mirror of
https://github.com/MODSetter/SurfSense.git
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aa00822169
- Added DOCLING as third ETL_SERVICE option (alongside UNSTRUCTURED/LLAMACLOUD) - Implemented add_received_file_document_using_docling function - Added Docling processing logic in documents_routes.py - Enhanced chunking with configurable overlap support - Added comprehensive document processing service - Supports both CPU and GPU processing with user selection Addresses #161 - Add Docling Support as an ETL_SERVICE Follows same pattern as LlamaCloud integration (PR #123)
523 lines
18 KiB
Python
523 lines
18 KiB
Python
from litellm import atranscription
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from fastapi import APIRouter, Depends, BackgroundTasks, UploadFile, Form, HTTPException
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy.future import select
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from typing import List
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from app.db import get_async_session, User, SearchSpace, Document, DocumentType
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from app.schemas import DocumentsCreate, DocumentUpdate, DocumentRead
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from app.users import current_active_user
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from app.utils.check_ownership import check_ownership
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from app.tasks.background_tasks import add_received_markdown_file_document, add_extension_received_document, add_received_file_document_using_unstructured, add_crawled_url_document, add_youtube_video_document, add_received_file_document_using_llamacloud, add_received_file_document_using_docling
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from app.config import config as app_config
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# Force asyncio to use standard event loop before unstructured imports
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import asyncio
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try:
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asyncio.set_event_loop_policy(asyncio.DefaultEventLoopPolicy())
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except RuntimeError:
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pass
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import os
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os.environ["UNSTRUCTURED_HAS_PATCHED_LOOP"] = "1"
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router = APIRouter()
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@router.post("/documents/")
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async def create_documents(
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request: DocumentsCreate,
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session: AsyncSession = Depends(get_async_session),
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user: User = Depends(current_active_user),
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fastapi_background_tasks: BackgroundTasks = BackgroundTasks()
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):
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try:
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# Check if the user owns the search space
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await check_ownership(session, SearchSpace, request.search_space_id, user)
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if request.document_type == DocumentType.EXTENSION:
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for individual_document in request.content:
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fastapi_background_tasks.add_task(
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process_extension_document_with_new_session,
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individual_document,
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request.search_space_id,
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str(user.id)
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)
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elif request.document_type == DocumentType.CRAWLED_URL:
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for url in request.content:
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fastapi_background_tasks.add_task(
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process_crawled_url_with_new_session,
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url,
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request.search_space_id,
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str(user.id)
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)
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elif request.document_type == DocumentType.YOUTUBE_VIDEO:
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for url in request.content:
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fastapi_background_tasks.add_task(
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process_youtube_video_with_new_session,
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url,
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request.search_space_id,
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str(user.id)
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)
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else:
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raise HTTPException(
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status_code=400,
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detail="Invalid document type"
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)
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await session.commit()
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return {"message": "Documents processed successfully"}
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except HTTPException:
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raise
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except Exception as e:
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await session.rollback()
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raise HTTPException(
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status_code=500,
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detail=f"Failed to process documents: {str(e)}"
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)
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@router.post("/documents/fileupload")
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async def create_documents(
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files: list[UploadFile],
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search_space_id: int = Form(...),
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session: AsyncSession = Depends(get_async_session),
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user: User = Depends(current_active_user),
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fastapi_background_tasks: BackgroundTasks = BackgroundTasks()
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):
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try:
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await check_ownership(session, SearchSpace, search_space_id, user)
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if not files:
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raise HTTPException(status_code=400, detail="No files provided")
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for file in files:
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try:
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# Save file to a temporary location to avoid stream issues
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import tempfile
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import aiofiles
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import os
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# Create temp file
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with tempfile.NamedTemporaryFile(delete=False, suffix=os.path.splitext(file.filename)[1]) as temp_file:
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temp_path = temp_file.name
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# Write uploaded file to temp file
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content = await file.read()
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with open(temp_path, "wb") as f:
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f.write(content)
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fastapi_background_tasks.add_task(
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process_file_in_background_with_new_session,
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temp_path,
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file.filename,
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search_space_id,
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str(user.id)
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)
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except Exception as e:
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raise HTTPException(
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status_code=422,
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detail=f"Failed to process file {file.filename}: {str(e)}"
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)
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await session.commit()
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return {"message": "Files uploaded for processing"}
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except HTTPException:
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raise
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except Exception as e:
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await session.rollback()
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raise HTTPException(
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status_code=500,
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detail=f"Failed to upload files: {str(e)}"
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)
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async def process_file_in_background(
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file_path: str,
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filename: str,
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search_space_id: int,
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user_id: str,
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session: AsyncSession
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):
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try:
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# Check if the file is a markdown or text file
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if filename.lower().endswith(('.md', '.markdown', '.txt')):
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# For markdown files, read the content directly
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with open(file_path, 'r', encoding='utf-8') as f:
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markdown_content = f.read()
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# Clean up the temp file
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import os
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try:
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os.unlink(file_path)
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except:
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pass
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# Process markdown directly through specialized function
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await add_received_markdown_file_document(
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session,
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filename,
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markdown_content,
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search_space_id,
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user_id
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)
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# Check if the file is an audio file
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elif filename.lower().endswith(('.mp3', '.mp4', '.mpeg', '.mpga', '.m4a', '.wav', '.webm')):
