barbie-raq-hf / app.py
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init app
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import chainlit as cl
from faissdenseretrieval import initialize_documents, initialize_faiss_document_store, initialize_rag_pipeline
import os
from dotenv import load_dotenv
# Load environment variables (if any)
load_dotenv("../.env")
load_dotenv()
serp = os.getenv("SERP_API_KEY")
openai_key = os.getenv("OPENAI_API_KEY")
# Initialize documents
documents = initialize_documents(serp_key=serp, nl_query="IMDB movie reviews for the Barbie movie (2023)")
# Initialize document store and retriever
document_store, retriever = initialize_faiss_document_store(documents=documents)
# Initialize pipeline
query_pipeline = initialize_rag_pipeline(retriever=retriever, openai_key=openai_key)
@cl.on_message
async def main(message: str):
# Use the pipeline to get a response
output = query_pipeline.run(query=message)
# Create a Chainlit message with the response
response = output['answers'][0].answer
msg = cl.Message(content=response)
# Send the message to the user
await msg.send()