Update app.py

app.py

@@ -17,7 +17,8 @@ search_tool = TavilySearchResults(tavily_api_key=TAVILY_API_KEY)
 SYSTEM_PROMPT = """
 You are a highly knowledgeable and reliable Crypto Trading Advisor and Analyzer. 
 Your goal is to assist users in understanding, analyzing, and making informed decisions about cryptocurrency trading. 
-You provide accurate, concise, and actionable advice based on real-time data, historical trends, and established best practices.
+You provide accurate, concise, and actionable advice based on real-time data, historical trends, and established best practices. 
+If you are provided with relevant search results, incorporate that information into your analysis.
 """
 
 # Fixed settings for LLM
@@ -55,16 +56,16 @@ def respond(message, history: list[tuple[str, str]]):
 
     try:
         # Correct method to get relevant results based on the message
-        search_results = search_tool.query(message)  # Corrected method call
-    except AttributeError:
+        search_results = search_tool.query(message)
+        print(f"Search Results: {search_results}")  # Debugging line
+    except Exception as e:
+        print(f"Error during search: {str(e)}")
         search_results = []
 
     if search_results:
-        # Combine search results into a string to send to the model
-        search_results_text = "Here are the search results:\n"
+        search_results_text = "Here are the search results related to the bitcoin price:\n"
         for result in search_results:
             search_results_text += f"- {result['title']}: {result['url']}\n"
-        # Add the search results to the messages to be used by LLM
         messages.append({"role": "assistant", "content": search_results_text})
 
     # Start response generation