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# Open the audio file for transcription
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with open(file_path, "rb") as audio_file:
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# Use LiteLLM for audio transcription
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if app_config.STT_SERVICE_API_BASE:
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transcription_response = await atranscription(
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model=app_config.STT_SERVICE,
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file=audio_file,
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api_base=app_config.STT_SERVICE_API_BASE,
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api_key=app_config.STT_SERVICE_API_KEY
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)
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else:
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transcription_response = await atranscription(
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model=app_config.STT_SERVICE,
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api_key=app_config.STT_SERVICE_API_KEY,
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file=audio_file
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)
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# Extract the transcribed text
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transcribed_text = transcription_response.get("text", "")
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# Add metadata about the transcription
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transcribed_text = f"# Transcription of {filename}\n\n{transcribed_text}"
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# Clean up the temp file
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try:
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os.unlink(file_path)
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except:
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pass
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# Process transcription as markdown document
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await add_received_markdown_file_document(
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session,
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filename,
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transcribed_text,
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search_space_id,
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user_id
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)
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else:
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if app_config.ETL_SERVICE == "UNSTRUCTURED":
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from langchain_unstructured import UnstructuredLoader
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# Process the file
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loader = UnstructuredLoader(
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file_path,
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mode="elements",
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post_processors=[],
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languages=["eng"],
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include_orig_elements=False,
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include_metadata=False,
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strategy="auto",
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)
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docs = await loader.aload()
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# Clean up the temp file
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import os
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try:
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os.unlink(file_path)
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except:
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pass
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# Pass the documents to the existing background task
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await add_received_file_document_using_unstructured(
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session,
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filename,
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docs,
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search_space_id,
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user_id
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)
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elif app_config.ETL_SERVICE == "LLAMACLOUD":
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from llama_cloud_services import LlamaParse
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from llama_cloud_services.parse.utils import ResultType
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# Create LlamaParse parser instance
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parser = LlamaParse(
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api_key=app_config.LLAMA_CLOUD_API_KEY,
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num_workers=1, # Use single worker for file processing
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verbose=True,
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language="en",
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result_type=ResultType.MD
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)
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# Parse the file asynchronously
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result = await parser.aparse(file_path)
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# Clean up the temp file
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import os
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try:
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os.unlink(file_path)
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except:
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pass
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# Get markdown documents from the result
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markdown_documents = await result.aget_markdown_documents(split_by_page=False)
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for doc in markdown_documents:
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# Extract text content from the markdown documents
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markdown_content = doc.text
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# Process the documents using our LlamaCloud background task
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await add_received_file_document_using_llamacloud(
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session,
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filename,
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llamacloud_markdown_document=markdown_content,
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search_space_id=search_space_id,
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user_id=user_id
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)
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elif app_config.ETL_SERVICE == "DOCLING":
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# Use Docling service for document processing
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from app.services.document_processing.docling_service import create_docling_service
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# Create Docling service
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docling_service = create_docling_service()
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# Process the document
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result = await docling_service.process_document(file_path, filename)
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# Clean up the temp file
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import os
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try:
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os.unlink(file_path)
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except:
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pass
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# Process the document using our Docling background task
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await add_received_file_document_using_docling(
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session,
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filename,
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docling_markdown_document=result['content'],
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search_space_id=search_space_id,
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user_id=user_id
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)
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except Exception as e:
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import logging
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logging.error(f"Error processing file in background: {str(e)}")
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@router.get("/documents/", response_model=List[DocumentRead])
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async def read_documents(
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skip: int = 0,
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limit: int = 300,
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search_space_id: int = None,
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session: AsyncSession = Depends(get_async_session),
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user: User = Depends(current_active_user)
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):
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try:
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query = select(Document).join(SearchSpace).filter(
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SearchSpace.user_id == user.id)
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# Filter by search_space_id if provided
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if search_space_id is not None:
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query = query.filter(Document.search_space_id == search_space_id)
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result = await session.execute(
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query.offset(skip).limit(limit)
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)
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db_documents = result.scalars().all()
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# Convert database objects to API-friendly format
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api_documents = []
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for doc in db_documents:
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api_documents.append(DocumentRead(
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id=doc.id,
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title=doc.title,
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document_type=doc.document_type,
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document_metadata=doc.document_metadata,
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content=doc.content,
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created_at=doc.created_at,
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search_space_id=doc.search_space_id
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))
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return api_documents
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except Exception as e:
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raise HTTPException(
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status_code=500,
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detail=f"Failed to fetch documents: {str(e)}"
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)
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@router.get("/documents/{document_id}", response_model=DocumentRead)
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async def read_document(
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document_id: int,
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session: AsyncSession = Depends(get_async_session),
