get_graph_dataset_database_handler +from .get_vector_dataset_database_handler import get_vector_dataset_database_handler diff --git a/cognee/infrastructure/databases/utils/get_graph_dataset_database_handler.py b/cognee/infrastructure/databases/utils/get_graph_dataset_database_handler.py new file mode 100644 index 000000000..d88685b48 --- /dev/null +++ b/cognee/infrastructure/databases/utils/get_graph_dataset_database_handler.py @@ -0,0 +1,10 @@ +from cognee.modules.users.models.DatasetDatabase import DatasetDatabase + + +def get_graph_dataset_database_handler(dataset_database: DatasetDatabase) -> dict: + from cognee.infrastructure.databases.dataset_database_handler.supported_dataset_database_handlers import ( + supported_dataset_database_handlers, + ) + + handler = supported_dataset_database_handlers[dataset_database.graph_dataset_database_handler] + return handler diff --git a/cognee/infrastructure/databases/utils/get_vector_dataset_database_handler.py b/cognee/infrastructure/databases/utils/get_vector_dataset_database_handler.py new file mode 100644 index 000000000..5d1152c04 --- /dev/null +++ b/cognee/infrastructure/databases/utils/get_vector_dataset_database_handler.py @@ -0,0 +1,10 @@ +from cognee.modules.users.models.DatasetDatabase import DatasetDatabase + + +def get_vector_dataset_database_handler(dataset_database: DatasetDatabase) -> dict: + from cognee.infrastructure.databases.dataset_database_handler.supported_dataset_database_handlers import ( + supported_dataset_database_handlers, + ) + + handler = supported_dataset_database_handlers[dataset_database.vector_dataset_database_handler] + return handler diff --git a/cognee/infrastructure/databases/utils/resolve_dataset_database_connection_info.py b/cognee/infrastructure/databases/utils/resolve_dataset_database_connection_info.py index d33169642..561268eaf 100644 --- a/cognee/infrastructure/databases/utils/resolve_dataset_database_connection_info.py +++ b/cognee/infrastructure/databases/utils/resolve_dataset_database_connection_info.py @@ -1,24 +1,12 @@ +from cognee.infrastructure.databases.utils.get_graph_dataset_database_handler import ( + get_graph_dataset_database_handler, +) +from cognee.infrastructure.databases.utils.get_vector_dataset_database_handler import ( + get_vector_dataset_database_handler, +) from cognee.modules.users.models.DatasetDatabase import DatasetDatabase -async def _get_vector_db_connection_info(dataset_database: DatasetDatabase) -> DatasetDatabase: - from cognee.infrastructure.databases.dataset_database_handler.supported_dataset_database_handlers import ( - supported_dataset_database_handlers, - ) - - handler = supported_dataset_database_handlers[dataset_database.vector_dataset_database_handler] - return await handler["handler_instance"].resolve_dataset_connection_info(dataset_database) - - -async def _get_graph_db_connection_info(dataset_database: DatasetDatabase) -> DatasetDatabase: - from cognee.infrastructure.databases.dataset_database_handler.supported_dataset_database_handlers import ( - supported_dataset_database_handlers, - ) - - handler = supported_dataset_database_handlers[dataset_database.graph_dataset_database_handler] - return await handler["handler_instance"].resolve_dataset_connection_info(dataset_database) - - async def resolve_dataset_database_connection_info( dataset_database: DatasetDatabase, ) -> DatasetDatabase: @@ -31,6 +19,12 @@ async def resolve_dataset_database_connection_info( Returns: DatasetDatabase instance with resolved connection info """ - dataset_database = await _get_vector_db_connection_info(dataset_database) - dataset_database = await _get_graph_db_connection_info(dataset_database) + vector_dataset_database_handler = get_vector_dataset_database_handler(dataset_database) + graph_dataset_database_handler = get_graph_dataset_database_handler(dataset_database) + dataset_database = await vector_dataset_database_handler[ + "handler_instance" + ].resolve_dataset_connection_info(dataset_database) + dataset_database = await graph_dataset_database_handler[ + "handler_instance" + ].resolve_dataset_connection_info(dataset_database) return dataset_database diff --git a/cognee/infrastructure/files/storage/s3_config.py b/cognee/infrastructure/files/storage/s3_config.py index cefe5cd2f..4cc6b1d63 100644 --- a/cognee/infrastructure/files/storage/s3_config.py +++ b/cognee/infrastructure/files/storage/s3_config.py @@ -9,6 +9,8 @@ class S3Config(BaseSettings): aws_access_key_id: Optional[str] = None aws_secret_access_key: Optional[str] = None aws_session_token: Optional[str] = None + aws_profile_name: Optional[str] = None + aws_bedrock_runtime_endpoint: Optional[str] = None model_config = SettingsConfigDict(env_file=".env", extra="allow") diff --git a/cognee/infrastructure/llm/LLMGateway.py b/cognee/infrastructure/llm/LLMGateway.py index ab5bb35d7..7bec9ca01 100644 --- a/cognee/infrastructure/llm/LLMGateway.py +++ b/cognee/infrastructure/llm/LLMGateway.py @@ -11,7 +11,7 @@ class LLMGateway: @staticmethod def acreate_structured_output( - text_input: str, system_prompt: str, response_model: Type[BaseModel] + text_input: str, system_prompt: str, response_model: Type[BaseModel], **kwargs ) -> Coroutine: llm_config = get_llm_config() if llm_config.structured_output_framework.upper() == "BAML": @@ -31,7 +31,10 @@ class LLMGateway: llm_client = get_llm_client() return llm_client.acreate_structured_output( - text_input=text_input, system_prompt=system_prompt, response_model=response_model + text_input=text_input, + system_prompt=system_prompt, + response_model=response_model, + **kwargs, ) @staticmethod diff --git a/cognee/infrastructure/llm/extraction/knowledge_graph/extract_content_graph.py b/cognee/infrastructure/llm/extraction/knowledge_graph/extract_content_graph.py index 59e6f563a..4a40979f4 100644 --- a/cognee/infrastructure/llm/extraction/knowledge_graph/extract_content_graph.py +++ b/cognee/infrastructure/llm/extraction/knowledge_graph/extract_content_graph.py @@ -10,7 +10,7 @@ from cognee.infrastructure.llm.config import ( async def extract_content_graph( - content: str, response_model: Type[BaseModel], custom_prompt: Optional[str] = None + content: str, response_model: Type[BaseModel], custom_prompt: Optional[str] = None, **kwargs ): if custom_prompt: system_prompt = custom_prompt @@ -30,7 +30,7 @@ async def extract_content_graph( system_prompt = render_prompt(prompt_path, {}, base_directory=base_directory) content_graph = await LLMGateway.acreate_structured_output( - content, system_prompt, response_model + content, system_prompt, response_model, **kwargs ) return content_graph diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py index b6f218022..58b68436c 100644 --- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/anthropic/adapter.py @@ -52,7 +52,7 @@ class AnthropicAdapter(LLMInterface): reraise=True, ) async def acreate_structured_output( - self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + self, text_input: str, system_prompt: str, response_model: Type[BaseModel], **kwargs ) -> BaseModel: """ Generate a response from a user query. diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/__init__.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/__init__.py new file mode 100644 index 000000000..ad7cdf994 --- /dev/null +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/__init__.py @@ -0,0 +1,5 @@ +"""Bedrock LLM adapter module.""" + +from .adapter import BedrockAdapter + +__all__ = ["BedrockAdapter"] diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/adapter.py new file mode 100644 index 000000000..1faec2d0b --- /dev/null +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/bedrock/adapter.py @@ -0,0 +1,153 @@ +import litellm +import instructor +from typing import Type +from pydantic import BaseModel +from litellm.exceptions import ContentPolicyViolationError +from instructor.exceptions import InstructorRetryException + +from cognee.infrastructure.llm.LLMGateway import LLMGateway +from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.llm_interface import ( + LLMInterface, +) +from cognee.infrastructure.llm.exceptions import ( + ContentPolicyFilterError, + MissingSystemPromptPathError, +) +from cognee.infrastructure.files.storage.s3_config import get_s3_config +from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.rate_limiter import ( + rate_limit_async, + rate_limit_sync, + sleep_and_retry_async, + sleep_and_retry_sync, +) +from cognee.modules.observability.get_observe import get_observe + +observe = get_observe() + + +class BedrockAdapter(LLMInterface): + """ + Adapter for AWS Bedrock API with support for three authentication methods: + 1. API Key (Bearer Token) + 2. AWS Credentials (access key + secret key) + 3. AWS Profile (boto3 credential chain) + """ + + name = "Bedrock" + model: str + api_key: str + default_instructor_mode = "json_schema_mode" + + MAX_RETRIES = 5 + + def __init__( + self, + model: str, + api_key: str = None, + max_completion_tokens: int = 16384, + streaming: bool = False, + instructor_mode: str = None, + ): + self.instructor_mode = instructor_mode if instructor_mode else self.default_instructor_mode + + self.aclient = instructor.from_litellm( + litellm.acompletion, mode=instructor.Mode(self.instructor_mode) + ) + self.client = instructor.from_litellm(litellm.completion) + self.model = model + self.api_key = api_key + self.max_completion_tokens = max_completion_tokens + self.streaming = streaming + + def _create_bedrock_request( + self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + ) -> dict: + """Create Bedrock request with authentication.""" + + request_params = { + "model": self.model, + "custom_llm_provider": "bedrock", + "drop_params": True, + "messages": [ + {"role": "user", "content": text_input}, + {"role": "system", "content": system_prompt}, + ], + "response_model": response_model, + "max_retries": self.MAX_RETRIES, + "max_completion_tokens": self.max_completion_tokens, + "stream": self.streaming, + } + + s3_config = get_s3_config() + + # Add authentication parameters + if self.api_key: + request_params["api_key"] = self.api_key + elif s3_config.aws_access_key_id and s3_config.aws_secret_access_key: + request_params["aws_access_key_id"] = s3_config.aws_access_key_id + request_params["aws_secret_access_key"] = s3_config.aws_secret_access_key + if s3_config.aws_session_token: + request_params["aws_session_token"] = s3_config.aws_session_token + elif s3_config.aws_profile_name: + request_params["aws_profile_name"] = s3_config.aws_profile_name + + if s3_config.aws_region: + request_params["aws_region_name"] = s3_config.aws_region + + # Add optional parameters + if s3_config.aws_bedrock_runtime_endpoint: + request_params["aws_bedrock_runtime_endpoint"] = s3_config.aws_bedrock_runtime_endpoint + + return request_params + + @observe(as_type="generation") + @sleep_and_retry_async() + @rate_limit_async + async def acreate_structured_output( + self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + ) -> BaseModel: + """Generate structured output from AWS Bedrock API.""" + + try: + request_params = self._create_bedrock_request(text_input, system_prompt, response_model) + return await self.aclient.chat.completions.create(**request_params) + + except ( + ContentPolicyViolationError, + InstructorRetryException, + ) as error: + if ( + isinstance(error, InstructorRetryException) + and "content management policy" not in str(error).lower() + ): + raise error + + raise ContentPolicyFilterError( + f"The provided input contains content that is not aligned with our content policy: {text_input}" + ) + + @observe + @sleep_and_retry_sync() + @rate_limit_sync + def create_structured_output( + self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + ) -> BaseModel: + """Generate structured output from AWS Bedrock API (synchronous).""" + + request_params = self._create_bedrock_request(text_input, system_prompt, response_model) + return self.client.chat.completions.create(**request_params) + + def show_prompt(self, text_input: str, system_prompt: str) -> str: + """Format and display the prompt for a user query.""" + if not text_input: + text_input = "No user input provided." + if not system_prompt: + raise MissingSystemPromptPathError() + system_prompt = LLMGateway.read_query_prompt(system_prompt) + + formatted_prompt = ( + f"""System Prompt:\n{system_prompt}\n\nUser Input:\n{text_input}\n""" + if system_prompt + else None + ) + return formatted_prompt diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py index a8fcebbee..208c3729d 100644 --- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/gemini/adapter.py @@ -80,7 +80,7 @@ class GeminiAdapter(LLMInterface): reraise=True, ) async def acreate_structured_output( - self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + self, text_input: str, system_prompt: str, response_model: Type[BaseModel], **kwargs ) -> BaseModel: """ Generate a response from a user query. diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/generic_llm_api/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/generic_llm_api/adapter.py index 9beb702e5..d6e00d40a 100644 --- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/generic_llm_api/adapter.py +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/generic_llm_api/adapter.py @@ -80,7 +80,7 @@ class GenericAPIAdapter(LLMInterface): reraise=True, ) async def acreate_structured_output( - self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + self, text_input: str, system_prompt: str, response_model: Type[BaseModel], **kwargs ) -> BaseModel: """ Generate a response from a user query. diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py index 39558f36d..954d85c1d 100644 --- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/get_llm_client.py @@ -24,6 +24,7 @@ class LLMProvider(Enum): - CUSTOM: Represents a custom provider option. - GEMINI: Represents the Gemini provider. - MISTRAL: Represents the Mistral AI provider. + - BEDROCK: Represents the AWS Bedrock provider. """ OPENAI = "openai" @@ -32,6 +33,7 @@ class LLMProvider(Enum): CUSTOM = "custom" GEMINI = "gemini" MISTRAL = "mistral" + BEDROCK = "bedrock" def get_llm_client(raise_api_key_error: bool = True): @@ -154,7 +156,7 @@ def get_llm_client(raise_api_key_error: bool = True): ) elif provider == LLMProvider.MISTRAL: - if llm_config.llm_api_key is None: + if llm_config.llm_api_key is None and raise_api_key_error: raise LLMAPIKeyNotSetError() from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.mistral.adapter import ( @@ -169,5 +171,21 @@ def get_llm_client(raise_api_key_error: bool = True): instructor_mode=llm_config.llm_instructor_mode.lower(), ) + elif provider == LLMProvider.BEDROCK: + # if llm_config.llm_api_key is None and raise_api_key_error: + # raise LLMAPIKeyNotSetError() + + from cognee.infrastructure.llm.structured_output_framework.litellm_instructor.llm.bedrock.adapter import ( + BedrockAdapter, + ) + + return BedrockAdapter( + model=llm_config.llm_model, + api_key=llm_config.llm_api_key, + max_completion_tokens=max_completion_tokens, + streaming=llm_config.llm_streaming, + instructor_mode=llm_config.llm_instructor_mode.lower(), + ) + else: raise UnsupportedLLMProviderError(provider) diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/mistral/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/mistral/adapter.py index e9580faeb..e1131524d 100644 --- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/mistral/adapter.py +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/mistral/adapter.py @@ -69,7 +69,7 @@ class MistralAdapter(LLMInterface): reraise=True, ) async def acreate_structured_output( - self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + self, text_input: str, system_prompt: str, response_model: