From 766b6be25b1ae363075e7a92132d18a3fcc228ac Mon Sep 17 00:00:00 2001 From: Boris Arzentar Date: Tue, 17 Sep 2024 21:36:35 +0200 Subject: [PATCH 1/8] feat: add sqlalchemy as dlt destination After this change we can easily switch database providers. Default database is sqlite now. --- .github/workflows/test_neo4j.yml | 41 - .github/workflows/test_python_3_10.yml | 49 - .github/workflows/test_python_3_11.yml | 49 - .github/workflows/test_python_3_9.yml | 49 - .github/workflows/test_qdrant.yml | 41 - .github/workflows/test_weaviate.yml | 41 - cognee/api/client.py | 6 +- cognee/api/v1/add/add.py | 27 +- .../databases/relational/DatabaseEngine.py | 23 - .../databases/relational/FakeAsyncSession.py | 29 - .../databases/relational/__init__.py | 6 +- .../databases/relational/config.py | 15 +- .../relational/create_db_and_tables.py | 7 +- .../relational/create_relational_engine.py | 20 +- .../databases/relational/data_types/UUID.py | 43 + .../relational/duckdb/DuckDBAdapter.py | 169 - .../databases/relational/duckdb/__init__.py | 0 .../relational/relational_db_interface.py | 26 - .../sqlalchemy/SqlAlchemyAdapter.py | 63 +- .../relational/sqlite/SqliteEngine.py | 82 - .../databases/relational/sqlite/__init__.py | 0 .../databases/relational/utils/__init__.py | 1 - .../relational/utils/with_rollback.py | 18 - .../pipeline/models/Operation.py | 8 +- cognee/modules/data/models/Data.py | 6 +- cognee/modules/data/models/Dataset.py | 6 +- cognee/modules/data/models/DatasetData.py | 8 +- cognee/modules/pipelines/models/Pipeline.py | 6 +- .../modules/pipelines/models/PipelineRun.py | 8 +- .../modules/pipelines/models/PipelineTask.py | 8 +- cognee/modules/pipelines/models/Task.py | 6 +- cognee/modules/pipelines/models/TaskRun.py | 6 +- cognee/modules/users/models/ACL.py | 10 +- cognee/modules/users/models/ACLResources.py | 8 +- cognee/modules/users/models/Group.py | 5 +- cognee/modules/users/models/Permission.py | 4 +- cognee/modules/users/models/Principal.py | 6 +- cognee/modules/users/models/Resource.py | 8 +- cognee/modules/users/models/User.py | 5 +- cognee/modules/users/models/UserGroup.py | 8 +- poetry.lock | 3177 +++++++++-------- pyproject.toml | 10 +- 42 files changed, 1759 insertions(+), 2349 deletions(-) delete mode 100644 cognee/infrastructure/databases/relational/DatabaseEngine.py delete mode 100644 cognee/infrastructure/databases/relational/FakeAsyncSession.py create mode 100644 cognee/infrastructure/databases/relational/data_types/UUID.py delete mode 100644 cognee/infrastructure/databases/relational/duckdb/DuckDBAdapter.py delete mode 100644 cognee/infrastructure/databases/relational/duckdb/__init__.py delete mode 100644 cognee/infrastructure/databases/relational/relational_db_interface.py delete mode 100644 cognee/infrastructure/databases/relational/sqlite/SqliteEngine.py delete mode 100644 cognee/infrastructure/databases/relational/sqlite/__init__.py delete mode 100644 cognee/infrastructure/databases/relational/utils/__init__.py delete mode 100644 cognee/infrastructure/databases/relational/utils/with_rollback.py diff --git a/.github/workflows/test_neo4j.yml b/.github/workflows/test_neo4j.yml index 64e783284..47d928fd9 100644 --- a/.github/workflows/test_neo4j.yml +++ b/.github/workflows/test_neo4j.yml @@ -18,13 +18,6 @@ jobs: name: docs changes uses: ./.github/workflows/get_docs_changes.yml - setup_docker: - name: Set up Docker Buildx - runs-on: ubuntu-latest - steps: - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - run_neo4j_integration_test: name: test needs: get_docs_changes @@ -35,18 +28,6 @@ jobs: run: shell: bash - services: - postgres: - image: postgres:latest - env: - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - volumes: - - postgres_data:/var/lib/postgresql/data - ports: - - 5432:5432 - steps: - name: Check out uses: actions/checkout@master @@ -66,18 +47,6 @@ jobs: - name: Install dependencies run: poetry install --no-interaction - - name: Create .cognee_system directory and print path - run: | - mkdir .cognee_system - echo $(pwd)/.cognee_system - - - name: Wait for PostgreSQL to be ready - run: | - echo "Waiting for PostgreSQL to be ready..." - until pg_isready -h localhost -p 5432 -U cognee; do - sleep 1 - done - - name: Run default Neo4j env: ENV: 'dev' @@ -85,14 +54,4 @@ jobs: GRAPH_DATABASE_URL: ${{ secrets.NEO4J_API_URL }} GRAPH_DATABASE_PASSWORD: ${{ secrets.NEO4J_API_KEY }} GRAPH_DATABASE_USERNAME: "neo4j" - DB_USER: cognee - DB_PASSWORD: cognee - DB_NAME: cognee_db - DB_HOST: localhost - DB_PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__HOST: localhost - DESTINATION__POSTGRES__CREDENTIALS__PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__USERNAME: cognee - DESTINATION__POSTGRES__CREDENTIALS__PASSWORD: cognee - DESTINATION__POSTGRES__CREDENTIALS__DATABASE: cognee_db run: poetry run python ./cognee/tests/test_neo4j.py diff --git a/.github/workflows/test_python_3_10.yml b/.github/workflows/test_python_3_10.yml index c6bcd3656..0ee5bd2cd 100644 --- a/.github/workflows/test_python_3_10.yml +++ b/.github/workflows/test_python_3_10.yml @@ -18,15 +18,6 @@ jobs: name: docs changes uses: ./.github/workflows/get_docs_changes.yml - setup_docker: - name: Set up Docker Buildx - runs-on: ubuntu-latest - strategy: - fail-fast: false - steps: - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - run_common: name: test needs: get_docs_changes @@ -38,19 +29,6 @@ jobs: run: shell: bash - services: - postgres: - image: postgres:latest - env: - PGUSER: cognee - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - volumes: - - postgres_data:/var/lib/postgresql/data - ports: - - 5432:5432 - steps: - name: Check out uses: actions/checkout@master @@ -71,23 +49,6 @@ jobs: - name: Install dependencies run: poetry install --no-interaction - - name: Create .cognee_system directory and print path - run: | - mkdir .cognee_system - echo $(pwd)/.cognee_system - - - name: Wait for PostgreSQL to be ready - env: - PGUSER: cognee - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - run: | - echo "Waiting for PostgreSQL to be ready..." - until pg_isready -h localhost -p 5432 -U cognee; do - sleep 1 - done - - name: Run tests run: poetry run pytest tests/ @@ -95,16 +56,6 @@ jobs: env: ENV: 'dev' LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }} - DB_HOST: localhost - DB_USERNAME: cognee - DB_PASSWORD: cognee - DB_DATABASE: cognee_db - DB_PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__HOST: localhost - DESTINATION__POSTGRES__CREDENTIALS__PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__USERNAME: cognee - DESTINATION__POSTGRES__CREDENTIALS__PASSWORD: cognee - DESTINATION__POSTGRES__CREDENTIALS__DATABASE: cognee_db run: poetry run python ./cognee/tests/test_library.py - name: Clean up disk space diff --git a/.github/workflows/test_python_3_11.yml b/.github/workflows/test_python_3_11.yml index 2b5a05775..4327312ec 100644 --- a/.github/workflows/test_python_3_11.yml +++ b/.github/workflows/test_python_3_11.yml @@ -18,15 +18,6 @@ jobs: name: docs changes uses: ./.github/workflows/get_docs_changes.yml - setup_docker: - name: Set up Docker Buildx - runs-on: ubuntu-latest - strategy: - fail-fast: false - steps: - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - run_common: name: test needs: get_docs_changes @@ -38,19 +29,6 @@ jobs: run: shell: bash - services: - postgres: - image: postgres:latest - env: - PGUSER: cognee - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - volumes: - - postgres_data:/var/lib/postgresql/data - ports: - - 5432:5432 - steps: - name: Check out uses: actions/checkout@master @@ -71,23 +49,6 @@ jobs: - name: Install dependencies run: poetry install --no-interaction - - name: Create .cognee_system directory and print path - run: | - mkdir .cognee_system - echo $(pwd)/.cognee_system - - - name: Wait for PostgreSQL to be ready - env: - PGUSER: cognee - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - run: | - echo "Waiting for PostgreSQL to be ready..." - until pg_isready -h localhost -p 5432 -U cognee; do - sleep 1 - done - - name: Run tests run: poetry run pytest tests/ @@ -95,16 +56,6 @@ jobs: env: ENV: 'dev' LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }} - DB_HOST: localhost - DB_USERNAME: cognee - DB_PASSWORD: cognee - DB_DATABASE: cognee_db - DB_PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__HOST: localhost - DESTINATION__POSTGRES__CREDENTIALS__PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__USERNAME: cognee - DESTINATION__POSTGRES__CREDENTIALS__PASSWORD: cognee - DESTINATION__POSTGRES__CREDENTIALS__DATABASE: cognee_db run: poetry run python ./cognee/tests/test_library.py - name: Clean up disk space diff --git a/.github/workflows/test_python_3_9.yml b/.github/workflows/test_python_3_9.yml index 15931b44a..154e0eab3 100644 --- a/.github/workflows/test_python_3_9.yml +++ b/.github/workflows/test_python_3_9.yml @@ -18,15 +18,6 @@ jobs: name: docs changes uses: ./.github/workflows/get_docs_changes.yml - setup_docker: - name: Set up Docker Buildx - runs-on: ubuntu-latest - strategy: - fail-fast: false - steps: - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - run_common: name: test needs: get_docs_changes @@ -38,19 +29,6 @@ jobs: run: shell: bash - services: - postgres: - image: postgres:latest - env: - PGUSER: cognee - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - volumes: - - postgres_data:/var/lib/postgresql/data - ports: - - 5432:5432 - steps: - name: Check out uses: actions/checkout@master @@ -71,23 +49,6 @@ jobs: - name: Install dependencies run: poetry install --no-interaction - - name: Create .cognee_system directory and print path - run: | - mkdir .cognee_system - echo $(pwd)/.cognee_system - - - name: Wait for PostgreSQL to be ready - env: - PGUSER: cognee - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - run: | - echo "Waiting for PostgreSQL to be ready..." - until pg_isready -h localhost -p 5432 -U cognee; do - sleep 1 - done - - name: Run tests run: poetry run pytest tests/ @@ -95,16 +56,6 @@ jobs: env: ENV: 'dev' LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }} - DB_HOST: localhost - DB_USERNAME: cognee - DB_PASSWORD: cognee - DB_DATABASE: cognee_db - DB_PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__HOST: localhost - DESTINATION__POSTGRES__CREDENTIALS__PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__USERNAME: cognee - DESTINATION__POSTGRES__CREDENTIALS__PASSWORD: cognee - DESTINATION__POSTGRES__CREDENTIALS__DATABASE: cognee_db run: poetry run python ./cognee/tests/test_library.py - name: Clean up disk space diff --git a/.github/workflows/test_qdrant.yml b/.github/workflows/test_qdrant.yml index 606b42606..af9f66257 100644 --- a/.github/workflows/test_qdrant.yml +++ b/.github/workflows/test_qdrant.yml @@ -18,13 +18,6 @@ jobs: name: docs changes uses: ./.github/workflows/get_docs_changes.yml - setup_docker: - name: Set up Docker Buildx - runs-on: ubuntu-latest - steps: - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - run_qdrant_integration_test: name: test needs: get_docs_changes @@ -35,18 +28,6 @@ jobs: run: shell: bash - services: - postgres: - image: postgres:latest - env: - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - volumes: - - postgres_data:/var/lib/postgresql/data - ports: - - 5432:5432 - steps: - name: Check out uses: actions/checkout@master @@ -66,32 +47,10 @@ jobs: - name: Install dependencies run: poetry install --no-interaction - - name: Create .cognee_system directory and print path - run: | - mkdir .cognee_system - echo $(pwd)/.cognee_system - - - name: Wait for PostgreSQL to be ready - run: | - echo "Waiting for PostgreSQL to be ready..." - until pg_isready -h localhost -p 5432 -U cognee; do - sleep 1 - done - - name: Run default Qdrant env: ENV: 'dev' LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }} VECTOR_DB_URL: ${{ secrets.QDRANT_API_URL }} VECTOR_DB_KEY: ${{ secrets.QDRANT_API_KEY }} - DB_USER: cognee - DB_PASSWORD: cognee - DB_NAME: cognee_db - DB_HOST: localhost - DB_PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__HOST: localhost - DESTINATION__POSTGRES__CREDENTIALS__PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__USERNAME: cognee - DESTINATION__POSTGRES__CREDENTIALS__PASSWORD: cognee - DESTINATION__POSTGRES__CREDENTIALS__DATABASE: cognee_db run: poetry run python ./cognee/tests/test_qdrant.py diff --git a/.github/workflows/test_weaviate.yml b/.github/workflows/test_weaviate.yml index 06a0aa64a..cbdd28cef 100644 --- a/.github/workflows/test_weaviate.yml +++ b/.github/workflows/test_weaviate.yml @@ -18,13 +18,6 @@ jobs: name: docs changes uses: ./.github/workflows/get_docs_changes.yml - setup_docker: - name: Set up Docker Buildx - runs-on: ubuntu-latest - steps: - - name: Set up Docker Buildx - uses: docker/setup-buildx-action@v3 - run_weaviate_integration_test: name: test needs: get_docs_changes @@ -35,18 +28,6 @@ jobs: run: shell: bash - services: - postgres: - image: postgres:latest - env: - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - volumes: - - postgres_data:/var/lib/postgresql/data - ports: - - 5432:5432 - steps: - name: Check out uses: actions/checkout@master @@ -66,32 +47,10 @@ jobs: - name: Install dependencies run: poetry install --no-interaction - - name: Create .cognee_system directory and print path - run: | - mkdir .cognee_system - echo $(pwd)/.cognee_system - - - name: Wait for PostgreSQL to be ready - run: | - echo "Waiting for PostgreSQL to be ready..." - until pg_isready -h localhost -p 5432 -U cognee; do - sleep 1 - done - - name: Run default Weaviate env: ENV: 'dev' LLM_API_KEY: ${{ secrets.OPENAI_API_KEY }} VECTOR_DB_URL: ${{ secrets.WEAVIATE_API_URL }} VECTOR_DB_KEY: ${{ secrets.WEAVIATE_API_KEY }} - DB_USER: cognee - DB_PASSWORD: cognee - DB_NAME: cognee_db - DB_HOST: localhost - DB_PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__HOST: localhost - DESTINATION__POSTGRES__CREDENTIALS__PORT: 5432 - DESTINATION__POSTGRES__CREDENTIALS__USERNAME: cognee - DESTINATION__POSTGRES__CREDENTIALS__PASSWORD: cognee - DESTINATION__POSTGRES__CREDENTIALS__DATABASE: cognee_db run: poetry run python ./cognee/tests/test_weaviate.py diff --git a/cognee/api/client.py b/cognee/api/client.py index fa50cc573..89af9fcfb 100644 --- a/cognee/api/client.py +++ b/cognee/api/client.py @@ -14,8 +14,6 @@ from cognee.modules.users.methods import get_authenticated_user -from cognee.infrastructure.databases.relational import create_db_and_tables - # Set up logging logging.basicConfig( level=logging.INFO, # Set the logging level (e.g., DEBUG, INFO, WARNING, ERROR, CRITICAL) @@ -34,8 +32,12 @@ @asynccontextmanager async def lifespan(app: FastAPI): + from cognee.infrastructure.databases.relational import create_db_and_tables + from cognee.modules.users.methods import create_default_user + # Not needed if you setup a migration system like Alembic await create_db_and_tables() + await create_default_user() yield app = FastAPI(debug = os.getenv("ENV") != "prod", lifespan = lifespan) diff --git a/cognee/api/v1/add/add.py b/cognee/api/v1/add/add.py index 308dce70e..64b1e1fed 100644 --- a/cognee/api/v1/add/add.py +++ b/cognee/api/v1/add/add.py @@ -2,7 +2,6 @@ from os import path import asyncio import dlt -import duckdb import cognee.modules.ingestion as ingestion from cognee.infrastructure.files.storage import LocalStorage @@ -81,22 +80,16 @@ async def add_files(file_paths: List[str], dataset_name: str, user: User = None) relational_config = get_relational_config() - if relational_config.db_provider == "duckdb": - db = duckdb.connect(relational_config.db_file_path) - - destination = dlt.destinations.duckdb( - credentials = db, - ) - else: - destination = dlt.destinations.postgres( - credentials = { - "host": relational_config.db_host, - "port": relational_config.db_port, - "user": relational_config.db_user, - "password": relational_config.db_password, - "database": relational_config.db_name, - }, - ) + destination = dlt.destinations.sqlalchemy( + credentials = { + "host": relational_config.db_host, + "port": relational_config.db_port, + "username": relational_config.db_username, + "password": relational_config.db_password, + "database": relational_config.db_name, + "drivername": relational_config.db_provider, + }, + ) pipeline = dlt.pipeline( pipeline_name = "file_load_from_filesystem", diff --git a/cognee/infrastructure/databases/relational/DatabaseEngine.py b/cognee/infrastructure/databases/relational/DatabaseEngine.py deleted file mode 100644 index 9df88db46..000000000 --- a/cognee/infrastructure/databases/relational/DatabaseEngine.py +++ /dev/null @@ -1,23 +0,0 @@ -from typing import Protocol - -class DatabaseEngine(Protocol): - async def ensure_tables(self): - pass - - def database_exists(self, db_name: str) -> bool: - pass - - def create_database(self, db_name: str): - pass - - def drop_database(self, db_name: str): - pass - - async def table_exists(self, table_name: str) -> bool: - pass - - async def create_tables(self): - pass - - async def create(self, data): - pass diff --git a/cognee/infrastructure/databases/relational/FakeAsyncSession.py b/cognee/infrastructure/databases/relational/FakeAsyncSession.py deleted file mode 100644 index cd7e4b6a3..000000000 --- a/cognee/infrastructure/databases/relational/FakeAsyncSession.py +++ /dev/null @@ -1,29 +0,0 @@ -import inspect -from typing import Any - -from sqlalchemy.ext.asyncio import AsyncSession -from sqlalchemy.orm import Session - -class FakeAsyncSession: - def __init__(self, session: Session): - self.session = session - - def run_sync(self, *args, **kwargs): - return self.execute(*args, **kwargs) - - def __getattr__(self, name: str) -> Any: - """ - If the method being called is async in AsyncSession, create a fake async version - for Session so callers can `await` as usual. Think `commit`, `refresh`, - `delete`, etc. - """ - async_session_attr = getattr(AsyncSession, name, None) - session_attr = getattr(self.session, name) - - if not inspect.iscoroutinefunction(async_session_attr): - return session_attr - - async def async_wrapper(*args, **kwargs): - return session_attr(*args, **kwargs) - - return async_wrapper diff --git a/cognee/infrastructure/databases/relational/__init__.py b/cognee/infrastructure/databases/relational/__init__.py index 61ff4ef85..1ef847903 100644 --- a/cognee/infrastructure/databases/relational/__init__.py +++ b/cognee/infrastructure/databases/relational/__init__.py @@ -1,7 +1,7 @@ from .ModelBase import Base -from .DatabaseEngine import DatabaseEngine -from .sqlite.SqliteEngine import SqliteEngine -from .duckdb.DuckDBAdapter import DuckDBAdapter from .config import get_relational_config from .create_db_and_tables import create_db_and_tables from .get_relational_engine import get_relational_engine + +# Global data types +from .data_types.UUID import UUID diff --git a/cognee/infrastructure/databases/relational/config.py b/cognee/infrastructure/databases/relational/config.py index e7ab1b30f..ef8dca608 100644 --- a/cognee/infrastructure/databases/relational/config.py +++ b/cognee/infrastructure/databases/relational/config.py @@ -1,4 +1,5 @@ import os +from typing import Union from functools import lru_cache from pydantic_settings import BaseSettings, SettingsConfigDict from cognee.root_dir import get_absolute_path @@ -6,13 +7,11 @@ class RelationalConfig(BaseSettings): db_path: str = os.path.join(get_absolute_path(".cognee_system"), "databases") db_name: str = "cognee_db" - db_host: str = "localhost" - db_port: str = "5432" - db_user: str = "cognee" - db_password: str = "cognee" - db_provider: str = "postgresql+asyncpg" - db_file_path: str = os.path.join(db_path, db_name) - + db_host: Union[str, None] = None # "localhost" + db_port: Union[str, None] = None # "5432" + db_username: Union[str, None] = None # "cognee" + db_password: Union[str, None] = None # "cognee" + db_provider: str = "sqlite" model_config = SettingsConfigDict(env_file = ".env", extra = "allow") @@ -22,7 +21,7 @@ def to_dict(self) -> dict: "db_name": self.db_name, "db_host": self.db_host, "db_port": self.db_port, - "db_user": self.db_user, + "db_username": self.db_username, "db_password": self.db_password, "db_provider": self.db_provider, } diff --git a/cognee/infrastructure/databases/relational/create_db_and_tables.py b/cognee/infrastructure/databases/relational/create_db_and_tables.py index d6cf22f87..02ff680df 100644 --- a/cognee/infrastructure/databases/relational/create_db_and_tables.py +++ b/cognee/infrastructure/databases/relational/create_db_and_tables.py @@ -1,9 +1,14 @@ +from cognee.infrastructure.files.storage import LocalStorage from .ModelBase import Base -from .get_relational_engine import get_relational_engine +from .get_relational_engine import get_relational_engine, get_relational_config async def create_db_and_tables(): + relational_config = get_relational_config() relational_engine = get_relational_engine() + if relational_engine.engine.dialect.name == "sqlite": + LocalStorage.ensure_directory_exists(relational_config.db_path) + async with relational_engine.engine.begin() as connection: if len(Base.metadata.tables.keys()) > 0: await connection.run_sync(Base.metadata.create_all) diff --git a/cognee/infrastructure/databases/relational/create_relational_engine.py b/cognee/infrastructure/databases/relational/create_relational_engine.py index 53abf831f..08cf171d5 100644 --- a/cognee/infrastructure/databases/relational/create_relational_engine.py +++ b/cognee/infrastructure/databases/relational/create_relational_engine.py @@ -3,18 +3,16 @@ def create_relational_engine( db_path: str, db_name: str, - db_provider: str, db_host: str, db_port: str, - db_user: str, + db_username: str, db_password: str, + db_provider: str, ): - return SQLAlchemyAdapter( - db_name = db_name, - db_path = db_path, - db_type = db_provider, - db_host = db_host, - db_port = db_port, - db_user = db_user, - db_password = db_password - ) + if db_provider == "sqlite": + connection_string = f"sqlite+aiosqlite:///{db_path}/{db_name}" + + if db_provider == "postgres": + connection_string = f"postgresql+asyncpg://{db_username}:{db_password}@{db_host}:{db_port}/{db_name}" + + return SQLAlchemyAdapter(connection_string) diff --git a/cognee/infrastructure/databases/relational/data_types/UUID.py b/cognee/infrastructure/databases/relational/data_types/UUID.py new file mode 100644 index 000000000..5cd24c3d3 --- /dev/null +++ b/cognee/infrastructure/databases/relational/data_types/UUID.py @@ -0,0 +1,43 @@ +import uuid + +from sqlalchemy.types import TypeDecorator, BINARY +from sqlalchemy.dialects.postgresql import UUID as psqlUUID + +class UUID(TypeDecorator): + """Platform-independent GUID type. + + Uses Postgresql's UUID type, otherwise uses + BINARY(16), to store UUID. + + """ + impl = BINARY + + def load_dialect_impl(self, dialect): + if dialect.name == 'postgresql': + return dialect.type_descriptor(psqlUUID()) + else: + return dialect.type_descriptor(BINARY(16)) + + def process_bind_param(self, value, dialect): + if value is None: + return value + else: + if not isinstance(value, uuid.UUID): + if isinstance(value, bytes): + value = uuid.UUID(bytes = value) + elif isinstance(value, int): + value = uuid.UUID(int = value) + elif isinstance(value, str): + value = uuid.UUID(value) + if dialect.name == 'postgresql': + return str(value) + else: + return value.bytes + + def process_result_value(self, value, dialect): + if value is None: + return value + if dialect.name == 'postgresql': + return uuid.UUID(value) + else: + return uuid.UUID(bytes = value) diff --git a/cognee/infrastructure/databases/relational/duckdb/DuckDBAdapter.py b/cognee/infrastructure/databases/relational/duckdb/DuckDBAdapter.py deleted file mode 100644 index 2695e04cc..000000000 --- a/cognee/infrastructure/databases/relational/duckdb/DuckDBAdapter.py +++ /dev/null @@ -1,169 +0,0 @@ -import duckdb -import os -class DuckDBAdapter(): - def __init__(self, db_path: str, db_name: str): - self.db_location = os.path.abspath(os.path.join(db_path, db_name)) - - self.get_connection = lambda: duckdb.connect(self.db_location) - - def get_datasets(self): - with self.get_connection() as connection: - tables = connection.sql("SELECT DISTINCT schema_name FROM duckdb_tables();").to_df().to_dict("list") - - return list( - filter( - lambda schema_name: not schema_name.endswith("staging") and schema_name != "cognee", - tables["schema_name"] - ) - ) - - def get_files_metadata(self, dataset_name: str): - with self.get_connection() as connection: - return connection.sql(f"SELECT id, name, file_path, extension, mime_type FROM {dataset_name}.file_metadata;").to_df().to_dict("records") - - def create_table(self, schema_name: str, table_name: str, table_config: list[dict]): - fields_query_parts = [] - - for table_config_item in table_config: - fields_query_parts.append(f"{table_config_item['name']} {table_config_item['type']}") - - with self.get_connection() as connection: - query = f"CREATE SCHEMA IF NOT EXISTS {schema_name};" - connection.execute(query) - - with self.get_connection() as connection: - query = f"CREATE TABLE IF NOT EXISTS {schema_name}.