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user: User = Depends(current_active_user)
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):
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try:
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result = await session.execute(
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select(Document)
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.join(SearchSpace)
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.filter(Document.id == document_id, SearchSpace.user_id == user.id)
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)
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document = result.scalars().first()
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if not document:
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raise HTTPException(
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status_code=404,
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detail=f"Document with id {document_id} not found"
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)
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# Convert database object to API-friendly format
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return DocumentRead(
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id=document.id,
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title=document.title,
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document_type=document.document_type,
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document_metadata=document.document_metadata,
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content=document.content,
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created_at=document.created_at,
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search_space_id=document.search_space_id
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)
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except Exception as e:
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raise HTTPException(
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status_code=500,
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detail=f"Failed to fetch document: {str(e)}"
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)
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@router.put("/documents/{document_id}", response_model=DocumentRead)
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async def update_document(
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document_id: int,
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document_update: DocumentUpdate,
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session: AsyncSession = Depends(get_async_session),
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user: User = Depends(current_active_user)
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):
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try:
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# Query the document directly instead of using read_document function
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result = await session.execute(
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select(Document)
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.join(SearchSpace)
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.filter(Document.id == document_id, SearchSpace.user_id == user.id)
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)
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db_document = result.scalars().first()
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if not db_document:
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raise HTTPException(
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status_code=404,
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detail=f"Document with id {document_id} not found"
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)
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update_data = document_update.model_dump(exclude_unset=True)
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for key, value in update_data.items():
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setattr(db_document, key, value)
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await session.commit()
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await session.refresh(db_document)
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# Convert to DocumentRead for response
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return DocumentRead(
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id=db_document.id,
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title=db_document.title,
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document_type=db_document.document_type,
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document_metadata=db_document.document_metadata,
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content=db_document.content,
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created_at=db_document.created_at,
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search_space_id=db_document.search_space_id
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)
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except HTTPException:
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raise
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except Exception as e:
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await session.rollback()
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raise HTTPException(
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status_code=500,
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detail=f"Failed to update document: {str(e)}"
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)
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@router.delete("/documents/{document_id}", response_model=dict)
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async def delete_document(
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document_id: int,
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session: AsyncSession = Depends(get_async_session),
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user: User = Depends(current_active_user)
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):
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try:
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# Query the document directly instead of using read_document function
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result = await session.execute(
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select(Document)
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.join(SearchSpace)
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.filter(Document.id == document_id, SearchSpace.user_id == user.id)
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)
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document = result.scalars().first()
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if not document:
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raise HTTPException(
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status_code=404,
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detail=f"Document with id {document_id} not found"
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)
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await session.delete(document)
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await session.commit()
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return {"message": "Document deleted successfully"}
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except HTTPException:
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raise
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except Exception as e:
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await session.rollback()
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raise HTTPException(
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status_code=500,
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detail=f"Failed to delete document: {str(e)}"
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)
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async def process_extension_document_with_new_session(
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individual_document,
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search_space_id: int,
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user_id: str
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):
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"""Create a new session and process extension document."""
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from app.db import async_session_maker
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async with async_session_maker() as session:
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try:
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await add_extension_received_document(session, individual_document, search_space_id, user_id)
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except Exception as e:
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import logging
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logging.error(f"Error processing extension document: {str(e)}")
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async def process_crawled_url_with_new_session(
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url: str,
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search_space_id: int,
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user_id: str
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):
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"""Create a new session and process crawled URL."""
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from app.db import async_session_maker
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async with async_session_maker() as session:
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try:
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await add_crawled_url_document(session, url, search_space_id, user_id)
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except Exception as e:
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import logging
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logging.error(f"Error processing crawled URL: {str(e)}")
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async def process_file_in_background_with_new_session(
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file_path: str,
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filename: str,
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search_space_id: int,
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user_id: str
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):
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"""Create a new session and process file."""
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from app.db import async_session_maker
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async with async_session_maker() as session:
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await process_file_in_background(file_path, filename, search_space_id, user_id, session)
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|
|
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async def process_youtube_video_with_new_session(
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url: str,
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search_space_id: int,
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user_id: str
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):
|
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"""Create a new session and process YouTube video."""
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from app.db import async_session_maker
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async with async_session_maker() as session:
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try:
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await add_youtube_video_document(session, url, search_space_id, user_id)
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except Exception as e:
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import logging
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logging.error(f"Error processing YouTube video: {str(e)}")
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