Type[BaseModel], **kwargs ) -> BaseModel: """ Generate a response from the user query. diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/ollama/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/ollama/adapter.py index 877da23ef..211e49694 100644 --- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/ollama/adapter.py +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/ollama/adapter.py @@ -76,7 +76,7 @@ class OllamaAPIAdapter(LLMInterface): reraise=True, ) async def acreate_structured_output( - self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + self, text_input: str, system_prompt: str, response_model: Type[BaseModel], **kwargs ) -> BaseModel: """ Generate a structured output from the LLM using the provided text and system prompt. @@ -123,7 +123,7 @@ class OllamaAPIAdapter(LLMInterface): before_sleep=before_sleep_log(logger, logging.DEBUG), reraise=True, ) - async def create_transcript(self, input_file: str) -> str: + async def create_transcript(self, input_file: str, **kwargs) -> str: """ Generate an audio transcript from a user query. @@ -162,7 +162,7 @@ class OllamaAPIAdapter(LLMInterface): before_sleep=before_sleep_log(logger, logging.DEBUG), reraise=True, ) - async def transcribe_image(self, input_file: str) -> str: + async def transcribe_image(self, input_file: str, **kwargs) -> str: """ Transcribe content from an image using base64 encoding. diff --git a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py index 407b720a8..ca9b583b7 100644 --- a/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py +++ b/cognee/infrastructure/llm/structured_output_framework/litellm_instructor/llm/openai/adapter.py @@ -112,7 +112,7 @@ class OpenAIAdapter(LLMInterface): reraise=True, ) async def acreate_structured_output( - self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + self, text_input: str, system_prompt: str, response_model: Type[BaseModel], **kwargs ) -> BaseModel: """ Generate a response from a user query. @@ -154,6 +154,7 @@ class OpenAIAdapter(LLMInterface): api_version=self.api_version, response_model=response_model, max_retries=self.MAX_RETRIES, + **kwargs, ) except ( ContentFilterFinishReasonError, @@ -180,6 +181,7 @@ class OpenAIAdapter(LLMInterface): # api_base=self.fallback_endpoint, response_model=response_model, max_retries=self.MAX_RETRIES, + **kwargs, ) except ( ContentFilterFinishReasonError, @@ -205,7 +207,7 @@ class OpenAIAdapter(LLMInterface): reraise=True, ) def create_structured_output( - self, text_input: str, system_prompt: str, response_model: Type[BaseModel] + self, text_input: str, system_prompt: str, response_model: Type[BaseModel], **kwargs ) -> BaseModel: """ Generate a response from a user query. @@ -245,6 +247,7 @@ class OpenAIAdapter(LLMInterface): api_version=self.api_version, response_model=response_model, max_retries=self.MAX_RETRIES, + **kwargs, ) @retry( @@ -254,7 +257,7 @@ class OpenAIAdapter(LLMInterface): before_sleep=before_sleep_log(logger, logging.DEBUG), reraise=True, ) - async def create_transcript(self, input): + async def create_transcript(self, input, **kwargs): """ Generate an audio transcript from a user query. @@ -281,6 +284,7 @@ class OpenAIAdapter(LLMInterface): api_base=self.endpoint, api_version=self.api_version, max_retries=self.MAX_RETRIES, + **kwargs, ) return transcription @@ -292,7 +296,7 @@ class OpenAIAdapter(LLMInterface): before_sleep=before_sleep_log(logger, logging.DEBUG), reraise=True, ) - async def transcribe_image(self, input) -> BaseModel: + async def transcribe_image(self, input, **kwargs) -> BaseModel: """ Generate a transcription of an image from a user query. @@ -337,4 +341,5 @@ class OpenAIAdapter(LLMInterface): api_version=self.api_version, max_completion_tokens=300, max_retries=self.MAX_RETRIES, + **kwargs, ) diff --git a/cognee/modules/data/deletion/prune_system.py b/cognee/modules/data/deletion/prune_system.py index 645e1a223..22a0fde5f 100644 --- a/cognee/modules/data/deletion/prune_system.py +++ b/cognee/modules/data/deletion/prune_system.py @@ -5,6 +5,10 @@ from cognee.context_global_variables import backend_access_control_enabled from cognee.infrastructure.databases.vector import get_vector_engine from cognee.infrastructure.databases.graph.get_graph_engine import get_graph_engine from cognee.infrastructure.databases.relational import get_relational_engine +from cognee.infrastructure.databases.utils import ( + get_graph_dataset_database_handler, + get_vector_dataset_database_handler, +) from cognee.shared.cache import delete_cache from cognee.modules.users.models import DatasetDatabase from cognee.shared.logging_utils import get_logger @@ -13,22 +17,13 @@ logger = get_logger() async def prune_graph_databases(): - async def _prune_graph_db(dataset_database: DatasetDatabase) -> dict: - from cognee.infrastructure.databases.dataset_database_handler.supported_dataset_database_handlers import ( - supported_dataset_database_handlers, - ) - - handler = supported_dataset_database_handlers[ - dataset_database.graph_dataset_database_handler - ] - return await handler["handler_instance"].delete_dataset(dataset_database) - db_engine = get_relational_engine() try: - data = await db_engine.get_all_data_from_table("dataset_database") + dataset_databases = await db_engine.get_all_data_from_table("dataset_database") # Go through each dataset database and delete the graph database - for data_item in data: - await _prune_graph_db(data_item) + for dataset_database in dataset_databases: + handler = get_graph_dataset_database_handler(dataset_database) + await handler["handler_instance"].delete_dataset(dataset_database) except (OperationalError, EntityNotFoundError) as e: logger.debug( "Skipping pruning of graph DB. Error when accessing dataset_database table: %s", @@ -38,22 +33,13 @@ async def prune_graph_databases(): async def prune_vector_databases(): - async def _prune_vector_db(dataset_database: DatasetDatabase) -> dict: - from cognee.infrastructure.databases.dataset_database_handler.supported_dataset_database_handlers import ( - supported_dataset_database_handlers, - ) - - handler = supported_dataset_database_handlers[ - dataset_database.vector_dataset_database_handler - ] - return await handler["handler_instance"].delete_dataset(dataset_database) - db_engine = get_relational_engine() try: - data = await db_engine.get_all_data_from_table("dataset_database") + dataset_databases = await db_engine.get_all_data_from_table("dataset_database") # Go through each dataset database and delete the vector database - for data_item in data: - await _prune_vector_db(data_item) + for dataset_database in dataset_databases: + handler = get_vector_dataset_database_handler(dataset_database) + await handler["handler_instance"].delete_dataset(dataset_database) except (OperationalError, EntityNotFoundError) as e: logger.debug( "Skipping pruning of vector DB. Error when accessing dataset_database table: %s", diff --git a/cognee/modules/data/methods/delete_dataset.py b/cognee/modules/data/methods/delete_dataset.py index ff20ff9e7..dea10e741 100644 --- a/cognee/modules/data/methods/delete_dataset.py +++ b/cognee/modules/data/methods/delete_dataset.py @@ -1,8 +1,34 @@ +from cognee.modules.users.models import DatasetDatabase +from sqlalchemy import select + from cognee.modules.data.models import Dataset +from cognee.infrastructure.databases.utils.get_vector_dataset_database_handler import ( + get_vector_dataset_database_handler, +) +from cognee.infrastructure.databases.utils.get_graph_dataset_database_handler import ( + get_graph_dataset_database_handler, +) from cognee.infrastructure.databases.relational import get_relational_engine async def delete_dataset(dataset: Dataset): db_engine = get_relational_engine() + async with db_engine.get_async_session() as session: + stmt = select(DatasetDatabase).where( + DatasetDatabase.dataset_id == dataset.id, + ) + dataset_database: DatasetDatabase = await session.scalar(stmt) + if dataset_database: + graph_dataset_database_handler = get_graph_dataset_database_handler(dataset_database) + vector_dataset_database_handler = get_vector_dataset_database_handler(dataset_database) + await graph_dataset_database_handler["handler_instance"].delete_dataset( + dataset_database + ) + await vector_dataset_database_handler["handler_instance"].delete_dataset( + dataset_database + ) + # TODO: Remove dataset from pipeline_run_status in Data objects related to dataset as well + # This blocks recreation of the dataset with the same name and data after deletion as + # it's marked as completed and will be just skipped even though it's empty. return await db_engine.delete_entity_by_id(dataset.__tablename__, dataset.id) diff --git a/cognee/modules/retrieval/triplet_retriever.py b/cognee/modules/retrieval/triplet_retriever.py index d251d113a..b9d006312 100644 --- a/cognee/modules/retrieval/triplet_retriever.py +++ b/cognee/modules/retrieval/triplet_retriever.py @@ -36,7 +36,7 @@ class TripletRetriever(BaseRetriever): """Initialize retriever with optional custom prompt paths.""" self.user_prompt_path = user_prompt_path self.system_prompt_path = system_prompt_path - self.top_k = top_k if top_k is not None else 1 + self.top_k = top_k if top_k is not None else 5 self.system_prompt = system_prompt async def get_context(self, query: str) -> str: diff --git a/cognee/modules/retrieval/utils/brute_force_triplet_search.py b/cognee/modules/retrieval/utils/brute_force_triplet_search.py index bd412e0ca..a70fa661b 100644 --- a/cognee/modules/retrieval/utils/brute_force_triplet_search.py +++ b/cognee/modules/retrieval/utils/brute_force_triplet_search.py @@ -16,24 +16,6 @@ logger = get_logger(level=ERROR) def format_triplets(edges): - print("\n\n\n") - - def filter_attributes(obj, attributes): - """Helper function to filter out non-None properties, including nested dicts.""" - result = {} - for attr in attributes: - value = getattr(obj, attr, None) - if value is not None: - # If the value is a dict, extract relevant keys from it - if isinstance(value, dict): - nested_values = { - k: v for k, v in value.items() if k in attributes and v is not None - } - result[attr] = nested_values - else: - result[attr] = value - return result - triplets = [] for edge in edges: node1 = edge.node1 diff --git a/cognee/modules/settings/get_settings.py b/cognee/modules/settings/get_settings.py index 071bcca36..4132ba048 100644 --- a/cognee/modules/settings/get_settings.py +++ b/cognee/modules/settings/get_settings.py @@ -16,6 +16,7 @@ class ModelName(Enum): anthropic = "anthropic" gemini = "gemini" mistral = "mistral" + bedrock = "bedrock" class LLMConfig(BaseModel): @@ -77,6 +78,10 @@ def get_settings() -> SettingsDict: "value": "mistral", "label": "Mistral", }, + { + "value": "bedrock", + "label": "Bedrock", + }, ] return SettingsDict.model_validate( @@ -157,6 +162,20 @@ def get_settings() -> SettingsDict: "label": "Mistral Large 2.1", }, ], + "bedrock": [ + { + "value": "eu.anthropic.claude-sonnet-4-5-20250929-v1:0", + "label": "Claude 4.5 Sonnet", + }, + { + "value": "eu.anthropic.claude-haiku-4-5-20251001-v1:0", + "label": "Claude 4.5 Haiku", + }, + { + "value": "eu.amazon.nova-lite-v1:0", + "label": "Amazon Nova Lite", + }, + ], }, }, vector_db={ diff --git a/cognee/tasks/graph/extract_graph_from_data.py b/cognee/tasks/graph/extract_graph_from_data.py index 2d1eca17e..5b762d40c 100644 --- a/cognee/tasks/graph/extract_graph_from_data.py +++ b/cognee/tasks/graph/extract_graph_from_data.py @@ -97,6 +97,7 @@ async def extract_graph_from_data( graph_model: Type[BaseModel], config: Config = None, custom_prompt: Optional[str] = None, + **kwargs, ) -> List[DocumentChunk]: """ Extracts and integrates a knowledge graph from the text content of document chunks using a specified graph model. @@ -111,7 +112,7 @@ async def extract_graph_from_data( chunk_graphs = await asyncio.gather( *[ - extract_content_graph(chunk.text, graph_model, custom_prompt=custom_prompt) + extract_content_graph(chunk.text, graph_model, custom_prompt=custom_prompt, **kwargs) for chunk in data_chunks ] ) diff --git a/cognee/tasks/memify/get_triplet_datapoints.py b/cognee/tasks/memify/get_triplet_datapoints.py index bfc02ec6a..764adfb63 100644 --- a/cognee/tasks/memify/get_triplet_datapoints.py +++ b/cognee/tasks/memify/get_triplet_datapoints.py @@ -1,5 +1,6 @@ from typing import AsyncGenerator, Dict, Any, List, Optional from cognee.infrastructure.databases.graph.get_graph_engine import get_graph_engine +from cognee.modules.engine.utils import generate_node_id from cognee.shared.logging_utils import get_logger from cognee.modules.graph.utils.convert_node_to_data_point import get_all_subclasses from cognee.infrastructure.engine import DataPoint @@ -155,7 +156,12 @@ def _process_single_triplet( embeddable_text = f"{start_node_text}-โ€บ{relationship_text}-โ€บ{end_node_text}".strip() - triplet_obj = Triplet(from_node_id=start_node_id, to_node_id=end_node_id, text=embeddable_text) + relationship_name = relationship.get("relationship_name", "") + triplet_id = generate_node_id(str(start_node_id) + str(relationship_name) + str(end_node_id)) + + triplet_obj = Triplet( + id=triplet_id, from_node_id=start_node_id, to_node_id=end_node_id, text=embeddable_text + ) return triplet_obj, None diff --git a/cognee/tests/integration/retrieval/test_chunks_retriever.py b/cognee/tests/integration/retrieval/test_chunks_retriever.py new file mode 100644 index 000000000..d2e5e6149 --- /dev/null +++ b/cognee/tests/integration/retrieval/test_chunks_retriever.py @@ -0,0 +1,252 @@ +import os +import pytest +import pathlib +import pytest_asyncio +from typing import List +import cognee + +from cognee.low_level import setup +from cognee.tasks.storage import add_data_points +from cognee.infrastructure.databases.vector import get_vector_engine +from cognee.modules.chunking.models import DocumentChunk +from cognee.modules.data.processing.document_types import TextDocument +from cognee.modules.retrieval.exceptions.exceptions import NoDataError +from cognee.modules.retrieval.chunks_retriever import ChunksRetriever +from cognee.infrastructure.engine import DataPoint +from cognee.modules.data.processing.document_types import Document +from cognee.modules.engine.models import Entity + + +class DocumentChunkWithEntities(DataPoint): + text: str + chunk_size: int + chunk_index: int + cut_type: str + is_part_of: Document + contains: List[Entity] = None + + metadata: dict = {"index_fields": ["text"]} + + +@pytest_asyncio.fixture +async def setup_test_environment_with_chunks_simple(): + """Set up a clean test environment with simple chunks.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_chunks_retriever_context_simple") + data_directory_path = str(base_dir / ".data_storage/test_chunks_retriever_context_simple") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + document = TextDocument( + name="Steve Rodger's career", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + chunk1 = DocumentChunk( + text="Steve Rodger", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + chunk2 = DocumentChunk( + text="Mike Broski", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + chunk3 = DocumentChunk( + text="Christina Mayer", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + + entities = [chunk1, chunk2, chunk3] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_with_chunks_complex(): + """Set up a clean test environment with complex chunks.