Update app.py

app.py

@@ -10,79 +10,14 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
-import os
-import gradio as gr
-import requests
-import pandas as pd
-from langchain.agents import load_tools, initialize_agent
-from langchain.chat_models import ChatOpenAI
-
-# --- System Prompt Definition ---
-SYSTEM_PROMPT = """
-You are a general AI assistant with access to these tools:
-- search(query): web search
-- python(code): Python REPL
-- read_file(path): load local documents
-- vision(image): OCR/vision
-- calculator(expr): arithmetic
-
-When you get a question, think step by step:
-
-Thought: decide what to do next
-Action: call one tool (name + args) or “Answer” if ready
-Observation: result from the tool
-
-…repeat Thought/Action/Observation until you have what you need…
-
-Final Answer: [YOUR FINAL ANSWER]
-
-Constraints on YOUR FINAL ANSWER:
-• If it’s a number, write digits without commas or units (unless asked).
-• If it’s a string, omit articles (“a”, “the”), abbreviations, and write any digits in words.
-• If it’s a list, output a comma-separated list of numbers and/or strings, each following the above rules.
-"""
-
-# --- Constants ---
-DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-
-# --- SmolAgent Definition ---
 class BasicAgent:
-    """
-    A lightweight agent configured with GAIA tools, using GPT-4.1 via OpenAI API.
-    """
     def __init__(self):
-        # Load OpenAI API key from HF secret
-        api_key = os.getenv("OPENAI_API_KEY")
-        if not api_key:
-            raise ValueError("OPENAI_API_KEY environment variable not set")
-        # Initialize LLM with system prompt
-        self.llm = ChatOpenAI(
-            model_name="gpt-4.1",
-            temperature=0,
-            openai_api_key=api_key,
-            system_message=SYSTEM_PROMPT  # apply our GAIA prompt
-        )
-        # Load required GAIA tools
-        self.tools = load_tools(
-            [
-                "serpapi",        # web search
-                "requests",       # HTTP requests
-                "python_repl"     # python execution
-            ],
-            llm=self.llm
-        )
-        # Initialize the agent with zero-shot reasoning
-        self.agent = initialize_agent(
-            self.tools,
-            self.llm,
-            agent="zero-shot-react-description",
-            verbose=True
-        )
-
+        print("BasicAgent initialized.")
     def __call__(self, question: str) -> str:
-        # Delegate question to the agent
-        return self.agent.run(question)
-
+        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
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
@@ -211,11 +146,9 @@ with gr.Blocks() as demo:
     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.
-
         ---
         **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).