Update app.py

app.py

@@ -236,6 +236,12 @@ def generate_with_streaming(messages, model, max_tokens=8192, temperature=0.7, t
     except Exception as e:
         yield f"Connection error: {str(e)}"
 
+def is_news_related_query(query):
+    """Check if query is related to news"""
+    news_keywords = ['news', 'headline', 'breaking', 'latest', 'today', 'current event', 'update', 'report']
+    query_lower = query.lower()
+    return any(word in query_lower for word in news_keywords)
+
 def respond(message, chat_history, model_choice, max_tokens, temperature, top_p, creativity, precision, system_prompt, use_web_search):
     """Main response handler with conversation history"""
     if not message:
@@ -252,7 +258,7 @@ def respond(message, chat_history, model_choice, max_tokens, temperature, top_p,
         chat_history = [system_message] + chat_history
     
     # Check if the message contains search results that need analysis
-    if "SEARCH RESULTS" in message:
+    if "SEARCH RESULTS" in message or "SEARCH RESULTS" in message:
         # This is search results that need analysis
         # Extract the original query and search results
         lines = message.split('\n')
@@ -263,6 +269,8 @@ def respond(message, chat_history, model_choice, max_tokens, temperature, top_p,
                 query = first_line.split("'")[1]
             else:
                 query = message[:100]  # Fallback
+        else:
+            query = "news summary"
         
         # Perform analysis
         analysis_prompt = analyze_search_results(query, message)
@@ -284,8 +292,40 @@ def respond(message, chat_history, model_choice, max_tokens, temperature, top_p,
     # Always perform search if web search is enabled
     if use_web_search:
         search_result = perform_search(message)
-        yield "", chat_history + [user_message, {"role": "assistant", "content": search_result}], search_result
-        return
+        
+        # If this is a news-related query, automatically analyze the results
+        if is_news_related_query(message):
+            # Extract the original query for analysis
+            lines = search_result.split('\n')
+            if len(lines) > 2:
+                first_line = lines[0]
+                if "'" in first_line:
+                    query = first_line.split("'")[1]
+                else:
+                    query = message
+            else:
+                query = message
+            
+            # Perform analysis of the search results
+            analysis_prompt = analyze_search_results(query, search_result)
+            
+            # Create history with analysis prompt
+            analysis_history = chat_history + [user_message, {"role": "assistant", "content": search_result}, {"role": "user", "content": analysis_prompt}]
+            
+            # Generate analyzed response
+            full_response = ""
+            search_results_output = search_result  # Store raw search results
+            
+            for chunk in generate_with_streaming(analysis_history, model_choice, max_tokens, temperature * creativity, top_p * precision):
+                if isinstance(chunk, str):
+                    full_response = chunk
+                    # Stream both the analysis and raw search results
+                    yield "", chat_history + [user_message, {"role": "assistant", "content": search_result}, {"role": "assistant", "content": full_response}], search_results_output
+            return
+        else:
+            # Non-news search, just return the search results
+            yield "", chat_history + [user_message, {"role": "assistant", "content": search_result}], search_result
+            return
     
     # Normal flow - generate response
     current_history = chat_history + [user_message]