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_chunks_retriever_context_complex") + data_directory_path = str(base_dir / ".data_storage/test_chunks_retriever_context_complex") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + document1 = TextDocument( + name="Employee List", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + document2 = TextDocument( + name="Car List", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + chunk1 = DocumentChunk( + text="Steve Rodger", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + chunk2 = DocumentChunk( + text="Mike Broski", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + chunk3 = DocumentChunk( + text="Christina Mayer", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + + chunk4 = DocumentChunk( + text="Range Rover", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + chunk5 = DocumentChunk( + text="Hyundai", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + chunk6 = DocumentChunk( + text="Chrysler", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + + entities = [chunk1, chunk2, chunk3, chunk4, chunk5, chunk6] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_empty(): + """Set up a clean test environment without chunks.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_chunks_retriever_context_empty") + data_directory_path = str(base_dir / ".data_storage/test_chunks_retriever_context_empty") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest.mark.asyncio +async def test_chunks_retriever_context_multiple_chunks(setup_test_environment_with_chunks_simple): + """Integration test: verify ChunksRetriever can retrieve multiple chunks.""" + retriever = ChunksRetriever() + + context = await retriever.get_context("Steve") + + assert isinstance(context, list), "Context should be a list" + assert len(context) > 0, "Context should not be empty" + assert any(chunk["text"] == "Steve Rodger" for chunk in context), ( + "Failed to get Steve Rodger chunk" + ) + + +@pytest.mark.asyncio +async def test_chunks_retriever_top_k_limit(setup_test_environment_with_chunks_complex): + """Integration test: verify ChunksRetriever respects top_k parameter.""" + retriever = ChunksRetriever(top_k=2) + + context = await retriever.get_context("Employee") + + assert isinstance(context, list), "Context should be a list" + assert len(context) <= 2, "Should respect top_k limit" + + +@pytest.mark.asyncio +async def test_chunks_retriever_context_complex(setup_test_environment_with_chunks_complex): + """Integration test: verify ChunksRetriever can retrieve chunk context (complex).""" + retriever = ChunksRetriever(top_k=20) + + context = await retriever.get_context("Christina") + + assert context[0]["text"] == "Christina Mayer", "Failed to get Christina Mayer" + + +@pytest.mark.asyncio +async def test_chunks_retriever_context_on_empty_graph(setup_test_environment_empty): + """Integration test: verify ChunksRetriever handles empty graph correctly.""" + retriever = ChunksRetriever() + + with pytest.raises(NoDataError): + await retriever.get_context("Christina Mayer") + + vector_engine = get_vector_engine() + await vector_engine.create_collection( + "DocumentChunk_text", payload_schema=DocumentChunkWithEntities + ) + + context = await retriever.get_context("Christina Mayer") + assert len(context) == 0, "Found chunks when none should exist" diff --git a/cognee/tests/unit/modules/retrieval/test_completion.py b/cognee/tests/integration/retrieval/test_completion.py similarity index 100% rename from cognee/tests/unit/modules/retrieval/test_completion.py rename to cognee/tests/integration/retrieval/test_completion.py diff --git a/cognee/tests/integration/retrieval/test_graph_completion_retriever.py b/cognee/tests/integration/retrieval/test_graph_completion_retriever.py new file mode 100644 index 000000000..7367b353b --- /dev/null +++ b/cognee/tests/integration/retrieval/test_graph_completion_retriever.py @@ -0,0 +1,268 @@ +import os +import pytest +import pathlib +import pytest_asyncio +from typing import Optional, Union +import cognee + +from cognee.low_level import setup, DataPoint +from cognee.modules.graph.utils import resolve_edges_to_text +from cognee.tasks.storage import add_data_points +from cognee.modules.retrieval.graph_completion_retriever import GraphCompletionRetriever + + +@pytest_asyncio.fixture +async def setup_test_environment_simple(): + """Set up a clean test environment with simple graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_graph_completion_context_simple") + data_directory_path = str(base_dir / ".data_storage/test_graph_completion_context_simple") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + class Company(DataPoint): + name: str + description: str + + class Person(DataPoint): + name: str + description: str + works_for: Company + + company1 = Company(name="Figma", description="Figma is a company") + company2 = Company(name="Canva", description="Canvas is a company") + person1 = Person( + name="Steve Rodger", + description="This is description about Steve Rodger", + works_for=company1, + ) + person2 = Person( + name="Ike Loma", description="This is description about Ike Loma", works_for=company1 + ) + person3 = Person( + name="Jason Statham", + description="This is description about Jason Statham", + works_for=company1, + ) + person4 = Person( + name="Mike Broski", + description="This is description about Mike Broski", + works_for=company2, + ) + person5 = Person( + name="Christina Mayer", + description="This is description about Christina Mayer", + works_for=company2, + ) + + entities = [company1, company2, person1, person2, person3, person4, person5] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_complex(): + """Set up a clean test environment with complex graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_graph_completion_context_complex") + data_directory_path = str(base_dir / ".data_storage/test_graph_completion_context_complex") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + class Company(DataPoint): + name: str + metadata: dict = {"index_fields": ["name"]} + + class Car(DataPoint): + brand: str + model: str + year: int + + class Location(DataPoint): + country: str + city: str + + class Home(DataPoint): + location: Location + rooms: int + sqm: int + + class Person(DataPoint): + name: str + works_for: Company + owns: Optional[list[Union[Car, Home]]] = None + + company1 = Company(name="Figma") + company2 = Company(name="Canva") + + person1 = Person(name="Mike Rodger", works_for=company1) + person1.owns = [Car(brand="Toyota", model="Camry", year=2020)] + + person2 = Person(name="Ike Loma", works_for=company1) + person2.owns = [ + Car(brand="Tesla", model="Model S", year=2021), + Home(location=Location(country="USA", city="New York"), sqm=80, rooms=4), + ] + + person3 = Person(name="Jason Statham", works_for=company1) + + person4 = Person(name="Mike Broski", works_for=company2) + person4.owns = [Car(brand="Ford", model="Mustang", year=1978)] + + person5 = Person(name="Christina Mayer", works_for=company2) + person5.owns = [Car(brand="Honda", model="Civic", year=2023)] + + entities = [company1, company2, person1, person2, person3, person4, person5] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_empty(): + """Set up a clean test environment without graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str( + base_dir / ".cognee_system/test_get_graph_completion_context_on_empty_graph" + ) + data_directory_path = str( + base_dir / ".data_storage/test_get_graph_completion_context_on_empty_graph" + ) + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest.mark.asyncio +async def test_graph_completion_context_simple(setup_test_environment_simple): + """Integration test: verify GraphCompletionRetriever can retrieve context (simple).""" + retriever = GraphCompletionRetriever() + + context = await resolve_edges_to_text(await retriever.get_context("Who works at Canva?")) + + # Ensure the top-level sections are present + assert "Nodes:" in context, "Missing 'Nodes:' section in context" + assert "Connections:" in context, "Missing 'Connections:' section in context" + + # --- Nodes headers --- + assert "Node: Steve Rodger" in context, "Missing node header for Steve Rodger" + assert "Node: Figma" in context, "Missing node header for Figma" + assert "Node: Ike Loma" in context, "Missing node header for Ike Loma" + assert "Node: Jason Statham" in context, "Missing node header for Jason Statham" + assert "Node: Mike Broski" in context, "Missing node header for Mike Broski" + assert "Node: Canva" in context, "Missing node header for Canva" + assert "Node: Christina Mayer" in context, "Missing node header for Christina Mayer" + + # --- Node contents --- + assert ( + "__node_content_start__\nThis is description about Steve Rodger\n__node_content_end__" + in context + ), "Description block for Steve Rodger altered" + assert "__node_content_start__\nFigma is a company\n__node_content_end__" in context, ( + "Description block for Figma altered" + ) + assert ( + "__node_content_start__\nThis is description about Ike Loma\n__node_content_end__" + in context + ), "Description block for Ike Loma altered" + assert ( + "__node_content_start__\nThis is description about Jason Statham\n__node_content_end__" + in context + ), "Description block for Jason Statham altered" + assert ( + "__node_content_start__\nThis is description about Mike Broski\n__node_content_end__" + in context + ), "Description block for Mike Broski altered" + assert "__node_content_start__\nCanvas is a company\n__node_content_end__" in context, ( + "Description block for Canva altered" + ) + assert ( + "__node_content_start__\nThis is description about Christina Mayer\n__node_content_end__" + in context + ), "Description block for Christina Mayer altered" + + # --- Connections --- + assert "Steve Rodger --[works_for]--> Figma" in context, ( + "Connection Steve Rodgerโ†’Figma missing or changed" + ) + assert "Ike Loma --[works_for]--> Figma" in context, ( + "Connection Ike Lomaโ†’Figma missing or changed" + ) + assert "Jason Statham --[works_for]--> Figma" in context, ( + "Connection Jason Stathamโ†’Figma missing or changed" + ) + assert "Mike Broski --[works_for]--> Canva" in context, ( + "Connection Mike Broskiโ†’Canva missing or changed" + ) + assert "Christina Mayer --[works_for]--> Canva" in context, ( + "Connection Christina Mayerโ†’Canva missing or changed" + ) + + +@pytest.mark.asyncio +async def test_graph_completion_context_complex(setup_test_environment_complex): + """Integration test: verify GraphCompletionRetriever can retrieve context (complex).""" + retriever = GraphCompletionRetriever(top_k=20) + + context = await resolve_edges_to_text(await retriever.get_context("Who works at Figma?")) + + assert "Mike Rodger --[works_for]--> Figma" in context, "Failed to get Mike Rodger" + assert "Ike Loma --[works_for]--> Figma" in context, "Failed to get Ike Loma" + assert "Jason Statham --[works_for]--> Figma" in context, "Failed to get Jason Statham" + + +@pytest.mark.asyncio +async def test_get_graph_completion_context_on_empty_graph(setup_test_environment_empty): + """Integration test: verify GraphCompletionRetriever handles empty graph correctly.""" + retriever = GraphCompletionRetriever() + + context = await retriever.get_context("Who works at Figma?") + assert context == [], "Context should be empty on an empty graph" + + +@pytest.mark.asyncio +async def test_graph_completion_get_triplets_empty(setup_test_environment_empty): + """Integration test: verify GraphCompletionRetriever get_triplets handles empty graph.""" + retriever = GraphCompletionRetriever() + + triplets = await retriever.get_triplets("Who works at Figma?") + + assert isinstance(triplets, list), "Triplets should be a list" + assert len(triplets) == 0, "Should return empty list on empty graph" diff --git a/cognee/tests/integration/retrieval/test_graph_completion_retriever_context_extension.py b/cognee/tests/integration/retrieval/test_graph_completion_retriever_context_extension.py new file mode 100644 index 000000000..c87de16ef --- /dev/null +++ b/cognee/tests/integration/retrieval/test_graph_completion_retriever_context_extension.py @@ -0,0 +1,226 @@ +import os +import pytest +import pathlib +import pytest_asyncio +from typing import Optional, Union +import cognee + +from cognee.low_level import setup, DataPoint +from cognee.tasks.storage import add_data_points +from cognee.modules.graph.utils import resolve_edges_to_text +from cognee.modules.retrieval.graph_completion_context_extension_retriever import ( + GraphCompletionContextExtensionRetriever, +) + + +@pytest_asyncio.fixture +async def setup_test_environment_simple(): + """Set up a clean test environment with simple graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str( + base_dir / ".cognee_system/test_graph_completion_extension_context_simple" + ) + data_directory_path = str( + base_dir / ".data_storage/test_graph_completion_extension_context_simple" + ) + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + class Company(DataPoint): + name: str + + class Person(DataPoint): + name: str + works_for: Company + + company1 = Company(name="Figma") + company2 = Company(name="Canva") + person1 = Person(name="Steve Rodger", works_for=company1) + person2 = Person(name="Ike Loma", works_for=company1) + person3 = Person(name="Jason Statham", works_for=company1) + person4 = Person(name="Mike Broski", works_for=company2) + person5 = Person(name="Christina Mayer", works_for=company2) + + entities = [company1, company2, person1, person2, person3, person4, person5] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_complex(): + """Set up a clean test environment with complex graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str( + base_dir / ".cognee_system/test_graph_completion_extension_context_complex" + ) + data_directory_path = str( + base_dir / ".data_storage/test_graph_completion_extension_context_complex" + ) + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + class Company(DataPoint): + name: str + metadata: dict = {"index_fields": ["name"]} + + class Car(DataPoint): + brand: str + model: str + year: int + + class Location(DataPoint): + country: str + city: str + + class Home(DataPoint): + location: Location + rooms: int + sqm: int + + class Person(DataPoint): + name: str + works_for: Company + owns: Optional[list[Union[Car, Home]]] = None + + company1 = Company(name="Figma") + company2 = Company(name="Canva") + + person1 = Person(name="Mike Rodger", works_for=company1) + person1.owns = [Car(brand="Toyota", model="Camry", year=2020)] + + person2 = Person(name="Ike Loma", works_for=company1) + person2.owns = [ + Car(brand="Tesla", model="Model S", year=2021), + Home(location=Location(country="USA", city="New York"), sqm=80, rooms=4), + ] + + person3 = Person(name="Jason Statham", works_for=company1) + + person4 = Person(name="Mike Broski", works_for=company2) + person4.owns = [Car(brand="Ford", model="Mustang", year=1978)] + + person5 = Person(name="Christina Mayer", works_for=company2) + person5.owns = [Car(brand="Honda", model="Civic", year=2023)] + + entities = [company1, company2, person1, person2, person3, person4, person5] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_empty(): + """Set up a clean test environment without graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str( + base_dir / ".cognee_system/test_get_graph_completion_extension_context_on_empty_graph" + ) + data_directory_path = str( + base_dir / ".data_storage/test_get_graph_completion_extension_context_on_empty_graph" + ) + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest.mark.asyncio +async def test_graph_completion_extension_context_simple(setup_test_environment_simple): + """Integration test: verify GraphCompletionContextExtensionRetriever can retrieve context (simple).""" + retriever = GraphCompletionContextExtensionRetriever() + + context = await resolve_edges_to_text(await retriever.get_context("Who works at Canva?")) + + assert "Mike Broski --[works_for]--> Canva" in context, "Failed to get Mike Broski" + assert "Christina Mayer --[works_for]--> Canva" in context, "Failed to get Christina Mayer" + + answer = await retriever.get_completion("Who works at Canva?") + + assert isinstance(answer, list), f"Expected list, got {type(answer).__name__}" + assert all(isinstance(item, str) and item.strip() for item in answer), ( + "Answer must contain only non-empty strings" + ) + + +@pytest.mark.asyncio +async def test_graph_completion_extension_context_complex(setup_test_environment_complex): + """Integration test: verify GraphCompletionContextExtensionRetriever can retrieve context (complex).""" + retriever = GraphCompletionContextExtensionRetriever(top_k=20) + + context = await resolve_edges_to_text( + await retriever.get_context("Who works at Figma and drives Tesla?") + ) + + assert "Mike Rodger --[works_for]--> Figma" in context, "Failed to get Mike Rodger" + assert "Ike Loma --[works_for]--> Figma" in context, "Failed to get Ike Loma" + assert "Jason Statham --[works_for]--> Figma" in context, "Failed to get Jason Statham" + + answer = await retriever.get_completion("Who works at Figma?") + + assert isinstance(answer, list), f"Expected list, got {type(answer).__name__}" + assert all(isinstance(item, str) and item.strip() for item in answer), ( + "Answer must contain only non-empty strings" + ) + + +@pytest.mark.asyncio +async def test_get_graph_completion_extension_context_on_empty_graph(setup_test_environment_empty): + """Integration test: verify GraphCompletionContextExtensionRetriever handles empty graph correctly.""" + retriever = GraphCompletionContextExtensionRetriever() + + context = await retriever.get_context("Who works at Figma?") + assert context == [], "Context should be empty on an empty graph" + + answer = await retriever.get_completion("Who works at Figma?") + + assert isinstance(answer, list), f"Expected list, got {type(answer).__name__}" + assert all(isinstance(item, str) and item.strip() for item in answer), ( + "Answer must contain only non-empty strings" + ) + + +@pytest.mark.asyncio +async def test_graph_completion_extension_get_triplets_empty(setup_test_environment_empty): + """Integration test: verify GraphCompletionContextExtensionRetriever get_triplets handles empty graph.""" + retriever = GraphCompletionContextExtensionRetriever() + + triplets = await retriever.get_triplets("Who works at Figma?") + + assert isinstance(triplets, list), "Triplets should be a list" + assert len(triplets) == 0, "Should return empty list on empty graph" diff --git a/cognee/tests/integration/retrieval/test_graph_completion_retriever_cot.py b/cognee/tests/integration/retrieval/test_graph_completion_retriever_cot.py new file mode 100644 index 000000000..0db035e03 --- /dev/null +++ b/cognee/tests/integration/retrieval/test_graph_completion_retriever_cot.py @@ -0,0 +1,218 @@ +import os +import pytest +import pathlib +import pytest_asyncio +from typing import Optional, Union +import cognee + +from cognee.low_level import setup, DataPoint +from cognee.modules.graph.utils import resolve_edges_to_text +from cognee.tasks.storage import add_data_points +from cognee.modules.retrieval.graph_completion_cot_retriever import GraphCompletionCotRetriever + + +@pytest_asyncio.fixture +async def setup_test_environment_simple(): + """Set up a clean test environment with simple graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str( + base_dir / ".cognee_system/test_graph_completion_cot_context_simple" + ) + data_directory_path = str(base_dir / ".data_storage/test_graph_completion_cot_context_simple") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + class Company(DataPoint): + name: str + + class Person(DataPoint): + name: str + works_for: Company + + company1 = Company(name="Figma") + company2 = Company(name="Canva") + person1 = Person(name="Steve Rodger", works_for=company1) + person2 = Person(name="Ike Loma", works_for=company1) + person3 = Person(name="Jason Statham", works_for=company1) + person4 = Person(name="Mike Broski", works_for=company2) + person5 = Person(name="Christina Mayer", works_for=company2) + + entities = [company1, company2, person1, person2, person3, person4, person5] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_complex(): + """Set up a clean test environment with complex graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str( + base_dir / ".cognee_system/test_graph_completion_cot_context_complex" + ) + data_directory_path = str(base_dir / ".data_storage/test_graph_completion_cot_context_complex") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + class Company(DataPoint): + name: str + metadata: dict = {"index_fields": ["name"]} + + class Car(DataPoint): + brand: str + model: str + year: int + + class Location(DataPoint): + country: str + city: str + + class Home(DataPoint): + location: Location + rooms: int + sqm: int + + class Person(DataPoint): + name: str + works_for: Company + owns: Optional[list[Union[Car, Home]]] = None + + company1 = Company(name="Figma") + company2 = Company(name="Canva") + + person1 = Person(name="Mike Rodger", works_for=company1) + person1.owns = [Car(brand="Toyota", model="Camry", year=2020)] + + person2 = Person(name="Ike Loma", works_for=company1) + person2.owns = [ + Car(brand="Tesla", model="Model S", year=2021), + Home(location=Location(country="USA", city="New York"), sqm=80, rooms=4), + ] + + person3 = Person(name="Jason Statham", works_for=company1) + + person4 = Person(name="Mike Broski", works_for=company2) + person4.owns = [Car(brand="Ford", model="Mustang", year=1978)] + + person5 = Person(name="Christina Mayer", works_for=company2) + person5.owns = [Car(brand="Honda", model="Civic", year=2023)] + + entities = [company1, company2, person1, person2, person3, person4, person5] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_empty(): + """Set up a clean test environment without graph data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str( + base_dir / ".cognee_system/test_get_graph_completion_cot_context_on_empty_graph" + ) + data_directory_path = str( + base_dir / ".data_storage/test_get_graph_completion_cot_context_on_empty_graph" + ) + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest.mark.asyncio +async def test_graph_completion_cot_context_simple(setup_test_environment_simple): + """Integration test: verify GraphCompletionCotRetriever can retrieve context (simple).""" + retriever = GraphCompletionCotRetriever() + + context = await resolve_edges_to_text(await retriever.get_context("Who works at Canva?")) + + assert "Mike Broski --[works_for]--> Canva" in context, "Failed to get Mike Broski" + assert "Christina Mayer --[works_for]--> Canva" in context, "Failed to get Christina Mayer" + + answer = await retriever.get_completion("Who works at Canva?") + + assert isinstance(answer, list), f"Expected list, got {type(answer).__name__}" + assert all(isinstance(item, str) and item.strip() for item in answer), ( + "Answer must contain only non-empty strings" + ) + + +@pytest.mark.asyncio +async def test_graph_completion_cot_context_complex(setup_test_environment_complex): + """Integration test: verify GraphCompletionCotRetriever can retrieve context (complex).""" + retriever = GraphCompletionCotRetriever(top_k=20) + + context = await resolve_edges_to_text(await retriever.get_context("Who works at Figma?")) + + assert "Mike Rodger --[works_for]--> Figma" in context, "Failed to get Mike Rodger" + assert "Ike Loma --[works_for]--> Figma" in context, "Failed to get Ike Loma" + assert "Jason Statham --[works_for]--> Figma" in context, "Failed to get Jason Statham" + + answer = await retriever.get_completion("Who works at Figma?") + + assert isinstance(answer, list), f"Expected list, got {type(answer).__name__}" + assert all(isinstance(item, str) and item.strip() for item in answer), ( + "Answer must contain only non-empty strings" + ) + + +@pytest.mark.asyncio +async def test_get_graph_completion_cot_context_on_empty_graph(setup_test_environment_empty): + """Integration test: verify GraphCompletionCotRetriever handles empty graph correctly.""" + retriever = GraphCompletionCotRetriever() + + context = await retriever.get_context("Who works at Figma?") + assert context == [], "Context should be empty on an empty graph" + + answer = await retriever.get_completion("Who works at Figma?") + + assert isinstance(answer, list), f"Expected list, got {type(answer).__name__}" + assert all(isinstance(item, str) and item.strip() for item in answer), ( + "Answer must contain only non-empty strings" + ) + + +@pytest.mark.asyncio +async def test_graph_completion_cot_get_triplets_empty(setup_test_environment_empty): + """Integration test: verify GraphCompletionCotRetriever get_triplets handles empty graph.""" + retriever = GraphCompletionCotRetriever() + + triplets = await retriever.get_triplets("Who works at Figma?") + + assert isinstance(triplets, list), "Triplets should be a list" + assert len(triplets) == 0, "Should return empty list on empty graph" diff --git a/cognee/tests/unit/modules/retrieval/test_graph_summary_completion_retriever.py b/cognee/tests/integration/retrieval/test_graph_summary_completion_retriever.py similarity index 100% rename from cognee/tests/unit/modules/retrieval/test_graph_summary_completion_retriever.py rename to cognee/tests/integration/retrieval/test_graph_summary_completion_retriever.py diff --git a/cognee/tests/integration/retrieval/test_rag_completion_retriever.py b/cognee/tests/integration/retrieval/test_rag_completion_retriever.py new file mode 100644 index 000000000..b01d58160 --- /dev/null +++ b/cognee/tests/integration/retrieval/test_rag_completion_retriever.py @@ -0,0 +1,254 @@ +import os +from typing import List +import pytest +import pathlib +import pytest_asyncio +import cognee + +from cognee.low_level import setup +from cognee.tasks.storage import add_data_points +from cognee.infrastructure.databases.vector import get_vector_engine +from cognee.modules.chunking.models import DocumentChunk +from cognee.modules.data.processing.document_types import TextDocument +from cognee.modules.retrieval.exceptions.exceptions import NoDataError +from cognee.modules.retrieval.completion_retriever import CompletionRetriever +from cognee.infrastructure.engine import DataPoint +from cognee.modules.data.processing.document_types import Document +from cognee.modules.engine.models import Entity + + +class DocumentChunkWithEntities(DataPoint): + text: str + chunk_size: int + chunk_index: int + cut_type: str + is_part_of: Document + contains: List[Entity] = None + + metadata: dict = {"index_fields": ["text"]} + + +@pytest_asyncio.fixture +async def setup_test_environment_with_chunks_simple(): + """Set up a clean test environment with simple chunks.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_rag_completion_context_simple") + data_directory_path = str(base_dir / ".data_storage/test_rag_completion_context_simple") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + document = TextDocument( + name="Steve Rodger's career", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + chunk1 = DocumentChunk( + text="Steve Rodger", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + chunk2 = DocumentChunk( + text="Mike Broski", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + chunk3 = DocumentChunk( + text="Christina Mayer", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + + entities = [chunk1, chunk2, chunk3] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_with_chunks_complex(): + """Set up a clean test environment with complex chunks.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_rag_completion_context_complex") + data_directory_path = str(base_dir / ".data_storage/test_rag_completion_context_complex") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + document1 = TextDocument( + name="Employee List", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + document2 = TextDocument( + name="Car List", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + chunk1 = DocumentChunk( + text="Steve Rodger", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + chunk2 = DocumentChunk( + text="Mike Broski", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + chunk3 = DocumentChunk( + text="Christina Mayer", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + + chunk4 = DocumentChunk( + text="Range Rover", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + chunk5 = DocumentChunk( + text="Hyundai", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + chunk6 = DocumentChunk( + text="Chrysler", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + + entities = [chunk1, chunk2, chunk3, chunk4, chunk5, chunk6] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_empty(): + """Set up a clean test environment without chunks.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str( + base_dir / ".cognee_system/test_get_rag_completion_context_on_empty_graph" + ) + data_directory_path = str( + base_dir / ".data_storage/test_get_rag_completion_context_on_empty_graph" + ) + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest.mark.asyncio +async def test_rag_completion_context_simple(setup_test_environment_with_chunks_simple): + """Integration test: verify CompletionRetriever can retrieve context (simple).""" + retriever = CompletionRetriever() + + context = await retriever.get_context("Mike") + + assert isinstance(context, str), "Context should be a string" + assert "Mike Broski" in context, "Failed to get Mike Broski" + + +@pytest.mark.asyncio +async def test_rag_completion_context_multiple_chunks(setup_test_environment_with_chunks_simple): + """Integration test: verify CompletionRetriever can retrieve context from multiple chunks.""" + retriever = CompletionRetriever() + + context = await retriever.get_context("Steve") + + assert isinstance(context, str), "Context should be a string" + assert "Steve Rodger" in context, "Failed to get Steve Rodger" + + +@pytest.mark.asyncio +async def test_rag_completion_context_complex(setup_test_environment_with_chunks_complex): + """Integration test: verify CompletionRetriever can retrieve context (complex).""" + # TODO: top_k doesn't affect the output, it should be fixed. + retriever = CompletionRetriever(top_k=20) + + context = await retriever.get_context("Christina") + + assert context[0:15] == "Christina Mayer", "Failed to get Christina Mayer" + + +@pytest.mark.asyncio +async def test_get_rag_completion_context_on_empty_graph(setup_test_environment_empty): + """Integration test: verify CompletionRetriever handles empty graph correctly.""" + retriever = CompletionRetriever() + + with pytest.raises(NoDataError): + await retriever.get_context("Christina Mayer") + + vector_engine = get_vector_engine() + await vector_engine.create_collection( + "DocumentChunk_text", payload_schema=DocumentChunkWithEntities + ) + + context = await retriever.get_context("Christina Mayer") + assert context == "", "Returned context should be empty on an empty graph" diff --git a/cognee/tests/unit/modules/retrieval/structured_output_test.py b/cognee/tests/integration/retrieval/test_structured_output.py similarity index 65% rename from cognee/tests/unit/modules/retrieval/structured_output_test.py rename to cognee/tests/integration/retrieval/test_structured_output.py index 4ad3019ff..13ffd8eef 100644 --- a/cognee/tests/unit/modules/retrieval/structured_output_test.py +++ b/cognee/tests/integration/retrieval/test_structured_output.py @@ -1,9 +1,9 @@ import asyncio - -import pytest -import cognee -import pathlib import os +import pytest +import pathlib +import pytest_asyncio +import cognee from pydantic import BaseModel from cognee.low_level import setup, DataPoint @@ -125,80 +125,90 @@ async def _test_get_structured_entity_completion(): _assert_structured_answer(structured_answer) -class TestStructuredOutputCompletion: - @pytest.mark.asyncio - async def test_get_structured_completion(self): - system_directory_path = os.path.join( - pathlib.Path(__file__).parent, ".cognee_system/test_get_structured_completion" - ) - cognee.config.system_root_directory(system_directory_path) - data_directory_path = os.path.join( - pathlib.Path(__file__).parent, ".data_storage/test_get_structured_completion" - ) - cognee.config.data_root_directory(data_directory_path) +@pytest_asyncio.fixture +async def setup_test_environment(): + """Set up a clean test environment with graph and document data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_get_structured_completion") + data_directory_path = str(base_dir / ".data_storage/test_get_structured_completion") + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + class Company(DataPoint): + name: str + + class Person(DataPoint): + name: str + works_for: Company + works_since: int + + company1 = Company(name="Figma") + person1 = Person(name="Steve Rodger", works_for=company1, works_since=2015) + + entities = [company1, person1] + await add_data_points(entities) + + document = TextDocument( + name="Steve Rodger's career", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + chunk1 = DocumentChunk( + text="Steve Rodger", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + chunk2 = DocumentChunk( + text="Mike Broski", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + chunk3 = DocumentChunk( + text="Christina Mayer", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document, + contains=[], + ) + + entities = [chunk1, chunk2, chunk3] + await add_data_points(entities) + + entity_type = EntityType(name="Person", description="A human individual") + entity = Entity(name="Albert Einstein", is_a=entity_type, description="A famous physicist") + + entities = [entity] + await add_data_points(entities) + + yield + + try: await cognee.prune.prune_data() await cognee.prune.prune_system(metadata=True) - await setup() + except Exception: + pass - class Company(DataPoint): - name: str - class Person(DataPoint): - name: str - works_for: Company - works_since: int - - company1 = Company(name="Figma") - person1 = Person(name="Steve Rodger", works_for=company1, works_since=2015) - - entities = [company1, person1] - await add_data_points(entities) - - document = TextDocument( - name="Steve Rodger's career", - raw_data_location="somewhere", - external_metadata="", - mime_type="text/plain", - ) - - chunk1 = DocumentChunk( - text="Steve Rodger", - chunk_size=2, - chunk_index=0, - cut_type="sentence_end", - is_part_of=document, - contains=[], - ) - chunk2 = DocumentChunk( - text="Mike Broski", - chunk_size=2, - chunk_index=1, - cut_type="sentence_end", - is_part_of=document, - contains=[], - ) - chunk3 = DocumentChunk( - text="Christina Mayer", - chunk_size=2, - chunk_index=2, - cut_type="sentence_end", - is_part_of=document, - contains=[], - ) - - entities = [chunk1, chunk2, chunk3] - await add_data_points(entities) - - entity_type = EntityType(name="Person", description="A human individual") - entity = Entity(name="Albert Einstein", is_a=entity_type, description="A famous physicist") - - entities = [entity] - await add_data_points(entities) - - await _test_get_structured_graph_completion_cot() - await _test_get_structured_graph_completion() - await _test_get_structured_graph_completion_temporal() - await _test_get_structured_graph_completion_rag() - await _test_get_structured_graph_completion_context_extension() - await _test_get_structured_entity_completion() +@pytest.mark.asyncio +async def test_get_structured_completion(setup_test_environment): + """Integration test: verify structured output completion for all retrievers.""" + await _test_get_structured_graph_completion_cot() + await _test_get_structured_graph_completion() + await _test_get_structured_graph_completion_temporal() + await _test_get_structured_graph_completion_rag() + await _test_get_structured_graph_completion_context_extension() + await _test_get_structured_entity_completion() diff --git a/cognee/tests/integration/retrieval/test_summaries_retriever.py b/cognee/tests/integration/retrieval/test_summaries_retriever.py new file mode 100644 index 000000000..a2f4e40b3 --- /dev/null +++ b/cognee/tests/integration/retrieval/test_summaries_retriever.py @@ -0,0 +1,184 @@ +import os +import pytest +import pathlib +import pytest_asyncio +import cognee + +from cognee.low_level import setup +from cognee.tasks.storage import add_data_points +from cognee.infrastructure.databases.vector import get_vector_engine +from cognee.modules.chunking.models import DocumentChunk +from cognee.tasks.summarization.models import TextSummary +from cognee.modules.data.processing.document_types import TextDocument +from cognee.modules.retrieval.exceptions.exceptions import NoDataError +from cognee.modules.retrieval.summaries_retriever import SummariesRetriever + + +@pytest_asyncio.fixture +async def setup_test_environment_with_summaries(): + """Set up a clean test environment with summaries.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_summaries_retriever_context") + data_directory_path = str(base_dir / ".data_storage/test_summaries_retriever_context") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + document1 = TextDocument( + name="Employee List", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + document2 = TextDocument( + name="Car List", + raw_data_location="somewhere", + external_metadata="", + mime_type="text/plain", + ) + + chunk1 = DocumentChunk( + text="Steve Rodger", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + chunk1_summary = TextSummary( + text="S.R.", + made_from=chunk1, + ) + chunk2 = DocumentChunk( + text="Mike Broski", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + chunk2_summary = TextSummary( + text="M.B.", + made_from=chunk2, + ) + chunk3 = DocumentChunk( + text="Christina Mayer", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document1, + contains=[], + ) + chunk3_summary = TextSummary( + text="C.M.", + made_from=chunk3, + ) + chunk4 = DocumentChunk( + text="Range Rover", + chunk_size=2, + chunk_index=0, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + chunk4_summary = TextSummary( + text="R.R.", + made_from=chunk4, + ) + chunk5 = DocumentChunk( + text="Hyundai", + chunk_size=2, + chunk_index=1, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + chunk5_summary = TextSummary( + text="H.Y.", + made_from=chunk5, + ) + chunk6 = DocumentChunk( + text="Chrysler", + chunk_size=2, + chunk_index=2, + cut_type="sentence_end", + is_part_of=document2, + contains=[], + ) + chunk6_summary = TextSummary( + text="C.H.", + made_from=chunk6, + ) + + entities = [ + chunk1_summary, + chunk2_summary, + chunk3_summary, + chunk4_summary, + chunk5_summary, + chunk6_summary, + ] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_empty(): + """Set up a clean test environment without summaries.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_summaries_retriever_context_empty") + data_directory_path = str(base_dir / ".data_storage/test_summaries_retriever_context_empty") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest.mark.asyncio +async def test_summaries_retriever_context(setup_test_environment_with_summaries): + """Integration test: verify SummariesRetriever can retrieve summary context.""" + retriever = SummariesRetriever(top_k=20) + + context = await retriever.get_context("Christina") + + assert isinstance(context, list), "Context should be a list" + assert len(context) > 0, "Context should not be empty" + assert context[0]["text"] == "C.M.", "Failed to get Christina Mayer" + + +@pytest.mark.asyncio +async def test_summaries_retriever_context_on_empty_graph(setup_test_environment_empty): + """Integration test: verify SummariesRetriever handles empty graph correctly.""" + retriever = SummariesRetriever() + + with pytest.raises(NoDataError): + await retriever.get_context("Christina Mayer") + + vector_engine = get_vector_engine() + await vector_engine.create_collection("TextSummary_text", payload_schema=TextSummary) + + context = await retriever.get_context("Christina Mayer") + assert context == [], "Returned context should be empty on an empty graph" diff --git a/cognee/tests/integration/retrieval/test_temporal_retriever.py b/cognee/tests/integration/retrieval/test_temporal_retriever.py new file mode 100644 index 000000000..8ce3b32f4 --- /dev/null +++ b/cognee/tests/integration/retrieval/test_temporal_retriever.py @@ -0,0 +1,306 @@ +import os +import pytest +import pathlib +import pytest_asyncio +import cognee + +from cognee.low_level import setup, DataPoint +from cognee.tasks.storage import add_data_points +from cognee.modules.retrieval.temporal_retriever import TemporalRetriever +from cognee.modules.engine.models.Event import Event +from cognee.modules.engine.models.Timestamp import Timestamp +from cognee.modules.engine.models.Interval import Interval + + +@pytest_asyncio.fixture +async def setup_test_environment_with_events(): + """Set up a clean test environment with temporal events.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_temporal_retriever_with_events") + data_directory_path = str(base_dir / ".data_storage/test_temporal_retriever_with_events") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + # Create timestamps for events + timestamp1 = Timestamp( + time_at=1609459200, # 2021-01-01 00:00:00 + year=2021, + month=1, + day=1, + hour=0, + minute=0, + second=0, + timestamp_str="2021-01-01T00:00:00", + ) + + timestamp2 = Timestamp( + time_at=1612137600, # 2021-02-01 00:00:00 + year=2021, + month=2, + day=1, + hour=0, + minute=0, + second=0, + timestamp_str="2021-02-01T00:00:00", + ) + + timestamp3 = Timestamp( + time_at=1614556800, # 2021-03-01 00:00:00 + year=2021, + month=3, + day=1, + hour=0, + minute=0, + second=0, + timestamp_str="2021-03-01T00:00:00", + ) + + timestamp4 = Timestamp( + time_at=1625097600, # 2021-07-01 00:00:00 + year=2021, + month=7, + day=1, + hour=0, + minute=0, + second=0, + timestamp_str="2021-07-01T00:00:00", + ) + + timestamp5 = Timestamp( + time_at=1633046400, # 2021-10-01 00:00:00 + year=2021, + month=10, + day=1, + hour=0, + minute=0, + second=0, + timestamp_str="2021-10-01T00:00:00", + ) + + # Create interval for event spanning multiple timestamps + interval1 = Interval(time_from=timestamp2, time_to=timestamp3) + + # Create events with timestamps + event1 = Event( + name="Project Alpha Launch", + description="Launched Project Alpha at the beginning of 2021", + at=timestamp1, + location="San Francisco", + ) + + event2 = Event( + name="Team Meeting", + description="Monthly team meeting discussing Q1 goals", + during=interval1, + location="New York", + ) + + event3 = Event( + name="Product Release", + description="Released new product features in July", + at=timestamp4, + location="Remote", + ) + + event4 = Event( + name="Company Retreat", + description="Annual company retreat in October", + at=timestamp5, + location="Lake Tahoe", + ) + + entities = [event1, event2, event3, event4] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_with_graph_data(): + """Set up a clean test environment with graph data (for fallback to triplets).""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_temporal_retriever_with_graph") + data_directory_path = str(base_dir / ".data_storage/test_temporal_retriever_with_graph") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + class Company(DataPoint): + name: str + description: str + + class Person(DataPoint): + name: str + description: str + works_for: Company + + company1 = Company(name="Figma", description="Figma is a company") + person1 = Person( + name="Steve Rodger", + description="This is description about Steve Rodger", + works_for=company1, + ) + + entities = [company1, person1] + + await add_data_points(entities) + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest_asyncio.fixture +async def setup_test_environment_empty(): + """Set up a clean test environment without data.""" + base_dir = pathlib.Path(__file__).parent.parent.parent.parent + system_directory_path = str(base_dir / ".cognee_system/test_temporal_retriever_empty") + data_directory_path = str(base_dir / ".data_storage/test_temporal_retriever_empty") + + cognee.config.system_root_directory(system_directory_path) + cognee.config.data_root_directory(data_directory_path) + + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + await setup() + + yield + + try: + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + except Exception: + pass + + +@pytest.mark.asyncio +async def test_temporal_retriever_context_with_time_range(setup_test_environment_with_events): + """Integration test: verify TemporalRetriever can retrieve events within time range.""" + retriever = TemporalRetriever(top_k=5) + + context = await retriever.get_context("What happened in January 2021?") + + assert isinstance(context, str), "Context should be a string" + assert len(context) > 0, "Context should not be empty" + assert "Project Alpha" in context or "Launch" in context, ( + "Should retrieve Project Alpha Launch event from January 2021" + ) + + +@pytest.mark.asyncio +async def test_temporal_retriever_context_with_single_time(setup_test_environment_with_events): + """Integration test: verify TemporalRetriever can retrieve events at specific time.""" + retriever = TemporalRetriever(top_k=5) + + context = await retriever.get_context("What happened in July 2021?") + + assert isinstance(context, str), "Context should be a string" + assert len(context) > 0, "Context should not be empty" + assert "Product Release" in context or "July" in context, ( + "Should retrieve Product Release event from July 2021" + ) + + +@pytest.mark.asyncio +async def test_temporal_retriever_context_fallback_to_triplets( + setup_test_environment_with_graph_data, +): + """Integration test: verify TemporalRetriever falls back to triplets when no time extracted.""" + retriever = TemporalRetriever(top_k=5) + + context = await retriever.get_context("Who works at Figma?") + + assert isinstance(context, str), "Context should be a string" + assert len(context) > 0, "Context should not be empty" + assert "Steve" in context or "Figma" in context, ( + "Should retrieve graph data via triplet search fallback" + ) + + +@pytest.mark.asyncio +async def test_temporal_retriever_context_empty_graph(setup_test_environment_empty): + """Integration test: verify TemporalRetriever handles empty graph correctly.""" + retriever = TemporalRetriever() + + context = await retriever.get_context("What happened?") + + assert isinstance(context, str), "Context should be a string" + assert len(context) >= 0, "Context should be a string (possibly empty)" + + +@pytest.mark.asyncio +async def test_temporal_retriever_get_completion(setup_test_environment_with_events): + """Integration test: verify TemporalRetriever can generate completions.""" + retriever = TemporalRetriever() + + completion = await retriever.get_completion("What happened in January 2021?") + + assert isinstance(completion, list), "Completion should be a list" + assert len(completion) > 0, "Completion should not be empty" + assert all(isinstance(item, str) and item.strip() for item in completion), ( + "Completion items should be non-empty strings" + ) + + +@pytest.mark.asyncio +async def test_temporal_retriever_get_completion_fallback(setup_test_environment_with_graph_data): + """Integration test: verify TemporalRetriever get_completion works with triplet fallback.""" + retriever = TemporalRetriever() + + completion = await retriever.get_completion("Who works at Figma?") + + assert isinstance(completion, list), "Completion should be a list" + assert len(completion) > 0, "Completion should not be empty" + assert all(isinstance(item, str) and