Update app.py

app.py

@@ -19,11 +19,11 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # Generation result wrapper to match smolagents expectations
 class GenerationResult:
-    def __init__(self, content, token_usage=None, input_tokens=0, output_tokens=0):
+    def __init__(self, content, input_tokens=0, output_tokens=0, token_usage=None):
         self.content = content
-        self.token_usage = token_usage or {}
         self.input_tokens = input_tokens
         self.output_tokens = output_tokens
+        self.token_usage = token_usage or {}
 
 # Gemini model wrapper
 class GeminiFlashModel:
@@ -32,14 +32,15 @@ class GeminiFlashModel:
         self.model = genai.GenerativeModel(model_id)
         self.system_prompt = SYSTEM_PROMPT
 
-    # Accept stop_sequences explicitly to avoid unexpected kwarg errors
-    def generate(self, messages, stop_sequences=None, **kwargs):
+    def generate(self, messages, **kwargs):
         if not isinstance(messages, list) or not all(isinstance(m, dict) for m in messages):
             raise TypeError("Expected 'messages' to be a list of dicts")
 
+        # Ensure system prompt is first message
         if not any(m.get("role") == "system" for m in messages):
             messages = [{"role": "system", "content": self.system_prompt}] + messages
 
+        # Build prompt text by concatenating messages with roles
         prompt = ""
         for m in messages:
             role = m["role"].capitalize()
@@ -47,20 +48,19 @@ class GeminiFlashModel:
             prompt += f"{role}: {content}\n"
 
         try:
-            # Note: genai.GenerativeModel.generate_content may not support stop_sequences
             response = self.model.generate_content(prompt)
+            # Always wrap the result in GenerationResult
             return GenerationResult(
                 content=response.text.strip(),
-                token_usage={},  # you can extend if API provides token info
-                input_tokens=0,
-                output_tokens=0
+                input_tokens=0,   # Could add token counts here if available
+                output_tokens=0,
             )
         except Exception as e:
+            # Wrap errors too, so agent doesn't fail
             return GenerationResult(
                 content=f"GENERATION ERROR: {e}",
-                token_usage={},
                 input_tokens=0,
-                output_tokens=0
+                output_tokens=0,
             )
 
 # Agent wrapper
@@ -70,15 +70,13 @@ class MyAgent:
         self.agent = CodeAgent(tools=[DuckDuckGoSearchTool()], model=self.model)
 
     def __call__(self, question: str) -> str:
-        # The agent.run expects a string answer
         result = self.agent.run(question)
-        # If result is GenerationResult or dict-like, convert to string
+        # result can be GenerationResult or maybe dict or str - normalize:
         if hasattr(result, "content"):
             return result.content
-        elif isinstance(result, dict):
+        if isinstance(result, dict):
             return result.get("content", str(result))
-        else:
-            return str(result)
+        return str(result)
 
 # Main evaluation function
 def run_and_submit_all(profile: gr.OAuthProfile | None):
@@ -172,4 +170,3 @@ if __name__ == "__main__":
 
 
 
-