Update app.py

app.py

@@ -10,6 +10,7 @@ import re
 import requests
 import pandas as pd
 import gradio as gr
+import yaml
 
 from smolagents import CodeAgent, HfApiModel, tool
 
@@ -41,10 +42,12 @@ def safe_calc(expr: str):
 def calculator(expr: str) -> str:
     """
     Safely evaluate a mathematical expression.
+
     Args:
-        expr (str): mathematical expression like "2 + 2 * 3"
+        expr (str): The math expression to calculate.
+
     Returns:
-        str: JSON string {"expression": expr, "result": value} or {"error": "..."}
+        str: JSON string with {"expression": expr, "result": value} or {"error": "..."} on failure.
     """
     try:
         val = safe_calc(expr)
@@ -52,15 +55,16 @@ def calculator(expr: str) -> str:
     except Exception as e:
         return json.dumps({"error": f"Calc error: {e}"})
 
-
 @tool
 def get_current_time_in_timezone(timezone: str) -> str:
     """
     Get the current local time in a specified timezone.
+
     Args:
-        timezone (str): valid timezone string (e.g., "Europe/Paris")
+        timezone (str): A valid timezone string (e.g., "Europe/Paris").
+
     Returns:
-        str: JSON string {"timezone": timezone, "local_time": "..."} or {"error": "..."}
+        str: JSON string with {"timezone": timezone, "local_time": "..."} or {"error": "..."} on failure.
     """
     try:
         tz = pytz.timezone(timezone)
@@ -69,25 +73,24 @@ def get_current_time_in_timezone(timezone: str) -> str:
     except Exception as e:
         return json.dumps({"error": f"Timezone error: {e}"})
 
-
 # -------------------------
 # Load prompts.yaml if exists
 # -------------------------
 prompt_templates = None
 try:
-    import yaml
     with open("prompts.yaml", "r") as fh:
         prompt_templates = yaml.safe_load(fh)
 except Exception:
     prompt_templates = None
 
-
 # -------------------------
-# HfApiModel + CodeAgent
+# HfApiModel + CodeAgent minimal
 # -------------------------
+hf_token = os.getenv("HF_API_TOKEN")  # token injecté automatiquement dans Spaces
+
 model = HfApiModel(
-    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
-    max_tokens=2048,
+    model_id="HuggingFaceTB/SmolLM-135M-Instruct",
+    max_tokens=1024,
     temperature=0.5,
     api_key=hf_token
 )
@@ -100,7 +103,6 @@ code_agent = CodeAgent(
     prompt_templates=prompt_templates
 )
 
-
 # -------------------------
 # GAIA Agent wrapper
 # -------------------------
@@ -118,22 +120,13 @@ class GaiaAgentMinimal:
     def run(self, question: str) -> str:
         try:
             q = question.strip()
-
-            # Calculator queries
             if self._is_calc(q):
                 m = re.search(r'([0-9\.\s\+\-\*\/\^\%\(\)]+)', q)
                 expr = m.group(1) if m else q
                 return calculator(expr)
-
-            # Time queries
             if self._is_time(q):
-                if "paris" in q.lower() or "france" in q.lower():
-                    tz = "Europe/Paris"
-                else:
-                    tz = "UTC"
+                tz = "Europe/Paris" if "paris" in q.lower() or "france" in q.lower() else "UTC"
                 return get_current_time_in_timezone(tz)
-
-            # fallback LLM via HfApiModel
             resp = self.code_agent.run(q)
             if isinstance(resp, dict):
                 for key in ("final_answer", "answer", "result", "output"):
@@ -144,11 +137,8 @@ class GaiaAgentMinimal:
         except Exception as e:
             return json.dumps({"error": f"Agent internal error: {e}"})
 
-
-# instantiate GAIA agent
 gaia_agent = GaiaAgentMinimal(code_agent)
 
-
 # -------------------------
 # GAIA runner
 # -------------------------
@@ -156,15 +146,11 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
-
     if not profile:
         return "Please Login to Hugging Face with the button.", None
-
-    username = f"{profile.username}"
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
-
+    username = profile.username.strip()
+    questions_url = f"{DEFAULT_API_URL}/questions"
+    submit_url = f"{DEFAULT_API_URL}/submit"
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else "unknown"
 
     # Fetch questions
@@ -177,7 +163,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     except Exception as e:
         return f"Error fetching questions: {e}", None
 
-    # Run agent
     results_log = []
     answers_payload = []
     for item in questions_data:
@@ -195,9 +180,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     if not answers_payload:
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
-
-    # Submit
+    submission_data = {"username": username, "agent_code": agent_code, "answers": answers_payload}
     try:
         response = requests.post(submit_url, json=submission_data, timeout=60)
         response.raise_for_status()
@@ -209,26 +192,20 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
             f"Message: {result_data.get('message', 'No message received.')}"
         )
-        results_df = pd.DataFrame(results_log)
-        return final_status, results_df
+        return final_status, pd.DataFrame(results_log)
     except Exception as e:
-        results_df = pd.DataFrame(results_log)
-        return f"Submission failed: {e}", results_df
-
+        return f"Submission failed: {e}", pd.DataFrame(results_log)
 
 # -------------------------
 # Gradio UI
 # -------------------------
 with gr.Blocks() as demo:
     gr.Markdown("# Minimal GAIA Agent Runner")
-    gr.Markdown(
-        "Log in to Hugging Face, click 'Run Evaluation & Submit All Answers' to fetch questions, run the agent, and submit answers."
-    )
+    gr.Markdown("Log in to Hugging Face, click 'Run Evaluation & Submit All Answers' to fetch questions, run the agent, and submit answers.")
     gr.LoginButton()
     run_button = gr.Button("Run Evaluation & Submit All Answers")
     status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
-
     run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 if __name__ == "__main__":