Update app.py

app.py

@@ -532,32 +532,7 @@ Highlight any conflicting information or gaps in the available data."""
                 overall_summary += chunk
         accumulated_response += f"Overall Summary:\n\n{overall_summary}\n\n"
         yield accumulated_response, ""
-    
-    # Generate an overall summary after processing all sources
-    overall_prompt = f"""Based on the summaries you've generated for each source: '{accumulated_response}', provide a concise overall summary that addresses the user's query: '{query}'
-Highlight any conflicting information or gaps in the available data."""
 
-    if model == "@cf/meta/llama-3.1-8b-instruct":
-        # Use Cloudflare API for overall summary
-        overall_response = ""
-        for response in get_response_from_cloudflare(prompt="", context="", query=overall_prompt, num_calls=1, temperature=temperature, search_type="web"):
-            overall_response += response
-        accumulated_response += f"Overall Summary:\n\n{overall_response}\n\n"
-        yield accumulated_response, ""
-    else:
-        # Use Hugging Face API for overall summary
-        overall_summary = ""
-        for message in client.chat_completion(
-            messages=[{"role": "user", "content": overall_prompt}],
-            max_tokens=2000,
-            temperature=temperature,
-            stream=True,
-        ):
-            if message.choices and message.choices[0].delta and message.choices[0].delta.content:
-                chunk = message.choices[0].delta.content
-                overall_summary += chunk
-        accumulated_response += f"Overall Summary:\n\n{overall_summary}\n\n"
-        yield accumulated_response, ""
 
 def get_response_from_pdf(query, model, selected_docs, num_calls=3, temperature=0.2):
     logging.info(f"Entering get_response_from_pdf with query: {query}, model: {model}, selected_docs: {selected_docs}")