item.strip() for item in completion), ( + "Completion items should be non-empty strings" + ) + + +@pytest.mark.asyncio +async def test_temporal_retriever_top_k_limit(setup_test_environment_with_events): + """Integration test: verify TemporalRetriever respects top_k parameter.""" + retriever = TemporalRetriever(top_k=2) + + context = await retriever.get_context("What happened in 2021?") + + assert isinstance(context, str), "Context should be a string" + separator_count = context.count("#####################") + assert separator_count <= 1, "Should respect top_k limit of 2 events" + + +@pytest.mark.asyncio +async def test_temporal_retriever_multiple_events(setup_test_environment_with_events): + """Integration test: verify TemporalRetriever can retrieve multiple events.""" + retriever = TemporalRetriever(top_k=10) + + context = await retriever.get_context("What events occurred in 2021?") + + assert isinstance(context, str), "Context should be a string" + assert len(context) > 0, "Context should not be empty" + + assert ( + "Project Alpha" in context + or "Team Meeting" in context + or "Product Release" in context + or "Company Retreat" in context + ), "Should retrieve at least one event from 2021" diff --git a/cognee/tests/integration/retrieval/test_triplet_retriever.py b/cognee/tests/integration/retrieval/test_triplet_retriever.py index e547b6cbe..ebe853e08 100644 --- a/cognee/tests/integration/retrieval/test_triplet_retriever.py +++ b/cognee/tests/integration/retrieval/test_triplet_retriever.py @@ -82,3 +82,38 @@ async def test_triplet_retriever_context_simple(setup_test_environment_with_trip context = await retriever.get_context("Alice") assert "Alice knows Bob" in context, "Failed to get Alice triplet" + assert isinstance(context, str), "Context should be a string" + assert len(context) > 0, "Context should not be empty" + + +@pytest.mark.asyncio +async def test_triplet_retriever_context_multiple_triplets(setup_test_environment_with_triplets): + """Integration test: verify TripletRetriever can retrieve multiple triplets.""" + retriever = TripletRetriever(top_k=5) + + context = await retriever.get_context("Bob") + + assert "Alice knows Bob" in context or "Bob works at Tech Corp" in context, ( + "Failed to get Bob-related triplets" + ) + + +@pytest.mark.asyncio +async def test_triplet_retriever_top_k_limit(setup_test_environment_with_triplets): + """Integration test: verify TripletRetriever respects top_k parameter.""" + retriever = TripletRetriever(top_k=1) + + context = await retriever.get_context("Alice") + + assert isinstance(context, str), "Context should be a string" + + +@pytest.mark.asyncio +async def test_triplet_retriever_context_empty(setup_test_environment_empty): + """Integration test: verify TripletRetriever handles empty graph correctly.""" + await setup() + + retriever = TripletRetriever() + + with pytest.raises(NoDataError): + await retriever.get_context("Alice") diff --git a/cognee/tests/unit/modules/retrieval/test_user_qa_feedback.py b/cognee/tests/integration/retrieval/test_user_qa_feedback.py similarity index 100% rename from cognee/tests/unit/modules/retrieval/test_user_qa_feedback.py rename to cognee/tests/integration/retrieval/test_user_qa_feedback.py diff --git a/cognee/tests/test_cognee_server_start.py b/cognee/tests/test_cognee_server_start.py index fece88240..a626088a3 100644 --- a/cognee/tests/test_cognee_server_start.py +++ b/cognee/tests/test_cognee_server_start.py @@ -148,8 +148,8 @@ class TestCogneeServerStart(unittest.TestCase): headers=headers, files=[("ontology_file", ("test.owl", ontology_content, "application/xml"))], data={ - "ontology_key": json.dumps([ontology_key]), - "description": json.dumps(["Test ontology"]), + "ontology_key": ontology_key, + "description": "Test ontology", }, ) self.assertEqual(ontology_response.status_code, 200) diff --git a/cognee/tests/test_dataset_delete.py b/cognee/tests/test_dataset_delete.py new file mode 100644 index 000000000..372945bdb --- /dev/null +++ b/cognee/tests/test_dataset_delete.py @@ -0,0 +1,76 @@ +import os +import asyncio +import pathlib +from uuid import UUID + +import cognee +from cognee.shared.logging_utils import setup_logging, ERROR +from cognee.modules.data.methods.delete_dataset import delete_dataset +from cognee.modules.data.methods.get_dataset import get_dataset +from cognee.modules.users.methods import get_default_user + + +async def main(): + # Set data and system directory paths + data_directory_path = str( + pathlib.Path( + os.path.join(pathlib.Path(__file__).parent, ".data_storage/test_dataset_delete") + ).resolve() + ) + cognee.config.data_root_directory(data_directory_path) + cognee_directory_path = str( + pathlib.Path( + os.path.join(pathlib.Path(__file__).parent, ".cognee_system/test_dataset_delete") + ).resolve() + ) + cognee.config.system_root_directory(cognee_directory_path) + + # Create a clean slate for cognee -- reset data and system state + print("Resetting cognee data...") + await cognee.prune.prune_data() + await cognee.prune.prune_system(metadata=True) + print("Data reset complete.\n") + + # cognee knowledge graph will be created based on this text + text = """ + Natural language processing (NLP) is an interdisciplinary + subfield of computer science and information retrieval. + """ + + # Add the text, and make it available for cognify + await cognee.add(text, "nlp_dataset") + await cognee.add("Quantum computing is the study of quantum computers.", "quantum_dataset") + + # Use LLMs and cognee to create knowledge graph + ret_val = await cognee.cognify() + user = await get_default_user() + + for val in ret_val: + dataset_id = str(val) + vector_db_path = os.path.join( + cognee_directory_path, "databases", str(user.id), dataset_id + ".lance.db" + ) + graph_db_path = os.path.join( + cognee_directory_path, "databases", str(user.id), dataset_id + ".pkl" + ) + + # Check if databases are properly created and exist before deletion + assert os.path.exists(graph_db_path), "Graph database file not found." + assert os.path.exists(vector_db_path), "Vector database file not found." + + dataset = await get_dataset(user_id=user.id, dataset_id=UUID(dataset_id)) + await delete_dataset(dataset) + + # Confirm databases have been deleted + assert not os.path.exists(graph_db_path), "Graph database file found." + assert not os.path.exists(vector_db_path), "Vector database file found." + + +if __name__ == "__main__": + logger = setup_logging(log_level=ERROR) + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + try: + loop.run_until_complete(main()) + finally: + loop.run_until_complete(loop.shutdown_asyncgens()) diff --git a/cognee/tests/test_search_db.py b/cognee/tests/test_search_db.py index ba150f813..0916be322 100644 --- a/cognee/tests/test_search_db.py +++ b/cognee/tests/test_search_db.py @@ -1,5 +1,10 @@ import pathlib import os +import asyncio +import pytest +import pytest_asyncio +from collections import Counter + import cognee from cognee.infrastructure.databases.graph import get_graph_engine from cognee.infrastructure.databases.vector import get_vector_engine @@ -13,127 +18,172 @@ from cognee.modules.retrieval.graph_completion_cot_retriever import GraphComplet from cognee.modules.retrieval.graph_summary_completion_retriever import ( GraphSummaryCompletionRetriever, ) +from cognee.modules.retrieval.chunks_retriever import ChunksRetriever +from cognee.modules.retrieval.summaries_retriever import SummariesRetriever +from cognee.modules.retrieval.completion_retriever import CompletionRetriever +from cognee.modules.retrieval.temporal_retriever import TemporalRetriever from cognee.modules.retrieval.triplet_retriever import TripletRetriever from cognee.shared.logging_utils import get_logger from cognee.modules.search.types import SearchType from cognee.modules.users.methods import get_default_user -from collections import Counter logger = get_logger() -async def main(): - # This test runs for multiple db settings, to run this locally set the corresponding db envs +async def _reset_engines_and_prune() -> None: + """Reset db engine caches and prune data/system. + + Kept intentionally identical to the inlined setup logic to avoid event loop issues when + using deployed databases (Neo4j, PostgreSQL) and to ensure fresh instances per run. + """ + # Dispose of existing engines and clear caches to ensure fresh instances for each test + try: + from cognee.infrastructure.databases.vector import get_vector_engine + + vector_engine = get_vector_engine() + # Dispose SQLAlchemy engine connection pool if it exists + if hasattr(vector_engine, "engine") and hasattr(vector_engine.engine, "dispose"): + await vector_engine.engine.dispose(close=True) + except Exception: + # Engine might not exist yet + pass + + from cognee.infrastructure.databases.graph.get_graph_engine import create_graph_engine + from cognee.infrastructure.databases.vector.create_vector_engine import create_vector_engine + from cognee.infrastructure.databases.relational.create_relational_engine import ( + create_relational_engine, + ) + + create_graph_engine.cache_clear() + create_vector_engine.cache_clear() + create_relational_engine.cache_clear() + await cognee.prune.prune_data() await cognee.prune.prune_system(metadata=True) - dataset_name = "test_dataset" +async def _seed_default_dataset(dataset_name: str) -> dict: + """Add the shared test dataset contents and run cognify (same steps/order as before).""" text_1 = """Germany is located in europe right next to the Netherlands""" + + logger.info(f"Adding text data to dataset: {dataset_name}") await cognee.add(text_1, dataset_name) explanation_file_path_quantum = os.path.join( pathlib.Path(__file__).parent, "test_data/Quantum_computers.txt" ) + logger.info(f"Adding file data to dataset: {dataset_name}") await cognee.add([explanation_file_path_quantum], dataset_name) + logger.info(f"Running cognify on dataset: {dataset_name}") await cognee.cognify([dataset_name]) + return { + "dataset_name": dataset_name, + "text_1": text_1, + "explanation_file_path_quantum": explanation_file_path_quantum, + } + + +@pytest.fixture(scope="session") +def event_loop(): + """Use a single asyncio event loop for this test module. + + This helps avoid "Future attached to a different loop" when running multiple async + tests that share clients/engines. + """ + loop = asyncio.new_event_loop() + try: + yield loop + finally: + loop.close() + + +async def setup_test_environment(): + """Helper function to set up test environment with data, cognify, and triplet embeddings.""" + # This test runs for multiple db settings, to run this locally set the corresponding db envs + + dataset_name = "test_dataset" + logger.info("Starting test setup: pruning data and system") + await _reset_engines_and_prune() + state = await _seed_default_dataset(dataset_name=dataset_name) + user = await get_default_user() from cognee.memify_pipelines.create_triplet_embeddings import create_triplet_embeddings + logger.info("Creating triplet embeddings") await create_triplet_embeddings(user=user, dataset=dataset_name, triplets_batch_size=5) + # Check if Triplet_text collection was created + vector_engine = get_vector_engine() + has_collection = await vector_engine.has_collection(collection_name="Triplet_text") + logger.info(f"Triplet_text collection exists after creation: {has_collection}") + + if has_collection: + collection = await vector_engine.get_collection("Triplet_text") + count = await collection.count_rows() if hasattr(collection, "count_rows") else "unknown" + logger.info(f"Triplet_text collection row count: {count}") + + return state + + +async def setup_test_environment_for_feedback(): + """Helper function to set up test environment for feedback weight calculation test.""" + dataset_name = "test_dataset" + await _reset_engines_and_prune() + return await _seed_default_dataset(dataset_name=dataset_name) + + +@pytest_asyncio.fixture(scope="session") +async def e2e_state(): + """Compute E2E artifacts once; tests only assert. + + This avoids repeating expensive setup and LLM calls across multiple tests. + """ + await setup_test_environment() + + # --- Graph/vector engine consistency --- graph_engine = await get_graph_engine() - nodes, edges = await graph_engine.get_graph_data() + _nodes, edges = await graph_engine.get_graph_data() vector_engine = get_vector_engine() collection = await vector_engine.search( - query_text="Test", limit=None, collection_name="Triplet_text" + collection_name="Triplet_text", query_text="Test", limit=None ) - assert len(edges) == len(collection), ( - f"Expected {len(edges)} edges but got {len(collection)} in Triplet_text collection" - ) + # --- Retriever contexts --- + query = "Next to which country is Germany located?" - context_gk = await GraphCompletionRetriever().get_context( - query="Next to which country is Germany located?" - ) - context_gk_cot = await GraphCompletionCotRetriever().get_context( - query="Next to which country is Germany located?" - ) - context_gk_ext = await GraphCompletionContextExtensionRetriever().get_context( - query="Next to which country is Germany located?" - ) - context_gk_sum = await GraphSummaryCompletionRetriever().get_context( - query="Next to which country is Germany located?" - ) - context_triplet = await TripletRetriever().get_context( - query="Next to which country is Germany located?" - ) + contexts = { + "graph_completion": await GraphCompletionRetriever().get_context(query=query), + "graph_completion_cot": await GraphCompletionCotRetriever().get_context(query=query), + "graph_completion_context_extension": await GraphCompletionContextExtensionRetriever().get_context( + query=query + ), + "graph_summary_completion": await GraphSummaryCompletionRetriever().get_context( + query=query + ), + "chunks": await ChunksRetriever(top_k=5).get_context(query=query), + "summaries": await SummariesRetriever(top_k=5).get_context(query=query), + "rag_completion": await CompletionRetriever(top_k=3).get_context(query=query), + "temporal": await TemporalRetriever(top_k=5).get_context(query=query), + "triplet": await TripletRetriever().get_context(query=query), + } - for name, context in [ - ("GraphCompletionRetriever", context_gk), - ("GraphCompletionCotRetriever", context_gk_cot), - ("GraphCompletionContextExtensionRetriever", context_gk_ext), - ("GraphSummaryCompletionRetriever", context_gk_sum), - ]: - assert isinstance(context, list), f"{name}: Context should be a list" - assert len(context) > 0, f"{name}: Context should not be empty" - - context_text = await resolve_edges_to_text(context) - lower = context_text.lower() - assert "germany" in lower or "netherlands" in lower, ( - f"{name}: Context did not contain 'germany' or 'netherlands'; got: {context!r}" - ) - - assert isinstance(context_triplet, str), "TripletRetriever: Context should be a string" - assert len(context_triplet) > 0, "TripletRetriever: Context should not be empty" - lower_triplet = context_triplet.lower() - assert "germany" in lower_triplet or "netherlands" in lower_triplet, ( - f"TripletRetriever: Context did not contain 'germany' or 'netherlands'; got: {context_triplet!r}" - ) - - triplets_gk = await GraphCompletionRetriever().get_triplets( - query="Next to which country is Germany located?" - ) - triplets_gk_cot = await GraphCompletionCotRetriever().get_triplets( - query="Next to which country is Germany located?" - ) - triplets_gk_ext = await GraphCompletionContextExtensionRetriever().get_triplets( - query="Next to which country is Germany located?" - ) - triplets_gk_sum = await GraphSummaryCompletionRetriever().get_triplets( - query="Next to which country is Germany located?" - ) - - for name, triplets in [ - ("GraphCompletionRetriever", triplets_gk), - ("GraphCompletionCotRetriever", triplets_gk_cot), - ("GraphCompletionContextExtensionRetriever", triplets_gk_ext), - ("GraphSummaryCompletionRetriever", triplets_gk_sum), - ]: - assert isinstance(triplets, list), f"{name}: Triplets should be a list" - assert triplets, f"{name}: Triplets list should not be empty" - for edge in triplets: - assert isinstance(edge, Edge), f"{name}: Elements should be Edge instances" - distance = edge.attributes.get("vector_distance") - node1_distance = edge.node1.attributes.get("vector_distance") - node2_distance = edge.node2.attributes.get("vector_distance") - assert isinstance(distance, float), ( - f"{name}: vector_distance should be float, got {type(distance)}" - ) - assert 0 <= distance <= 1, ( - f"{name}: edge vector_distance {distance} out of [0,1], this shouldn't happen" - ) - assert 0 <= node1_distance <= 1, ( - f"{name}: node_1 vector_distance {distance} out of [0,1], this shouldn't happen" - ) - assert 0 <= node2_distance <= 1, ( - f"{name}: node_2 vector_distance {distance} out of [0,1], this shouldn't happen" - ) + # --- Retriever triplets + vector distance validation --- + triplets = { + "graph_completion": await GraphCompletionRetriever().get_triplets(query=query), + "graph_completion_cot": await GraphCompletionCotRetriever().get_triplets(query=query), + "graph_completion_context_extension": await GraphCompletionContextExtensionRetriever().get_triplets( + query=query + ), + "graph_summary_completion": await GraphSummaryCompletionRetriever().get_triplets( + query=query + ), + } + # --- Search operations + graph side effects --- completion_gk = await cognee.search( query_type=SearchType.GRAPH_COMPLETION, query_text="Where is germany located, next to which country?", @@ -164,6 +214,26 @@ async def main(): query_text="Next to which country is Germany located?", save_interaction=True, ) + completion_chunks = await cognee.search( + query_type=SearchType.CHUNKS, + query_text="Germany", + save_interaction=False, + ) + completion_summaries = await cognee.search( + query_type=SearchType.SUMMARIES, + query_text="Germany", + save_interaction=False, + ) + completion_rag = await cognee.search( + query_type=SearchType.RAG_COMPLETION, + query_text="Next to which country is Germany located?", + save_interaction=False, + ) + completion_temporal = await cognee.search( + query_type=SearchType.TEMPORAL, + query_text="Next to which country is Germany located?", + save_interaction=False, + ) await cognee.search( query_type=SearchType.FEEDBACK, @@ -171,134 +241,217 @@ async def main(): last_k=1, ) - for name, search_results in [ - ("GRAPH_COMPLETION", completion_gk), - ("GRAPH_COMPLETION_COT", completion_cot), - ("GRAPH_COMPLETION_CONTEXT_EXTENSION", completion_ext), - ("GRAPH_SUMMARY_COMPLETION", completion_sum), - ("TRIPLET_COMPLETION", completion_triplet), - ]: - assert isinstance(search_results, list), f"{name}: should return a list" - assert len(search_results) == 1, ( - f"{name}: expected single-element list, got {len(search_results)}" - ) + # Snapshot after all E2E operations above (used by assertion-only tests). + graph_snapshot = await (await get_graph_engine()).get_graph_data() - from cognee.context_global_variables import backend_access_control_enabled + return { + "graph_edges": edges, + "triplet_collection": collection, + "vector_collection_edges_count": len(collection), + "graph_edges_count": len(edges), + "contexts": contexts, + "triplets": triplets, + "search_results": { + "graph_completion": completion_gk, + "graph_completion_cot": completion_cot, + "graph_completion_context_extension": completion_ext, + "graph_summary_completion": completion_sum, + "triplet_completion": completion_triplet, + "chunks": completion_chunks, + "summaries": completion_summaries, + "rag_completion": completion_rag, + "temporal": completion_temporal, + }, + "graph_snapshot": graph_snapshot, + } - if backend_access_control_enabled(): - text = search_results[0]["search_result"][0] - else: - text = search_results[0] - assert isinstance(text, str), f"{name}: element should be a string" - assert text.strip(), f"{name}: string should not be empty" - assert "netherlands" in text.lower(), ( - f"{name}: expected 'netherlands' in result, got: {text!r}" - ) - graph_engine = await get_graph_engine() - graph = await graph_engine.get_graph_data() - - type_counts = Counter(node_data[1].get("type", {}) for node_data in graph[0]) - - edge_type_counts = Counter(edge_type[2] for edge_type in graph[1]) - - # Assert there are exactly 4 CogneeUserInteraction nodes. - assert type_counts.get("CogneeUserInteraction", 0) == 4, ( - f"Expected exactly four CogneeUserInteraction nodes, but found {type_counts.get('CogneeUserInteraction', 0)}" - ) - - # Assert there is exactly two CogneeUserFeedback nodes. - assert type_counts.get("CogneeUserFeedback", 0) == 2, ( - f"Expected exactly two CogneeUserFeedback nodes, but found {type_counts.get('CogneeUserFeedback', 0)}" - ) - - # Assert there is exactly two NodeSet. - assert type_counts.get("NodeSet", 0) == 2, ( - f"Expected exactly two NodeSet nodes, but found {type_counts.get('NodeSet', 0)}" - ) - - # Assert that there are at least 10 'used_graph_element_to_answer' edges. - assert edge_type_counts.get("used_graph_element_to_answer", 0) >= 10, ( - f"Expected at least ten 'used_graph_element_to_answer' edges, but found {edge_type_counts.get('used_graph_element_to_answer', 0)}" - ) - - # Assert that there are exactly 2 'gives_feedback_to' edges. - assert edge_type_counts.get("gives_feedback_to", 0) == 2, ( - f"Expected exactly two 'gives_feedback_to' edges, but found {edge_type_counts.get('gives_feedback_to', 0)}" - ) - - # Assert that there are at least 6 'belongs_to_set' edges. - assert edge_type_counts.get("belongs_to_set", 0) == 6, ( - f"Expected at least six 'belongs_to_set' edges, but found {edge_type_counts.get('belongs_to_set', 0)}" - ) - - nodes = graph[0] - - required_fields_user_interaction = {"question", "answer", "context"} - required_fields_feedback = {"feedback", "sentiment"} - - for node_id, data in nodes: - if data.get("type") == "CogneeUserInteraction": - assert required_fields_user_interaction.issubset(data.keys()), ( - f"Node {node_id} is missing fields: {required_fields_user_interaction - set(data.keys())}" - ) - - for field in required_fields_user_interaction: - value = data[field] - assert isinstance(value, str) and value.strip(), ( - f"Node {node_id} has invalid value for '{field}': {value!r}" - ) - - if data.get("type") == "CogneeUserFeedback": - assert required_fields_feedback.issubset(data.keys()), ( - f"Node {node_id} is missing fields: {required_fields_feedback - set(data.keys())}" - ) - - for field in required_fields_feedback: - value = data[field] - assert isinstance(value, str) and value.strip(), ( - f"Node {node_id} has invalid value for '{field}': {value!r}" - ) - - await cognee.prune.prune_data() - await cognee.prune.prune_system(metadata=True) - - await cognee.add(text_1, dataset_name) - - await cognee.add([text], dataset_name) - - await cognee.cognify([dataset_name]) +@pytest_asyncio.fixture(scope="session") +async def feedback_state(): + """Feedback-weight scenario computed once (fresh environment).""" + await setup_test_environment_for_feedback() await cognee.search( query_type=SearchType.GRAPH_COMPLETION, query_text="Next to which country is Germany located?", save_interaction=True, ) - await cognee.search( query_type=SearchType.FEEDBACK, query_text="This was the best answer I've ever seen", last_k=1, ) - await cognee.search( query_type=SearchType.FEEDBACK, query_text="Wow the correctness of this answer blows my mind", last_k=1, ) + graph_engine = await get_graph_engine() graph = await graph_engine.get_graph_data() + return {"graph_snapshot": graph} - edges = graph[1] - for from_node, to_node, relationship_name, properties in edges: +@pytest.mark.asyncio +async def test_e2e_graph_vector_consistency(e2e_state): + """Graph and vector stores contain the same triplet edges.""" + assert e2e_state["graph_edges_count"] == e2e_state["vector_collection_edges_count"] + + +@pytest.mark.asyncio +async def test_e2e_retriever_contexts(e2e_state): + """All retrievers return non-empty, well-typed contexts.""" + contexts = e2e_state["contexts"] + + for name in [ + "graph_completion", + "graph_completion_cot", + "graph_completion_context_extension", + "graph_summary_completion", + ]: + ctx = contexts[name] + assert isinstance(ctx, list), f"{name}: Context should be a list" + assert ctx, f"{name}: Context should not be empty" + ctx_text = await resolve_edges_to_text(ctx) + lower = ctx_text.lower() + assert "germany" in lower or "netherlands" in lower, ( + f"{name}: Context did not contain 'germany' or 'netherlands'; got: {ctx!r}" + ) + + triplet_ctx = contexts["triplet"] + assert isinstance(triplet_ctx, str), "triplet: Context should be a string" + assert triplet_ctx.strip(), "triplet: Context should not be empty" + + chunks_ctx = contexts["chunks"] + assert isinstance(chunks_ctx, list), "chunks: Context should be a list" + assert chunks_ctx, "chunks: Context should not be empty" + chunks_text = "\n".join(str(item.get("text", "")) for item in chunks_ctx).lower() + assert "germany" in chunks_text or "netherlands" in chunks_text + + summaries_ctx = contexts["summaries"] + assert isinstance(summaries_ctx, list), "summaries: Context should be a list" + assert summaries_ctx, "summaries: Context should not be empty" + assert any(str(item.get("text", "")).strip() for item in summaries_ctx) + + rag_ctx = contexts["rag_completion"] + assert isinstance(rag_ctx, str), "rag_completion: Context should be a string" + assert rag_ctx.strip(), "rag_completion: Context should not be empty" + + temporal_ctx = contexts["temporal"] + assert isinstance(temporal_ctx, str), "temporal: Context should be a string" + assert temporal_ctx.strip(), "temporal: Context should not be empty" + + +@pytest.mark.asyncio +async def test_e2e_retriever_triplets_have_vector_distances(e2e_state): + """Graph retriever triplets include sane vector_distance metadata.""" + for name, triplets in e2e_state["triplets"].items(): + assert isinstance(triplets, list), f"{name}: Triplets should be a list" + assert triplets, f"{name}: Triplets list should not be empty" + for edge in triplets: + assert isinstance(edge, Edge), f"{name}: Elements should be Edge instances" + distance = edge.attributes.get("vector_distance") + node1_distance = edge.node1.attributes.get("vector_distance") + node2_distance = edge.node2.attributes.get("vector_distance") + assert isinstance(distance, float), f"{name}: vector_distance should be float" + assert 0 <= distance <= 1 + assert 0 <= node1_distance <= 1 + assert 0 <= node2_distance <= 1 + + +@pytest.mark.asyncio +async def test_e2e_search_results_and_wrappers(e2e_state): + """Search returns expected shapes across search types and access modes.""" + from cognee.context_global_variables import backend_access_control_enabled + + sr = e2e_state["search_results"] + + # Completion-like search types: validate wrapper + content + for name in [ + "graph_completion", + "graph_completion_cot", + "graph_completion_context_extension", + "graph_summary_completion", + "triplet_completion", + "rag_completion", + "temporal", + ]: + search_results = sr[name] + assert isinstance(search_results, list), f"{name}: should return a list" + assert len(search_results) == 1, f"{name}: expected single-element list" + + if backend_access_control_enabled(): + wrapper = search_results[0] + assert isinstance(wrapper, dict), ( + f"{name}: expected wrapper dict in access control mode" + ) + assert wrapper.get("dataset_id"), f"{name}: missing dataset_id in wrapper" + assert wrapper.get("dataset_name") == "test_dataset" + assert "graphs" in wrapper + text = wrapper["search_result"][0] + else: + text = search_results[0] + + assert isinstance(text, str) and text.strip() + assert "netherlands" in text.lower() + + # Non-LLM search types: CHUNKS / SUMMARIES validate payload list + text + for name in ["chunks", "summaries"]: + search_results = sr[name] + assert isinstance(search_results, list), f"{name}: should return a list" + assert search_results, f"{name}: should not be empty" + + first = search_results[0] + assert isinstance(first, dict), f"{name}: expected dict entries" + + payloads = search_results + if "search_result" in first and "text" not in first: + payloads = (first.get("search_result") or [None])[0] + + assert isinstance(payloads, list) and payloads + assert isinstance(payloads[0], dict) + assert str(payloads[0].get("text", "")).strip() + + +@pytest.mark.asyncio +async def test_e2e_graph_side_effects_and_node_fields(e2e_state): + """Search interactions create expected graph nodes/edges and required fields.""" + graph = e2e_state["graph_snapshot"] + nodes, edges = graph + + type_counts = Counter(node_data[1].get("type", {}) for node_data in nodes) + edge_type_counts = Counter(edge_type[2] for edge_type in edges) + + assert type_counts.get("CogneeUserInteraction", 0) == 4 + assert type_counts.get("CogneeUserFeedback", 0) == 2 + assert type_counts.get("NodeSet", 0) == 2 + assert edge_type_counts.get("used_graph_element_to_answer", 0) >= 10 + assert edge_type_counts.get("gives_feedback_to", 0) == 2 + assert edge_type_counts.get("belongs_to_set", 0) >= 6 + + required_fields_user_interaction = {"question", "answer", "context"} + required_fields_feedback = {"feedback", "sentiment"} + + for node_id, data in nodes: + if data.get("type") == "CogneeUserInteraction": + assert required_fields_user_interaction.issubset(data.keys()) + for field in required_fields_user_interaction: + value = data[field] + assert isinstance(value, str) and value.strip() + + if data.get("type") == "CogneeUserFeedback": + assert required_fields_feedback.issubset(data.keys()) + for field in required_fields_feedback: + value = data[field] + assert isinstance(value, str) and value.strip() + + +@pytest.mark.asyncio +async def test_e2e_feedback_weight_calculation(feedback_state): + """Positive feedback increases used_graph_element_to_answer feedback_weight.""" + _nodes, edges = feedback_state["graph_snapshot"] + for _from_node, _to_node, relationship_name, properties in edges: if relationship_name == "used_graph_element_to_answer": assert properties["feedback_weight"] >= 6, ( "Feedback weight calculation is not correct, it should be more then 6." ) - - -if __name__ == "__main__": - import asyncio - - asyncio.run(main()) diff --git a/cognee/tests/unit/api/test_ontology_endpoint.py b/cognee/tests/unit/api/test_ontology_endpoint.py index af3a4d90e..e072ceda8 100644 --- a/cognee/tests/unit/api/test_ontology_endpoint.py +++ b/cognee/tests/unit/api/test_ontology_endpoint.py @@ -1,17 +1,28 @@ import pytest import uuid from fastapi.testclient import TestClient -from unittest.mock import patch, Mock, AsyncMock +from unittest.mock import Mock from types import SimpleNamespace -import importlib from cognee.api.client import app +from cognee.modules.users.methods import get_authenticated_user -gau_mod = importlib.import_module("cognee.modules.users.methods.get_authenticated_user") + +@pytest.fixture(scope="session") +def test_client(): + # Keep a single TestClient (and event loop) for the whole module. + # Re-creating TestClient repeatedly can break async DB connections (asyncpg loop mismatch). + with TestClient(app) as c: + yield c @pytest.fixture -def client(): - return TestClient(app) +def client(test_client, mock_default_user): + async def override_get_authenticated_user(): + return mock_default_user + + app.dependency_overrides[get_authenticated_user] = override_get_authenticated_user + yield test_client + app.dependency_overrides.pop(get_authenticated_user, None) @pytest.fixture @@ -32,12 +43,8 @@ def