Cog 678 relational database singleton (#38)
1. Set relational database in cognee to be used as singleton and made necessary changes to enable this 2. Added SQLite support to dlt pipeline in ingest_data
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commit
34971d16cc
5 changed files with 74 additions and 32 deletions
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@ -1,8 +1,10 @@
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from functools import lru_cache
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from .config import get_relational_config
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from .create_relational_engine import create_relational_engine
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@lru_cache
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def get_relational_engine():
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relational_config = get_relational_config()
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return create_relational_engine(**relational_config.to_dict())
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return create_relational_engine(**relational_config.to_dict())
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@ -6,7 +6,6 @@ from contextlib import asynccontextmanager
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from sqlalchemy import text, select, MetaData, Table
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from sqlalchemy.orm import joinedload
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from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine, async_sessionmaker
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from ..ModelBase import Base
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class SQLAlchemyAdapter():
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@ -171,6 +170,27 @@ class SQLAlchemyAdapter():
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results = await connection.execute(query)
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return {result["data_id"]: result["status"] for result in results}
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async def get_all_data_from_table(self, table_name: str, schema: str = "public"):
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async with self.get_async_session() as session:
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# Validate inputs to prevent SQL injection
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if not table_name.isidentifier():
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raise ValueError("Invalid table name")
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if schema and not schema.isidentifier():
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raise ValueError("Invalid schema name")
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if self.engine.dialect.name == "sqlite":
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table = await self.get_table(table_name)
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else:
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table = await self.get_table(table_name, schema)
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# Query all data from the table
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query = select(table)
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result = await session.execute(query)
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# Fetch all rows as a list of dictionaries
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rows = result.mappings().all()
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return rows
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async def execute_query(self, query):
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async with self.engine.begin() as connection:
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result = await connection.execute(text(query))
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@ -205,7 +225,6 @@ class SQLAlchemyAdapter():
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from cognee.infrastructure.files.storage import LocalStorage
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LocalStorage.remove(self.db_path)
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self.db_path = None
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else:
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async with self.engine.begin() as connection:
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schema_list = await self.get_schema_list()
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@ -1,12 +1,12 @@
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from ...relational.ModelBase import Base
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from ..get_vector_engine import get_vector_engine, get_vectordb_config
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from sqlalchemy import text
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async def create_db_and_tables():
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vector_config = get_vectordb_config()
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vector_engine = get_vector_engine()
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if vector_config.vector_db_provider == "pgvector":
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await vector_engine.create_database()
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async with vector_engine.engine.begin() as connection:
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await connection.execute(text("CREATE EXTENSION IF NOT EXISTS vector;"))
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@ -1,9 +1,12 @@
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import os
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from functools import lru_cache
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import dlt
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from typing import Union
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from cognee.infrastructure.databases.relational import get_relational_config
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@lru_cache
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def get_dlt_destination() -> Union[type[dlt.destinations.sqlalchemy], None]:
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"""
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Handles propagation of the cognee database configuration to the dlt library
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@ -1,6 +1,7 @@
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import dlt
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import cognee.modules.ingestion as ingestion
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from uuid import UUID
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from cognee.shared.utils import send_telemetry
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from cognee.modules.users.models import User
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from cognee.infrastructure.databases.relational import get_relational_engine
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@ -17,25 +18,33 @@ async def ingest_data(file_paths: list[str], dataset_name: str, user: User):
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)
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@dlt.resource(standalone = True, merge_key = "id")
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async def data_resources(file_paths: str, user: User):
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async def data_resources(file_paths: str):
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for file_path in file_paths:
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with open(file_path.replace("file://", ""), mode = "rb") as file:
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classified_data = ingestion.classify(file)
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data_id = ingestion.identify(classified_data)
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file_metadata = classified_data.get_metadata()
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yield {
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"id": data_id,
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"name": file_metadata["name"],
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"file_path": file_metadata["file_path"],
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"extension": file_metadata["extension"],
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"mime_type": file_metadata["mime_type"],
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}
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from sqlalchemy import select
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from cognee.modules.data.models import Data
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async def data_storing(table_name, dataset_name, user: User):
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db_engine = get_relational_engine()
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db_engine = get_relational_engine()
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async with db_engine.get_async_session() as session:
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async with db_engine.get_async_session() as session:
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# Read metadata stored with dlt
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files_metadata = await db_engine.get_all_data_from_table(table_name, dataset_name)
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for file_metadata in files_metadata:
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from sqlalchemy import select
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from cognee.modules.data.models import Data
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dataset = await create_dataset(dataset_name, user.id, session)
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data = (await session.execute(
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select(Data).filter(Data.id == data_id)
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select(Data).filter(Data.id == UUID(file_metadata["id"]))
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)).scalar_one_or_none()
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if data is not None:
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@ -48,7 +57,7 @@ async def ingest_data(file_paths: list[str], dataset_name: str, user: User):
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await session.commit()
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else:
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data = Data(
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id = data_id,
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id = UUID(file_metadata["id"]),
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name = file_metadata["name"],
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raw_data_location = file_metadata["file_path"],
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extension = file_metadata["extension"],
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@ -58,25 +67,34 @@ async def ingest_data(file_paths: list[str], dataset_name: str, user: User):
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dataset.data.append(data)
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await session.commit()
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yield {
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"id": data_id,
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"name": file_metadata["name"],
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"file_path": file_metadata["file_path"],
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"extension": file_metadata["extension"],
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"mime_type": file_metadata["mime_type"],
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}
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await give_permission_on_document(user, data_id, "read")
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await give_permission_on_document(user, data_id, "write")
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await give_permission_on_document(user, UUID(file_metadata["id"]), "read")
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await give_permission_on_document(user, UUID(file_metadata["id"]), "write")
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send_telemetry("cognee.add EXECUTION STARTED", user_id = user.id)
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run_info = pipeline.run(
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data_resources(file_paths, user),
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table_name = "file_metadata",
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dataset_name = dataset_name,
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write_disposition = "merge",
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)
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db_engine = get_relational_engine()
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# Note: DLT pipeline has its own event loop, therefore objects created in another event loop
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# can't be used inside the pipeline
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if db_engine.engine.dialect.name == "sqlite":
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# To use sqlite with dlt dataset_name must be set to "main".
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# Sqlite doesn't support schemas
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run_info = pipeline.run(
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data_resources(file_paths),
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table_name = "file_metadata",
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dataset_name = "main",
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write_disposition = "merge",
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)
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else:
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run_info = pipeline.run(
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data_resources(file_paths),
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table_name="file_metadata",
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dataset_name=dataset_name,
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write_disposition="merge",
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)
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await data_storing("file_metadata", dataset_name, user)
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send_telemetry("cognee.add EXECUTION COMPLETED", user_id = user.id)
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return run_info
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