{table_name} ({', '.join(fields_query_parts)});" - connection.execute(query) - - def delete_table(self, table_name: str): - with self.get_connection() as connection: - query = f"DROP TABLE IF EXISTS {table_name};" - connection.execute(query) - - def insert_data(self, schema_name: str, table_name: str, data: list[dict]): - def get_values(data_entry: list): - return ", ".join([f"'{value}'" if isinstance(value, str) else value for value in data_entry]) - - columns = ", ".join(data[0].keys()) - values = ", ".join([f"({get_values(data_entry.values())})" for data_entry in data]) - - with self.get_connection() as connection: - query = f"INSERT INTO {schema_name}.{table_name} ({columns}) VALUES {values};" - connection.execute(query) - - def get_data(self, table_name: str, filters: dict = None): - with self.get_connection() as connection: - def get_values(values: list): - return ", ".join([f"'{value}'" for value in values]) - - def get_filters(filters: dict): - return " AND ".join([ - f"{key} IN ({get_values(value)})" if isinstance(value, list) - else f"{key} = '{value}'" for (key, value) in filters.items() - ]) - - query = f"SELECT * FROM {table_name}" + (";" if filters is None else f" WHERE {get_filters(filters)};") - results = connection.sql(query).to_df().to_dict("records") - - return { - result["data_id"]: result["status"] for result in results - } - - def execute_query(self, query): - with self.get_connection() as connection: - return connection.sql(query).to_df().to_dict("records") - - def load_cognify_data(self, data): - with self.get_connection() as connection: - # Ensure the "cognify" table exists - connection.execute(""" - CREATE TABLE IF NOT EXISTS cognify ( - document_id STRING, - created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, - updated_at TIMESTAMP DEFAULT NULL, - processed BOOLEAN DEFAULT FALSE, - document_id_target STRING NULL - ); - """) - - # Prepare the insert statement - insert_query = """ - INSERT INTO cognify (document_id) - VALUES (?); - """ - - # Insert each record into the "cognify" table - for record in data: - with self.get_connection() as connection: - connection.execute(insert_query, [ - record.get("document_id"), - ]) - - def fetch_cognify_data(self, excluded_document_id: str): - # SQL command to create the "cognify" table with the specified columns - create_table_sql = """ - CREATE TABLE IF NOT EXISTS cognify ( - document_id STRING, - created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, - updated_at TIMESTAMP DEFAULT NULL, - processed BOOLEAN DEFAULT FALSE, - document_id_target STRING NULL - ); - """ - with self.get_connection() as connection: - # Execute the SQL command to create the table - connection.execute(create_table_sql) - - # SQL command to select data from the "cognify" table - select_data_sql = f"SELECT document_id, created_at, updated_at, processed FROM cognify WHERE document_id != '{excluded_document_id}' AND processed = FALSE;" - - with self.get_connection() as connection: - # Execute the query and fetch the results - records = connection.sql(select_data_sql).to_df().to_dict("records") - - # If records are fetched, update the "processed" column to "True" - if records: - # Fetching document_ids from the records to update the "processed" column - document_ids = tuple(record["document_id"] for record in records) - # SQL command to update the "processed" column to "True" for fetched records - update_data_sql = f"UPDATE cognify SET processed = TRUE WHERE document_id IN {document_ids};" - - with self.get_connection() as connection: - # Execute the update query - connection.execute(update_data_sql) - - # Return the fetched records - return records - - - def delete_cognify_data(self): - # SQL command to create the "cognify" table with the specified columns - create_table_sql = """ - CREATE TABLE IF NOT EXISTS cognify ( - document_id STRING, - created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, - updated_at TIMESTAMP DEFAULT NULL, - processed BOOLEAN DEFAULT FALSE, - document_id_target STRING NULL - ); - """ - - with self.get_connection() as connection: - # Execute the SQL command to create the table - connection.execute(create_table_sql) - - with self.get_connection() as connection: - # SQL command to select data from the "cognify" table - select_data_sql = "DELETE FROM cognify;" - connection.sql(select_data_sql) - drop_data_sql = "DROP TABLE cognify;" - connection.sql(drop_data_sql) - - def delete_database(self): - from cognee.infrastructure.files.storage import LocalStorage - - if LocalStorage.file_exists(self.db_location): - LocalStorage.remove(self.db_location) - - if LocalStorage.file_exists(self.db_location + ".wal"): - LocalStorage.remove(self.db_location + ".wal") diff --git a/cognee/infrastructure/databases/relational/duckdb/__init__.py b/cognee/infrastructure/databases/relational/duckdb/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/cognee/infrastructure/databases/relational/relational_db_interface.py b/cognee/infrastructure/databases/relational/relational_db_interface.py deleted file mode 100644 index 3fa923b0f..000000000 --- a/cognee/infrastructure/databases/relational/relational_db_interface.py +++ /dev/null @@ -1,26 +0,0 @@ -from abc import abstractmethod -from typing import Protocol, TypeVar, Type, List - -RowDataType = TypeVar('RowDataType') - -class RelationalDBInterface(Protocol): - @abstractmethod - async def create_database(self, database_name: str, database_path: str): raise NotImplementedError - - @abstractmethod - async def create_table(self, table_name: str, table_config: object): raise NotImplementedError - - @abstractmethod - async def add_row(self, table_name: str, row_data: Type[RowDataType]): raise NotImplementedError - - @abstractmethod - async def add_rows(self, table_name: str, rows_data: List[Type[RowDataType]]): raise NotImplementedError - - @abstractmethod - async def get_row(self, table_name: str, row_id: str): raise NotImplementedError - - @abstractmethod - async def update_row(self, table_name: str, row_id: str, row_data: Type[RowDataType]): raise NotImplementedError - - @abstractmethod - async def delete_row(self, table_name: str, row_id: str): raise NotImplementedError diff --git a/cognee/infrastructure/databases/relational/sqlalchemy/SqlAlchemyAdapter.py b/cognee/infrastructure/databases/relational/sqlalchemy/SqlAlchemyAdapter.py index c52ad92cf..3dfbc5680 100644 --- a/cognee/infrastructure/databases/relational/sqlalchemy/SqlAlchemyAdapter.py +++ b/cognee/infrastructure/databases/relational/sqlalchemy/SqlAlchemyAdapter.py @@ -1,39 +1,18 @@ -import os -import asyncio from typing import AsyncGenerator from contextlib import asynccontextmanager -from sqlalchemy import create_engine, text, select -from sqlalchemy.orm import sessionmaker, joinedload +from sqlalchemy import text, select +from sqlalchemy.orm import joinedload from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine, async_sessionmaker -from cognee.infrastructure.files.storage import LocalStorage -from cognee.infrastructure.databases.relational.FakeAsyncSession import FakeAsyncSession -from ..ModelBase import Base - -def make_async_sessionmaker(sessionmaker): - @asynccontextmanager - async def async_session_maker(): - await asyncio.sleep(0.1) - session = FakeAsyncSession(sessionmaker()) - try: - yield session - finally: - await session.close() # Ensure the session is closed - return async_session_maker +from ..ModelBase import Base class SQLAlchemyAdapter(): - def __init__(self, db_type: str, db_path: str, db_name: str, db_user: str, db_password: str, db_host: str, db_port: str): - self.db_location = os.path.abspath(os.path.join(db_path, db_name)) - self.db_name = db_name - - if db_type == "duckdb": - LocalStorage.ensure_directory_exists(db_path) + def __init__(self, connection_string: str): + self.engine = create_async_engine(connection_string) + self.sessionmaker = async_sessionmaker(bind=self.engine, expire_on_commit=False) - self.engine = create_engine(f"duckdb:///{self.db_location}") - self.sessionmaker = make_async_sessionmaker(sessionmaker(bind=self.engine)) - else: - self.engine = create_async_engine(f"postgresql+asyncpg://{db_user}:{db_password}@{db_host}:{db_port}/{db_name}") - self.sessionmaker = async_sessionmaker(bind=self.engine, expire_on_commit=False) + if self.engine.dialect.name == "sqlite": + self.db_path = connection_string.split("///")[1] @asynccontextmanager async def get_async_session(self) -> AsyncGenerator[AsyncSession, None]: @@ -72,6 +51,7 @@ async def delete_table(self, table_name: str): await connection.execute(text(f"DROP TABLE IF EXISTS {table_name} CASCADE;")) await connection.close() + async def insert_data(self, schema_name: str, table_name: str, data: list[dict]): columns = ", ".join(data[0].keys()) values = ", ".join([f"({', '.join([f':{key}' for key in row.keys()])})" for row in data]) @@ -80,6 +60,7 @@ async def insert_data(self, schema_name: str, table_name: str, data: list[dict]) async with self.engine.begin() as connection: await connection.execute(insert_query, data) await connection.close() + async def get_data(self, table_name: str, filters: dict = None): async with self.engine.begin() as connection: query = f"SELECT * FROM {table_name}" @@ -113,11 +94,19 @@ async def drop_tables(self): print(f"Error dropping database tables: {e}") async def delete_database(self): - async with self.engine.begin() as connection: - try: - for table in Base.metadata.sorted_tables: - drop_table_query = text(f'DROP TABLE IF EXISTS {table.name} CASCADE') - await connection.execute(drop_table_query) - print("Database deleted successfully.") - except Exception as e: - print(f"Error deleting database: {e}") + try: + if self.engine.dialect.name == "sqlite": + from cognee.infrastructure.files.storage import LocalStorage + + LocalStorage.remove(self.db_path) + self.db_path = None + else: + async with self.engine.begin() as connection: + for table in Base.metadata.sorted_tables: + drop_table_query = text(f'DROP TABLE IF EXISTS {table.name} CASCADE') + await connection.execute(drop_table_query) + + except Exception as e: + print(f"Error deleting database: {e}") + + print("Database deleted successfully.") diff --git a/cognee/infrastructure/databases/relational/sqlite/SqliteEngine.py b/cognee/infrastructure/databases/relational/sqlite/SqliteEngine.py deleted file mode 100644 index c636b1fd3..000000000 --- a/cognee/infrastructure/databases/relational/sqlite/SqliteEngine.py +++ /dev/null @@ -1,82 +0,0 @@ -import os -import asyncio -from typing import Callable -from sqlalchemy.inspection import inspect -from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker, AsyncEngine, AsyncSession, async_scoped_session -from sqlalchemy.future import select -from cognee.infrastructure.files.storage.LocalStorage import LocalStorage -from ..DatabaseEngine import DatabaseEngine -from ..ModelBase import Base -from ..utils import with_rollback - -class SqliteEngine(DatabaseEngine): - db_path: str = None - db_name: str = None - engine: AsyncEngine = None - session_maker: Callable[[], async_scoped_session[AsyncSession]] = None - is_db_done: bool = False - - def __init__(self, db_path: str, db_name: str): - self.db_path = db_path - self.db_name = db_name - self.db_location = db_path + "/" + db_name - self.engine = create_async_engine( - f"sqlite+aiosqlite:///{self.db_location}", - pool_recycle = 3600, - echo = False - ) - self.session_maker = lambda: async_scoped_session( - async_sessionmaker( - bind = self.engine, - class_ = AsyncSession - ), - scopefunc = asyncio.current_task - ) - - async def ensure_tables(self): - if not self.database_exists(self.db_name): - self.create_database(self.db_name) - - await self.create_tables() - - self.is_db_done = True - - return True - - def database_exists(self, db_name: str) -> bool: - return os.path.exists(self.db_path + "/" + db_name) - - def create_database(self, db_name: str): - LocalStorage.ensure_directory_exists(self.db_path) - - with open(self.db_path + "/" + db_name, mode = "w+", encoding = "utf-8") as file: - file.write("") - - def drop_database(self, db_name: str): - os.remove(self.db_location) - - async def table_exists(self, table_name: str) -> bool: - return inspect(self.engine).has_table(table_name) - - async def create_tables(self): - async with self.engine.begin() as connection: - return await connection.run_sync(Base.metadata.create_all) - - async def create(self, data): - async with with_rollback(self.session_maker()) as session: - session.add(data) - - async def query(self, query_term): - async with with_rollback(self.session_maker()) as session: - return await session.execute(query_term) - - async def query_entity(self, entity): - async with with_rollback(self.session_maker()) as session: - return await session.execute( - select(type(entity)) - .where(type(entity).id == entity.id) - ) - - async def update(self, data_update_fn): - async with with_rollback(self.session_maker()): - data_update_fn() diff --git a/cognee/infrastructure/databases/relational/sqlite/__init__.py b/cognee/infrastructure/databases/relational/sqlite/__init__.py deleted file mode 100644 index e69de29bb..000000000 diff --git a/cognee/infrastructure/databases/relational/utils/__init__.py b/cognee/infrastructure/databases/relational/utils/__init__.py deleted file mode 100644 index dac1fbf82..000000000 --- a/cognee/infrastructure/databases/relational/utils/__init__.py +++ /dev/null @@ -1 +0,0 @@ -from .with_rollback import with_rollback diff --git a/cognee/infrastructure/databases/relational/utils/with_rollback.py b/cognee/infrastructure/databases/relational/utils/with_rollback.py deleted file mode 100644 index 99395e499..000000000 --- a/cognee/infrastructure/databases/relational/utils/with_rollback.py +++ /dev/null @@ -1,18 +0,0 @@ -import logging -from contextlib import asynccontextmanager -from sqlalchemy.ext.asyncio import async_scoped_session -logger = logging.getLogger(__name__) - -@asynccontextmanager -async def with_rollback(session: async_scoped_session): - """Provide a transactional scope around a series of operations.""" - - try: - # async with session.begin(): - yield session - await session.commit() - await session.remove() - except Exception as exception: - await session.rollback() - logger.error("Session rolled back due to: %s", str(exception)) - raise exception diff --git a/cognee/infrastructure/pipeline/models/Operation.py b/cognee/infrastructure/pipeline/models/Operation.py index 89c96ed0c..1834c1a36 100644 --- a/cognee/infrastructure/pipeline/models/Operation.py +++ b/cognee/infrastructure/pipeline/models/Operation.py @@ -1,7 +1,7 @@ from datetime import datetime from sqlalchemy.orm import Mapped, MappedColumn -from sqlalchemy import Column, String, DateTime, ForeignKey, Enum, UUID, JSON -from cognee.infrastructure.databases.relational import ModelBase +from sqlalchemy import Column, DateTime, ForeignKey, Enum, JSON +from cognee.infrastructure.databases.relational import Base, UUID class OperationType(Enum): MERGE_DATA = "MERGE_DATA" @@ -14,10 +14,10 @@ class OperationStatus(Enum): ERROR = "OPERATION_ERROR" CANCELLED = "OPERATION_CANCELLED" -class Operation(ModelBase): +class Operation(Base): __tablename__ = "operation" - id = Column(String, primary_key = True) + id = Column(UUID, primary_key = True) status = Column(Enum(OperationStatus)) operation_type = Column(Enum(OperationType)) diff --git a/cognee/modules/data/models/Data.py b/cognee/modules/data/models/Data.py index e3c711363..feb9e3bff 100644 --- a/cognee/modules/data/models/Data.py +++ b/cognee/modules/data/models/Data.py @@ -2,14 +2,14 @@ from typing import List from datetime import datetime, timezone from sqlalchemy.orm import relationship, Mapped -from sqlalchemy import Column, String, DateTime, UUID -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, String, DateTime +from cognee.infrastructure.databases.relational import Base, UUID from .DatasetData import DatasetData class Data(Base): __tablename__ = "data" - id = Column(UUID(as_uuid = True), primary_key = True, default = uuid4) + id = Column(UUID, primary_key = True, default = uuid4) name = Column(String) extension = Column(String) diff --git a/cognee/modules/data/models/Dataset.py b/cognee/modules/data/models/Dataset.py index a09983886..7e35ce982 100644 --- a/cognee/modules/data/models/Dataset.py +++ b/cognee/modules/data/models/Dataset.py @@ -2,14 +2,14 @@ from typing import List from datetime import datetime, timezone from sqlalchemy.orm import relationship, Mapped -from sqlalchemy import Column, Text, DateTime, UUID -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, Text, DateTime +from cognee.infrastructure.databases.relational import Base, UUID from .DatasetData import DatasetData class Dataset(Base): __tablename__ = "datasets" - id = Column(UUID(as_uuid = True), primary_key = True, default = uuid4) + id = Column(UUID, primary_key = True, default = uuid4) name = Column(Text) diff --git a/cognee/modules/data/models/DatasetData.py b/cognee/modules/data/models/DatasetData.py index d340889f2..b156d8d37 100644 --- a/cognee/modules/data/models/DatasetData.py +++ b/cognee/modules/data/models/DatasetData.py @@ -1,11 +1,11 @@ from datetime import datetime, timezone -from sqlalchemy import Column, DateTime, UUID, ForeignKey -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, DateTime, ForeignKey +from cognee.infrastructure.databases.relational import Base, UUID class DatasetData(Base): __tablename__ = "dataset_data" created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) - dataset_id = Column(UUID(as_uuid = True), ForeignKey("datasets.id"), primary_key = True) - data_id = Column(UUID(as_uuid = True), ForeignKey("data.id"), primary_key = True) + dataset_id = Column(UUID, ForeignKey("datasets.id"), primary_key = True) + data_id = Column(UUID, ForeignKey("data.id"), primary_key = True) diff --git a/cognee/modules/pipelines/models/Pipeline.py b/cognee/modules/pipelines/models/Pipeline.py index 8904e00dc..e9cad5945 100644 --- a/cognee/modules/pipelines/models/Pipeline.py +++ b/cognee/modules/pipelines/models/Pipeline.py @@ -1,14 +1,14 @@ from uuid import uuid4 from datetime import datetime, timezone -from sqlalchemy import Column, UUID, DateTime, String, Text +from sqlalchemy import Column, DateTime, String, Text from sqlalchemy.orm import relationship, Mapped -from cognee.infrastructure.databases.relational import Base +from cognee.infrastructure.databases.relational import Base, UUID from .PipelineTask import PipelineTask class Pipeline(Base): __tablename__ = "pipelines" - id = Column(UUID(as_uuid = True), primary_key = True, default = uuid4) + id = Column(UUID, primary_key = True, default = uuid4) name = Column(String) description = Column(Text, nullable = True) diff --git a/cognee/modules/pipelines/models/PipelineRun.py b/cognee/modules/pipelines/models/PipelineRun.py index ccd5e9eeb..18c815588 100644 --- a/cognee/modules/pipelines/models/PipelineRun.py +++ b/cognee/modules/pipelines/models/PipelineRun.py @@ -1,16 +1,16 @@ from uuid import uuid4 from datetime import datetime, timezone -from sqlalchemy import Column, UUID, DateTime, String, JSON -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, DateTime, String, JSON +from cognee.infrastructure.databases.relational import Base, UUID class PipelineRun(Base): __tablename__ = "pipeline_runs" - id = Column(UUID(as_uuid = True), primary_key = True, default = uuid4) + id = Column(UUID, primary_key = True, default = uuid4) created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) status = Column(String) - run_id = Column(UUID(as_uuid = True), index = True) + run_id = Column(UUID, index = True) run_info = Column(JSON) diff --git a/cognee/modules/pipelines/models/PipelineTask.py b/cognee/modules/pipelines/models/PipelineTask.py index 079b12f47..acbf44e5d 100644 --- a/cognee/modules/pipelines/models/PipelineTask.py +++ b/cognee/modules/pipelines/models/PipelineTask.py @@ -1,11 +1,11 @@ from datetime import datetime, timezone -from sqlalchemy import Column, DateTime, UUID, ForeignKey -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, DateTime, ForeignKey +from cognee.infrastructure.databases.relational import Base, UUID class PipelineTask(Base): __tablename__ = "pipeline_task" created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) - pipeline_id = Column("pipeline", UUID(as_uuid = True), ForeignKey("pipeline.id"), primary_key = True) - task_id = Column("task", UUID(as_uuid = True), ForeignKey("task.id"), primary_key = True) + pipeline_id = Column("pipeline", UUID, ForeignKey("pipeline.id"), primary_key = True) + task_id = Column("task", UUID, ForeignKey("task.id"), primary_key = True) diff --git a/cognee/modules/pipelines/models/Task.py b/cognee/modules/pipelines/models/Task.py index 3a56f4b71..eba6508e3 100644 --- a/cognee/modules/pipelines/models/Task.py +++ b/cognee/modules/pipelines/models/Task.py @@ -1,14 +1,14 @@ from uuid import uuid4 from datetime import datetime, timezone from sqlalchemy.orm import relationship, Mapped -from sqlalchemy import Column, String, DateTime, UUID, Text -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, String, DateTime, Text +from cognee.infrastructure.databases.relational import Base, UUID from .PipelineTask import PipelineTask class Task(Base): __tablename__ = "tasks" - id = Column(UUID(as_uuid = True), primary_key = True, default = uuid4) + id = Column(UUID, primary_key = True, default = uuid4) name = Column(String) description = Column(Text, nullable = True) diff --git a/cognee/modules/pipelines/models/TaskRun.py b/cognee/modules/pipelines/models/TaskRun.py index 89cda8b44..bf2e2a9f8 100644 --- a/cognee/modules/pipelines/models/TaskRun.py +++ b/cognee/modules/pipelines/models/TaskRun.py @@ -1,12 +1,12 @@ from uuid import uuid4 from datetime import datetime, timezone -from sqlalchemy import Column, UUID, DateTime, String, JSON -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, DateTime, String, JSON +from cognee.infrastructure.databases.relational import Base, UUID class TaskRun(Base): __tablename__ = "task_runs" - id = Column(UUID(as_uuid = True), primary_key = True, default = uuid4) + id = Column(UUID, primary_key = True, default = uuid4) task_name = Column(String) diff --git a/cognee/modules/users/models/ACL.py b/cognee/modules/users/models/ACL.py index 2bcffcc92..b01fe6010 100644 --- a/cognee/modules/users/models/ACL.py +++ b/cognee/modules/users/models/ACL.py @@ -1,20 +1,20 @@ from uuid import uuid4 from datetime import datetime, timezone from sqlalchemy.orm import relationship, Mapped -from sqlalchemy import Column, ForeignKey, DateTime, UUID -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, ForeignKey, DateTime +from cognee.infrastructure.databases.relational import Base, UUID from .ACLResources import ACLResources class ACL(Base): __tablename__ = "acls" - id = Column(UUID(as_uuid = True), primary_key = True, default = uuid4) + id = Column(UUID, primary_key = True, default = uuid4) created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) updated_at = Column(DateTime(timezone = True), onupdate = lambda: datetime.now(timezone.utc)) - principal_id = Column(UUID(as_uuid = True), ForeignKey("principals.id")) - permission_id = Column(UUID(as_uuid = True), ForeignKey("permissions.id")) + principal_id = Column(UUID, ForeignKey("principals.id")) + permission_id = Column(UUID, ForeignKey("permissions.id")) principal = relationship("Principal") permission = relationship("Permission") diff --git a/cognee/modules/users/models/ACLResources.py b/cognee/modules/users/models/ACLResources.py index 73d0a22fc..268d4a75a 100644 --- a/cognee/modules/users/models/ACLResources.py +++ b/cognee/modules/users/models/ACLResources.py @@ -1,11 +1,11 @@ from datetime import datetime, timezone -from sqlalchemy import Column, ForeignKey, UUID, DateTime -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, ForeignKey, DateTime +from cognee.infrastructure.databases.relational import Base, UUID class ACLResources(Base): __tablename__ = "acl_resources" created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) - acl_id = Column(UUID(as_uuid = True), ForeignKey("acls.id"), primary_key = True) - resource_id = Column(UUID(as_uuid = True), ForeignKey("resources.id"), primary_key = True) + acl_id = Column(UUID, ForeignKey("acls.id"), primary_key = True) + resource_id = Column(UUID, ForeignKey("resources.id"), primary_key = True) diff --git a/cognee/modules/users/models/Group.py b/cognee/modules/users/models/Group.py index 19b93443d..d86dbee90 100644 --- a/cognee/modules/users/models/Group.py +++ b/cognee/modules/users/models/Group.py @@ -1,12 +1,13 @@ from sqlalchemy.orm import relationship, Mapped -from sqlalchemy import Column, String, ForeignKey, UUID +from sqlalchemy import Column, String, ForeignKey +from cognee.infrastructure.databases.relational import UUID from .Principal import Principal from .UserGroup import UserGroup class Group(Principal): __tablename__ = "groups" - id = Column(UUID(as_uuid = True), ForeignKey("principals.id"), primary_key = True) + id = Column(UUID, ForeignKey("principals.id"), primary_key = True) name = Column(String, unique = True, nullable = False, index = True) diff --git a/cognee/modules/users/models/Permission.py b/cognee/modules/users/models/Permission.py index 44d719f99..84b1a3077 100644 --- a/cognee/modules/users/models/Permission.py +++ b/cognee/modules/users/models/Permission.py @@ -1,8 +1,8 @@ from uuid import uuid4 from datetime import datetime, timezone # from sqlalchemy.orm import relationship -from sqlalchemy import Column, DateTime, UUID, String -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, DateTime, String +from cognee.infrastructure.databases.relational import Base, UUID class Permission(Base): __tablename__ = "permissions" diff --git a/cognee/modules/users/models/Principal.py b/cognee/modules/users/models/Principal.py index b5f14a428..4ef91ffac 100644 --- a/cognee/modules/users/models/Principal.py +++ b/cognee/modules/users/models/Principal.py @@ -1,12 +1,12 @@ from uuid import uuid4 from datetime import datetime, timezone -from sqlalchemy import Column, String, DateTime, UUID -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, String, DateTime +from cognee.infrastructure.databases.relational import Base, UUID class Principal(Base): __tablename__ = "principals" - id = Column(UUID(as_uuid = True), primary_key = True, index = True, default = uuid4) + id = Column(UUID, primary_key = True, index = True, default = uuid4) created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) updated_at = Column(DateTime(timezone = True), onupdate = lambda: datetime.now(timezone.utc)) diff --git a/cognee/modules/users/models/Resource.py b/cognee/modules/users/models/Resource.py index bc9e14023..0eca509a2 100644 --- a/cognee/modules/users/models/Resource.py +++ b/cognee/modules/users/models/Resource.py @@ -1,18 +1,18 @@ from uuid import uuid4 from datetime import datetime, timezone from sqlalchemy.orm import relationship -from sqlalchemy import Column, DateTime, UUID -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, DateTime +from cognee.infrastructure.databases.relational import Base, UUID from .ACLResources import ACLResources class Resource(Base): __tablename__ = "resources" - id = Column(UUID(as_uuid = True), primary_key = True, default = uuid4) + id = Column(UUID, primary_key = True, default = uuid4) created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) updated_at = Column(DateTime(timezone = True), onupdate = lambda: datetime.now(timezone.utc)) - resource_id = Column(UUID(as_uuid = True), nullable = False) + resource_id = Column(UUID, nullable = False) acls = relationship("ACL", secondary = ACLResources.__tablename__, back_populates = "resources") diff --git a/cognee/modules/users/models/User.py b/cognee/modules/users/models/User.py index 4e792bbd5..c85abaec7 100644 --- a/cognee/modules/users/models/User.py +++ b/cognee/modules/users/models/User.py @@ -1,14 +1,15 @@ from uuid import UUID as uuid_UUID -from sqlalchemy import ForeignKey, UUID, Column +from sqlalchemy import ForeignKey, Column from sqlalchemy.orm import relationship, Mapped from fastapi_users.db import SQLAlchemyBaseUserTableUUID +from cognee.infrastructure.databases.relational import UUID from .Principal import Principal from .UserGroup import UserGroup class User(SQLAlchemyBaseUserTableUUID, Principal): __tablename__ = "users" - id = Column(UUID(as_uuid = True), ForeignKey("principals.id"), primary_key = True) + id = Column(UUID, ForeignKey("principals.id"), primary_key = True) groups: Mapped[list["Group"]] = relationship( secondary = UserGroup.__tablename__, diff --git a/cognee/modules/users/models/UserGroup.py b/cognee/modules/users/models/UserGroup.py index 0bb6cf657..a2dfa8bc1 100644 --- a/cognee/modules/users/models/UserGroup.py +++ b/cognee/modules/users/models/UserGroup.py @@ -1,11 +1,11 @@ from datetime import datetime, timezone -from sqlalchemy import Column, ForeignKey, DateTime, UUID -from cognee.infrastructure.databases.relational import Base +from sqlalchemy import Column, ForeignKey, DateTime +from cognee.infrastructure.databases.relational import Base, UUID class UserGroup(Base): __tablename__ = "user_groups" created_at = Column(DateTime(timezone = True), default = lambda: datetime.now(timezone.utc)) - user_id = Column(UUID(as_uuid = True), ForeignKey("users.id"), primary_key = True) - group_id = Column(UUID(as_uuid = True), ForeignKey("groups.id"), primary_key = True) + user_id = Column(UUID, ForeignKey("users.id"), primary_key = True) + group_id = Column(UUID, ForeignKey("groups.id"), primary_key = True) diff --git a/poetry.lock 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["postgres"], version = "^0.5.2"} -duckdb = {version = "^0.10.0", extras = ["dlt"]} +dlt = {extras = ["sqlalchemy"], version = "^1.0.0"} overrides = "^7.7.0" aiofiles = "^23.2.1" qdrant-client = "^1.9.0" -duckdb-engine = "0.13.0" graphistry = "^0.33.5" tenacity = "^8.2.3" weaviate-client = "4.6.7" @@ -75,14 +73,12 @@ asyncpg = "^0.29.0" [tool.poetry.extras] -duckdb = ["duckdb"] filesystem = ["s3fs", "botocore"] -motherduck = ["duckdb"] cli = ["pipdeptree", "cron-descriptor"] weaviate = ["weaviate-client"] qdrant = ["qdrant-client"] -neo4j = ["neo4j", "py2neo"] -notebook = ["ipykernel","overrides", "ipywidgets", "jupyterlab", "jupyterlab_widgets", "jupyterlab-server", "jupyterlab-git"] +neo4j = ["neo4j"] +notebook = ["ipykernel", "overrides", "ipywidgets", "jupyterlab", "jupyterlab_widgets", "jupyterlab-server", "jupyterlab-git"] [tool.poetry.group.dev.dependencies] pytest = "^7.4.0" From 6a0e017155312740fd5a49d58c0037179bdc4fe7 Mon Sep 17 00:00:00 2001 From: Boris Arzentar Date: Wed, 18 Sep 2024 11:41:06 +0200 Subject: [PATCH 2/8] fix: change adding points to qdrant after update --- cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py b/cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py index 7e4b39f10..cc6d80b27 100644 --- a/cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py +++ b/cognee/infrastructure/databases/vector/qdrant/QDrantAdapter.py @@ -106,11 +106,10 @@ def convert_to_qdrant_point(data_point: DataPoint): points = [convert_to_qdrant_point(point) for point in data_points] try: - result = await client.upload_points( + client.upload_points( collection_name = collection_name, points = points ) - return result except Exception as error: logger.error("Error uploading data points to Qdrant: %s", str(error)) raise error From 0b9656b5bb7fbf4df4e782c72b85cd932f0c5193 Mon Sep 17 00:00:00 2001 From: Vasilije <8619304+Vasilije1990@users.noreply.github.com> Date: Wed, 18 Sep 2024 16:24:32 +0200 Subject: [PATCH 3/8] Fix bug with single input --- cognee/modules/data/methods/get_datasets_by_name.py | 2 ++ 1 file changed, 2 insertions(+) diff --git a/cognee/modules/data/methods/get_datasets_by_name.py b/cognee/modules/data/methods/get_datasets_by_name.py index c94434443..f562268ce 100644 --- a/cognee/modules/data/methods/get_datasets_by_name.py +++ b/cognee/modules/data/methods/get_datasets_by_name.py @@ -7,6 +7,8 @@ async def get_datasets_by_name(dataset_names: list[str], user_id: UUID) -> list[ db_engine = get_relational_engine() async with db_engine.get_async_session() as session: + if isinstance(dataset_names, str): + dataset_names = [dataset_names] datasets = (await session.scalars( select(Dataset) .filter(Dataset.owner_id == user_id) From b818e36896431b63849f09db817d4efd7878da36 Mon Sep 17 00:00:00 2001 From: Vasilije <8619304+Vasilije1990@users.noreply.github.com> Date: Fri, 20 Sep 2024 07:33:02 +0200 Subject: [PATCH 4/8] Fix the demo, update Readme --- README.md | 174 ++++------ notebooks/cognee_demo_1.5.ipynb | 584 ++++++++++++++++++++++++++++++++ 2 files changed, 650 insertions(+), 108 deletions(-) create mode 100644 notebooks/cognee_demo_1.5.ipynb diff --git a/README.md b/README.md index e51442b63..bf883ec16 100644 --- a/README.md +++ b/README.md @@ -18,24 +18,12 @@ We build for developers who need a reliable, production-ready data layer for AI

-cognee implements scalable, modular data pipelines that allow for creating the LLM-enriched data layer using graph and vector stores. - - - - - - -

- cognee aims to be dbt for LLMOps -

- +## What is cognee? +cognee implements scalable, modular ECL (Extract, Cognify, Load) pipelines that allow you ability to interconnect and retrieve past conversations, documents, audio transcriptions, while also reducing hallucinations, developer effort and cost. Try it in a Google collab notebook or have a look at our documentation - - - If you have questions, join our Discord community @@ -58,7 +46,7 @@ poetry add cognee ``` -## 💻 Usage +## 💻 Basic Usage ### Setup @@ -75,24 +63,6 @@ cognee.config.llm_api_key = "YOUR_OPENAI_API_KEY" ``` You can use different LLM providers, for more info check out our documentation -In the next step make sure to launch a Postgres instance. Here is an example from our docker-compose: -``` - postgres: - image: postgres:latest - container_name: postgres - environment: - POSTGRES_USER: cognee - POSTGRES_PASSWORD: cognee - POSTGRES_DB: cognee_db - volumes: - - postgres_data:/var/lib/postgresql/data - ports: - - 5432:5432 - networks: - - cognee-network -``` - - If you are using Networkx, create an account on Graphistry to visualize results: ``` @@ -106,12 +76,7 @@ docker-compose up cognee ``` Then navigate to localhost:3000/wizard -### Run the default example - -Make sure to launch the Postgres instance first. Navigate to the cognee folder and run: -``` -docker compose up postgres -``` +### Simple example Run the default cognee pipeline: @@ -123,7 +88,7 @@ text = """Natural language processing (NLP) is an interdisciplinary await cognee.add([text], "example_dataset") # Add a new piece of information -await cognee.cognify() # Use LLMs and cognee to create knowledge +await cognee.cognify() # Use LLMs and cognee to create a semantic graph await search_results = cognee.search("SIMILARITY", {'query': 'Tell me about NLP'}) # Query cognee for the knowledge @@ -132,19 +97,20 @@ print(search_results) ``` -### Create your pipelines +### Create your own memory store + +cognee framework consists of tasks that can be grouped into pipelines. +Each task can be an independent part of business logic, that can be tied to other tasks to form a pipeline. +These tasks persist data into your memory store enabling you to search for relevant context of past conversations, documents, or any other data you have stored. -cognee framework consists of tasks that can be grouped into pipelines. Each task can be an independent part of business logic, that can be tied to other tasks to form a pipeline. -Here is an example of how it looks for a default cognify pipeline: +### Example: Classify your documents + +Here is an example of how it looks for a default cognify pipeline: 1. To prepare the data for the pipeline run, first we need to add it to our metastore and normalize it: -Start with: -``` -docker compose up postgres -``` -And then run: +Start with: ``` text = """Natural language processing (NLP) is an interdisciplinary subfield of computer science and information retrieval""" @@ -158,90 +124,62 @@ Here we show an example of creating a naive LLM classifier that takes a Pydantic We provided just a snippet for reference, but feel free to check out the implementation in our repo. ``` -async def chunk_naive_llm_classifier(data_chunks: list[DocumentChunk], classification_model: Type[BaseModel]): - if len(data_chunks) == 0: - return data_chunks - +async def chunk_naive_llm_classifier( + data_chunks: list[DocumentChunk], + classification_model: Type[BaseModel] +): + # Extract classifications asynchronously chunk_classifications = await asyncio.gather( - *[extract_categories(chunk.text, classification_model) for chunk in data_chunks], + *(extract_categories(chunk.text, classification_model) for chunk in data_chunks) ) - classification_data_points = [] - - for chunk_index, chunk in enumerate(data_chunks): - chunk_classification = chunk_classifications[chunk_index] - classification_data_points.append(uuid5(NAMESPACE_OID, chunk_classification.label.type)) - classification_data_points.append(uuid5(NAMESPACE_OID, chunk_classification.label.type)) - - for classification_subclass in chunk_classification.label.subclass: - classification_data_points.append(uuid5(NAMESPACE_OID, classification_subclass.value)) + # Collect classification data points using a set to avoid duplicates + classification_data_points = { + uuid5(NAMESPACE_OID, cls.label.type) + for cls in chunk_classifications + } | { + uuid5(NAMESPACE_OID, subclass.value) + for cls in chunk_classifications + for subclass in cls.label.subclass + } vector_engine = get_vector_engine() + collection_name = "classification" + # Define the payload schema class Keyword(BaseModel): uuid: str text: str chunk_id: str document_id: str - collection_name = "classification" - - if await vector_engine.has_collection(collection_name): - existing_data_points = await vector_engine.retrieve( - collection_name, - list(set(classification_data_points)), - ) if len(classification_data_points) > 0 else [] - - existing_points_map = {point.id: True for point in existing_data_points} + # Ensure the collection exists and retrieve existing data points + if not await vector_engine.has_collection(collection_name): + await vector_engine.create_collection(collection_name, payload_schema=Keyword) + existing_points_map = {} else: existing_points_map = {} - await vector_engine.create_collection(collection_name, payload_schema=Keyword) - - data_points = [] - nodes = [] - edges = [] - - for (chunk_index, data_chunk) in enumerate(data_chunks): - chunk_classification = chunk_classifications[chunk_index] - classification_type_label = chunk_classification.label.type - classification_type_id = uuid5(NAMESPACE_OID, classification_type_label) + return data_chunks ... ``` -To see existing tasks, have a look at the cognee.tasks +We have a large number of tasks that can be used in your pipelines, and you can also create your own tasks to fit your business logic. 3. Once we have our tasks, it is time to group them into a pipeline. -This snippet shows how a group of tasks can be added to a pipeline, and how they can pass the information forward from one to another. +This simplified snippet demonstrates how tasks can be added to a pipeline, and how they can pass the information forward from one to another. ``` - tasks = [ - Task(document_to_ontology, root_node_id = root_node_id), - Task(source_documents_to_chunks, parent_node_id = root_node_id), # Classify documents and save them as a nodes in graph db, extract text chunks based on the document type - Task(chunk_to_graph_decomposition, topology_model = KnowledgeGraph, task_config = { "batch_size": 10 }), # Set the graph topology for the document chunk data - Task(chunks_into_graph, graph_model = KnowledgeGraph, collection_name = "entities"), # Generate knowledge graphs from the document chunks and attach it to chunk nodes - Task(chunk_update_check, collection_name = "chunks"), # Find all affected chunks, so we don't process unchanged chunks - Task( - save_chunks_to_store, - collection_name = "chunks", - ), # Save the document chunks in vector db and as nodes in graph db (connected to the document node and between each other) - run_tasks_parallel([ - Task( - chunk_extract_summary, - summarization_model = cognee_config.summarization_model, - collection_name = "chunk_summaries", - ), # Summarize the document chunks - Task( - chunk_naive_llm_classifier, - classification_model = cognee_config.classification_model, - ), - ]), - Task(chunk_remove_disconnected), # Remove the obsolete document chunks. - ] - - pipeline = run_tasks(tasks, documents) + + +Task( + chunk_naive_llm_classifier, + classification_model = cognee_config.classification_model, +) + +pipeline = run_tasks(tasks, documents) ``` @@ -277,3 +215,23 @@ Check out our demo notebook [here](https://github.com/topoteretes/cognee/blob/ma [![Star History Chart](https://api.star-history.com/svg?repos=topoteretes/cognee&type=Date)](https://star-history.com/#topoteretes/cognee&Date) + +## Get Started + +### Install Server + +Please see the [cognee Quick Start Guide](https://topoteretes.github.io/cognee/quickstart/) for important configuration information. + +```bash +docker compose up +``` + + + +### Install SDK + +Please see the cognee [Develoment Guide](https://topoteretes.github.io/cognee/quickstart/) for important beta information and usage instructions. + +```bash +pip install cognee +``` diff --git a/notebooks/cognee_demo_1.5.ipynb b/notebooks/cognee_demo_1.5.ipynb new file mode 100644 index 000000000..32d977ed7 --- /dev/null +++ b/notebooks/cognee_demo_1.5.ipynb @@ -0,0 +1,584 @@ +{ + "cells": [ + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:11:39.250021Z", + "start_time": "2024-09-20T05:11:30.139927Z" + } + }, + "cell_type": "code", + "source": [ + "import asyncio\n", + "import logging\n", + "from typing import Union\n", + "\n", + "from cognee.modules.cognify.config import get_cognify_config\n", + "from cognee.shared.data_models import KnowledgeGraph\n", + "from cognee.modules.data.models import Dataset, Data\n", + "from cognee.modules.data.methods.get_dataset_data import get_dataset_data\n", + "from cognee.modules.data.methods import get_datasets, get_datasets_by_name\n", + "from cognee.modules.pipelines.tasks.Task import Task\n", + "from cognee.modules.pipelines import run_tasks, run_tasks_parallel\n", + "from cognee.modules.users.models import User\n", + "from cognee.modules.users.methods import get_default_user\n", + "from cognee.modules.pipelines.operations.get_pipeline_status import get_pipeline_status\n", + "from cognee.modules.pipelines.operations.log_pipeline_status import log_pipeline_status\n", + "from cognee.tasks import chunk_extract_summary, \\\n", + " chunk_naive_llm_classifier, \\\n", + " chunk_remove_disconnected, \\\n", + " infer_data_ontology, \\\n", + " save_chunks_to_store, \\\n", + " chunk_update_check, \\\n", + " chunks_into_graph, \\\n", + " source_documents_to_chunks, \\\n", + " check_permissions_on_documents, \\\n", + " classify_documents\n", + "\n", + "logger = logging.getLogger(\"cognify.v2\")\n", + "\n", + "update_status_lock = asyncio.Lock()" + ], + "id": "958375a6ffc0c2e4", + "outputs": [], + "execution_count": 1 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:11:44.669755Z", + "start_time": "2024-09-20T05:11:44.666218Z" + } + }, + "cell_type": "code", + "source": [ + "job_position = \"\"\"Senior Data Scientist (Machine Learning)\n", + "\n", + "Company: TechNova Solutions\n", + "Location: San Francisco, CA\n", + "\n", + "Job Description:\n", + "\n", + "TechNova Solutions is seeking a Senior Data Scientist specializing in Machine Learning to join our dynamic analytics team. The ideal candidate will have a strong background in developing and deploying machine learning models, working with large datasets, and translating complex data into actionable insights.