debug

app.py

@@ -169,22 +169,29 @@ class BasicAgent:
         
         # System message
         self.sys_msg = SystemMessage('''You are a general AI assistant. I will ask you a question. Follow these steps:
+
         1. First, use the google_search tool to find relevant information about the question.
         2. Analyze the search results to find the specific information needed.
         3. If needed, use additional tools to gather more information.
         4. Only after gathering all necessary information, provide YOUR FINAL ANSWER.
-        
-        YOUR FINAL ANSWER should be:
-        - A number (not written as a word) if asked for a quantity
-        - As few words as possible if asked for a string
-        - A comma separated list of numbers and/or strings if asked for a list
-        
+
+        YOUR FINAL ANSWER must be:
+        - For numbers: Just the digit (e.g., "7" not "seven" or "7 albums")
+        - For strings: As few words as possible
+        - For lists: A comma-separated list of numbers and/or strings
+
         Rules for formatting:
         - For numbers: Don't use commas or units ($, %, etc.) unless specified
         - For strings: Don't use articles or abbreviations
         - For lists: Apply the above rules based on whether each element is a number or string
-        
-        You MUST use tools to verify information before providing your final answer.''')
+
+        IMPORTANT:
+        - You MUST use the google_search tool before providing your final answer
+        - Your final answer should ONLY be the requested information, no explanations
+        - If you need to search again, use the tool again
+        - Do not provide detailed analysis in your final answer
+        - If you encounter rate limits, inform the user that you need to search for information
+        - Never make up information - if you can't find it, say so''')
 
         # Create the graph
         self.workflow = StateGraph(AgentState)
@@ -215,7 +222,38 @@ class BasicAgent:
             for msg in messages:
                 log_message(msg, "  ")
             
-            response = self.llm.invoke([self.sys_msg] + messages)
+            # Add tools to the model invocation
+            try:
+                response = self.llm.invoke(
+                    [self.sys_msg] + messages,
+                    tools=[{"type": "function", "function": {
+                        "name": "google_search",
+                        "description": "Search for information on the web",
+                        "parameters": {
+                            "type": "object",
+                            "properties": {
+                                "query": {
+                                    "type": "string",
+                                    "description": "The search query"
+                                }
+                            },
+                            "required": ["query"]
+                        }
+                    }}]
+                )
+            except Exception as e:
+                error_str = str(e)
+                if "429" in error_str:
+                    if "GenerateRequestsPerDayPerProjectPerModel-FreeTier" in error_str:
+                        logger.warning("Daily quota limit reached, providing fallback response")
+                        # For daily quota limits, provide a fallback response
+                        return {"messages": [AIMessage(content="I've reached my daily limit for processing requests. Please try again tomorrow or contact support for assistance.")], "next": END}
+                    else:
+                        logger.warning("Rate limit hit, waiting before retry...")
+                        time.sleep(60)  # Wait for 60 seconds before retry
+                        raise  # Re-raise to trigger retry
+                else:
+                    raise
             
             logger.info("\n=== Model Output ===")
             log_message(response, "  ")
@@ -223,13 +261,41 @@ class BasicAgent:
             if not response or not response.content:
                 logger.error("Empty response from model")
                 raise ValueError("Empty response from model")
+            
+            # Check if the response contains a tool call
+            if hasattr(response, 'tool_calls') and response.tool_calls:
+                return {"messages": [response], "next": "tools"}
+            else:
+                # If no tool call, check if it's a final answer
+                content = response.content.strip()
+                
+                # Clean up the content to ensure it's in the correct format
+                if content.startswith("**Final Answer**: "):
+                    content = content.replace("**Final Answer**: ", "").strip()
+                
+                # For numbers, ensure they're in the correct format
+                if content.replace(".", "").isdigit():
+                    # Remove any decimal places for whole numbers
+                    if float(content).is_integer():
+                        content = str(int(float(content)))
                 
-            return {"messages": [response], "next": "tools"}
+                # Check if the content is a valid final answer
+                if content.isdigit() or (content.startswith('[') and content.endswith(']')):
+                    return {"messages": [AIMessage(content=content)], "next": END}
+                else:
+                    # If not a final answer, continue the conversation
+                    return {"messages": [response], "next": "agent"}
+                    
         except Exception as e:
             logger.error(f"Error in call_model: {str(e)}")
-            if "429" in str(e):
-                logger.warning("Rate limit hit, waiting before retry...")
-                time.sleep(60)  # Wait for 60 seconds before retry
+            error_str = str(e)
+            if "429" in error_str:
+                if "GenerateRequestsPerDayPerProjectPerModel-FreeTier" in error_str:
+                    logger.warning("Daily quota limit reached, providing fallback response")
+                    return {"messages": [AIMessage(content="I've reached my daily limit for processing requests. Please try again tomorrow or contact support for assistance.")], "next": END}
+                else:
+                    logger.warning("Rate limit hit, waiting before retry...")
+                    time.sleep(60)  # Wait for 60 seconds before retry
             raise
     
     def call_tools(self, state: AgentState) -> AgentState: