Update app.py

app.py

@@ -3,25 +3,64 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
+from groq import Groq
 
-# (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-class BasicAgent:
-    def __init__(self):
-        print("BasicAgent initialized.")
+# --- Groq Powered Agent Definition ---
+# This new agent uses the Groq API to generate answers.
+class GroqAgent:
+    def __init__(self, api_key):
+        """
+        Initializes the GroqAgent with the Groq API client.
+        """
+        print("Initializing GroqAgent...")
+        self.client = Groq(api_key=api_key)
+        print("GroqAgent initialized successfully.")
+
     def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+        """
+        This method is called to answer a question using the Groq API.
+        """
+        print(f"GroqAgent received question (first 50 chars): {question[:50]}...")
+
+        # A system prompt is used to guide the model to provide concise, direct answers,
+        # which is ideal for the GAIA benchmark's exact-match scoring.
+        system_prompt = (
+            "You are an expert AI agent. Your goal is to answer the following question as accurately "
+            "and concisely as possible. Provide only the final answer, without any introductory text, "
+            "explanations, or additional formatting."
+        )
+
+        try:
+            chat_completion = self.client.chat.completions.create(
+                messages=[
+                    {
+                        "role": "system",
+                        "content": system_prompt,
+                    },
+                    {
+                        "role": "user",
+                        "content": question,
+                    }
+                ],
+                model="llama3-70b-8192",  # A powerful model available via Groq
+                temperature=0.0, # Set to 0 for deterministic, factual answers
+            )
+
+            answer = chat_completion.choices[0].message.content.strip()
+            print(f"GroqAgent generated answer: {answer}")
+            return answer
+
+        except Exception as e:
+            print(f"An error occurred while calling Groq API: {e}")
+            return f"Error generating answer: {e}"
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+
+def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
-    Fetches all questions, runs the BasicAgent on them, submits all answers,
+    Fetches all questions, runs the GroqAgent on them, submits all answers,
     and displays the results.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
@@ -38,15 +77,20 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
 
-    # 1. Instantiate Agent ( modify this part to create your agent)
+    # 1. Instantiate Agent (Now using GroqAgent)
     try:
-        agent = BasicAgent()
+        # Securely get the API key from Hugging Face Space secrets
+        groq_api_key = os.getenv("GROQ_API_KEY")
+        if not groq_api_key:
+            raise ValueError("GROQ_API_KEY secret not found! Please set it in your Space's settings.")
+        agent = GroqAgent(api_key=groq_api_key)
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
-    # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
+
+    # The link to your codebase (useful for verification, so please keep your space public)
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-    print(agent_code)
+    print(f"Agent code link: {agent_code}")
 
     # 2. Fetch Questions
     print(f"Fetching questions from: {questions_url}")
@@ -91,7 +135,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission 
+    # 4. Prepare Submission
     submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
@@ -142,55 +186,50 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
 
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
-    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.Markdown("# Groq-Powered Agent Evaluation Runner")
     gr.Markdown(
         """
         **Instructions:**
-
-        1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
-        2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
-        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
-
+        1.  Make sure you have set your `GROQ_API_KEY` in the 'Secrets' section of your Space settings.
+        2.  Log in to your Hugging Face account using the button below. This is required for submission.
+        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see your score.
         ---
         **Disclaimers:**
-        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
-        This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
+        Once you click the "submit" button, the process can take some time as the agent answers all the questions.
+        This space provides a basic setup. You are encouraged to modify the `GroqAgent` class to experiment with different models, prompts, or even add tools to improve your score!
         """
     )
 
-    gr.LoginButton()
+    # We need to get the user's profile information for the submission
+    auth_button = gr.LoginButton()
 
     run_button = gr.Button("Run Evaluation & Submit All Answers")
 
     status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
-    # Removed max_rows=10 from DataFrame constructor
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
+    # The `auth_button` provides the profile info to the click function
     run_button.click(
         fn=run_and_submit_all,
+        inputs=[auth_button],
         outputs=[status_output, results_table]
     )
 
 if __name__ == "__main__":
     print("\n" + "-"*30 + " App Starting " + "-"*30)
-    # Check for SPACE_HOST and SPACE_ID at startup for information
-    space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
-
-    if space_host_startup:
-        print(f"✅ SPACE_HOST found: {space_host_startup}")
-        print(f"   Runtime URL should be: https://{space_host_startup}.hf.space")
-    else:
-        print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
-
-    if space_id_startup: # Print repo URLs if SPACE_ID is found
+    space_id_startup = os.getenv("SPACE_ID")
+    if space_id_startup:
         print(f"✅ SPACE_ID found: {space_id_startup}")
         print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
     else:
-        print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
+        print("ℹ️  SPACE_ID environment variable not found (running locally?).")
+    
+    if not os.getenv("GROQ_API_KEY"):
+         print("⚠️  WARNING: GROQ_API_KEY secret is not set. The app will fail if run.")
+    else:
+         print("✅ GROQ_API_KEY secret is set.")
 
-    print("-"*(60 + len(" App Starting ")) + "\n")
 
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
+    print("-"*(60 + len(" App Starting ")) + "\n")
+    print("Launching Gradio Interface for Groq Agent Evaluation...")
     demo.launch(debug=True, share=False)