\n", + "\n", + "Responsibilities:\n", + "\n", + "Develop and implement advanced machine learning algorithms and models.\n", + "Analyze large, complex datasets to extract meaningful patterns and insights.\n", + "Collaborate with cross-functional teams to integrate predictive models into products.\n", + "Stay updated with the latest advancements in machine learning and data science.\n", + "Mentor junior data scientists and provide technical guidance.\n", + "Qualifications:\n", + "\n", + "Master’s or Ph.D. in Data Science, Computer Science, Statistics, or a related field.\n", + "5+ years of experience in data science and machine learning.\n", + "Proficient in Python, R, and SQL.\n", + "Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).\n", + "Strong problem-solving skills and attention to detail.\n", + "Candidate CVs\n", + "\"\"\"\n" + ], + "id": "df16431d0f48b006", + "outputs": [], + "execution_count": 3 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:11:45.277312Z", + "start_time": "2024-09-20T05:11:45.272644Z" + } + }, + "cell_type": "code", + "source": [ + "job_1 = \"\"\"\n", + "CV 1: Relevant\n", + "Name: Dr. Emily Carter\n", + "Contact Information:\n", + "\n", + "Email: emily.carter@example.com\n", + "Phone: (555) 123-4567\n", + "Summary:\n", + "\n", + "Senior Data Scientist with over 8 years of experience in machine learning and predictive analytics. Expertise in developing advanced algorithms and deploying scalable models in production environments.\n", + "\n", + "Education:\n", + "\n", + "Ph.D. in Computer Science, Stanford University (2014)\n", + "B.S. in Mathematics, University of California, Berkeley (2010)\n", + "Experience:\n", + "\n", + "Senior Data Scientist, InnovateAI Labs (2016 – Present)\n", + "Led a team in developing machine learning models for natural language processing applications.\n", + "Implemented deep learning algorithms that improved prediction accuracy by 25%.\n", + "Collaborated with cross-functional teams to integrate models into cloud-based platforms.\n", + "Data Scientist, DataWave Analytics (2014 – 2016)\n", + "Developed predictive models for customer segmentation and churn analysis.\n", + "Analyzed large datasets using Hadoop and Spark frameworks.\n", + "Skills:\n", + "\n", + "Programming Languages: Python, R, SQL\n", + "Machine Learning: TensorFlow, Keras, Scikit-Learn\n", + "Big Data Technologies: Hadoop, Spark\n", + "Data Visualization: Tableau, Matplotlib\n", + "\"\"\"" + ], + "id": "9086abf3af077ab4", + "outputs": [], + "execution_count": 4 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:11:45.753246Z", + "start_time": "2024-09-20T05:11:45.751035Z" + } + }, + "cell_type": "code", + "source": [ + "job_2 = \"\"\"\n", + "CV 2: Relevant\n", + "Name: Michael Rodriguez\n", + "Contact Information:\n", + "\n", + "Email: michael.rodriguez@example.com\n", + "Phone: (555) 234-5678\n", + "Summary:\n", + "\n", + "Data Scientist with a strong background in machine learning and statistical modeling. Skilled in handling large datasets and translating data into actionable business insights.\n", + "\n", + "Education:\n", + "\n", + "M.S. in Data Science, Carnegie Mellon University (2013)\n", + "B.S. in Computer Science, University of Michigan (2011)\n", + "Experience:\n", + "\n", + "Senior Data Scientist, Alpha Analytics (2017 – Present)\n", + "Developed machine learning models to optimize marketing strategies.\n", + "Reduced customer acquisition cost by 15% through predictive modeling.\n", + "Data Scientist, TechInsights (2013 – 2017)\n", + "Analyzed user behavior data to improve product features.\n", + "Implemented A/B testing frameworks to evaluate product changes.\n", + "Skills:\n", + "\n", + "Programming Languages: Python, Java, SQL\n", + "Machine Learning: Scikit-Learn, XGBoost\n", + "Data Visualization: Seaborn, Plotly\n", + "Databases: MySQL, MongoDB\n", + "\"\"\"" + ], + "id": "a9de0cc07f798b7f", + "outputs": [], + "execution_count": 5 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:11:46.238147Z", + "start_time": "2024-09-20T05:11:46.235463Z" + } + }, + "cell_type": "code", + "source": [ + "job_3 = \"\"\"\n", + "CV 3: Relevant\n", + "Name: Sarah Nguyen\n", + "Contact Information:\n", + "\n", + "Email: sarah.nguyen@example.com\n", + "Phone: (555) 345-6789\n", + "Summary:\n", + "\n", + "Data Scientist specializing in machine learning with 6 years of experience. Passionate about leveraging data to drive business solutions and improve product performance.\n", + "\n", + "Education:\n", + "\n", + "M.S. in Statistics, University of Washington (2014)\n", + "B.S. in Applied Mathematics, University of Texas at Austin (2012)\n", + "Experience:\n", + "\n", + "Data Scientist, QuantumTech (2016 – Present)\n", + "Designed and implemented machine learning algorithms for financial forecasting.\n", + "Improved model efficiency by 20% through algorithm optimization.\n", + "Junior Data Scientist, DataCore Solutions (2014 – 2016)\n", + "Assisted in developing predictive models for supply chain optimization.\n", + "Conducted data cleaning and preprocessing on large datasets.\n", + "Skills:\n", + "\n", + "Programming Languages: Python, R\n", + "Machine Learning Frameworks: PyTorch, Scikit-Learn\n", + "Statistical Analysis: SAS, SPSS\n", + "Cloud Platforms: AWS, Azure\n", + "\"\"\"" + ], + "id": "185ff1c102d06111", + "outputs": [], + "execution_count": 6 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:11:46.706952Z", + "start_time": "2024-09-20T05:11:46.705079Z" + } + }, + "cell_type": "code", + "source": [ + "job_4 = \"\"\"\n", + "CV 4: Not Relevant\n", + "Name: David Thompson\n", + "Contact Information:\n", + "\n", + "Email: david.thompson@example.com\n", + "Phone: (555) 456-7890\n", + "Summary:\n", + "\n", + "Creative Graphic Designer with over 8 years of experience in visual design and branding. Proficient in Adobe Creative Suite and passionate about creating compelling visuals.\n", + "\n", + "Education:\n", + "\n", + "B.F.A. in Graphic Design, Rhode Island School of Design (2012)\n", + "Experience:\n", + "\n", + "Senior Graphic Designer, CreativeWorks Agency (2015 – Present)\n", + "Led design projects for clients in various industries.\n", + "Created branding materials that increased client engagement by 30%.\n", + "Graphic Designer, Visual Innovations (2012 – 2015)\n", + "Designed marketing collateral, including brochures, logos, and websites.\n", + "Collaborated with the marketing team to develop cohesive brand strategies.\n", + "Skills:\n", + "\n", + "Design Software: Adobe Photoshop, Illustrator, InDesign\n", + "Web Design: HTML, CSS\n", + "Specialties: Branding and Identity, Typography\n", + "\"\"\"" + ], + "id": "d55ce4c58f8efb67", + "outputs": [], + "execution_count": 7 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:11:47.329735Z", + "start_time": "2024-09-20T05:11:47.326711Z" + } + }, + "cell_type": "code", + "source": [ + "job_5 = \"\"\"\n", + "CV 5: Not Relevant\n", + "Name: Jessica Miller\n", + "Contact Information:\n", + "\n", + "Email: jessica.miller@example.com\n", + "Phone: (555) 567-8901\n", + "Summary:\n", + "\n", + "Experienced Sales Manager with a strong track record in driving sales growth and building high-performing teams. Excellent communication and leadership skills.\n", + "\n", + "Education:\n", + "\n", + "B.A. in Business Administration, University of Southern California (2010)\n", + "Experience:\n", + "\n", + "Sales Manager, Global Enterprises (2015 – Present)\n", + "Managed a sales team of 15 members, achieving a 20% increase in annual revenue.\n", + "Developed sales strategies that expanded customer base by 25%.\n", + "Sales Representative, Market Leaders Inc. (2010 – 2015)\n", + "Consistently exceeded sales targets and received the 'Top Salesperson' award in 2013.\n", + "Skills:\n", + "\n", + "Sales Strategy and Planning\n", + "Team Leadership and Development\n", + "CRM Software: Salesforce, Zoho\n", + "Negotiation and Relationship Building\n", + "\"\"\"" + ], + "id": "ca4ecc32721ad332", + "outputs": [], + "execution_count": 8 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:11:50.271409Z", + "start_time": "2024-09-20T05:11:48.529182Z" + } + }, + "cell_type": "code", + "source": [ + "import cognee\n", + "from os import listdir, path\n", + "\n", + "data_path = path.abspath(\".data\")\n", + "\n", + "results = await cognee.add([job_1, job_2,job_3,job_4,job_5,job_position], \"example\")\n", + "\n", + "for result in results:\n", + " print(result)" + ], + "id": "904df61ba484a8e5", + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "sys:1: SAWarning: TypeDecorator UUID() will not produce a cache key because the ``cache_ok`` attribute is not set to True. This can have significant performance implications including some performance degradations in comparison to prior SQLAlchemy versions. Set this attribute to True if this type object's state is safe to use in a cache key, or False to disable this warning. (Background on this warning at: https://sqlalche.me/e/20/cprf)\n", + "2024-09-20 07:11:48,925|[WARNING]|43272|8480345088|dlt|utils.py|resolve_merge_strategy:223|Destination does not support any merge strategies and `merge` write disposition for table `file_metadata` cannot be met and will fall back to `append`. Change write disposition.2024-09-20 07:11:49,246|[WARNING]|43272|8480345088|dlt|utils.py|resolve_merge_strategy:223|Destination does not support any merge strategies and `merge` write disposition for table `file_metadata` cannot be met and will fall back to `append`. Change write disposition." + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "{'1726809108.767254': [{'started_at': DateTime(2024, 9, 20, 5, 11, 49, 245902, tzinfo=Timezone('UTC')), 'finished_at': DateTime(2024, 9, 20, 5, 11, 50, 268147, tzinfo=Timezone('UTC')), 'job_metrics': {'_dlt_pipeline_state.a91de88b58.typed-jsonl': LoadJobMetrics(job_id='_dlt_pipeline_state.a91de88b58.typed-jsonl', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/normalized/1726809108.767254/started_jobs/_dlt_pipeline_state.a91de88b58.0.typed-jsonl', table_name='_dlt_pipeline_state', started_at=DateTime(2024, 9, 20, 5, 11, 49, 256768, tzinfo=Timezone('UTC')), finished_at=DateTime(2024, 9, 20, 5, 11, 49, 258007, tzinfo=Timezone('UTC')), state='completed', remote_url=None), 'file_metadata.a639414384.typed-jsonl': LoadJobMetrics(job_id='file_metadata.a639414384.typed-jsonl', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/normalized/1726809108.767254/started_jobs/file_metadata.a639414384.0.typed-jsonl', table_name='file_metadata', started_at=DateTime(2024, 9, 20, 5, 11, 49, 257362, tzinfo=Timezone('UTC')), finished_at=DateTime(2024, 9, 20, 5, 11, 49, 259366, tzinfo=Timezone('UTC')), state='completed', remote_url=None)}}]}\n", + "dlt.destinations.sqlalchemy\n", + "sqlite:///cognee_db\n", + "sqlalchemy\n", + "None\n", + "None\n", + "None\n", + "None\n", + "\n", + "example\n", + "['1726809108.767254']\n", + "[LoadPackageInfo(load_id='1726809108.767254', package_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726809108.767254', state='loaded', schema=Schema file_load_from_filesystem at 6016359056, schema_update={'_dlt_loads': {'name': '_dlt_loads', 'columns': {'load_id': {'name': 'load_id', 'data_type': 'text', 'nullable': False}, 'schema_name': {'name': 'schema_name', 'data_type': 'text', 'nullable': True}, 'status': {'name': 'status', 'data_type': 'bigint', 'nullable': False}, 'inserted_at': {'name': 'inserted_at', 'data_type': 'timestamp', 'nullable': False}, 'schema_version_hash': {'name': 'schema_version_hash', 'data_type': 'text', 'nullable': True}}, 'write_disposition': 'skip', 'resource': '_dlt_loads', 'description': 'Created by DLT. Tracks completed loads'}, 'file_metadata': {'columns': {'id': {'name': 'id', 'nullable': False, 'merge_key': True, 'data_type': 'text'}, 'name': {'name': 'name', 'data_type': 'text', 'nullable': True}, 'file_path': {'name': 'file_path', 'data_type': 'text', 'nullable': True}, 'extension': {'name': 'extension', 'data_type': 'text', 'nullable': True}, 'mime_type': {'name': 'mime_type', 'data_type': 'text', 'nullable': True}, '_dlt_load_id': {'name': '_dlt_load_id', 'data_type': 'text', 'nullable': False}, '_dlt_id': {'name': '_dlt_id', 'data_type': 'text', 'nullable': False, 'unique': True, 'row_key': True}}, 'name': 'file_metadata', 'write_disposition': 'merge', 'resource': 'data_resources', 'x-normalizer': {'seen-data': True}}, '_dlt_pipeline_state': {'columns': {'version': {'name': 'version', 'data_type': 'bigint', 'nullable': False}, 'engine_version': {'name': 'engine_version', 'data_type': 'bigint', 'nullable': False}, 'pipeline_name': {'name': 'pipeline_name', 'data_type': 'text', 'nullable': False}, 'state': {'name': 'state', 'data_type': 'text', 'nullable': False}, 'created_at': {'name': 'created_at', 'data_type': 'timestamp', 'nullable': False}, 'version_hash': {'name': 'version_hash', 'data_type': 'text', 'nullable': True}, '_dlt_load_id': {'name': '_dlt_load_id', 'data_type': 'text', 'nullable': False}, '_dlt_id': {'name': '_dlt_id', 'data_type': 'text', 'nullable': False, 'unique': True, 'row_key': True}}, 'write_disposition': 'append', 'file_format': 'preferred', 'name': '_dlt_pipeline_state', 'resource': '_dlt_pipeline_state', 'x-normalizer': {'seen-data': True}}, '_dlt_version': {'name': '_dlt_version', 'columns': {'version': {'name': 'version', 'data_type': 'bigint', 'nullable': False}, 'engine_version': {'name': 'engine_version', 'data_type': 'bigint', 'nullable': False}, 'inserted_at': {'name': 'inserted_at', 'data_type': 'timestamp', 'nullable': False}, 'schema_name': {'name': 'schema_name', 'data_type': 'text', 'nullable': False}, 'version_hash': {'name': 'version_hash', 'data_type': 'text', 'nullable': False}, 'schema': {'name': 'schema', 'data_type': 'text', 'nullable': False}}, 'write_disposition': 'skip', 'resource': '_dlt_version', 'description': 'Created by DLT. Tracks schema updates'}}, completed_at=DateTime(2024, 9, 20, 5, 11, 50, 264990, tzinfo=Timezone('UTC')), jobs={'completed_jobs': [LoadJobInfo(state='completed_jobs', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726809108.767254/completed_jobs/_dlt_pipeline_state.a91de88b58.0.typed-jsonl', file_size=514, created_at=DateTime(2024, 9, 20, 5, 11, 48, 927162, tzinfo=Timezone('UTC')), elapsed=1.3378276824951172, job_file_info=ParsedLoadJobFileName(table_name='_dlt_pipeline_state', file_id='a91de88b58', retry_count=0, file_format='typed-jsonl'), failed_message=None), LoadJobInfo(state='completed_jobs', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726809108.767254/completed_jobs/file_metadata.a639414384.0.typed-jsonl', file_size=668, created_at=DateTime(2024, 9, 20, 5, 11, 48, 927453, tzinfo=Timezone('UTC')), elapsed=1.3375375270843506, job_file_info=ParsedLoadJobFileName(table_name='file_metadata', file_id='a639414384', retry_count=0, file_format='typed-jsonl'), failed_message=None)], 'started_jobs': [], 'new_jobs': [], 'failed_jobs': []})]\n", + "True\n" + ] + } + ], + "execution_count": 9 + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": [ + "from typing import Any, Dict, List, Optional, Union\n", + "from pydantic import BaseModel, Field\n", + "from uuid import uuid4\n", + "\n", + "class Node(BaseModel):\n", + " \"\"\"Node in a knowledge graph.\"\"\"\n", + " id: str = Field(default_factory=lambda: str(uuid4()))\n", + " name: Optional[str] = None\n", + " types: List[str] = Field(default_factory=list, description=\"Types or categories of the node (e.g., 'Person', 'Skill').\")\n", + " properties: Dict[str, Any] = Field(default_factory=dict, description=\"Properties associated with the node.\")\n", + "\n", + " def merge(self, other: 'Node'):\n", + " \"\"\"Merge another node into this one.\"\"\"\n", + " # Combine types\n", + " self.types = list(set(self.types + other.types))\n", + " # Combine properties\n", + " self.properties.update(other.properties)\n", + " # Update name if necessary\n", + " if not self.name and other.name:\n", + " self.name = other.name\n", + "\n", + "class Edge(BaseModel):\n", + " \"\"\"Edge in a knowledge graph.\"\"\"\n", + " id: str = Field(default_factory=lambda: str(uuid4()))\n", + " source_node_id: str\n", + " target_node_id: str\n", + " relationship_types: List[str] = Field(default_factory=list, description=\"Types of relationships (e.g., 'has_skill').\")\n", + " properties: Dict[str, Any] = Field(default_factory=dict, description=\"Properties associated with the edge.\")\n", + " confidence: Optional[float] = Field(None, description=\"Confidence score for the relationship.\")\n", + "\n", + "class KnowledgeGraph(BaseModel):\n", + " \"\"\"Knowledge graph.\"\"\"\n", + " nodes: Dict[str, Node] = Field(default_factory=dict)\n", + " edges: List[Edge] = Field(default_factory=list)\n", + "\n", + " def add_node(self, node: Node):\n", + " if node.id in self.nodes:\n", + " self.nodes[node.id].merge(node)\n", + " else:\n", + " self.nodes[node.id] = node\n", + "\n", + " def add_edge(self, edge: Edge):\n", + " self.edges.append(edge)" + ], + "id": "6f9b564de121713d" + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:12:24.360343Z", + "start_time": "2024-09-20T05:12:24.335507Z" + } + }, + "cell_type": "code", + "source": [ + "from enum import Enum, auto\n", + "from typing import Optional, List, Union, Dict, Any\n", + "from pydantic import BaseModel, Field\n", + "\n", + "class Node(BaseModel):\n", + " \"\"\"Node in a knowledge graph.\"\"\"\n", + " id: str\n", + " name: str\n", + " type: str\n", + " description: str\n", + " properties: Optional[Dict[str, Any]] = Field(None, description = \"A dictionary of properties associated with the node.\")\n", + "\n", + "class Edge(BaseModel):\n", + " \"\"\"Edge in a knowledge graph.\"\"\"\n", + " source_node_id: str\n", + " target_node_id: str\n", + " relationship_name: str\n", + " properties: Optional[Dict[str, Any]] = Field(None, description = \"A dictionary of properties associated with the edge.\")\n", + "\n", + "class KnowledgeGraph(BaseModel):\n", + " \"\"\"Knowledge graph.\"\"\"\n", + " nodes: List[Node] = Field(..., default_factory=list)\n", + " edges: List[Edge] = Field(..., default_factory=list)" + ], + "id": "8911f8bd4f8c440a", + "outputs": [], + "execution_count": 10 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:12:25.635711Z", + "start_time": "2024-09-20T05:12:25.631576Z" + } + }, + "cell_type": "code", + "source": [ + "async def run_cognify_pipeline(dataset: Dataset, user: User = None):\n", + " data_documents: list[Data] = await get_dataset_data(dataset_id = dataset.id)\n", + " try:\n", + "\n", + " root_node_id = None\n", + "\n", + " tasks = [\n", + " Task(classify_documents),\n", + " Task(check_permissions_on_documents, user = user, permissions = [\"write\"]),\n", + " Task(source_documents_to_chunks, parent_node_id = root_node_id), # Classify documents and save them as a nodes in graph db, extract text chunks based on the document type\n", + " Task(chunks_into_graph, graph_model = KnowledgeGraph, collection_name = \"entities\", task_config = { \"batch_size\": 10 }), # Generate knowledge graphs from the document chunks and attach it to chunk nodes\n", + " Task(chunk_update_check, collection_name = \"chunks\"), # Find all affected chunks, so we don't process unchanged chunks\n", + " Task(\n", + " save_chunks_to_store,\n", + " collection_name = \"chunks\",\n", + " ), \n", + " Task(chunk_remove_disconnected), # Remove the obsolete document chunks.\n", + " ]\n", + "\n", + " pipeline = run_tasks(tasks, data_documents)\n", + "\n", + " async for result in pipeline:\n", + " print(result)\n", + " except Exception as error:\n", + " raise error" + ], + "id": "7c431fdef4921ae0", + "outputs": [], + "execution_count": 11 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:12:26.489432Z", + "start_time": "2024-09-20T05:12:26.486869Z" + } + }, + "cell_type": "code", + "source": [ + "\n", + "\n", + "async def cognify(datasets: Union[str, list[str]] = None, user: User = None):\n", + " if user is None:\n", + " user = await get_default_user()\n", + "\n", + " existing_datasets = await get_datasets(user.id)\n", + "\n", + " # if datasets is None or len(datasets) == 0:\n", + " # # If no datasets are provided, cognify all existing datasets.