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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 | |
load_dotenv() | |
hf_token = os.environ.get('HUGGINGFACEHUB_API_TOKEN') | |
#starchat_repo_id = os.environ.get('starchat_repo_id') | |
#repo_id=os.environ.get('repo_id') | |
#port = os.getenv('port') | |
llm = HuggingFaceHub(repo_id=starchat_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() | |
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"} | |
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") |