Update app.py

app.py

@@ -1,42 +1,37 @@
 import os
-import time
 import streamlit as st
-from getpass import getpass
 from openai import OpenAI
 from llama_index.node_parser import SemanticSplitterNodeParser
 from llama_index.embeddings import OpenAIEmbedding
 from llama_index.ingestion import IngestionPipeline
-
 from pinecone.grpc import PineconeGRPC
-from pinecone import ServerlessSpec
-
 from llama_index.vector_stores import PineconeVectorStore
-
 from llama_index import VectorStoreIndex
 from llama_index.retrievers import VectorIndexRetriever
 from llama_index.query_engine import RetrieverQueryEngine
 
-# Set OpenAI API key from Streamlit secrets
-pinecone_api_key = os.getenv("PINECONE_API_KEY") 
+# Set OpenAI API key from environment variables
 openai_api_key = os.getenv("OPENAI_API_KEY")
+pinecone_api_key = os.getenv("PINECONE_API_KEY")
+index_name = os.getenv("annualreport")
 
 # Initialize OpenAI client
 client = OpenAI(api_key=openai_api_key)
 
-
 # Initialize connection to Pinecone
 pc = PineconeGRPC(api_key=pinecone_api_key)
-index_name = "anualreport"
+
 
 # Initialize your index
+if index_name not in pc.list_indexes():
+    pc.create_index(name=index_name, dimension=1536)
+
 pinecone_index = pc.Index(index_name)
 
 # Initialize VectorStore
 vector_store = PineconeVectorStore(pinecone_index=pinecone_index)
-
 pinecone_index.describe_index_stats()
 
-
 # Initialize vector index and retriever
 vector_index = VectorStoreIndex.from_vector_store(vector_store=vector_store)
 retriever = VectorIndexRetriever(index=vector_index, similarity_top_k=5)