\n", + " # datasets = existing_datasets\n", + " # \n", + " # if type(datasets[0]) == str:\n", + " # datasets = await get_datasets_by_name(datasets, user.id)\n", + "\n", + "\n", + "\n", + "\n", + " existing_datasets_map = {\n", + " dataset.name: True for dataset in existing_datasets\n", + " }\n", + "\n", + " awaitables = []\n", + "\n", + " for dataset in datasets:\n", + " dataset_name = dataset.name\n", + "\n", + " if dataset_name in existing_datasets_map:\n", + " awaitables.append(run_cognify_pipeline(dataset, user))\n", + "\n", + " return await asyncio.gather(*awaitables)\n", + "\n" + ], + "id": "e7d4f03f7dab9807", + "outputs": [], + "execution_count": 12 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T05:12:33.605592Z", + "start_time": "2024-09-20T05:12:33.378035Z" + } + }, + "cell_type": "code", + "source": "await cognify(\"example\")", + "id": "d9248a01352964e2", + "outputs": [ + { + "ename": "AttributeError", + "evalue": "'str' object has no attribute 'name'", + "output_type": "error", + "traceback": [ + "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[0;31mAttributeError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[0;32mIn[14], line 1\u001B[0m\n\u001B[0;32m----> 1\u001B[0m \u001B[38;5;28;01mawait\u001B[39;00m cognify(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mexample\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n", + "Cell \u001B[0;32mIn[12], line 24\u001B[0m, in \u001B[0;36mcognify\u001B[0;34m(datasets, user)\u001B[0m\n\u001B[1;32m 21\u001B[0m awaitables \u001B[38;5;241m=\u001B[39m []\n\u001B[1;32m 23\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m dataset \u001B[38;5;129;01min\u001B[39;00m datasets:\n\u001B[0;32m---> 24\u001B[0m dataset_name \u001B[38;5;241m=\u001B[39m \u001B[43mdataset\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mname\u001B[49m\n\u001B[1;32m 26\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m dataset_name \u001B[38;5;129;01min\u001B[39;00m existing_datasets_map:\n\u001B[1;32m 27\u001B[0m awaitables\u001B[38;5;241m.\u001B[39mappend(run_cognify_pipeline(dataset, user))\n", + "\u001B[0;31mAttributeError\u001B[0m: 'str' object has no attribute 'name'" + ] + } + ], + "execution_count": 14 + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "", + "id": "6afc6307bd115dbe" + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From a609716556d018a6cec72a10da4131e5277eac3c Mon Sep 17 00:00:00 2001 From: Vasilije <8619304+Vasilije1990@users.noreply.github.com> Date: Fri, 20 Sep 2024 07:38:05 +0200 Subject: [PATCH 5/8] Fix the demo, update Readme --- notebooks/cognee_demo_1.5.ipynb | 79 ++++++++++++++++++++++++--------- 1 file changed, 57 insertions(+), 22 deletions(-) diff --git a/notebooks/cognee_demo_1.5.ipynb b/notebooks/cognee_demo_1.5.ipynb index 32d977ed7..0b43ae2e6 100644 --- a/notebooks/cognee_demo_1.5.ipynb +++ b/notebooks/cognee_demo_1.5.ipynb @@ -443,20 +443,20 @@ { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:12:25.635711Z", - "start_time": "2024-09-20T05:12:25.631576Z" + "end_time": "2024-09-20T05:36:49.096914Z", + "start_time": "2024-09-20T05:36:49.089721Z" } }, "cell_type": "code", "source": [ "async def run_cognify_pipeline(dataset: Dataset, user: User = None):\n", " data_documents: list[Data] = await get_dataset_data(dataset_id = dataset.id)\n", + "\n", " try:\n", "\n", " root_node_id = None\n", "\n", " tasks = [\n", - " Task(classify_documents),\n", " Task(check_permissions_on_documents, user = user, permissions = [\"write\"]),\n", " Task(source_documents_to_chunks, parent_node_id = root_node_id), # Classify documents and save them as a nodes in graph db, extract text chunks based on the document type\n", " Task(chunks_into_graph, graph_model = KnowledgeGraph, collection_name = \"entities\", task_config = { \"batch_size\": 10 }), # Generate knowledge graphs from the document chunks and attach it to chunk nodes\n", @@ -477,13 +477,13 @@ ], "id": "7c431fdef4921ae0", "outputs": [], - "execution_count": 11 + "execution_count": 25 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:12:26.489432Z", - "start_time": "2024-09-20T05:12:26.486869Z" + "end_time": "2024-09-20T05:36:49.776759Z", + "start_time": "2024-09-20T05:36:49.773859Z" } }, "cell_type": "code", @@ -496,12 +496,12 @@ "\n", " existing_datasets = await get_datasets(user.id)\n", "\n", - " # if datasets is None or len(datasets) == 0:\n", - " # # If no datasets are provided, cognify all existing datasets.\n", - " # datasets = existing_datasets\n", - " # \n", - " # if type(datasets[0]) == str:\n", - " # datasets = await get_datasets_by_name(datasets, user.id)\n", + " if datasets is None or len(datasets) == 0:\n", + " # If no datasets are provided, cognify all existing datasets.\n", + " datasets = existing_datasets\n", + "\n", + " if type(datasets[0]) == str:\n", + " datasets = await get_datasets_by_name(datasets, user.id)\n", "\n", "\n", "\n", @@ -513,6 +513,7 @@ " awaitables = []\n", "\n", " for dataset in datasets:\n", + " # print(\"here is the dataset\", dataset)\n", " dataset_name = dataset.name\n", "\n", " if dataset_name in existing_datasets_map:\n", @@ -523,13 +524,13 @@ ], "id": "e7d4f03f7dab9807", "outputs": [], - "execution_count": 12 + "execution_count": 26 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:12:33.605592Z", - "start_time": "2024-09-20T05:12:33.378035Z" + "end_time": "2024-09-20T05:36:50.641924Z", + "start_time": "2024-09-20T05:36:50.554094Z" } }, "cell_type": "code", @@ -537,19 +538,53 @@ "id": "d9248a01352964e2", "outputs": [ { - "ename": "AttributeError", - "evalue": "'str' object has no attribute 'name'", + "name": "stderr", + "output_type": "stream", + "text": [ + "Error occurred while running async generator task: `source_documents_to_chunks`\n", + "too many values to unpack (expected 2)\n", + "Traceback (most recent call last):\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 26, in run_tasks\n", + " async for partial_result in async_iterator:\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py\", line 9, in source_documents_to_chunks\n", + " documents, parent_node_id = documents\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", + "ValueError: too many values to unpack (expected 2)Error occurred while running coroutine task: `check_permissions_on_documents`\n", + "too many values to unpack (expected 2)\n", + "Traceback (most recent call last):\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 86, in run_tasks\n", + " async for result in run_tasks(leftover_tasks, task_result):\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 49, in run_tasks\n", + " raise error\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 26, in run_tasks\n", + " async for partial_result in async_iterator:\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py\", line 9, in source_documents_to_chunks\n", + " documents, parent_node_id = documents\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", + "ValueError: too many values to unpack (expected 2)" + ] + }, + { + "ename": "ValueError", + "evalue": "too many values to unpack (expected 2)", "output_type": "error", "traceback": [ "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mAttributeError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[14], line 1\u001B[0m\n\u001B[0;32m----> 1\u001B[0m \u001B[38;5;28;01mawait\u001B[39;00m cognify(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mexample\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n", - "Cell \u001B[0;32mIn[12], line 24\u001B[0m, in \u001B[0;36mcognify\u001B[0;34m(datasets, user)\u001B[0m\n\u001B[1;32m 21\u001B[0m awaitables \u001B[38;5;241m=\u001B[39m []\n\u001B[1;32m 23\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m dataset \u001B[38;5;129;01min\u001B[39;00m datasets:\n\u001B[0;32m---> 24\u001B[0m dataset_name \u001B[38;5;241m=\u001B[39m \u001B[43mdataset\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mname\u001B[49m\n\u001B[1;32m 26\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m dataset_name \u001B[38;5;129;01min\u001B[39;00m existing_datasets_map:\n\u001B[1;32m 27\u001B[0m awaitables\u001B[38;5;241m.\u001B[39mappend(run_cognify_pipeline(dataset, user))\n", - "\u001B[0;31mAttributeError\u001B[0m: 'str' object has no attribute 'name'" + "\u001B[0;31mValueError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[0;32mIn[27], line 1\u001B[0m\n\u001B[0;32m----> 1\u001B[0m \u001B[38;5;28;01mawait\u001B[39;00m cognify(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mexample\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n", + "Cell \u001B[0;32mIn[26], line 30\u001B[0m, in \u001B[0;36mcognify\u001B[0;34m(datasets, user)\u001B[0m\n\u001B[1;32m 27\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m dataset_name \u001B[38;5;129;01min\u001B[39;00m existing_datasets_map:\n\u001B[1;32m 28\u001B[0m awaitables\u001B[38;5;241m.\u001B[39mappend(run_cognify_pipeline(dataset, user))\n\u001B[0;32m---> 30\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;01mawait\u001B[39;00m asyncio\u001B[38;5;241m.\u001B[39mgather(\u001B[38;5;241m*\u001B[39mawaitables)\n", + "Cell \u001B[0;32mIn[25], line 24\u001B[0m, in \u001B[0;36mrun_cognify_pipeline\u001B[0;34m(dataset, user)\u001B[0m\n\u001B[1;32m 22\u001B[0m \u001B[38;5;28mprint\u001B[39m(result)\n\u001B[1;32m 23\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[0;32m---> 24\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n", + "Cell \u001B[0;32mIn[25], line 21\u001B[0m, in \u001B[0;36mrun_cognify_pipeline\u001B[0;34m(dataset, user)\u001B[0m\n\u001B[1;32m 7\u001B[0m tasks \u001B[38;5;241m=\u001B[39m [\n\u001B[1;32m 8\u001B[0m Task(check_permissions_on_documents, user \u001B[38;5;241m=\u001B[39m user, permissions \u001B[38;5;241m=\u001B[39m [\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mwrite\u001B[39m\u001B[38;5;124m\"\u001B[39m]),\n\u001B[1;32m 9\u001B[0m Task(source_documents_to_chunks, parent_node_id \u001B[38;5;241m=\u001B[39m root_node_id), \u001B[38;5;66;03m# Classify documents and save them as a nodes in graph db, extract text chunks based on the document type\u001B[39;00m\n\u001B[0;32m (...)\u001B[0m\n\u001B[1;32m 16\u001B[0m Task(chunk_remove_disconnected), \u001B[38;5;66;03m# Remove the obsolete document chunks.\u001B[39;00m\n\u001B[1;32m 17\u001B[0m ]\n\u001B[1;32m 19\u001B[0m pipeline \u001B[38;5;241m=\u001B[39m run_tasks(tasks, data_documents)\n\u001B[0;32m---> 21\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m result \u001B[38;5;129;01min\u001B[39;00m pipeline:\n\u001B[1;32m 22\u001B[0m \u001B[38;5;28mprint\u001B[39m(result)\n\u001B[1;32m 23\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:97\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 90\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[1;32m 91\u001B[0m logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 92\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mError occurred while running coroutine task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 93\u001B[0m running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m,\n\u001B[1;32m 94\u001B[0m \u001B[38;5;28mstr\u001B[39m(error),\n\u001B[1;32m 95\u001B[0m exc_info \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m,\n\u001B[1;32m 96\u001B[0m )\n\u001B[0;32m---> 97\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n\u001B[1;32m 99\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m inspect\u001B[38;5;241m.\u001B[39misfunction(running_task\u001B[38;5;241m.\u001B[39mexecutable):\n\u001B[1;32m 100\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mRunning function task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:86\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 83\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m 84\u001B[0m task_result \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m running_task\u001B[38;5;241m.\u001B[39mrun(\u001B[38;5;241m*\u001B[39margs)\n\u001B[0;32m---> 86\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m result \u001B[38;5;129;01min\u001B[39;00m run_tasks(leftover_tasks, task_result):\n\u001B[1;32m 87\u001B[0m \u001B[38;5;28;01myield\u001B[39;00m result\n\u001B[1;32m 89\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mFinished coroutine task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:49\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 42\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[1;32m 43\u001B[0m logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 44\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mError occurred while running async generator task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 45\u001B[0m running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m,\n\u001B[1;32m 46\u001B[0m \u001B[38;5;28mstr\u001B[39m(error),\n\u001B[1;32m 47\u001B[0m exc_info \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m,\n\u001B[1;32m 48\u001B[0m )\n\u001B[0;32m---> 49\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n\u001B[1;32m 51\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m inspect\u001B[38;5;241m.\u001B[39misgeneratorfunction(running_task\u001B[38;5;241m.\u001B[39mexecutable):\n\u001B[1;32m 52\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mRunning generator task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:26\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 22\u001B[0m results \u001B[38;5;241m=\u001B[39m []\n\u001B[1;32m 24\u001B[0m async_iterator \u001B[38;5;241m=\u001B[39m running_task\u001B[38;5;241m.\u001B[39mrun(\u001B[38;5;241m*\u001B[39margs)\n\u001B[0;32m---> 26\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m partial_result \u001B[38;5;129;01min\u001B[39;00m async_iterator:\n\u001B[1;32m 27\u001B[0m results\u001B[38;5;241m.\u001B[39mappend(partial_result)\n\u001B[1;32m 29\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mlen\u001B[39m(results) \u001B[38;5;241m==\u001B[39m next_task_batch_size:\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py:9\u001B[0m, in \u001B[0;36msource_documents_to_chunks\u001B[0;34m(documents, parent_node_id)\u001B[0m\n\u001B[1;32m 6\u001B[0m graph_engine \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m get_graph_engine()\n\u001B[1;32m 8\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m parent_node_id \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[0;32m----> 9\u001B[0m documents, parent_node_id \u001B[38;5;241m=\u001B[39m documents\n\u001B[1;32m 12\u001B[0m nodes \u001B[38;5;241m=\u001B[39m []\n\u001B[1;32m 13\u001B[0m edges \u001B[38;5;241m=\u001B[39m []\n", + "\u001B[0;31mValueError\u001B[0m: too many values to unpack (expected 2)" ] } ], - "execution_count": 14 + "execution_count": 27 }, { "metadata": {}, From a1dc147b1bee61c335ec8cd98799c55e46a5fbcd Mon Sep 17 00:00:00 2001 From: Vasilije <8619304+Vasilije1990@users.noreply.github.com> Date: Fri, 20 Sep 2024 16:03:21 +0200 Subject: [PATCH 6/8] Fix the demo, update Readme --- .../infer_data_ontology.py | 4 +- notebooks/cognee_demo_1.5.ipynb | 310 ++++++++---------- 2 files changed, 145 insertions(+), 169 deletions(-) diff --git a/cognee/tasks/infer_data_ontology/infer_data_ontology.py b/cognee/tasks/infer_data_ontology/infer_data_ontology.py index bbf6b2e7c..6415eb005 100644 --- a/cognee/tasks/infer_data_ontology/infer_data_ontology.py +++ b/cognee/tasks/infer_data_ontology/infer_data_ontology.py @@ -89,7 +89,7 @@ async def add_graph_ontology(self, file_path: str = None, documents: list = None chunk_strategy = chunk_config.chunk_strategy for base_file in documents: - with open(base_file.file_path, "rb") as file: + with open(base_file.raw_data_location, "rb") as file: try: file_type = guess_file_type(file) text = extract_text_from_file(file, file_type) @@ -175,7 +175,7 @@ async def infer_data_ontology(documents, ontology_model = KnowledgeGraph, root_n ontology_engine = OntologyEngine() root_node_id = await ontology_engine.add_graph_ontology(documents = documents) else: - graph_engine = get_graph_engine() + graph_engine = await get_graph_engine() await add_model_class_to_graph(ontology_model, graph_engine) yield (documents, root_node_id) diff --git a/notebooks/cognee_demo_1.5.ipynb b/notebooks/cognee_demo_1.5.ipynb index 0b43ae2e6..4cf72171b 100644 --- a/notebooks/cognee_demo_1.5.ipynb +++ b/notebooks/cognee_demo_1.5.ipynb @@ -3,8 +3,8 @@ { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:11:39.250021Z", - "start_time": "2024-09-20T05:11:30.139927Z" + "end_time": "2024-09-20T14:02:47.336283Z", + "start_time": "2024-09-20T14:02:43.652444Z" } }, "cell_type": "code", @@ -46,8 +46,8 @@ { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:11:44.669755Z", - "start_time": "2024-09-20T05:11:44.666218Z" + "end_time": "2024-09-20T14:02:48.519686Z", + "start_time": "2024-09-20T14:02:48.515589Z" } }, "cell_type": "code", @@ -80,13 +80,13 @@ ], "id": "df16431d0f48b006", "outputs": [], - "execution_count": 3 + "execution_count": 2 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:11:45.277312Z", - "start_time": "2024-09-20T05:11:45.272644Z" + "end_time": "2024-09-20T14:02:49.120838Z", + "start_time": "2024-09-20T14:02:49.118294Z" } }, "cell_type": "code", @@ -125,13 +125,13 @@ ], "id": "9086abf3af077ab4", "outputs": [], - "execution_count": 4 + "execution_count": 3 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:11:45.753246Z", - "start_time": "2024-09-20T05:11:45.751035Z" + "end_time": "2024-09-20T14:02:49.675003Z", + "start_time": "2024-09-20T14:02:49.671615Z" } }, "cell_type": "code", @@ -169,13 +169,13 @@ ], "id": "a9de0cc07f798b7f", "outputs": [], - "execution_count": 5 + "execution_count": 4 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:11:46.238147Z", - "start_time": "2024-09-20T05:11:46.235463Z" + "end_time": "2024-09-20T14:02:50.286828Z", + "start_time": "2024-09-20T14:02:50.284369Z" } }, "cell_type": "code", @@ -213,13 +213,13 @@ ], "id": "185ff1c102d06111", "outputs": [], - "execution_count": 6 + "execution_count": 5 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:11:46.706952Z", - "start_time": "2024-09-20T05:11:46.705079Z" + "end_time": "2024-09-20T14:02:50.950343Z", + "start_time": "2024-09-20T14:02:50.946378Z" } }, "cell_type": "code", @@ -255,13 +255,13 @@ ], "id": "d55ce4c58f8efb67", "outputs": [], - "execution_count": 7 + "execution_count": 6 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:11:47.329735Z", - "start_time": "2024-09-20T05:11:47.326711Z" + "end_time": "2024-09-20T14:02:51.548191Z", + "start_time": "2024-09-20T14:02:51.545520Z" } }, "cell_type": "code", @@ -297,13 +297,13 @@ ], "id": "ca4ecc32721ad332", "outputs": [], - "execution_count": 8 + "execution_count": 7 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:11:50.271409Z", - "start_time": "2024-09-20T05:11:48.529182Z" + "end_time": "2024-09-20T14:02:54.243987Z", + "start_time": "2024-09-20T14:02:52.498195Z" } }, "cell_type": "code", @@ -325,15 +325,15 @@ "output_type": "stream", "text": [ "sys:1: SAWarning: TypeDecorator UUID() will not produce a cache key because the ``cache_ok`` attribute is not set to True. This can have significant performance implications including some performance degradations in comparison to prior SQLAlchemy versions. Set this attribute to True if this type object's state is safe to use in a cache key, or False to disable this warning. (Background on this warning at: https://sqlalche.me/e/20/cprf)\n", - "2024-09-20 07:11:48,925|[WARNING]|43272|8480345088|dlt|utils.py|resolve_merge_strategy:223|Destination does not support any merge strategies and `merge` write disposition for table `file_metadata` cannot be met and will fall back to `append`. Change write disposition.2024-09-20 07:11:49,246|[WARNING]|43272|8480345088|dlt|utils.py|resolve_merge_strategy:223|Destination does not support any merge strategies and `merge` write disposition for table `file_metadata` cannot be met and will fall back to `append`. Change write disposition." + "2024-09-20 16:02:52,880|[WARNING]|53377|8480345088|dlt|utils.py|resolve_merge_strategy:223|Destination does not support any merge strategies and `merge` write disposition for table `file_metadata` cannot be met and will fall back to `append`. Change write disposition.2024-09-20 16:02:53,216|[WARNING]|53377|8480345088|dlt|utils.py|resolve_merge_strategy:223|Destination does not support any merge strategies and `merge` write disposition for table `file_metadata` cannot be met and will fall back to `append`. Change write disposition." ] }, { "name": "stdout", "output_type": "stream", "text": [ - "\n", - "{'1726809108.767254': [{'started_at': DateTime(2024, 9, 20, 5, 11, 49, 245902, tzinfo=Timezone('UTC')), 'finished_at': DateTime(2024, 9, 20, 5, 11, 50, 268147, tzinfo=Timezone('UTC')), 'job_metrics': {'_dlt_pipeline_state.a91de88b58.typed-jsonl': LoadJobMetrics(job_id='_dlt_pipeline_state.a91de88b58.typed-jsonl', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/normalized/1726809108.767254/started_jobs/_dlt_pipeline_state.a91de88b58.0.typed-jsonl', table_name='_dlt_pipeline_state', started_at=DateTime(2024, 9, 20, 5, 11, 49, 256768, tzinfo=Timezone('UTC')), finished_at=DateTime(2024, 9, 20, 5, 11, 49, 258007, tzinfo=Timezone('UTC')), state='completed', remote_url=None), 'file_metadata.a639414384.typed-jsonl': LoadJobMetrics(job_id='file_metadata.a639414384.typed-jsonl', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/normalized/1726809108.767254/started_jobs/file_metadata.a639414384.0.typed-jsonl', table_name='file_metadata', started_at=DateTime(2024, 9, 20, 5, 11, 49, 257362, tzinfo=Timezone('UTC')), finished_at=DateTime(2024, 9, 20, 5, 11, 49, 259366, tzinfo=Timezone('UTC')), state='completed', remote_url=None)}}]}\n", + "\n", + "{'1726840972.7469912': [{'started_at': DateTime(2024, 9, 20, 14, 2, 53, 214773, tzinfo=Timezone('UTC')), 'finished_at': DateTime(2024, 9, 20, 14, 2, 54, 239978, tzinfo=Timezone('UTC')), 'job_metrics': {'file_metadata.a5a9170f4c.typed-jsonl': LoadJobMetrics(job_id='file_metadata.a5a9170f4c.typed-jsonl', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/normalized/1726840972.7469912/started_jobs/file_metadata.a5a9170f4c.0.typed-jsonl', table_name='file_metadata', started_at=DateTime(2024, 