Update app.py

app.py

@@ -5,45 +5,56 @@ import gradio as gr
 import requests
 import pandas as pd
 
+import google.generativeai as genai
 from smolagents import CodeAgent, DuckDuckGoSearchTool
-from smolagents.models import LocalModel
+from smolagents.models.base import BaseModel
 
 # Define the system prompt
 SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question.
-Report your thoughts, and finish your answer concisely.
-Your answer should be a number OR as few words as possible OR a comma separated list 
-of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such 
-as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations 
-(e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, 
-apply the above rules depending of whether the element to be put in the list is a number or a string."""
-
+Report your thoughts, and finish your answer with just the answer — no prefixes like "FINAL ANSWER:".
+Your answer should be a number OR as few words as possible OR a comma-separated list of numbers and/or strings.
+If you're asked for a number, don’t use commas or units like $ or %, unless specified.
+If you're asked for a string, don’t use articles or abbreviations (e.g. for cities), and write digits in plain text unless told otherwise."""
 
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # Gemini model wrapper
-class GeminiFlashModel(LocalModel):
-    def __init__(self, model_id="gemini-2.0-flash", api_url=None):
-        super().__init__(model_id=model_id, api_url=api_url)
-        self.system_prompt = SYSTEM_PROMPT
+class GeminiFlashModel(BaseModel):
+    def __init__(self, model_name="gemini-1.5-flash", api_key=None):
+        self.model_name = model_name
+        self.api_key = api_key or os.getenv("GOOGLE_API_KEY")
+        if not self.api_key:
+            raise ValueError("GOOGLE_API_KEY is not set in environment variables.")
+        genai.configure(api_key=self.api_key)
+        self.model = genai.GenerativeModel(model_name)
 
     def generate(self, messages, stop_sequences=None, **kwargs):
+        # Insert system prompt if missing
         if isinstance(messages, list):
             if not any(m["role"] == "system" for m in messages):
-                messages = [{"role": "system", "content": self.system_prompt}] + messages
+                messages = [{"role": "system", "content": SYSTEM_PROMPT}] + messages
         else:
             raise TypeError("Expected 'messages' to be a list of message dicts")
 
-        return super().generate(messages=messages, stop_sequences=stop_sequences, **kwargs)
+        # Convert messages to a single string (Gemini expects plain prompt)
+        prompt = "\n".join([f"{m['role'].capitalize()}: {m['content']}" for m in messages])
+
+        try:
+            response = self.model.generate_content(prompt)
+            return response.text.strip()
+        except Exception as e:
+            return f"GENERATION ERROR: {e}"
 
-# Agent definition
+# Agent using Gemini-1.5-flash
 class MyAgent:
     def __init__(self):
-        self.model = GeminiFlashModel(model_id="gemini-2.0-flash")
+        self.model = GeminiFlashModel(model_name="gemini-1.5-flash")
         self.agent = CodeAgent(tools=[DuckDuckGoSearchTool()], model=self.model)
 
     def __call__(self, question: str) -> str:
         return self.agent.run(question)
 
+# Evaluation & submission flow
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
 
@@ -52,7 +63,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
-        return "Please Login to Hugging Face with the button.", None
+        return "Please login to Hugging Face with the button.", None
 
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
@@ -61,12 +72,9 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     try:
         agent = MyAgent()
     except Exception as e:
-        print(f"Error initializing agent: {e}")
         return f"Error initializing agent: {e}", None
 
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    print(f"Agent code URL: {agent_code}")
-
     print(f"Fetching questions from: {questions_url}")
     try:
         response = requests.get(questions_url, timeout=15)
@@ -80,7 +88,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
     results_log = []
     answers_payload = []
-    print(f"Running agent on {len(questions_data)} questions...")
     for item in questions_data:
         task_id = item.get("task_id")
         question_text = item.get("question")
@@ -97,8 +104,12 @@ 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}
-    print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
+    submission_data = {
+        "username": username.strip(),
+        "agent_code": agent_code,
+        "answers": answers_payload
+    }
+
     try:
         response = requests.post(submit_url, json=submission_data, timeout=60)
         response.raise_for_status()
@@ -123,15 +134,14 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     except Exception as e:
         return f"An unexpected error occurred during submission: {e}", pd.DataFrame(results_log)
 
-# Gradio UI setup
+# Gradio UI
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
     gr.Markdown("""
-        **Instructions:**
-        1. Clone this space, modify code to define your agent's logic, tools, and packages.
-        2. Log in to your Hugging Face account using the button below.
-        3. Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see your score.
-        **Note:** Submitting can take some time.
+    **Instructions:**
+    1. Clone this space and modify it to define your agent's logic.
+    2. Log in with Hugging Face.
+    3. Click 'Run Evaluation & Submit All Answers' to run and submit.
     """)
 
     gr.LoginButton()
@@ -143,26 +153,22 @@ with gr.Blocks() as demo:
     run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 if __name__ == "__main__":
-    print("\n" + "-"*30 + " App Starting " + "-"*30)
+    print("\n" + "="*10 + " App Startup " + "="*10)
     space_host = os.getenv("SPACE_HOST")
     space_id = os.getenv("SPACE_ID")
 
     if space_host:
-        print(f"✅ SPACE_HOST found: {space_host}")
-        print(f"   Runtime URL should be: https://{space_host}.hf.space")
+        print(f"✅ SPACE_HOST: {space_host} -> https://{space_host}.hf.space")
     else:
-        print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
+        print("ℹ️  SPACE_HOST not set.")
 
     if space_id:
-        print(f"✅ SPACE_ID found: {space_id}")
-        print(f"   Repo URL: https://huggingface.co/spaces/{space_id}")
-        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id}/tree/main")
+        print(f"✅ SPACE_ID: {space_id}")
     else:
-        print("ℹ️  SPACE_ID environment variable not found (running locally?).")
+        print("ℹ️  SPACE_ID not set.")
 
-    print("-"*(60 + len(" App Starting ")) + "\n")
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
     demo.launch(debug=True, share=False)
 
 
 
+