main.py

import os
from dotenv import load_dotenv
from fastapi import FastAPI, Request, HTTPException
from langchain.document_loaders import WebBaseLoader
from langchain.chains.summarize import load_summarize_chain
from langchain import HuggingFaceHub
from huggingface_hub import InferenceClient
#from bs4 import BeautifulSoup
import requests
import sys

load_dotenv()
hf_token = os.environ.get('HUGGINGFACEHUB_API_TOKEN')
repo_id=os.environ.get('repo_id')
#port = os.getenv('port')

llm = HuggingFaceHub(repo_id=repo_id,  # for StarChat
                     huggingfacehub_api_token=hf_token,
                     model_kwargs={"min_length": 512,  # for StarChat
                                   "max_new_tokens": 1024, "do_sample": True,  # for StarChat
                                   "temperature": 0.01,
                                   "top_k": 50,
                                   "top_p": 0.95, "eos_token_id": 49155})
chain = load_summarize_chain(llm, chain_type="stuff")

app = FastAPI()

@app.post('/api/chat')
async def home_api(request: Request):
    data = await request.json()
    user_query = data['user_question']
    print(user_query)
    return {"Message": "FastAPI Home API Deploy Success on HF"}

@app.post('/api/chat')
async def chat(request: Request):
    data = await request.json()
    user_query = data['user_question']
    print(user_query)
    if user_query.strip() != "":
        try:
            loader = WebBaseLoader(user_query)
            print(user_query)
            docs = loader.load()
            result = chain.run(docs)
            
            
            print("AI Summarization: " + result)
            return {'response': result}
        except Exception as e:
            err_msg = "Wrong URL or URL not parsable."
            print(err_msg)
            raise HTTPException(status_code=400, detail=err_msg)
    else:
        raise HTTPException(status_code=400, detail="Invalid user question")