mock_default_user(): ) -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_upload_ontology_success(mock_get_default_user, client, mock_default_user): +def test_upload_ontology_success(client): """Test successful ontology upload""" - import json - - mock_get_default_user.return_value = mock_default_user ontology_content = ( b"" ) @@ -46,7 +53,7 @@ def test_upload_ontology_success(mock_get_default_user, client, mock_default_use response = client.post( "/api/v1/ontologies", files=[("ontology_file", ("test.owl", ontology_content, "application/xml"))], - data={"ontology_key": json.dumps([unique_key]), "description": json.dumps(["Test"])}, + data={"ontology_key": unique_key, "description": "Test"}, ) assert response.status_code == 200 @@ -55,10 +62,8 @@ def test_upload_ontology_success(mock_get_default_user, client, mock_default_use assert "uploaded_at" in data["uploaded_ontologies"][0] -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_upload_ontology_invalid_file(mock_get_default_user, client, mock_default_user): +def test_upload_ontology_invalid_file(client): """Test 400 response for non-.owl files""" - mock_get_default_user.return_value = mock_default_user unique_key = f"test_ontology_{uuid.uuid4().hex[:8]}" response = client.post( "/api/v1/ontologies", @@ -68,14 +73,10 @@ def test_upload_ontology_invalid_file(mock_get_default_user, client, mock_defaul assert response.status_code == 400 -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_upload_ontology_missing_data(mock_get_default_user, client, mock_default_user): +def test_upload_ontology_missing_data(client): """Test 400 response for missing file or key""" - import json - - mock_get_default_user.return_value = mock_default_user # Missing file - response = client.post("/api/v1/ontologies", data={"ontology_key": json.dumps(["test"])}) + response = client.post("/api/v1/ontologies", data={"ontology_key": "test"}) assert response.status_code == 400 # Missing key @@ -85,34 +86,25 @@ def test_upload_ontology_missing_data(mock_get_default_user, client, mock_defaul assert response.status_code == 400 -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_upload_ontology_unauthorized(mock_get_default_user, client, mock_default_user): - """Test behavior when default user is provided (no explicit authentication)""" - import json - +def test_upload_ontology_without_auth_header(client): + """Test behavior when no explicit authentication header is provided.""" unique_key = f"test_ontology_{uuid.uuid4().hex[:8]}" - mock_get_default_user.return_value = mock_default_user response = client.post( "/api/v1/ontologies", files=[("ontology_file", ("test.owl", b"", "application/xml"))], - data={"ontology_key": json.dumps([unique_key])}, + data={"ontology_key": unique_key}, ) - # The current system provides a default user when no explicit authentication is given - # This test verifies the system works with conditional authentication assert response.status_code == 200 data = response.json() assert data["uploaded_ontologies"][0]["ontology_key"] == unique_key assert "uploaded_at" in data["uploaded_ontologies"][0] -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_upload_multiple_ontologies(mock_get_default_user, client, mock_default_user): - """Test uploading multiple ontology files in single request""" +def test_upload_multiple_ontologies_in_single_request_is_rejected(client): + """Uploading multiple ontology files in a single request should fail.""" import io - mock_get_default_user.return_value = mock_default_user - # Create mock files file1_content = b"" file2_content = b"" @@ -120,45 +112,34 @@ def test_upload_multiple_ontologies(mock_get_default_user, client, mock_default_ ("ontology_file", ("vehicles.owl", io.BytesIO(file1_content), "application/xml")), ("ontology_file", ("manufacturers.owl", io.BytesIO(file2_content), "application/xml")), ] - data = { - "ontology_key": '["vehicles", "manufacturers"]', - "descriptions": '["Base vehicles", "Car manufacturers"]', - } + data = {"ontology_key": "vehicles", "description": "Base vehicles"} response = client.post("/api/v1/ontologies", files=files, data=data) - assert response.status_code == 200 - result = response.json() - assert "uploaded_ontologies" in result - assert len(result["uploaded_ontologies"]) == 2 - assert result["uploaded_ontologies"][0]["ontology_key"] == "vehicles" - assert result["uploaded_ontologies"][1]["ontology_key"] == "manufacturers" + assert response.status_code == 400 + assert "Only one ontology_file is allowed" in response.json()["error"] -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_upload_endpoint_accepts_arrays(mock_get_default_user, client, mock_default_user): - """Test that upload endpoint accepts array parameters""" +def test_upload_endpoint_rejects_array_style_fields(client): + """Array-style form values should be rejected (no backwards compatibility).""" import io import json - mock_get_default_user.return_value = mock_default_user file_content = b"" files = [("ontology_file", ("single.owl", io.BytesIO(file_content), "application/xml"))] data = { "ontology_key": json.dumps(["single_key"]), - "descriptions": json.dumps(["Single ontology"]), + "description": json.dumps(["Single ontology"]), } response = client.post("/api/v1/ontologies", files=files, data=data) - assert response.status_code == 200 - result = response.json() - assert result["uploaded_ontologies"][0]["ontology_key"] == "single_key" + assert response.status_code == 400 + assert "ontology_key must be a string" in response.json()["error"] -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_cognify_with_multiple_ontologies(mock_get_default_user, client, mock_default_user): +def test_cognify_with_multiple_ontologies(client): """Test cognify endpoint accepts multiple ontology keys""" payload = { "datasets": ["test_dataset"], @@ -172,14 +153,11 @@ def test_cognify_with_multiple_ontologies(mock_get_default_user, client, mock_de assert response.status_code in [200, 400, 409] # May fail for other reasons, not type -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_complete_multifile_workflow(mock_get_default_user, client, mock_default_user): - """Test complete workflow: upload multiple ontologies โ†’ cognify with multiple keys""" +def test_complete_multifile_workflow(client): + """Test workflow: upload ontologies one-by-one โ†’ cognify with multiple keys""" import io - import json - mock_get_default_user.return_value = mock_default_user - # Step 1: Upload multiple ontologies + # Step 1: Upload two ontologies (one-by-one) file1_content = b""" @@ -192,17 +170,21 @@ def test_complete_multifile_workflow(mock_get_default_user, client, mock_default """ - files = [ - ("ontology_file", ("vehicles.owl", io.BytesIO(file1_content), "application/xml")), - ("ontology_file", ("manufacturers.owl", io.BytesIO(file2_content), "application/xml")), - ] - data = { - "ontology_key": json.dumps(["vehicles", "manufacturers"]), - "descriptions": json.dumps(["Vehicle ontology", "Manufacturer ontology"]), - } + upload_response_1 = client.post( + "/api/v1/ontologies", + files=[("ontology_file", ("vehicles.owl", io.BytesIO(file1_content), "application/xml"))], + data={"ontology_key": "vehicles", "description": "Vehicle ontology"}, + ) + assert upload_response_1.status_code == 200 - upload_response = client.post("/api/v1/ontologies", files=files, data=data) - assert upload_response.status_code == 200 + upload_response_2 = client.post( + "/api/v1/ontologies", + files=[ + ("ontology_file", ("manufacturers.owl", io.BytesIO(file2_content), "application/xml")) + ], + data={"ontology_key": "manufacturers", "description": "Manufacturer ontology"}, + ) + assert upload_response_2.status_code == 200 # Step 2: Verify ontologies are listed list_response = client.get("/api/v1/ontologies") @@ -223,44 +205,42 @@ def test_complete_multifile_workflow(mock_get_default_user, client, mock_default assert cognify_response.status_code != 400 # Not a validation error -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_multifile_error_handling(mock_get_default_user, client, mock_default_user): - """Test error handling for invalid multifile uploads""" +def test_upload_error_handling(client): + """Test error handling for invalid uploads (single-file endpoint).""" import io import json - # Test mismatched array lengths + # Array-style key should be rejected file_content = b"" files = [("ontology_file", ("test.owl", io.BytesIO(file_content), "application/xml"))] data = { - "ontology_key": json.dumps(["key1", "key2"]), # 2 keys, 1 file - "descriptions": json.dumps(["desc1"]), + "ontology_key": json.dumps(["key1", "key2"]), + "description": "desc1", } response = client.post("/api/v1/ontologies", files=files, data=data) assert response.status_code == 400 - assert "Number of keys must match number of files" in response.json()["error"] + assert "ontology_key must be a string" in response.json()["error"] - # Test duplicate keys - files = [ - ("ontology_file", ("test1.owl", io.BytesIO(file_content), "application/xml")), - ("ontology_file", ("test2.owl", io.BytesIO(file_content), "application/xml")), - ] - data = { - "ontology_key": json.dumps(["duplicate", "duplicate"]), - "descriptions": json.dumps(["desc1", "desc2"]), - } + # Duplicate key should be rejected + response_1 = client.post( + "/api/v1/ontologies", + files=[("ontology_file", ("test1.owl", io.BytesIO(file_content), "application/xml"))], + data={"ontology_key": "duplicate", "description": "desc1"}, + ) + assert response_1.status_code == 200 - response = client.post("/api/v1/ontologies", files=files, data=data) - assert response.status_code == 400 - assert "Duplicate ontology keys not allowed" in response.json()["error"] + response_2 = client.post( + "/api/v1/ontologies", + files=[("ontology_file", ("test2.owl", io.BytesIO(file_content), "application/xml"))], + data={"ontology_key": "duplicate", "description": "desc2"}, + ) + assert response_2.status_code == 400 + assert "already exists" in response_2.json()["error"] -@patch.object(gau_mod, "get_default_user", new_callable=AsyncMock) -def test_cognify_missing_ontology_key(mock_get_default_user, client, mock_default_user): +def test_cognify_missing_ontology_key(client): """Test cognify with non-existent ontology key""" - mock_get_default_user.return_value = mock_default_user - payload = { "datasets": ["test_dataset"], "ontology_key": ["nonexistent_key"], diff --git a/cognee/tests/unit/eval_framework/benchmark_adapters_test.py b/cognee/tests/unit/eval_framework/benchmark_adapters_test.py index 70ec43cf8..b18012594 100644 --- a/cognee/tests/unit/eval_framework/benchmark_adapters_test.py +++ b/cognee/tests/unit/eval_framework/benchmark_adapters_test.py @@ -11,6 +11,22 @@ MOCK_JSONL_DATA = """\ {"id": "2", "question": "What is ML?", "answer": "Machine Learning", "paragraphs": [{"paragraph_text": "ML is a subset of AI."}]} """ +MOCK_HOTPOT_CORPUS = [ + { + "_id": "1", + "question": "Next to which country is Germany located?", + "answer": "Netherlands", + # HotpotQA uses "level"; TwoWikiMultiHop uses "type". + "level": "easy", + "type": "comparison", + "context": [ + ["Germany", ["Germany is in Europe."]], + ["Netherlands", ["The Netherlands borders Germany."]], + ], + "supporting_facts": [["Netherlands", 0]], + } +] + ADAPTER_CLASSES = [ HotpotQAAdapter, @@ -35,6 +51,11 @@ def test_adapter_can_instantiate_and_load(AdapterClass): adapter = AdapterClass() result = adapter.load_corpus() + elif AdapterClass in (HotpotQAAdapter, TwoWikiMultihopAdapter): + with patch.object(AdapterClass, "_get_raw_corpus", return_value=MOCK_HOTPOT_CORPUS): + adapter = AdapterClass() + result = adapter.load_corpus() + else: adapter = AdapterClass() result = adapter.load_corpus() @@ -64,6 +85,10 @@ def test_adapter_returns_some_content(AdapterClass): ): adapter = AdapterClass() corpus_list, qa_pairs = adapter.load_corpus(limit=limit) + elif AdapterClass in (HotpotQAAdapter, TwoWikiMultihopAdapter): + with patch.object(AdapterClass, "_get_raw_corpus", return_value=MOCK_HOTPOT_CORPUS): + adapter = AdapterClass() + corpus_list, qa_pairs = adapter.load_corpus(limit=limit) else: adapter = AdapterClass() corpus_list, qa_pairs = adapter.load_corpus(limit=limit) diff --git a/cognee/tests/unit/eval_framework/corpus_builder_test.py b/cognee/tests/unit/eval_framework/corpus_builder_test.py index 14136bea5..53f886b58 100644 --- a/cognee/tests/unit/eval_framework/corpus_builder_test.py +++ b/cognee/tests/unit/eval_framework/corpus_builder_test.py @@ -2,15 +2,38 @@ import pytest from cognee.eval_framework.corpus_builder.corpus_builder_executor import CorpusBuilderExecutor from cognee.infrastructure.databases.graph import get_graph_engine from unittest.mock import AsyncMock, patch +from cognee.eval_framework.benchmark_adapters.hotpot_qa_adapter import HotpotQAAdapter benchmark_options = ["HotPotQA", "Dummy", "TwoWikiMultiHop"] +MOCK_HOTPOT_CORPUS = [ + { + "_id": "1", + "question": "Next to which country is Germany located?", + "answer": "Netherlands", + # HotpotQA uses "level"; TwoWikiMultiHop uses "type". + "level": "easy", + "type": "comparison", + "context": [ + ["Germany", ["Germany is in Europe."]], + ["Netherlands", ["The Netherlands borders Germany."]], + ], + "supporting_facts": [["Netherlands", 0]], + } +] + @pytest.mark.parametrize("benchmark", benchmark_options) def test_corpus_builder_load_corpus(benchmark): limit = 2 - corpus_builder = CorpusBuilderExecutor(benchmark, "Default") - raw_corpus, questions = corpus_builder.load_corpus(limit=limit) + if benchmark in ("HotPotQA", "TwoWikiMultiHop"): + with patch.object(HotpotQAAdapter, "_get_raw_corpus", return_value=MOCK_HOTPOT_CORPUS): + corpus_builder = CorpusBuilderExecutor(benchmark, "Default") + raw_corpus, questions = corpus_builder.load_corpus(limit=limit) + else: + corpus_builder = CorpusBuilderExecutor(benchmark, "Default") + raw_corpus, questions = corpus_builder.load_corpus(limit=limit) + assert len(raw_corpus) > 0, f"Corpus builder loads empty corpus for {benchmark}" assert len(questions) <= 2, ( f"Corpus builder loads {len(questions)} for {benchmark} when limit is {limit}" @@ -22,8 +45,14 @@ def test_corpus_builder_load_corpus(benchmark): @patch.object(CorpusBuilderExecutor, "run_cognee", new_callable=AsyncMock) async def test_corpus_builder_build_corpus(mock_run_cognee, benchmark): limit = 2 - corpus_builder = CorpusBuilderExecutor(benchmark, "Default") - questions = await corpus_builder.build_corpus(limit=limit) + if benchmark in ("HotPotQA", "TwoWikiMultiHop"): + with patch.object(HotpotQAAdapter, "_get_raw_corpus", return_value=MOCK_HOTPOT_CORPUS): + corpus_builder = CorpusBuilderExecutor(benchmark, "Default") + questions = await corpus_builder.build_corpus(limit=limit) + else: + corpus_builder = CorpusBuilderExecutor(benchmark, "Default") + questions = await corpus_builder.build_corpus(limit=limit) + assert len(questions) <= 2, ( f"Corpus builder loads {len(questions)} for {benchmark} when limit is {limit}" ) diff --git a/pyproject.toml b/pyproject.toml index 8e4ed8a0d..cf2081d0a 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,7 +1,7 @@ [project] name = "cognee" -version = "0.5.0.dev0" +version = "0.5.0.dev1" description = "Cognee - is a library for enriching LLM context with a semantic layer for better understanding and reasoning." authors = [ { name = "Vasilije Markovic" }, diff --git a/uv.lock b/uv.lock index fccab8c40..884fb63be 100644 --- a/uv.lock +++ b/uv.lock @@ -1,5 +1,5 @@ version = 1 -revision = 2 +revision = 3 requires-python = ">=3.10, <3.14" resolution-markers = [ "python_full_version >= '3.13' and platform_python_implementation != 'PyPy' and sys_platform == 'darwin'", @@ -946,7 +946,7 @@ wheels = [ [[package]] name = "cognee" -version = "0.5.0.dev0" +version = "0.5.0.dev1" source = { editable = "." } dependencies = [ { name = "aiofiles" },