Update app.py

app.py

@@ -1,51 +1,8 @@
-import streamlit as st
-import pinecone
-import os  # To access environment variables
-from sentence_transformers import SentenceTransformer
-import numpy as np
-from datasets import load_dataset
+from pinecone import Pinecone, ServerlessSpec
 
-# Step 1: Get the Pinecone API key from the environment variable (Hugging Face secret)
-pinecone_api_key = st.secrets["PINECONE_API_KEY"]  # Fetch Pinecone API key from Hugging Face secrets
+# Initialize Pinecone
+pc = Pinecone(api_key=pinecone_api_key)
 
-if not pinecone_api_key:
-    st.error("Pinecone API key not found! Make sure to set the secret in Hugging Face settings.")
-    st.stop()
-
-# Initialize Pinecone client using the API key
-pinecone.init(api_key=pinecone_api_key, environment="us-esst-1")  # Change the environment if needed
-
-# Connect to your Pinecone index
-index_name = "legal-docs-index-dji2ip8"  # Your Pinecone index name
-index = pinecone.Index(index_name)
-
-# Step 2: Load the sentence-transformers model for embeddings
-model = SentenceTransformer("all-MiniLM-L6-v2")
-
-# Step 3: Load dataset (for reference in your app)
-dataset = load_dataset("macadeliccc/US-LegalKit", split="train")
-law_texts = [item['text'] for item in dataset if 'text' in item]
-
-# Step 4: Function to search Pinecone index
-def search_pinecone(query, top_k=5):
-    # Create an embedding for the user's query
-    query_embedding = model.encode([query])
-    
-    # Query the Pinecone index for similar documents
-    results = index.query(query_embedding, top_k=top_k, include_metadata=True)
-    
-    # Extract the text of the top-k results
-    return [match['metadata']['text'] for match in results['matches']]
-
-# Step 5: Streamlit UI
-st.title("🔍 Legal AI Assistant (US-LegalKit)")
-
-query = st.text_input("📌 Enter your legal query:")
-
-if query:
-    # Get the top results from Pinecone
-    results = search_pinecone(query)
-    
-    st.write("### 📄 Relevant Legal Documents:")
-    for i, doc in enumerate(results, 1):
-        st.write(f"**{i}.** {doc[:500]}...")  # Show preview of the document
+# Connect to your existing index
+index_name = "legal-docs-index-dji2ip8"
+index = pc.Index(index_name)