0ce254b262
If text is added to cognee it will be saved by hash so the same text can't be stored multiple times Feature COG-505
157 lines
6.2 KiB
Python
157 lines
6.2 KiB
Python
from typing import List, Union, BinaryIO
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from os import path
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import asyncio
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import dlt
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import cognee.modules.ingestion as ingestion
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from cognee.infrastructure.files.storage import LocalStorage
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from cognee.modules.ingestion import get_matched_datasets, save_data_to_file
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from cognee.shared.utils import send_telemetry
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from cognee.base_config import get_base_config
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from cognee.infrastructure.databases.relational import get_relational_engine
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from cognee.modules.users.methods import get_default_user
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from cognee.tasks.ingestion import get_dlt_destination
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from cognee.modules.users.permissions.methods import give_permission_on_document
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from cognee.modules.users.models import User
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from cognee.modules.data.methods import create_dataset
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from cognee.infrastructure.databases.relational import create_db_and_tables as create_relational_db_and_tables
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from cognee.infrastructure.databases.vector.pgvector import create_db_and_tables as create_pgvector_db_and_tables
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async def add(data: Union[BinaryIO, List[BinaryIO], str, List[str]], dataset_name: str = "main_dataset", user: User = None):
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await create_relational_db_and_tables()
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await create_pgvector_db_and_tables()
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if isinstance(data, str):
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if "data://" in data:
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# data is a data directory path
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datasets = get_matched_datasets(data.replace("data://", ""), dataset_name)
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return await asyncio.gather(*[add(file_paths, dataset_name) for [dataset_name, file_paths] in datasets])
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if "file://" in data:
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# data is a file path
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return await add([data], dataset_name)
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# data is text
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else:
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file_path = save_data_to_file(data)
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return await add([file_path], dataset_name)
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if hasattr(data, "file"):
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file_path = save_data_to_file(data.file, filename = data.filename)
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return await add([file_path], dataset_name)
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# data is a list of file paths or texts
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file_paths = []
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for data_item in data:
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if hasattr(data_item, "file"):
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file_paths.append(save_data_to_file(data_item, filename = data_item.filename))
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elif isinstance(data_item, str) and (
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data_item.startswith("/") or data_item.startswith("file://")
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):
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file_paths.append(data_item)
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elif isinstance(data_item, str):
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file_paths.append(save_data_to_file(data_item))
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if len(file_paths) > 0:
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return await add_files(file_paths, dataset_name, user)
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return []
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async def add_files(file_paths: List[str], dataset_name: str, user: User = None):
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if user is None:
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user = await get_default_user()
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base_config = get_base_config()
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data_directory_path = base_config.data_root_directory
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processed_file_paths = []
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for file_path in file_paths:
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file_path = file_path.replace("file://", "")
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if data_directory_path not in file_path:
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file_name = file_path.split("/")[-1]
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file_directory_path = data_directory_path + "/" + (dataset_name.replace(".", "/") + "/" if dataset_name != "main_dataset" else "")
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dataset_file_path = path.join(file_directory_path, file_name)
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LocalStorage.ensure_directory_exists(file_directory_path)
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LocalStorage.copy_file(file_path, dataset_file_path)
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processed_file_paths.append(dataset_file_path)
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else:
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processed_file_paths.append(file_path)
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destination = get_dlt_destination()
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pipeline = dlt.pipeline(
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pipeline_name = "file_load_from_filesystem",
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destination = destination,
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)
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dataset_name = dataset_name.replace(" ", "_").replace(".", "_") if dataset_name is not None else "main_dataset"
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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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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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from sqlalchemy import select
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from cognee.modules.data.models import Data
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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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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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)).scalar_one_or_none()
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if data is not None:
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data.name = file_metadata["name"]
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data.raw_data_location = file_metadata["file_path"]
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data.extension = file_metadata["extension"]
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data.mime_type = file_metadata["mime_type"]
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await session.merge(data)
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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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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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mime_type = file_metadata["mime_type"],
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)
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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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send_telemetry("cognee.add EXECUTION STARTED", user_id = user.id)
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run_info = pipeline.run(
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data_resources(processed_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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send_telemetry("cognee.add EXECUTION COMPLETED", user_id = user.id)
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return run_info
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