from fastapi.middleware.cors import CORSMiddleware from fastapi import FastAPI, UploadFile, File, HTTPException import os from pydantic import BaseModel from typing import List, Tuple from supabase import create_client, Client from tempfile import SpooledTemporaryFile import shutil import pypandoc from llm.summarization import llm_evaluate_summaries from utils import similarity_search from utils import CommonsDep from utils import ChatMessage from llm.qa import get_qa_llm from parsers.common import file_already_exists from parsers.txt import process_txt from parsers.csv import process_csv from parsers.docx import process_docx from parsers.pdf import process_pdf from parsers.notebook import process_ipnyb from parsers.markdown import process_markdown from parsers.powerpoint import process_powerpoint from parsers.html import process_html from parsers.epub import process_epub from parsers.audio import process_audio from crawl.crawler import CrawlWebsite from logger import get_logger logger = get_logger(__name__) app = FastAPI() origins = [ "http://localhost", "http://localhost:3000", "*", ] app.add_middleware( CORSMiddleware, allow_origins=origins, allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) @app.on_event("startup") async def startup_event(): pypandoc.download_pandoc() file_processors = { ".txt": process_txt, ".csv": process_csv, ".md": process_markdown, ".markdown": process_markdown, ".m4a": process_audio, ".mp3": process_audio, ".webm": process_audio, ".mp4": process_audio, ".mpga": process_audio, ".wav": process_audio, ".mpeg": process_audio, ".pdf": process_pdf, ".html": process_html, ".pptx": process_powerpoint, ".docx": process_docx, ".epub": process_epub, ".ipynb": process_ipnyb, } async def filter_file(file: UploadFile, enable_summarization: bool, supabase_client: Client): if await file_already_exists(supabase_client, file): return {"message": f"🤔 {file.filename} already exists.", "type": "warning"} elif file.file._file.tell() < 1: return {"message": f"❌ {file.filename} is empty.", "type": "error"} else: file_extension = os.path.splitext(file.filename)[-1] if file_extension in file_processors: await file_processors[file_extension](file, enable_summarization) return {"message": f"✅ {file.filename} has been uploaded.", "type": "success"} else: return {"message": f"❌ {file.filename} is not supported.", "type": "error"} @app.post("/upload") async def upload_file(commons: CommonsDep, file: UploadFile, enable_summarization: bool = False): message = await filter_file(file, enable_summarization, commons['supabase']) return message @app.post("/chat/") async def chat_endpoint(commons: CommonsDep, chat_message: ChatMessage): history = chat_message.history qa = get_qa_llm(chat_message) history.append(("user", chat_message.question)) if chat_message.use_summarization: # 1. get summaries from the vector store based on question summaries = similarity_search( chat_message.question, table='match_summaries') # 2. evaluate summaries against the question evaluations = llm_evaluate_summaries( chat_message.question, summaries, chat_message.model) # 3. pull in the top documents from summaries logger.info('Evaluations: %s', evaluations) if evaluations: reponse = commons['supabase'].from_('documents').select( '*').in_('id', values=[e['document_id'] for e in evaluations]).execute() # 4. use top docs as additional context additional_context = '---\nAdditional Context={}'.format( '---\n'.join(data['content'] for data in reponse.data) ) + '\n' model_response = qa( {"question": additional_context + chat_message.question}) else: model_response = qa({"question": chat_message.question}) history.append(("assistant", model_response["answer"])) return {"history": history} @app.post("/crawl/") async def crawl_endpoint(commons: CommonsDep, crawl_website: CrawlWebsite, enable_summarization: bool = False): file_path, file_name = crawl_website.process() # Create a SpooledTemporaryFile from the file_path spooled_file = SpooledTemporaryFile() with open(file_path, 'rb') as f: shutil.copyfileobj(f, spooled_file) # Pass the SpooledTemporaryFile to UploadFile file = UploadFile(file=spooled_file, filename=file_name) message = await filter_file(file, enable_summarization, commons['supabase']) return message @app.get("/explore") async def explore_endpoint(commons: CommonsDep): response = commons['supabase'].table("documents").select( "name:metadata->>file_name, size:metadata->>file_size", count="exact").execute() documents = response.data # Access the data from the response # Convert each dictionary to a tuple of items, then to a set to remove duplicates, and then back to a dictionary unique_data = [dict(t) for t in set(tuple(d.items()) for d in documents)] # Sort the list of documents by size in decreasing order unique_data.sort(key=lambda x: int(x['size']), reverse=True) return {"documents": unique_data} @app.delete("/explore/{file_name}") async def delete_endpoint(commons: CommonsDep, file_name: str): # Cascade delete the summary from the database first, because it has a foreign key constraint commons['supabase'].table("summaries").delete().match( {"metadata->>file_name": file_name}).execute() commons['supabase'].table("documents").delete().match( {"metadata->>file_name": file_name}).execute() return {"message": f"{file_name} has been deleted."} @app.get("/explore/{file_name}") async def download_endpoint(commons: CommonsDep, file_name: str): response = commons['supabase'].table("documents").select( "metadata->>file_name, metadata->>file_size, metadata->>file_extension, metadata->>file_url").match({"metadata->>file_name": file_name}).execute() documents = response.data # Returns all documents with the same file name return {"documents": documents} @app.get("/") async def root(): return {"message": "Hello World"}