AnukulChandra/Mini-AI_Assistant

1import logging2 3from fastapi import APIRouter, UploadFile, File, HTTPException4from services.chunking import split_text5from services.ingestion import validate_file, read_document6from services.vector_store import create_vector_store, save_vector_store7 8logger = logging.getLogger(__name__)9 10router = APIRouter(prefix="/upload")11 12 13@router.post("/document")14async def upload_document(file: UploadFile = File(...)):15    try:16        validate_file(file)17    except ValueError as e:18        raise HTTPException(status_code=400, detail=str(e))19 20    try:21        text = read_document(file)22    except ValueError as e:23        raise HTTPException(status_code=400, detail=str(e))24 25    try:26        chunks = split_text(text)27        vector_store = create_vector_store(chunks)28        save_vector_store(vector_store)29    except Exception as e:30        logger.exception("Document processing failed")31        raise HTTPException(status_code=500, detail=f"Document processing failed: {e}")32 33    return {34        "filename": file.filename,35        "chunks": len(chunks),36        "message": "Document processed and indexed successfully.",37    }38