Update app.py

app.py

@@ -37,22 +37,23 @@ def file_reader(file_path: str) -> str:
     except Exception as e:
         return f"Error reading or processing file '{file_path}': {e}"
 
-# --- Agent Class (Completely Rewritten) ---
+# --- Agent Class (Now using a free Open-Source LLM) ---
 class GaiaSmolAgent:
     def __init__(self):
-        print("Initializing GaiaSmolAgent with OpenAI...")
-        api_key = os.getenv("OPENAI_API_KEY")
+        # --- MODIFICATION: Switched to Groq for free, fast inference ---
+        print("Initializing GaiaSmolAgent with a free Open-Source LLM via Groq...")
+        api_key = os.getenv("GROQ_API_KEY")
         if not api_key:
-            raise ValueError("API key 'OPENAI_API_KEY' not found in environment secrets.")
+            raise ValueError("API key 'GROQ_API_KEY' not found in environment secrets.")
 
         self.planner_model = LiteLLMModel(
-            model_id="gpt-4o",
+            # Using Llama 3 8B via Groq's free API
+            model_id="groq/llama3-8b-8192", 
             api_key=api_key,
             temperature=0.0,
         )
 
         # Initialize the agent with the tools it can use.
-        # The agent will make these available to the script it runs.
         self.executor_agent = CodeAgent(
             model=self.planner_model,
             tools=[file_reader, DuckDuckGoSearchTool()],
@@ -64,7 +65,6 @@ class GaiaSmolAgent:
         """Generates a self-contained Python script to answer the question."""
         print(f"Generating script for question: {question[:100]}...")
         
-        # This new prompt asks for a single, complete script.
         prompt = f"""
         You are an expert Python programmer. Your task is to write a single, self-contained Python script to answer the user's question.
 
@@ -89,11 +89,9 @@ class GaiaSmolAgent:
         
         Now, write the Python script to answer the user's question.
         """
-        # The generate method expects a list of message dictionaries, not a raw string.
         messages = [{"role": "user", "content": prompt}]
         response = self.planner_model.generate(messages)
         
-        # Clean up the response from the LLM, which sometimes wraps it in markdown
         if "```python" in response:
             response = response.split("```python")[1].split("```")[0].strip()
         
@@ -105,12 +103,7 @@ class GaiaSmolAgent:
         print(f"Agent received question: {question[:100]}...")
         
         try:
-            # Step 1: Generate a single, complete script
             script_to_execute = self._generate_script(question)
-            
-            # Step 2: Execute the entire script in one go.
-            # The agent will match the function calls in the script (e.g., duck_duck_go_search)
-            # to the tools it was initialized with.
             final_answer = self.executor_agent.run(script_to_execute)
 
         except Exception as e:
@@ -167,7 +160,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e:
-            # This catches errors in the __call__ method itself
             error_message = f"AGENT ERROR: {e}"
             print(f"Error running agent on task {task_id}: {e}")
             print(traceback.format_exc())
@@ -193,13 +185,13 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     except Exception as e:
         return f"Submission Failed: {e}", pd.DataFrame(results_log)
 
-# --- Gradio Interface (Unchanged) ---
+# --- Gradio Interface (Updated Instructions) ---
 with gr.Blocks() as demo:
     gr.Markdown("# GAIA Agent Evaluation Runner (smol-agent)")
     gr.Markdown(
         """
         **Instructions:**
-        1.  Ensure you have added your **OpenAI API key** (as `OPENAI_API_KEY`) in the Space's secrets.
+        1.  Ensure you have added your **Groq API key** (as `GROQ_API_KEY`) in the Space's secrets.
         2.  Log in to your Hugging Face account using the button below.
         3.  Click 'Run Evaluation & Submit All Answers' to run your agent and see the score.
         """
@@ -209,7 +201,6 @@ with gr.Blocks() as demo:
     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]
@@ -217,4 +208,4 @@ with gr.Blocks() as demo:
 
 if __name__ == "__main__":
     print("Launching Gradio Interface for GAIA Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)