Update app.py

app.py

@@ -17,7 +17,6 @@ import gradio as gr
 from pinecone import Pinecone, ServerlessSpec 
 import openai
     
-# Load environment variables
 load_dotenv()
 
 # Initialize OpenAI and Pinecone credentials
@@ -51,10 +50,8 @@ embeddings = VoyageAIEmbeddings(
 
 def search_documents(query):
     try:
-        # Initialize the vector store and retriever
         vector_store = PineconeVectorStore(index_name=pinecone_index_name, embedding=embeddings)
         
-        # Use maxMarginalRelevanceSearch to improve diversity in results
         results = vector_store.max_marginal_relevance_search(query, k=7, fetch_k=20)  # Adjust fetch_k for more diverse results
         
         # Filter results to ensure uniqueness based on metadata.id
@@ -105,7 +102,6 @@ def generate_output(context, query):
 def complete_workflow(query):
     try:
         context_data, combined_context = search_documents(query)
-        #natural_language_output = generate_output(combined_context, query)
         
         document_titles = list({os.path.basename(doc["title"]) for doc in context_data})  # Get only file names
 
@@ -131,18 +127,6 @@ def complete_workflow(query):
         return {"results": []}, f"Error in workflow: {str(e)}"
 
 
-def delete_index():
-    try:
-        pinecone_index_name = "rag-proto011"
-        if pinecone_index_name in pc.list_indexes().names():
-            pc.delete_index(name=pinecone_index_name)
-            return "Pinecone Index Deleted"
-        else:
-            return "Pinecone Index Had Already Been Deleted"
-    except Exception as e:
-        return f"Error deleting Pinecone index: {str(e)}"
-
-
 def gradio_app():
     with gr.Blocks(css=".result-output {width: 150%; font-size: 16px; padding: 10px;}") as app:
         gr.Markdown("### Intelligent Document Search Prototype-v0.1.2 ")