9, 20, 14, 2, 53, 220755, tzinfo=Timezone('UTC')), finished_at=DateTime(2024, 9, 20, 14, 2, 53, 222174, tzinfo=Timezone('UTC')), state='completed', remote_url=None)}}]}\n", "dlt.destinations.sqlalchemy\n", "sqlite:///cognee_db\n", "sqlalchemy\n", @@ -343,108 +343,69 @@ "None\n", "\n", "example\n", - "['1726809108.767254']\n", - "[LoadPackageInfo(load_id='1726809108.767254', package_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726809108.767254', state='loaded', schema=Schema file_load_from_filesystem at 6016359056, schema_update={'_dlt_loads': {'name': '_dlt_loads', 'columns': {'load_id': {'name': 'load_id', 'data_type': 'text', 'nullable': False}, 'schema_name': {'name': 'schema_name', 'data_type': 'text', 'nullable': True}, 'status': {'name': 'status', 'data_type': 'bigint', 'nullable': False}, 'inserted_at': {'name': 'inserted_at', 'data_type': 'timestamp', 'nullable': False}, 'schema_version_hash': {'name': 'schema_version_hash', 'data_type': 'text', 'nullable': True}}, 'write_disposition': 'skip', 'resource': '_dlt_loads', 'description': 'Created by DLT. Tracks completed loads'}, 'file_metadata': {'columns': {'id': {'name': 'id', 'nullable': False, 'merge_key': True, 'data_type': 'text'}, 'name': {'name': 'name', 'data_type': 'text', 'nullable': True}, 'file_path': {'name': 'file_path', 'data_type': 'text', 'nullable': True}, 'extension': {'name': 'extension', 'data_type': 'text', 'nullable': True}, 'mime_type': {'name': 'mime_type', 'data_type': 'text', 'nullable': True}, '_dlt_load_id': {'name': '_dlt_load_id', 'data_type': 'text', 'nullable': False}, '_dlt_id': {'name': '_dlt_id', 'data_type': 'text', 'nullable': False, 'unique': True, 'row_key': True}}, 'name': 'file_metadata', 'write_disposition': 'merge', 'resource': 'data_resources', 'x-normalizer': {'seen-data': True}}, '_dlt_pipeline_state': {'columns': {'version': {'name': 'version', 'data_type': 'bigint', 'nullable': False}, 'engine_version': {'name': 'engine_version', 'data_type': 'bigint', 'nullable': False}, 'pipeline_name': {'name': 'pipeline_name', 'data_type': 'text', 'nullable': False}, 'state': {'name': 'state', 'data_type': 'text', 'nullable': False}, 'created_at': {'name': 'created_at', 'data_type': 'timestamp', 'nullable': False}, 'version_hash': {'name': 'version_hash', 'data_type': 'text', 'nullable': True}, '_dlt_load_id': {'name': '_dlt_load_id', 'data_type': 'text', 'nullable': False}, '_dlt_id': {'name': '_dlt_id', 'data_type': 'text', 'nullable': False, 'unique': True, 'row_key': True}}, 'write_disposition': 'append', 'file_format': 'preferred', 'name': '_dlt_pipeline_state', 'resource': '_dlt_pipeline_state', 'x-normalizer': {'seen-data': True}}, '_dlt_version': {'name': '_dlt_version', 'columns': {'version': {'name': 'version', 'data_type': 'bigint', 'nullable': False}, 'engine_version': {'name': 'engine_version', 'data_type': 'bigint', 'nullable': False}, 'inserted_at': {'name': 'inserted_at', 'data_type': 'timestamp', 'nullable': False}, 'schema_name': {'name': 'schema_name', 'data_type': 'text', 'nullable': False}, 'version_hash': {'name': 'version_hash', 'data_type': 'text', 'nullable': False}, 'schema': {'name': 'schema', 'data_type': 'text', 'nullable': False}}, 'write_disposition': 'skip', 'resource': '_dlt_version', 'description': 'Created by DLT. Tracks schema updates'}}, completed_at=DateTime(2024, 9, 20, 5, 11, 50, 264990, tzinfo=Timezone('UTC')), jobs={'completed_jobs': [LoadJobInfo(state='completed_jobs', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726809108.767254/completed_jobs/_dlt_pipeline_state.a91de88b58.0.typed-jsonl', file_size=514, created_at=DateTime(2024, 9, 20, 5, 11, 48, 927162, tzinfo=Timezone('UTC')), elapsed=1.3378276824951172, job_file_info=ParsedLoadJobFileName(table_name='_dlt_pipeline_state', file_id='a91de88b58', retry_count=0, file_format='typed-jsonl'), failed_message=None), LoadJobInfo(state='completed_jobs', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726809108.767254/completed_jobs/file_metadata.a639414384.0.typed-jsonl', file_size=668, created_at=DateTime(2024, 9, 20, 5, 11, 48, 927453, tzinfo=Timezone('UTC')), elapsed=1.3375375270843506, job_file_info=ParsedLoadJobFileName(table_name='file_metadata', file_id='a639414384', retry_count=0, file_format='typed-jsonl'), failed_message=None)], 'started_jobs': [], 'new_jobs': [], 'failed_jobs': []})]\n", - "True\n" + "['1726840972.7469912']\n", + "[LoadPackageInfo(load_id='1726840972.7469912', package_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726840972.7469912', state='loaded', schema=Schema file_load_from_filesystem at 6038968784, schema_update={}, completed_at=DateTime(2024, 9, 20, 14, 2, 54, 235948, tzinfo=Timezone('UTC')), jobs={'failed_jobs': [], 'started_jobs': [], 'completed_jobs': [LoadJobInfo(state='completed_jobs', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726840972.7469912/completed_jobs/file_metadata.a5a9170f4c.0.typed-jsonl', file_size=670, created_at=DateTime(2024, 9, 20, 14, 2, 52, 881922, tzinfo=Timezone('UTC')), elapsed=1.3540260791778564, job_file_info=ParsedLoadJobFileName(table_name='file_metadata', file_id='a5a9170f4c', retry_count=0, file_format='typed-jsonl'), failed_message=None)], 'new_jobs': []})]\n", + "False\n" ] } ], - "execution_count": 9 + "execution_count": 8 }, { - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-20T14:02:55.564445Z", + "start_time": "2024-09-20T14:02:55.562784Z" + } + }, "cell_type": "code", + "source": "", + "id": "6f9b564de121713d", "outputs": [], - "execution_count": null, - "source": [ - "from typing import Any, Dict, List, Optional, Union\n", - "from pydantic import BaseModel, Field\n", - "from uuid import uuid4\n", - "\n", - "class Node(BaseModel):\n", - " \"\"\"Node in a knowledge graph.\"\"\"\n", - " id: str = Field(default_factory=lambda: str(uuid4()))\n", - " name: Optional[str] = None\n", - " types: List[str] = Field(default_factory=list, description=\"Types or categories of the node (e.g., 'Person', 'Skill').\")\n", - " properties: Dict[str, Any] = Field(default_factory=dict, description=\"Properties associated with the node.\")\n", - "\n", - " def merge(self, other: 'Node'):\n", - " \"\"\"Merge another node into this one.\"\"\"\n", - " # Combine types\n", - " self.types = list(set(self.types + other.types))\n", - " # Combine properties\n", - " self.properties.update(other.properties)\n", - " # Update name if necessary\n", - " if not self.name and other.name:\n", - " self.name = other.name\n", - "\n", - "class Edge(BaseModel):\n", - " \"\"\"Edge in a knowledge graph.\"\"\"\n", - " id: str = Field(default_factory=lambda: str(uuid4()))\n", - " source_node_id: str\n", - " target_node_id: str\n", - " relationship_types: List[str] = Field(default_factory=list, description=\"Types of relationships (e.g., 'has_skill').\")\n", - " properties: Dict[str, Any] = Field(default_factory=dict, description=\"Properties associated with the edge.\")\n", - " confidence: Optional[float] = Field(None, description=\"Confidence score for the relationship.\")\n", - "\n", - "class KnowledgeGraph(BaseModel):\n", - " \"\"\"Knowledge graph.\"\"\"\n", - " nodes: Dict[str, Node] = Field(default_factory=dict)\n", - " edges: List[Edge] = Field(default_factory=list)\n", - "\n", - " def add_node(self, node: Node):\n", - " if node.id in self.nodes:\n", - " self.nodes[node.id].merge(node)\n", - " else:\n", - " self.nodes[node.id] = node\n", - "\n", - " def add_edge(self, edge: Edge):\n", - " self.edges.append(edge)" - ], - "id": "6f9b564de121713d" + "execution_count": 8 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:12:24.360343Z", - "start_time": "2024-09-20T05:12:24.335507Z" + "end_time": "2024-09-20T14:02:56.714408Z", + "start_time": "2024-09-20T14:02:56.711812Z" } }, "cell_type": "code", "source": [ - "from enum import Enum, auto\n", - "from typing import Optional, List, Union, Dict, Any\n", - "from pydantic import BaseModel, Field\n", - "\n", - "class Node(BaseModel):\n", - " \"\"\"Node in a knowledge graph.\"\"\"\n", - " id: str\n", - " name: str\n", - " type: str\n", - " description: str\n", - " properties: Optional[Dict[str, Any]] = Field(None, description = \"A dictionary of properties associated with the node.\")\n", - "\n", - "class Edge(BaseModel):\n", - " \"\"\"Edge in a knowledge graph.\"\"\"\n", - " source_node_id: str\n", - " target_node_id: str\n", - " relationship_name: str\n", - " properties: Optional[Dict[str, Any]] = Field(None, description = \"A dictionary of properties associated with the edge.\")\n", - "\n", - "class KnowledgeGraph(BaseModel):\n", - " \"\"\"Knowledge graph.\"\"\"\n", - " nodes: List[Node] = Field(..., default_factory=list)\n", - " edges: List[Edge] = Field(..., default_factory=list)" + "# from enum import Enum, auto\n", + "# from typing import Optional, List, Union, Dict, Any\n", + "# from pydantic import BaseModel, Field\n", + "# \n", + "# class Node(BaseModel):\n", + "# \"\"\"Node in a knowledge graph.\"\"\"\n", + "# id: str\n", + "# name: str\n", + "# type: str\n", + "# description: str\n", + "# properties: Optional[Dict[str, Any]] = Field(None, description = \"A dictionary of properties associated with the node.\")\n", + "# \n", + "# class Edge(BaseModel):\n", + "# \"\"\"Edge in a knowledge graph.\"\"\"\n", + "# source_node_id: str\n", + "# target_node_id: str\n", + "# relationship_name: str\n", + "# properties: Optional[Dict[str, Any]] = Field(None, description = \"A dictionary of properties associated with the edge.\")\n", + "# \n", + "# class KnowledgeGraph(BaseModel):\n", + "# \"\"\"Knowledge graph.\"\"\"\n", + "# nodes: List[Node] = Field(..., default_factory=list)\n", + "# edges: List[Edge] = Field(..., default_factory=list)" ], "id": "8911f8bd4f8c440a", "outputs": [], - "execution_count": 10 + "execution_count": 9 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:36:49.096914Z", - "start_time": "2024-09-20T05:36:49.089721Z" + "end_time": "2024-09-20T14:02:57.925667Z", + "start_time": "2024-09-20T14:02:57.922353Z" } }, "cell_type": "code", @@ -457,7 +418,9 @@ " root_node_id = None\n", "\n", " tasks = [\n", + " \n", " Task(check_permissions_on_documents, user = user, permissions = [\"write\"]),\n", + " Task(infer_data_ontology, root_node_id = root_node_id, ontology_model = KnowledgeGraph),\n", " Task(source_documents_to_chunks, parent_node_id = root_node_id), # Classify documents and save them as a nodes in graph db, extract text chunks based on the document type\n", " Task(chunks_into_graph, graph_model = KnowledgeGraph, collection_name = \"entities\", task_config = { \"batch_size\": 10 }), # Generate knowledge graphs from the document chunks and attach it to chunk nodes\n", " Task(chunk_update_check, collection_name = \"chunks\"), # Find all affected chunks, so we don't process unchanged chunks\n", @@ -477,16 +440,81 @@ ], "id": "7c431fdef4921ae0", "outputs": [], - "execution_count": 25 + "execution_count": 10 }, { "metadata": { "ExecuteTime": { - "end_time": "2024-09-20T05:36:49.776759Z", - "start_time": "2024-09-20T05:36:49.773859Z" + "end_time": "2024-09-20T14:02:58.905774Z", + "start_time": "2024-09-20T14:02:58.625915Z" } }, "cell_type": "code", + "source": [ + "user = await get_default_user()\n", + "datasets = await get_datasets_by_name([\"example\"], user.id)\n", + "await run_cognify_pipeline(datasets[0], user)" + ], + "id": "f0a91b99c6215e09", + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Error occurred while running async generator task: `infer_data_ontology`\n", + "'Data' object has no attribute 'file_path'\n", + "Traceback (most recent call last):\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 26, in run_tasks\n", + " async for partial_result in async_iterator:\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py\", line 176, in infer_data_ontology\n", + " root_node_id = await ontology_engine.add_graph_ontology(documents = documents)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py\", line 92, in add_graph_ontology\n", + " with open(base_file.file_path, \"rb\") as file:\n", + " ^^^^^^^^^^^^^^^^^^^\n", + "AttributeError: 'Data' object has no attribute 'file_path'Error occurred while running coroutine task: `check_permissions_on_documents`\n", + "'Data' object has no attribute 'file_path'\n", + "Traceback (most recent call last):\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 86, in run_tasks\n", + " async for result in run_tasks(leftover_tasks, task_result):\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 49, in run_tasks\n", + " raise error\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 26, in run_tasks\n", + " async for partial_result in async_iterator:\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py\", line 176, in infer_data_ontology\n", + " root_node_id = await ontology_engine.add_graph_ontology(documents = documents)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py\", line 92, in add_graph_ontology\n", + " with open(base_file.file_path, \"rb\") as file:\n", + " ^^^^^^^^^^^^^^^^^^^\n", + "AttributeError: 'Data' object has no attribute 'file_path'" + ] + }, + { + "ename": "AttributeError", + "evalue": "'Data' object has no attribute 'file_path'", + "output_type": "error", + "traceback": [ + "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", + "\u001B[0;31mAttributeError\u001B[0m Traceback (most recent call last)", + "Cell \u001B[0;32mIn[11], line 3\u001B[0m\n\u001B[1;32m 1\u001B[0m user \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m get_default_user()\n\u001B[1;32m 2\u001B[0m datasets \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m get_datasets_by_name([\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mexample\u001B[39m\u001B[38;5;124m\"\u001B[39m], user\u001B[38;5;241m.\u001B[39mid)\n\u001B[0;32m----> 3\u001B[0m \u001B[38;5;28;01mawait\u001B[39;00m run_cognify_pipeline(datasets[\u001B[38;5;241m0\u001B[39m], user)\n", + "Cell \u001B[0;32mIn[10], line 27\u001B[0m, in \u001B[0;36mrun_cognify_pipeline\u001B[0;34m(dataset, user)\u001B[0m\n\u001B[1;32m 25\u001B[0m \u001B[38;5;28mprint\u001B[39m(result)\n\u001B[1;32m 26\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[0;32m---> 27\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n", + "Cell \u001B[0;32mIn[10], line 24\u001B[0m, in \u001B[0;36mrun_cognify_pipeline\u001B[0;34m(dataset, user)\u001B[0m\n\u001B[1;32m 8\u001B[0m tasks \u001B[38;5;241m=\u001B[39m [\n\u001B[1;32m 9\u001B[0m \n\u001B[1;32m 10\u001B[0m Task(check_permissions_on_documents, user \u001B[38;5;241m=\u001B[39m user, permissions \u001B[38;5;241m=\u001B[39m [\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mwrite\u001B[39m\u001B[38;5;124m\"\u001B[39m]),\n\u001B[0;32m (...)\u001B[0m\n\u001B[1;32m 19\u001B[0m Task(chunk_remove_disconnected), \u001B[38;5;66;03m# Remove the obsolete document chunks.\u001B[39;00m\n\u001B[1;32m 20\u001B[0m ]\n\u001B[1;32m 22\u001B[0m pipeline \u001B[38;5;241m=\u001B[39m run_tasks(tasks, data_documents)\n\u001B[0;32m---> 24\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m result \u001B[38;5;129;01min\u001B[39;00m pipeline:\n\u001B[1;32m 25\u001B[0m \u001B[38;5;28mprint\u001B[39m(result)\n\u001B[1;32m 26\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:97\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 90\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[1;32m 91\u001B[0m logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 92\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mError occurred while running coroutine task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 93\u001B[0m running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m,\n\u001B[1;32m 94\u001B[0m \u001B[38;5;28mstr\u001B[39m(error),\n\u001B[1;32m 95\u001B[0m exc_info \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m,\n\u001B[1;32m 96\u001B[0m )\n\u001B[0;32m---> 97\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n\u001B[1;32m 99\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m inspect\u001B[38;5;241m.\u001B[39misfunction(running_task\u001B[38;5;241m.\u001B[39mexecutable):\n\u001B[1;32m 100\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mRunning function task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:86\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 83\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m 84\u001B[0m task_result \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m running_task\u001B[38;5;241m.\u001B[39mrun(\u001B[38;5;241m*\u001B[39margs)\n\u001B[0;32m---> 86\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m result \u001B[38;5;129;01min\u001B[39;00m run_tasks(leftover_tasks, task_result):\n\u001B[1;32m 87\u001B[0m \u001B[38;5;28;01myield\u001B[39;00m result\n\u001B[1;32m 89\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mFinished coroutine task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:49\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 42\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[1;32m 43\u001B[0m logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 44\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mError occurred while running async generator task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 45\u001B[0m running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m,\n\u001B[1;32m 46\u001B[0m \u001B[38;5;28mstr\u001B[39m(error),\n\u001B[1;32m 47\u001B[0m exc_info \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m,\n\u001B[1;32m 48\u001B[0m )\n\u001B[0;32m---> 49\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n\u001B[1;32m 51\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m inspect\u001B[38;5;241m.\u001B[39misgeneratorfunction(running_task\u001B[38;5;241m.\u001B[39mexecutable):\n\u001B[1;32m 52\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mRunning generator task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:26\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 22\u001B[0m results \u001B[38;5;241m=\u001B[39m []\n\u001B[1;32m 24\u001B[0m async_iterator \u001B[38;5;241m=\u001B[39m running_task\u001B[38;5;241m.\u001B[39mrun(\u001B[38;5;241m*\u001B[39margs)\n\u001B[0;32m---> 26\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m partial_result \u001B[38;5;129;01min\u001B[39;00m async_iterator:\n\u001B[1;32m 27\u001B[0m results\u001B[38;5;241m.\u001B[39mappend(partial_result)\n\u001B[1;32m 29\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mlen\u001B[39m(results) \u001B[38;5;241m==\u001B[39m next_task_batch_size:\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py:176\u001B[0m, in \u001B[0;36minfer_data_ontology\u001B[0;34m(documents, ontology_model, root_node_id)\u001B[0m\n\u001B[1;32m 174\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m ontology_model \u001B[38;5;241m==\u001B[39m KnowledgeGraph:\n\u001B[1;32m 175\u001B[0m ontology_engine \u001B[38;5;241m=\u001B[39m OntologyEngine()\n\u001B[0;32m--> 176\u001B[0m root_node_id \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m ontology_engine\u001B[38;5;241m.\u001B[39madd_graph_ontology(documents \u001B[38;5;241m=\u001B[39m documents)\n\u001B[1;32m 177\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m 178\u001B[0m graph_engine \u001B[38;5;241m=\u001B[39m get_graph_engine()\n", + "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py:92\u001B[0m, in \u001B[0;36mOntologyEngine.add_graph_ontology\u001B[0;34m(self, file_path, documents)\u001B[0m\n\u001B[1;32m 89\u001B[0m chunk_strategy \u001B[38;5;241m=\u001B[39m chunk_config\u001B[38;5;241m.\u001B[39mchunk_strategy\n\u001B[1;32m 91\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m base_file \u001B[38;5;129;01min\u001B[39;00m documents:\n\u001B[0;32m---> 92\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m \u001B[38;5;28mopen\u001B[39m(\u001B[43mbase_file\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mfile_path\u001B[49m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mrb\u001B[39m\u001B[38;5;124m\"\u001B[39m) \u001B[38;5;28;01mas\u001B[39;00m file:\n\u001B[1;32m 93\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m 94\u001B[0m file_type \u001B[38;5;241m=\u001B[39m guess_file_type(file)\n", + "\u001B[0;31mAttributeError\u001B[0m: 'Data' object has no attribute 'file_path'" + ] + } + ], + "execution_count": 11 + }, + { + "metadata": {}, + "cell_type": "code", "source": [ "\n", "\n", @@ -524,75 +552,23 @@ ], "id": "e7d4f03f7dab9807", "outputs": [], - "execution_count": 26 + "execution_count": null }, { - "metadata": { - "ExecuteTime": { - "end_time": "2024-09-20T05:36:50.641924Z", - "start_time": "2024-09-20T05:36:50.554094Z" - } - }, + "metadata": {}, "cell_type": "code", "source": "await cognify(\"example\")", "id": "d9248a01352964e2", - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Error occurred while running async generator task: `source_documents_to_chunks`\n", - "too many values to unpack (expected 2)\n", - "Traceback (most recent call last):\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 26, in run_tasks\n", - " async for partial_result in async_iterator:\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py\", line 9, in source_documents_to_chunks\n", - " documents, parent_node_id = documents\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", - "ValueError: too many values to unpack (expected 2)Error occurred while running coroutine task: `check_permissions_on_documents`\n", - "too many values to unpack (expected 2)\n", - "Traceback (most recent call last):\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 86, in run_tasks\n", - " async for result in run_tasks(leftover_tasks, task_result):\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 49, in run_tasks\n", - " raise error\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 26, in run_tasks\n", - " async for partial_result in async_iterator:\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py\", line 9, in source_documents_to_chunks\n", - " documents, parent_node_id = documents\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", - "ValueError: too many values to unpack (expected 2)" - ] - }, - { - "ename": "ValueError", - "evalue": "too many values to unpack (expected 2)", - "output_type": "error", - "traceback": [ - "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mValueError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[27], line 1\u001B[0m\n\u001B[0;32m----> 1\u001B[0m \u001B[38;5;28;01mawait\u001B[39;00m cognify(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mexample\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n", - "Cell \u001B[0;32mIn[26], line 30\u001B[0m, in \u001B[0;36mcognify\u001B[0;34m(datasets, user)\u001B[0m\n\u001B[1;32m 27\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m dataset_name \u001B[38;5;129;01min\u001B[39;00m existing_datasets_map:\n\u001B[1;32m 28\u001B[0m awaitables\u001B[38;5;241m.