Update app.py

app.py

@@ -3,7 +3,7 @@ import streamlit as st
 import fitz  # PyMuPDF
 import openai
 from dotenv import load_dotenv
-import pinecone
+from pinecone import Pinecone, ServerlessSpec
 
 # Load the environment variables from the .env file
 load_dotenv()
@@ -12,7 +12,7 @@ pinecone_api_key = os.getenv('PINECONE_API_KEY')
 pinecone_environment = os.getenv('PINECONE_ENVIRONMENT')
 
 # Initialize Pinecone
-pinecone.init(api_key=pinecone_api_key, environment=pinecone_environment)
+pc = Pinecone(api_key=pinecone_api_key)
 
 # Streamlit app
 st.title("Chat with Your Document")
@@ -34,9 +34,14 @@ if uploaded_file is not None:
 
     # Create a Pinecone vector store
     index_name = "pdf-analysis"
-    if index_name not in pinecone.list_indexes():
-        pinecone.create_index(index_name, dimension=512)
-    vector_store = pinecone.Index(index_name)
+    if index_name not in pc.list_indexes().names():
+        pc.create_index(
+            name=index_name,
+            dimension=512,
+            metric='euclidean',
+            spec=ServerlessSpec(cloud='aws', region=pinecone_environment)
+        )
+    vector_store = pc.Index(index_name)
 
     # Add the PDF text to the vector store
     vector_store.upsert([(str(i), openai.Embedding.create(input=pdf_text)["data"][0]["embedding"]) for i in range(len(pdf_text))])