Back to what works

MAKE SURE AND ADD PINECONE RAG CORRECTION SOON

app.py

@@ -61,24 +61,9 @@ def generate_response(question):
     recent_messages = st.session_state.messages[-5:]  # Get last 5 messages
     conversation_context = "\n".join([f"{m['role']}: {m['content']}" for m in recent_messages])
     
-    # Generate embedding for the current question using OpenAI's API (new API usage)
-    query_embedding = openai.Embedding.create(
-        input=question,
-        model="text-embedding-ada-002"
-    )['data'][0]['embedding']
-    
-    # Query Pinecone for the top 3 relevant documents
-    query_response = index.query(vector=query_embedding, top_k=3, include_metadata=True)
-    retrieved_docs = [match['metadata']['text'] for match in query_response['matches'] if match.get('metadata')]
-    docs_context = "\n".join(retrieved_docs)
-    
-    # Combine conversation context, retrieved document context, and the current question with the master prompt
+    # Combine context with current question
     full_prompt = f"""Previous conversation:
 {conversation_context}
-
-Relevant documents:
-{docs_context}
-
 Current question: {question}
 {master_prompt}"""