\u001B[39mappend(run_cognify_pipeline(dataset, user))\n\u001B[0;32m---> 30\u001B[0m \u001B[38;5;28;01mreturn\u001B[39;00m \u001B[38;5;28;01mawait\u001B[39;00m asyncio\u001B[38;5;241m.\u001B[39mgather(\u001B[38;5;241m*\u001B[39mawaitables)\n", - "Cell \u001B[0;32mIn[25], line 24\u001B[0m, in \u001B[0;36mrun_cognify_pipeline\u001B[0;34m(dataset, user)\u001B[0m\n\u001B[1;32m 22\u001B[0m \u001B[38;5;28mprint\u001B[39m(result)\n\u001B[1;32m 23\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[0;32m---> 24\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n", - "Cell \u001B[0;32mIn[25], line 21\u001B[0m, in \u001B[0;36mrun_cognify_pipeline\u001B[0;34m(dataset, user)\u001B[0m\n\u001B[1;32m 7\u001B[0m tasks \u001B[38;5;241m=\u001B[39m [\n\u001B[1;32m 8\u001B[0m Task(check_permissions_on_documents, user \u001B[38;5;241m=\u001B[39m user, permissions \u001B[38;5;241m=\u001B[39m [\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mwrite\u001B[39m\u001B[38;5;124m\"\u001B[39m]),\n\u001B[1;32m 9\u001B[0m Task(source_documents_to_chunks, parent_node_id \u001B[38;5;241m=\u001B[39m root_node_id), \u001B[38;5;66;03m# Classify documents and save them as a nodes in graph db, extract text chunks based on the document type\u001B[39;00m\n\u001B[0;32m (...)\u001B[0m\n\u001B[1;32m 16\u001B[0m Task(chunk_remove_disconnected), \u001B[38;5;66;03m# Remove the obsolete document chunks.\u001B[39;00m\n\u001B[1;32m 17\u001B[0m ]\n\u001B[1;32m 19\u001B[0m pipeline \u001B[38;5;241m=\u001B[39m run_tasks(tasks, data_documents)\n\u001B[0;32m---> 21\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m result \u001B[38;5;129;01min\u001B[39;00m pipeline:\n\u001B[1;32m 22\u001B[0m \u001B[38;5;28mprint\u001B[39m(result)\n\u001B[1;32m 23\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:97\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 90\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[1;32m 91\u001B[0m logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 92\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mError occurred while running coroutine task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 93\u001B[0m running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m,\n\u001B[1;32m 94\u001B[0m \u001B[38;5;28mstr\u001B[39m(error),\n\u001B[1;32m 95\u001B[0m exc_info \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m,\n\u001B[1;32m 96\u001B[0m )\n\u001B[0;32m---> 97\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n\u001B[1;32m 99\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m inspect\u001B[38;5;241m.\u001B[39misfunction(running_task\u001B[38;5;241m.\u001B[39mexecutable):\n\u001B[1;32m 100\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mRunning function task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:86\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 83\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m 84\u001B[0m task_result \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m running_task\u001B[38;5;241m.\u001B[39mrun(\u001B[38;5;241m*\u001B[39margs)\n\u001B[0;32m---> 86\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m result \u001B[38;5;129;01min\u001B[39;00m run_tasks(leftover_tasks, task_result):\n\u001B[1;32m 87\u001B[0m \u001B[38;5;28;01myield\u001B[39;00m result\n\u001B[1;32m 89\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mFinished coroutine task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:49\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 42\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[1;32m 43\u001B[0m logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 44\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mError occurred while running async generator task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 45\u001B[0m running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m,\n\u001B[1;32m 46\u001B[0m \u001B[38;5;28mstr\u001B[39m(error),\n\u001B[1;32m 47\u001B[0m exc_info \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m,\n\u001B[1;32m 48\u001B[0m )\n\u001B[0;32m---> 49\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n\u001B[1;32m 51\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m inspect\u001B[38;5;241m.\u001B[39misgeneratorfunction(running_task\u001B[38;5;241m.\u001B[39mexecutable):\n\u001B[1;32m 52\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mRunning generator task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:26\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 22\u001B[0m results \u001B[38;5;241m=\u001B[39m []\n\u001B[1;32m 24\u001B[0m async_iterator \u001B[38;5;241m=\u001B[39m running_task\u001B[38;5;241m.\u001B[39mrun(\u001B[38;5;241m*\u001B[39margs)\n\u001B[0;32m---> 26\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m partial_result \u001B[38;5;129;01min\u001B[39;00m async_iterator:\n\u001B[1;32m 27\u001B[0m results\u001B[38;5;241m.\u001B[39mappend(partial_result)\n\u001B[1;32m 29\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mlen\u001B[39m(results) \u001B[38;5;241m==\u001B[39m next_task_batch_size:\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/source_documents_to_chunks/source_documents_to_chunks.py:9\u001B[0m, in \u001B[0;36msource_documents_to_chunks\u001B[0;34m(documents, parent_node_id)\u001B[0m\n\u001B[1;32m 6\u001B[0m graph_engine \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m get_graph_engine()\n\u001B[1;32m 8\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m parent_node_id \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[0;32m----> 9\u001B[0m documents, parent_node_id \u001B[38;5;241m=\u001B[39m documents\n\u001B[1;32m 12\u001B[0m nodes \u001B[38;5;241m=\u001B[39m []\n\u001B[1;32m 13\u001B[0m edges \u001B[38;5;241m=\u001B[39m []\n", - "\u001B[0;31mValueError\u001B[0m: too many values to unpack (expected 2)" - ] - } - ], - "execution_count": 27 + "outputs": [], + "execution_count": null }, { "metadata": {}, "cell_type": "code", - "outputs": [], - "execution_count": null, "source": "", - "id": "6afc6307bd115dbe" + "id": "6afc6307bd115dbe", + "outputs": [], + "execution_count": null } ], "metadata": { From d22608ed2adde47b7491171fabbe08a244b653f3 Mon Sep 17 00:00:00 2001 From: Boris Arzentar Date: Fri, 20 Sep 2024 17:56:08 +0200 Subject: [PATCH 7/8] fix: small bug fixes --- cognee/api/client.py | 12 +- cognee/api/v1/cognify/cognify_v2.py | 134 +++++++++--------- .../embeddings/LiteLLMEmbeddingEngine.py | 2 +- .../document_types/AudioDocument.py | 12 +- .../processing/document_types/Document.py | 2 +- .../document_types/ImageDocument.py | 10 +- .../processing/document_types/PdfDocument.py | 10 +- .../processing/document_types/TextDocument.py | 10 +- cognee/tasks/chunking/chunk_by_word.py | 2 +- .../classify_documents/classify_documents.py | 8 +- 10 files changed, 101 insertions(+), 101 deletions(-) diff --git a/cognee/api/client.py b/cognee/api/client.py index 89af9fcfb..86a22fc44 100644 --- a/cognee/api/client.py +++ b/cognee/api/client.py @@ -33,11 +33,11 @@ @asynccontextmanager async def lifespan(app: FastAPI): from cognee.infrastructure.databases.relational import create_db_and_tables - from cognee.modules.users.methods import create_default_user + from cognee.modules.users.methods import get_default_user # Not needed if you setup a migration system like Alembic await create_db_and_tables() - await create_default_user() + await get_default_user() yield app = FastAPI(debug = os.getenv("ENV") != "prod", lifespan = lifespan) @@ -396,10 +396,10 @@ def start_api_server(host: str = "0.0.0.0", port: int = 8000): try: logger.info("Starting server at %s:%s", host, port) - import asyncio - from cognee.modules.data.deletion import prune_system, prune_data - asyncio.run(prune_data()) - asyncio.run(prune_system(metadata = True)) + # import asyncio + # from cognee.modules.data.deletion import prune_system, prune_data + # asyncio.run(prune_data()) + # asyncio.run(prune_system(metadata = True)) uvicorn.run(app, host = host, port = port) except Exception as e: diff --git a/cognee/api/v1/cognify/cognify_v2.py b/cognee/api/v1/cognify/cognify_v2.py index fad1f175c..27fd120b9 100644 --- a/cognee/api/v1/cognify/cognify_v2.py +++ b/cognee/api/v1/cognify/cognify_v2.py @@ -46,72 +46,6 @@ async def cognify(datasets: Union[str, list[str]] = None, user: User = None): if type(datasets[0]) == str: datasets = await get_datasets_by_name(datasets, user.id) - async def run_cognify_pipeline(dataset: Dataset): - data_documents: list[Data] = await get_dataset_data(dataset_id = dataset.id) - - document_ids_str = [str(document.id) for document in data_documents] - - dataset_id = dataset.id - dataset_name = generate_dataset_name(dataset.name) - - async with update_status_lock: - task_status = await get_pipeline_status([dataset_id]) - - if dataset_id in task_status and task_status[dataset_id] == "DATASET_PROCESSING_STARTED": - logger.info("Dataset %s is already being processed.", dataset_name) - return - - await log_pipeline_status(dataset_id, "DATASET_PROCESSING_STARTED", { - "dataset_name": dataset_name, - "files": document_ids_str, - }) - try: - cognee_config = get_cognify_config() - - root_node_id = None - - tasks = [ - Task(classify_documents), - Task(check_permissions_on_documents, user = user, permissions = ["write"]), - Task(infer_data_ontology, root_node_id = root_node_id, ontology_model = KnowledgeGraph), - Task(source_documents_to_chunks, parent_node_id = root_node_id), # Classify documents and save them as a nodes in graph db, extract text chunks based on the document type - Task(chunks_into_graph, graph_model = KnowledgeGraph, collection_name = "entities", task_config = { "batch_size": 10 }), # Generate knowledge graphs from the document chunks and attach it to chunk nodes - Task(chunk_update_check, collection_name = "chunks"), # Find all affected chunks, so we don't process unchanged chunks - Task( - save_chunks_to_store, - collection_name = "chunks", - ), # Save the document chunks in vector db and as nodes in graph db (connected to the document node and between each other) - run_tasks_parallel([ - Task( - chunk_extract_summary, - summarization_model = cognee_config.summarization_model, - collection_name = "chunk_summaries", - ), # Summarize the document chunks - Task( - chunk_naive_llm_classifier, - classification_model = cognee_config.classification_model, - ), - ]), - Task(chunk_remove_disconnected), # Remove the obsolete document chunks. - ] - - pipeline = run_tasks(tasks, data_documents) - - async for result in pipeline: - print(result) - - await log_pipeline_status(dataset_id, "DATASET_PROCESSING_FINISHED", { - "dataset_name": dataset_name, - "files": document_ids_str, - }) - except Exception as error: - await log_pipeline_status(dataset_id, "DATASET_PROCESSING_ERROR", { - "dataset_name": dataset_name, - "files": document_ids_str, - }) - raise error - - existing_datasets_map = { generate_dataset_name(dataset.name): True for dataset in existing_datasets } @@ -122,10 +56,76 @@ async def run_cognify_pipeline(dataset: Dataset): dataset_name = generate_dataset_name(dataset.name) if dataset_name in existing_datasets_map: - awaitables.append(run_cognify_pipeline(dataset)) + awaitables.append(run_cognify_pipeline(dataset, user)) return await asyncio.gather(*awaitables) +async def run_cognify_pipeline(dataset: Dataset, user: User): + data_documents: list[Data] = await get_dataset_data(dataset_id = dataset.id) + + document_ids_str = [str(document.id) for document in data_documents] + + dataset_id = dataset.id + dataset_name = generate_dataset_name(dataset.name) + + async with update_status_lock: + task_status = await get_pipeline_status([dataset_id]) + + if dataset_id in task_status and task_status[dataset_id] == "DATASET_PROCESSING_STARTED": + logger.info("Dataset %s is already being processed.", dataset_name) + return + + await log_pipeline_status(dataset_id, "DATASET_PROCESSING_STARTED", { + "dataset_name": dataset_name, + "files": document_ids_str, + }) + try: + cognee_config = get_cognify_config() + + root_node_id = None + + tasks = [ + Task(classify_documents), + Task(check_permissions_on_documents, user = user, permissions = ["write"]), + Task(infer_data_ontology, root_node_id = root_node_id, ontology_model = KnowledgeGraph), + Task(source_documents_to_chunks, parent_node_id = root_node_id), # Classify documents and save them as a nodes in graph db, extract text chunks based on the document type + Task(chunks_into_graph, graph_model = KnowledgeGraph, collection_name = "entities", task_config = { "batch_size": 10 }), # Generate knowledge graphs from the document chunks and attach it to chunk nodes + Task(chunk_update_check, collection_name = "chunks"), # Find all affected chunks, so we don't process unchanged chunks + Task( + save_chunks_to_store, + collection_name = "chunks", + ), # Save the document chunks in vector db and as nodes in graph db (connected to the document node and between each other) + run_tasks_parallel([ + Task( + chunk_extract_summary, + summarization_model = cognee_config.summarization_model, + collection_name = "chunk_summaries", + ), # Summarize the document chunks + Task( + chunk_naive_llm_classifier, + classification_model = cognee_config.classification_model, + ), + ]), + Task(chunk_remove_disconnected), # Remove the obsolete document chunks. + ] + + pipeline = run_tasks(tasks, data_documents) + + async for result in pipeline: + print(result) + + await log_pipeline_status(dataset_id, "DATASET_PROCESSING_FINISHED", { + "dataset_name": dataset_name, + "files": document_ids_str, + }) + except Exception as error: + await log_pipeline_status(dataset_id, "DATASET_PROCESSING_ERROR", { + "dataset_name": dataset_name, + "files": document_ids_str, + }) + raise error + + def generate_dataset_name(dataset_name: str) -> str: return dataset_name.replace(".", "_").replace(" ", "_") diff --git a/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py b/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py index 0f0e7bd1a..a41618f18 100644 --- a/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py +++ b/cognee/infrastructure/databases/vector/embeddings/LiteLLMEmbeddingEngine.py @@ -4,7 +4,7 @@ from litellm import aembedding from cognee.infrastructure.databases.vector.embeddings.EmbeddingEngine import EmbeddingEngine -litellm.set_verbose = True +litellm.set_verbose = False class LiteLLMEmbeddingEngine(EmbeddingEngine): api_key: str diff --git a/cognee/modules/data/processing/document_types/AudioDocument.py b/cognee/modules/data/processing/document_types/AudioDocument.py index e27726338..1eb85f177 100644 --- a/cognee/modules/data/processing/document_types/AudioDocument.py +++ b/cognee/modules/data/processing/document_types/AudioDocument.py @@ -6,18 +6,18 @@ class AudioDocument(Document): type: str = "audio" title: str - file_path: str - chunking_strategy:str + raw_data_location: str + chunking_strategy: str - def __init__(self, id: UUID, title: str, file_path: str, chunking_strategy:str="paragraph"): + def __init__(self, id: UUID, title: str, raw_data_location: str, chunking_strategy:str="paragraph"): self.id = id or uuid5(NAMESPACE_OID, title) self.title = title - self.file_path = file_path + self.raw_data_location = raw_data_location self.chunking_strategy = chunking_strategy def read(self): # Transcribe the audio file - result = get_llm_client().create_transcript(self.file_path) + result = get_llm_client().create_transcript(self.raw_data_location) text = result.text chunker = TextChunker(self.id, get_text = lambda: text) @@ -30,5 +30,5 @@ def to_dict(self) -> dict: id=str(self.id), type=self.type, title=self.title, - file_path=self.file_path, + raw_data_location=self.raw_data_location, ) diff --git a/cognee/modules/data/processing/document_types/Document.py b/cognee/modules/data/processing/document_types/Document.py index 6978ff83d..78eeecc11 100644 --- a/cognee/modules/data/processing/document_types/Document.py +++ b/cognee/modules/data/processing/document_types/Document.py @@ -5,7 +5,7 @@ class Document(Protocol): id: UUID type: str title: str - file_path: str + raw_data_location: str def read(self) -> str: pass diff --git a/cognee/modules/data/processing/document_types/ImageDocument.py b/cognee/modules/data/processing/document_types/ImageDocument.py index 6a7d83039..cd157a90b 100644 --- a/cognee/modules/data/processing/document_types/ImageDocument.py +++ b/cognee/modules/data/processing/document_types/ImageDocument.py @@ -7,16 +7,16 @@ class ImageDocument(Document): type: str = "image" title: str - file_path: str + raw_data_location: str - def __init__(self, id: UUID, title: str, file_path: str): + def __init__(self, id: UUID, title: str, raw_data_location: str): self.id = id or uuid5(NAMESPACE_OID, title) self.title = title - self.file_path = file_path + self.raw_data_location = raw_data_location def read(self): # Transcribe the image file - result = get_llm_client().transcribe_image(self.file_path) + result = get_llm_client().transcribe_image(self.raw_data_location) text = result.choices[0].message.content chunker = TextChunker(self.id, get_text = lambda: text) @@ -29,5 +29,5 @@ def to_dict(self) -> dict: id=str(self.id), type=self.type, title=self.title, - file_path=self.file_path, + raw_data_location=self.raw_data_location, ) diff --git a/cognee/modules/data/processing/document_types/PdfDocument.py b/cognee/modules/data/processing/document_types/PdfDocument.py index 67b95ea35..d8adb69b8 100644 --- a/cognee/modules/data/processing/document_types/PdfDocument.py +++ b/cognee/modules/data/processing/document_types/PdfDocument.py @@ -6,15 +6,15 @@ class PdfDocument(Document): type: str = "pdf" title: str - file_path: str + raw_data_location: str - def __init__(self, id: UUID, title: str, file_path: str): + def __init__(self, id: UUID, title: str, raw_data_location: str): self.id = id or uuid5(NAMESPACE_OID, title) self.title = title - self.file_path = file_path + self.raw_data_location = raw_data_location def read(self) -> PdfReader: - file = PdfReader(self.file_path) + file = PdfReader(self.raw_data_location) def get_text(): for page in file.pages: @@ -32,5 +32,5 @@ def to_dict(self) -> dict: id = str(self.id), type = self.type, title = self.title, - file_path = self.file_path, + raw_data_location = self.raw_data_location, ) diff --git a/cognee/modules/data/processing/document_types/TextDocument.py b/cognee/modules/data/processing/document_types/TextDocument.py index 8660af391..84678dfa4 100644 --- a/cognee/modules/data/processing/document_types/TextDocument.py +++ b/cognee/modules/data/processing/document_types/TextDocument.py @@ -5,16 +5,16 @@ class TextDocument(Document): type: str = "text" title: str - file_path: str + raw_data_location: str - def __init__(self, id: UUID, title: str, file_path: str): + def __init__(self, id: UUID, title: str, raw_data_location: str): self.id = id or uuid5(NAMESPACE_OID, title) self.title = title - self.file_path = file_path + self.raw_data_location = raw_data_location def read(self): def get_text(): - with open(self.file_path, mode = "r", encoding = "utf-8") as file: + with open(self.raw_data_location, mode = "r", encoding = "utf-8") as file: while True: text = file.read(1024) @@ -34,5 +34,5 @@ def to_dict(self) -> dict: id = str(self.id), type = self.type, title = self.title, - file_path = self.file_path, + raw_data_location = self.raw_data_location, ) diff --git a/cognee/tasks/chunking/chunk_by_word.py b/cognee/tasks/chunking/chunk_by_word.py index 644404b2d..8621754d5 100644 --- a/cognee/tasks/chunking/chunk_by_word.py +++ b/cognee/tasks/chunking/chunk_by_word.py @@ -24,7 +24,7 @@ def is_real_paragraph_end(): while next_character is not None and (re.match(paragraph_endings, next_character) or next_character == " "): j += 1 next_character = data[j] if j < len(data) else None - if next_character.isupper(): + if next_character and next_character.isupper(): return True return False diff --git a/cognee/tasks/classify_documents/classify_documents.py b/cognee/tasks/classify_documents/classify_documents.py index 1428ee785..0c71ecc8a 100644 --- a/cognee/tasks/classify_documents/classify_documents.py +++ b/cognee/tasks/classify_documents/classify_documents.py @@ -3,10 +3,10 @@ def classify_documents(data_documents: list[Data]) -> list[Document]: documents = [ - PdfDocument(id = data_item.id, title=f"{data_item.name}.{data_item.extension}", file_path=data_item.raw_data_location) if data_item.extension == "pdf" else - AudioDocument(id = data_item.id, title=f"{data_item.name}.{data_item.extension}", file_path=data_item.raw_data_location) if data_item.extension == "audio" else - ImageDocument(id = data_item.id, title=f"{data_item.name}.{data_item.extension}", file_path=data_item.raw_data_location) if data_item.extension == "image" else - TextDocument(id = data_item.id, title=f"{data_item.name}.{data_item.extension}", file_path=data_item.raw_data_location) + PdfDocument(id = data_item.id, title=f"{data_item.name}.{data_item.extension}", raw_data_location=data_item.raw_data_location) if data_item.extension == "pdf" else + AudioDocument(id = data_item.id, title=f"{data_item.name}.{data_item.extension}", raw_data_location=data_item.raw_data_location) if data_item.extension == "audio" else + ImageDocument(id = data_item.id, title=f"{data_item.name}.{data_item.extension}", raw_data_location=data_item.raw_data_location) if data_item.extension == "image" else + TextDocument(id = data_item.id, title=f"{data_item.name}.