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import uuid | |
from fastapi import FastAPI, HTTPException | |
from pydantic import BaseModel | |
from pymongo import MongoClient | |
import urllib.parse | |
import os | |
from langchain_groq import ChatGroq | |
from langchain_community.embeddings import HuggingFaceBgeEmbeddings | |
from chatbot import Comsatsbot | |
# FastAPI app setup | |
app = FastAPI() | |
model_name = "BAAI/bge-small-en" | |
model_kwargs = {"device": "cpu"} | |
encode_kwargs = {"normalize_embeddings": True} | |
hf = HuggingFaceBgeEmbeddings( | |
model_name=model_name, model_kwargs=model_kwargs, encode_kwargs=encode_kwargs | |
) | |
api_keys = [ | |
'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', | |
'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', | |
'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', | |
'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', | |
] | |
llm = ChatGroq(temperature=0, groq_api_key=api_keys[2], model_name="llama3-70b-8192") | |
# MongoDB setup | |
username = 'laiba' | |
password = 'VRwiQ8padD_gN8t' | |
encoded_username = urllib.parse.quote_plus(username) | |
encoded_password = urllib.parse.quote_plus(password) | |
MONGODB_ATLAS_CLUSTER_URI = f'mongodb+srv://{encoded_username}:{encoded_password}@comsatsbot.04y7a.mongodb.net/' | |
client = MongoClient(MONGODB_ATLAS_CLUSTER_URI) | |
db = client.get_database('chat_db') # Assume this is your database | |
chats_collection = db.get_collection('chats') # Collection to store chats | |
paths = ['FYP Supervisor Feedback.csv', 'urdu_data.csv', 'english_data.csv'] | |
chatbot = Comsatsbot(hf, llm, api_keys, chats_collection, paths) | |
# Endpoint for creating a new chat ID | |
def create_new_chat(): | |
try: | |
chat_id = str(uuid.uuid4()) | |
message = chatbot.new_chat(chat_id) | |
return {"chat_id": chat_id, "message": "Successfully created new chat."} | |
except KeyError: | |
raise HTTPException(status_code=404, detail="Chat ID already exist try again plz...") | |
except Exception as e: | |
raise HTTPException(status_code=500, detail=str(e)) | |
# Request model for response endpoint | |
class ChatRequest(BaseModel): | |
chat_id: str | |
question: str | |
# Endpoint for retrieving chat history by chat ID | |
def get_chat(chat_id: str): | |
try: | |
history = chatbot.load_chat(chat_id) | |
return {"chat_id": chat_id, "history": history} | |
except KeyError: | |
raise HTTPException(status_code=404, detail="Chat ID not found") | |
except Exception as e: | |
raise HTTPException(status_code=500, detail=str(e)) | |
# Endpoint for deleting a chat by chat ID | |
def delete_chat(chat_id: str): | |
try: | |
message = chatbot.delete_chat(chat_id) | |
return {"message": f"Chat with ID {chat_id} has been deleted successfully."} | |
except KeyError: | |
raise HTTPException(status_code=404, detail="Chat ID not found") | |
except Exception as e: | |
raise HTTPException(status_code=500, detail=str(e)) | |
# Endpoint for getting a response based on chat ID and question | |
def response(request: ChatRequest): | |
chat_id = request.chat_id | |
question = request.question | |
try: | |
answer = chatbot.response(question, chat_id) | |
return {"answer": answer} | |
except KeyError: | |
raise HTTPException(status_code=404, detail="Chat ID not found") | |
except Exception as e: | |
raise HTTPException(status_code=500, detail="GPU error, try after some time...") | |