Update app.py

app.py

@@ -3,64 +3,11 @@ import gradio as gr
 import requests
 import inspect
 import pandas as pd
-from PIL import Image
-from io import BytesIO
-import google.generativeai as genai
+from agent import Agent  # Importing custom Agent
 
-# (Keep Constants as is)
-# --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Basic Agent Definition ---
-class BasicAgent:
-    def __init__(self):
-        genai.configure(api_key=os.getenv("GEMINI_API_KEY"))
-        self.model = genai.GenerativeModel("gemini-1.5-pro")
-        self.files_base_url = "https://agents-course-unit4-scoring.hf.space/files"
-        print("Gemini-powered BasicAgent initialized.")
-
-    def __call__(self, question_data: dict) -> str:
-        question_text = question_data.get("question", "")
-        task_id = question_data.get("task_id", "")
-        file_names = question_data.get("file_names", [])
-
-        # Takeshi Kojima-style Research Advisory Prompt (Enhanced)
-        system_prompt = (
-            "You are part of an advanced research laboratory composed of intelligent agents who specialize in integrating complex knowledge to solve unknown challenges.\n"
-            "Within this lab, there are experts who analyze visual information, interpret documents, and reason through past knowledge to deduce accurate conclusions.\n"
-            "This task is highly sophisticated and may require a combination of inference, retrieval, and visual understanding.\n"
-            "Approach it collaboratively, methodically, and with precision.\n\n"
-            "There is no need to rush.\n"
-            "This is an experiment, an investigation, and a pursuit of understanding.\n"
-            "Your research team’s calm and thorough process will guide you to the correct answer.\n\n"
-            "---\n"
-            "However, your final answer must be in English and strictly follow the required format described in the question.\n"
-            "You must return only the answer exactly as requested. Do not rephrase, repeat the question, or provide any explanation.\n"
-            "If the question asks for a list or a name, return that only.\n\n"
-            f"[Problem]\n{question_text}"
-        )
-
-        try:
-            if file_names:
-                file_url = f"{self.files_base_url}/{task_id}/{file_names[0]}"
-                response = requests.get(file_url, timeout=10)
-                response.raise_for_status()
-                image = Image.open(BytesIO(response.content))
-                gemini_response = self.model.generate_content([system_prompt, image])
-            else:
-                gemini_response = self.model.generate_content(system_prompt)
-
-            return gemini_response.text.strip()
-
-        except Exception as e:
-            print(f"Error generating answer: {e}")
-            return f"Error generating answer: {e}"
-
 def run_and_submit_all(profile: gr.OAuthProfile | None):
-    """
-    Fetches all questions, runs the BasicAgent on them, submits all answers,
-    and displays the results.
-    """
     space_id = os.getenv("SPACE_ID")
 
     if profile:
@@ -75,7 +22,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     submit_url = f"{api_url}/submit"
 
     try:
-        agent = BasicAgent()
+        agent = Agent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
@@ -171,19 +118,14 @@ 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("# Advanced 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.
-
-        ---
-        **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 separate action or even to answer the questions in async.
+        1. Clone this space and modify the agent logic in `agent.py`.
+        2. Log in to Hugging Face with the button below.
+        3. Click 'Run Evaluation & Submit All Answers' to begin.
         """
     )
 
@@ -198,23 +140,5 @@ with gr.Blocks() as demo:
     )
 
 if __name__ == "__main__":
-    print("\n" + "-"*30 + " App Starting " + "-"*30)
-    space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID")
-
-    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(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("-"*(60 + len(" App Starting ")) + "\n")
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
+    print("Launching Gradio Interface for Advanced Agent Evaluation...")
     demo.launch(debug=True, share=False)