{data_item.extension}", raw_data_location=data_item.raw_data_location) for data_item in data_documents ] From 3c07bc6e4a7ed7e81be8913194f1b13c170c8157 Mon Sep 17 00:00:00 2001 From: Boris Arzentar Date: Fri, 20 Sep 2024 17:59:06 +0200 Subject: [PATCH 8/8] fix: update 1.5 notebook --- notebooks/cognee_demo_1.5.ipynb | 297 ++++++++++++-------------------- 1 file changed, 107 insertions(+), 190 deletions(-) diff --git a/notebooks/cognee_demo_1.5.ipynb b/notebooks/cognee_demo_1.5.ipynb index 4cf72171b..52760d949 100644 --- a/notebooks/cognee_demo_1.5.ipynb +++ b/notebooks/cognee_demo_1.5.ipynb @@ -1,13 +1,16 @@ { "cells": [ { + "cell_type": "code", + "execution_count": 1, + "id": "958375a6ffc0c2e4", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:47.336283Z", "start_time": "2024-09-20T14:02:43.652444Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "import asyncio\n", "import logging\n", @@ -33,24 +36,20 @@ " chunks_into_graph, \\\n", " source_documents_to_chunks, \\\n", " check_permissions_on_documents, \\\n", - " classify_documents\n", - "\n", - "logger = logging.getLogger(\"cognify.v2\")\n", - "\n", - "update_status_lock = asyncio.Lock()" - ], - "id": "958375a6ffc0c2e4", - "outputs": [], - "execution_count": 1 + " classify_documents" + ] }, { + "cell_type": "code", + "execution_count": 2, + "id": "df16431d0f48b006", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:48.519686Z", "start_time": "2024-09-20T14:02:48.515589Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "job_position = \"\"\"Senior Data Scientist (Machine Learning)\n", "\n", @@ -77,19 +76,19 @@ "Strong problem-solving skills and attention to detail.\n", "Candidate CVs\n", "\"\"\"\n" - ], - "id": "df16431d0f48b006", - "outputs": [], - "execution_count": 2 + ] }, { + "cell_type": "code", + "execution_count": 3, + "id": "9086abf3af077ab4", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:49.120838Z", "start_time": "2024-09-20T14:02:49.118294Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "job_1 = \"\"\"\n", "CV 1: Relevant\n", @@ -122,19 +121,19 @@ "Big Data Technologies: Hadoop, Spark\n", "Data Visualization: Tableau, Matplotlib\n", "\"\"\"" - ], - "id": "9086abf3af077ab4", - "outputs": [], - "execution_count": 3 + ] }, { + "cell_type": "code", + "execution_count": 4, + "id": "a9de0cc07f798b7f", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:49.675003Z", "start_time": "2024-09-20T14:02:49.671615Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "job_2 = \"\"\"\n", "CV 2: Relevant\n", @@ -166,19 +165,19 @@ "Data Visualization: Seaborn, Plotly\n", "Databases: MySQL, MongoDB\n", "\"\"\"" - ], - "id": "a9de0cc07f798b7f", - "outputs": [], - "execution_count": 4 + ] }, { + "cell_type": "code", + "execution_count": 5, + "id": "185ff1c102d06111", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:50.286828Z", "start_time": "2024-09-20T14:02:50.284369Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "job_3 = \"\"\"\n", "CV 3: Relevant\n", @@ -210,19 +209,19 @@ "Statistical Analysis: SAS, SPSS\n", "Cloud Platforms: AWS, Azure\n", "\"\"\"" - ], - "id": "185ff1c102d06111", - "outputs": [], - "execution_count": 5 + ] }, { + "cell_type": "code", + "execution_count": 6, + "id": "d55ce4c58f8efb67", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:50.950343Z", "start_time": "2024-09-20T14:02:50.946378Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "job_4 = \"\"\"\n", "CV 4: Not Relevant\n", @@ -252,19 +251,19 @@ "Web Design: HTML, CSS\n", "Specialties: Branding and Identity, Typography\n", "\"\"\"" - ], - "id": "d55ce4c58f8efb67", - "outputs": [], - "execution_count": 6 + ] }, { + "cell_type": "code", + "execution_count": 7, + "id": "ca4ecc32721ad332", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:51.548191Z", "start_time": "2024-09-20T14:02:51.545520Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "job_5 = \"\"\"\n", "CV 5: Not Relevant\n", @@ -294,19 +293,19 @@ "CRM Software: Salesforce, Zoho\n", "Negotiation and Relationship Building\n", "\"\"\"" - ], - "id": "ca4ecc32721ad332", - "outputs": [], - "execution_count": 7 + ] }, { + "cell_type": "code", + "execution_count": null, + "id": "904df61ba484a8e5", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:54.243987Z", "start_time": "2024-09-20T14:02:52.498195Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "import cognee\n", "from os import listdir, path\n", @@ -317,61 +316,32 @@ "\n", "for result in results:\n", " print(result)" - ], - "id": "904df61ba484a8e5", - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "sys:1: SAWarning: TypeDecorator UUID() will not produce a cache key because the ``cache_ok`` attribute is not set to True. This can have significant performance implications including some performance degradations in comparison to prior SQLAlchemy versions. Set this attribute to True if this type object's state is safe to use in a cache key, or False to disable this warning. (Background on this warning at: https://sqlalche.me/e/20/cprf)\n", - "2024-09-20 16:02:52,880|[WARNING]|53377|8480345088|dlt|utils.py|resolve_merge_strategy:223|Destination does not support any merge strategies and `merge` write disposition for table `file_metadata` cannot be met and will fall back to `append`. Change write disposition.2024-09-20 16:02:53,216|[WARNING]|53377|8480345088|dlt|utils.py|resolve_merge_strategy:223|Destination does not support any merge strategies and `merge` write disposition for table `file_metadata` cannot be met and will fall back to `append`. Change write disposition." - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "{'1726840972.7469912': [{'started_at': DateTime(2024, 9, 20, 14, 2, 53, 214773, tzinfo=Timezone('UTC')), 'finished_at': DateTime(2024, 9, 20, 14, 2, 54, 239978, tzinfo=Timezone('UTC')), 'job_metrics': {'file_metadata.a5a9170f4c.typed-jsonl': LoadJobMetrics(job_id='file_metadata.a5a9170f4c.typed-jsonl', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/normalized/1726840972.7469912/started_jobs/file_metadata.a5a9170f4c.0.typed-jsonl', table_name='file_metadata', started_at=DateTime(2024, 9, 20, 14, 2, 53, 220755, tzinfo=Timezone('UTC')), finished_at=DateTime(2024, 9, 20, 14, 2, 53, 222174, tzinfo=Timezone('UTC')), state='completed', remote_url=None)}}]}\n", - "dlt.destinations.sqlalchemy\n", - "sqlite:///cognee_db\n", - "sqlalchemy\n", - "None\n", - "None\n", - "None\n", - "None\n", - "\n", - "example\n", - "['1726840972.7469912']\n", - "[LoadPackageInfo(load_id='1726840972.7469912', package_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726840972.7469912', state='loaded', schema=Schema file_load_from_filesystem at 6038968784, schema_update={}, completed_at=DateTime(2024, 9, 20, 14, 2, 54, 235948, tzinfo=Timezone('UTC')), jobs={'failed_jobs': [], 'started_jobs': [], 'completed_jobs': [LoadJobInfo(state='completed_jobs', file_path='/Users/vasa/.dlt/pipelines/file_load_from_filesystem/load/loaded/1726840972.7469912/completed_jobs/file_metadata.a5a9170f4c.0.typed-jsonl', file_size=670, created_at=DateTime(2024, 9, 20, 14, 2, 52, 881922, tzinfo=Timezone('UTC')), elapsed=1.3540260791778564, job_file_info=ParsedLoadJobFileName(table_name='file_metadata', file_id='a5a9170f4c', retry_count=0, file_format='typed-jsonl'), failed_message=None)], 'new_jobs': []})]\n", - "False\n" - ] - } - ], - "execution_count": 8 + ] }, { + "cell_type": "code", + "execution_count": 8, + "id": "6f9b564de121713d", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:55.564445Z", "start_time": "2024-09-20T14:02:55.562784Z" } }, - "cell_type": "code", - "source": "", - "id": "6f9b564de121713d", "outputs": [], - "execution_count": 8 + "source": [] }, { + "cell_type": "code", + "execution_count": 9, + "id": "8911f8bd4f8c440a", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:56.714408Z", "start_time": "2024-09-20T14:02:56.711812Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "# from enum import Enum, auto\n", "# from typing import Optional, List, Union, Dict, Any\n", @@ -396,19 +366,19 @@ "# \"\"\"Knowledge graph.\"\"\"\n", "# nodes: List[Node] = Field(..., default_factory=list)\n", "# edges: List[Edge] = Field(..., default_factory=list)" - ], - "id": "8911f8bd4f8c440a", - "outputs": [], - "execution_count": 9 + ] }, { + "cell_type": "code", + "execution_count": 10, + "id": "7c431fdef4921ae0", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:57.925667Z", "start_time": "2024-09-20T14:02:57.922353Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "async def run_cognify_pipeline(dataset: Dataset, user: User = None):\n", " data_documents: list[Data] = await get_dataset_data(dataset_id = dataset.id)\n", @@ -418,7 +388,7 @@ " root_node_id = None\n", "\n", " tasks = [\n", - " \n", + " Task(classify_documents),\n", " Task(check_permissions_on_documents, user = user, permissions = [\"write\"]),\n", " Task(infer_data_ontology, root_node_id = root_node_id, ontology_model = KnowledgeGraph),\n", " Task(source_documents_to_chunks, parent_node_id = root_node_id), # Classify documents and save them as a nodes in graph db, extract text chunks based on the document type\n", @@ -437,138 +407,85 @@ " print(result)\n", " except Exception as error:\n", " raise error" - ], - "id": "7c431fdef4921ae0", - "outputs": [], - "execution_count": 10 + ] }, { + "cell_type": "code", + "execution_count": null, + "id": "f0a91b99c6215e09", "metadata": { "ExecuteTime": { "end_time": "2024-09-20T14:02:58.905774Z", "start_time": "2024-09-20T14:02:58.625915Z" } }, - "cell_type": "code", + "outputs": [], "source": [ "user = await get_default_user()\n", "datasets = await get_datasets_by_name([\"example\"], user.id)\n", "await run_cognify_pipeline(datasets[0], user)" - ], - "id": "f0a91b99c6215e09", - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Error occurred while running async generator task: `infer_data_ontology`\n", - "'Data' object has no attribute 'file_path'\n", - "Traceback (most recent call last):\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 26, in run_tasks\n", - " async for partial_result in async_iterator:\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py\", line 176, in infer_data_ontology\n", - " root_node_id = await ontology_engine.add_graph_ontology(documents = documents)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py\", line 92, in add_graph_ontology\n", - " with open(base_file.file_path, \"rb\") as file:\n", - " ^^^^^^^^^^^^^^^^^^^\n", - "AttributeError: 'Data' object has no attribute 'file_path'Error occurred while running coroutine task: `check_permissions_on_documents`\n", - "'Data' object has no attribute 'file_path'\n", - "Traceback (most recent call last):\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 86, in run_tasks\n", - " async for result in run_tasks(leftover_tasks, task_result):\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 49, in run_tasks\n", - " raise error\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py\", line 26, in run_tasks\n", - " async for partial_result in async_iterator:\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py\", line 176, in infer_data_ontology\n", - " root_node_id = await ontology_engine.add_graph_ontology(documents = documents)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/Users/vasa/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py\", line 92, in add_graph_ontology\n", - " with open(base_file.file_path, \"rb\") as file:\n", - " ^^^^^^^^^^^^^^^^^^^\n", - "AttributeError: 'Data' object has no attribute 'file_path'" - ] - }, - { - "ename": "AttributeError", - "evalue": "'Data' object has no attribute 'file_path'", - "output_type": "error", - "traceback": [ - "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mAttributeError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[11], line 3\u001B[0m\n\u001B[1;32m 1\u001B[0m user \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m get_default_user()\n\u001B[1;32m 2\u001B[0m datasets \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m get_datasets_by_name([\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mexample\u001B[39m\u001B[38;5;124m\"\u001B[39m], user\u001B[38;5;241m.\u001B[39mid)\n\u001B[0;32m----> 3\u001B[0m \u001B[38;5;28;01mawait\u001B[39;00m run_cognify_pipeline(datasets[\u001B[38;5;241m0\u001B[39m], user)\n", - "Cell \u001B[0;32mIn[10], line 27\u001B[0m, in \u001B[0;36mrun_cognify_pipeline\u001B[0;34m(dataset, user)\u001B[0m\n\u001B[1;32m 25\u001B[0m \u001B[38;5;28mprint\u001B[39m(result)\n\u001B[1;32m 26\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[0;32m---> 27\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n", - "Cell \u001B[0;32mIn[10], line 24\u001B[0m, in \u001B[0;36mrun_cognify_pipeline\u001B[0;34m(dataset, user)\u001B[0m\n\u001B[1;32m 8\u001B[0m tasks \u001B[38;5;241m=\u001B[39m [\n\u001B[1;32m 9\u001B[0m \n\u001B[1;32m 10\u001B[0m Task(check_permissions_on_documents, user \u001B[38;5;241m=\u001B[39m user, permissions \u001B[38;5;241m=\u001B[39m [\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mwrite\u001B[39m\u001B[38;5;124m\"\u001B[39m]),\n\u001B[0;32m (...)\u001B[0m\n\u001B[1;32m 19\u001B[0m Task(chunk_remove_disconnected), \u001B[38;5;66;03m# Remove the obsolete document chunks.\u001B[39;00m\n\u001B[1;32m 20\u001B[0m ]\n\u001B[1;32m 22\u001B[0m pipeline \u001B[38;5;241m=\u001B[39m run_tasks(tasks, data_documents)\n\u001B[0;32m---> 24\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m result \u001B[38;5;129;01min\u001B[39;00m pipeline:\n\u001B[1;32m 25\u001B[0m \u001B[38;5;28mprint\u001B[39m(result)\n\u001B[1;32m 26\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:97\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 90\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[1;32m 91\u001B[0m logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 92\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mError occurred while running coroutine task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 93\u001B[0m running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m,\n\u001B[1;32m 94\u001B[0m \u001B[38;5;28mstr\u001B[39m(error),\n\u001B[1;32m 95\u001B[0m exc_info \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m,\n\u001B[1;32m 96\u001B[0m )\n\u001B[0;32m---> 97\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n\u001B[1;32m 99\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m inspect\u001B[38;5;241m.\u001B[39misfunction(running_task\u001B[38;5;241m.\u001B[39mexecutable):\n\u001B[1;32m 100\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mRunning function task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:86\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 83\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m 84\u001B[0m task_result \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m running_task\u001B[38;5;241m.\u001B[39mrun(\u001B[38;5;241m*\u001B[39margs)\n\u001B[0;32m---> 86\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m result \u001B[38;5;129;01min\u001B[39;00m run_tasks(leftover_tasks, task_result):\n\u001B[1;32m 87\u001B[0m \u001B[38;5;28;01myield\u001B[39;00m result\n\u001B[1;32m 89\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mFinished coroutine task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:49\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 42\u001B[0m \u001B[38;5;28;01mexcept\u001B[39;00m \u001B[38;5;167;01mException\u001B[39;00m \u001B[38;5;28;01mas\u001B[39;00m error:\n\u001B[1;32m 43\u001B[0m logger\u001B[38;5;241m.\u001B[39merror(\n\u001B[1;32m 44\u001B[0m \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mError occurred while running async generator task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;130;01m\\n\u001B[39;00m\u001B[38;5;124m\"\u001B[39m,\n\u001B[1;32m 45\u001B[0m running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m,\n\u001B[1;32m 46\u001B[0m \u001B[38;5;28mstr\u001B[39m(error),\n\u001B[1;32m 47\u001B[0m exc_info \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mTrue\u001B[39;00m,\n\u001B[1;32m 48\u001B[0m )\n\u001B[0;32m---> 49\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m error\n\u001B[1;32m 51\u001B[0m \u001B[38;5;28;01melif\u001B[39;00m inspect\u001B[38;5;241m.\u001B[39misgeneratorfunction(running_task\u001B[38;5;241m.\u001B[39mexecutable):\n\u001B[1;32m 52\u001B[0m logger\u001B[38;5;241m.\u001B[39minfo(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mRunning generator task: `\u001B[39m\u001B[38;5;132;01m%s\u001B[39;00m\u001B[38;5;124m`\u001B[39m\u001B[38;5;124m\"\u001B[39m, running_task\u001B[38;5;241m.\u001B[39mexecutable\u001B[38;5;241m.\u001B[39m\u001B[38;5;18m__name__\u001B[39m)\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/modules/pipelines/operations/run_tasks.py:26\u001B[0m, in \u001B[0;36mrun_tasks\u001B[0;34m(tasks, data)\u001B[0m\n\u001B[1;32m 22\u001B[0m results \u001B[38;5;241m=\u001B[39m []\n\u001B[1;32m 24\u001B[0m async_iterator \u001B[38;5;241m=\u001B[39m running_task\u001B[38;5;241m.\u001B[39mrun(\u001B[38;5;241m*\u001B[39margs)\n\u001B[0;32m---> 26\u001B[0m \u001B[38;5;28;01masync\u001B[39;00m \u001B[38;5;28;01mfor\u001B[39;00m partial_result \u001B[38;5;129;01min\u001B[39;00m async_iterator:\n\u001B[1;32m 27\u001B[0m results\u001B[38;5;241m.\u001B[39mappend(partial_result)\n\u001B[1;32m 29\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mlen\u001B[39m(results) \u001B[38;5;241m==\u001B[39m next_task_batch_size:\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py:176\u001B[0m, in \u001B[0;36minfer_data_ontology\u001B[0;34m(documents, ontology_model, root_node_id)\u001B[0m\n\u001B[1;32m 174\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m ontology_model \u001B[38;5;241m==\u001B[39m KnowledgeGraph:\n\u001B[1;32m 175\u001B[0m ontology_engine \u001B[38;5;241m=\u001B[39m OntologyEngine()\n\u001B[0;32m--> 176\u001B[0m root_node_id \u001B[38;5;241m=\u001B[39m \u001B[38;5;28;01mawait\u001B[39;00m ontology_engine\u001B[38;5;241m.\u001B[39madd_graph_ontology(documents \u001B[38;5;241m=\u001B[39m documents)\n\u001B[1;32m 177\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m 178\u001B[0m graph_engine \u001B[38;5;241m=\u001B[39m get_graph_engine()\n", - "File \u001B[0;32m~/Projects/cognee/.venv/lib/python3.11/site-packages/cognee/tasks/infer_data_ontology/infer_data_ontology.py:92\u001B[0m, in \u001B[0;36mOntologyEngine.add_graph_ontology\u001B[0;34m(self, file_path, documents)\u001B[0m\n\u001B[1;32m 89\u001B[0m chunk_strategy \u001B[38;5;241m=\u001B[39m chunk_config\u001B[38;5;241m.\u001B[39mchunk_strategy\n\u001B[1;32m 91\u001B[0m \u001B[38;5;28;01mfor\u001B[39;00m base_file \u001B[38;5;129;01min\u001B[39;00m documents:\n\u001B[0;32m---> 92\u001B[0m \u001B[38;5;28;01mwith\u001B[39;00m \u001B[38;5;28mopen\u001B[39m(\u001B[43mbase_file\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mfile_path\u001B[49m, \u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mrb\u001B[39m\u001B[38;5;124m\"\u001B[39m) \u001B[38;5;28;01mas\u001B[39;00m file:\n\u001B[1;32m 93\u001B[0m \u001B[38;5;28;01mtry\u001B[39;00m:\n\u001B[1;32m 94\u001B[0m file_type \u001B[38;5;241m=\u001B[39m guess_file_type(file)\n", - "\u001B[0;31mAttributeError\u001B[0m: 'Data' object has no attribute 'file_path'" - ] - } - ], - "execution_count": 11 + ] }, { - "metadata": {}, "cell_type": "code", + "execution_count": null, + "id": "080389e5", + "metadata": {}, + "outputs": [], "source": [ + "import os\n", + "from cognee.shared.utils import render_graph\n", + "from cognee.infrastructure.databases.graph import get_graph_engine\n", + "import graphistry\n", "\n", + "# # Setting an environment variable\n", + "# os.environ[\"GRAPHISTRY_USERNAME\"] = placeholder\n", + "# os.environ[\"GRAPHISTRY_PASSWORD\"] = placeholder\n", "\n", - "async def cognify(datasets: Union[str, list[str]] = None, user: User = None):\n", - " if user is None:\n", - " user = await get_default_user()\n", "\n", - " existing_datasets = await get_datasets(user.id)\n", + "graphistry.login(username=os.getenv(\"GRAPHISTRY_USERNAME\"), password=os.getenv(\"GRAPHISTRY_PASSWORD\"))\n", "\n", - " if datasets is None or len(datasets) == 0:\n", - " # If no datasets are provided, cognify all existing datasets.\n", - " datasets = existing_datasets\n", - "\n", - " if type(datasets[0]) == str:\n", - " datasets = await get_datasets_by_name(datasets, user.id)\n", + "graph_engine = await get_graph_engine()\n", "\n", + "graph_url = await render_graph(graph_engine.graph)\n", + "print(graph_url)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5e7dfc8", + "metadata": {}, + "outputs": [], + "source": [ + "async def search(\n", + " vector_engine,\n", + " collection_name: str,\n", + " query_text: str = None,\n", + "):\n", + " query_vector = (await vector_engine.embedding_engine.embed_text([query_text]))[0]\n", "\n", + " connection = await vector_engine.get_connection()\n", + " collection = await connection.open_table(collection_name)\n", "\n", + " results = await collection.vector_search(query_vector).limit(10).to_pandas()\n", "\n", - " existing_datasets_map = {\n", - " dataset.name: True for dataset in existing_datasets\n", - " }\n", + " result_values = list(results.to_dict(\"index\").values())\n", "\n", - " awaitables = []\n", + " return [dict(\n", + " id = str(result[\"id\"]),\n", + " payload = result[\"payload\"],\n", + " score = result[\"_distance\"],\n", + " ) for result in result_values]\n", "\n", - " for dataset in datasets:\n", - " # print(\"here is the dataset\", dataset)\n", - " dataset_name = dataset.name\n", "\n", - " if dataset_name in existing_datasets_map:\n", - " awaitables.append(run_cognify_pipeline(dataset, user))\n", + "from cognee.infrastructure.databases.vector import get_vector_engine\n", "\n", - " return await asyncio.gather(*awaitables)\n", - "\n" - ], - "id": "e7d4f03f7dab9807", - "outputs": [], - "execution_count": null - }, - { - "metadata": {}, - "cell_type": "code", - "source": "await cognify(\"example\")", - "id": "d9248a01352964e2", - "outputs": [], - "execution_count": null - }, - { - "metadata": {}, - "cell_type": "code", - "source": "", - "id": "6afc6307bd115dbe", - "outputs": [], - "execution_count": null + "vector_engine = get_vector_engine()\n", + "results = await search(vector_engine, \"entities\", \"sarah.nguyen@example.com\")\n", + "for result in results:\n", + " print(result)" + ] } ], "metadata": { @@ -587,7 +504,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.6" + "version": "3.9.18" } }, "nbformat": 4,