Update app.py

app.py

@@ -1,78 +1,56 @@
-# app.py
-
 import os
 import time
 import requests
 import pandas as pd
 import gradio as gr
 
-from smolagents import (
-    CodeAgent,
-    DuckDuckGoSearchTool,
-    PythonInterpreterTool,
-    InferenceClientModel
-)
-
-# --- Configuration ---
+# --- Config from Env ---
 API_URL  = os.getenv("API_URL", "https://agents-course-unit4-scoring.hf.space")
-SPACE_ID = os.getenv("SPACE_ID")                     # e.g. "your-username/your-space"
-HF_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")     # Hugging Face token
-# No need for HF_USERNAME—Gradio OAuthProfile provides it
+SPACE_ID = os.getenv("SPACE_ID")
+HF_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
+MODEL_ID = os.getenv("MODEL_ID", "meta-llama/Llama-2-7b-instruct")
 
 if not all([SPACE_ID, HF_TOKEN]):
     raise RuntimeError(
-        "Please set the following environment variables in your Space settings:\n"
-        "  • SPACE_ID\n"
-        "  • HUGGINGFACEHUB_API_TOKEN"
+        "❌ Please set these in your Space Secrets:\n"
+        " • SPACE_ID       (e.g. user/your-space)\n"
+        " • HUGGINGFACEHUB_API_TOKEN"
     )
 
-WELCOME_TEXT = """
-## Welcome to the GAIA Benchmark Runner 🎉
+WELCOME = """
+## GAIA Benchmark Runner 🎉
 
-This challenge is your final hands-on project:
-- Build an agent and evaluate it on a subset of the GAIA benchmark.
-- You need **≥30%** to earn your Certificate of Completion. 🏅
-- Submit your score and see how you stack up on the Student Leaderboard!
+Build your agent, score **≥30%** to earn the Certificate of Completion,  
+and see where you land on the Student Leaderboard!
 """
 
-# --- Agent Definition ---
+# --- Simple HF-Inference Agent ---
 class GAIAAgent:
-    def __init__(self, model_id="meta-llama/Llama-3-70B-Instruct"):
-        # Initialize HF Inference client
-        self.model = InferenceClientModel(
-            model_id=model_id,
-            token=HF_TOKEN,
-            provider="hf-inference",
-            timeout=120,
-            temperature=0.2
-        )
-        # Attach search + code execution tools
-        tools = [
-            DuckDuckGoSearchTool(),
-            PythonInterpreterTool()
-        ]
-        self.agent = CodeAgent(
-            tools=tools,
-            model=self.model,
-            executor_type="local"
-        )
-
-    def answer(self, question: str, task_file: str = None) -> str:
-        prompt = question
-        if task_file:
-            try:
-                with open(task_file, "r") as f:
-                    content = f.read()
-                prompt += f"\n\nAttached file:\n```\n{content}\n```"
-            except:
-                pass
-        return self.agent.run(prompt)
-
-# --- Runner & Submission ---
+    def __init__(self, model_id: str, token: str):
+        self.model_id = model_id
+        self.headers = {"Authorization": f"Bearer {token}"}
+
+    def answer(self, prompt: str) -> str:
+        payload = {
+            "inputs": prompt,
+            "parameters": {
+                "max_new_tokens": 512,
+                "temperature": 0.2
+            }
+        }
+        url = f"https://api-inference.huggingface.co/models/{self.model_id}"
+        resp = requests.post(url, headers=self.headers, json=payload, timeout=60)
+        resp.raise_for_status()
+        data = resp.json()
+        # data is a list of {generated_text: "..."}
+        if isinstance(data, list) and data and "generated_text" in data[0]:
+            return data[0]["generated_text"].strip()
+        return str(data)
+
+# --- Gradio callback ---
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     if profile is None:
         return "⚠️ Please log in with your Hugging Face account.", pd.DataFrame()
-
     username = profile.username
 
     # 1) Fetch GAIA questions
@@ -80,36 +58,27 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     q_resp.raise_for_status()
     questions = q_resp.json() or []
     if not questions:
-        return "❌ No questions returned; check your API_URL.", pd.DataFrame()
+        return "❌ No questions found. Check your API_URL.", pd.DataFrame()
 
-    # 2) Initialize your agent
-    agent = GAIAAgent()
+    # 2) Init agent
+    agent = GAIAAgent(MODEL_ID, HF_TOKEN)
 
-    # 3) Run agent on each question
-    results, payload = [], []
+    # 3) Answer each
+    results = []
+    payload = []
     for item in questions:
-        task_id   = item.get("task_id")
-        question  = item.get("question", "")
-        file_path = item.get("task_file_path")  # optional
-
+        tid  = item.get("task_id")
+        qtxt = item.get("question","")
+        # Some tasks include a file path; you can fetch and append it if you like.
         try:
-            answer = agent.answer(question, file_path)
+            ans = agent.answer(qtxt)
         except Exception as e:
-            answer = f"ERROR: {e}"
-
-        results.append({
-            "Task ID": task_id,
-            "Question": question,
-            "Answer": answer
-        })
-        payload.append({
-            "task_id": task_id,
-            "submitted_answer": answer
-        })
-
-        time.sleep(0.5)  # throttle requests
+            ans = f"ERROR: {e}"
+        results.append({"Task ID": tid, "Question": qtxt, "Answer": ans})
+        payload.append({"task_id": tid, "submitted_answer": ans})
+        time.sleep(0.5)
 
-    # 4) Submit all answers
+    # 4) Submit
     submission = {
         "username":   username,
         "agent_code": f"https://huggingface.co/spaces/{SPACE_ID}/tree/main",
@@ -119,7 +88,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     s_resp.raise_for_status()
     data = s_resp.json()
 
-    # 5) Build status message
+    # 5) Build status text
     status = (
         f"✅ **Submission Successful!**\n\n"
         f"**User:** {data.get('username')}\n"
@@ -127,22 +96,20 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         f"({data.get('correct_count')}/{data.get('total_attempted')} correct)\n"
         f"**Message:** {data.get('message')}"
     )
-
     return status, pd.DataFrame(results)
 
-
-# --- Gradio Interface ---
+# --- Gradio UI ---
 with gr.Blocks() as demo:
-    gr.Markdown(WELCOME_TEXT)
+    gr.Markdown(WELCOME)
     login = gr.LoginButton()
-    run_btn = gr.Button("▶️ Run Benchmark & Submit")
-    status_out = gr.Markdown()
-    table_out  = gr.Dataframe(headers=["Task ID","Question","Answer"], wrap=True)
+    run_btn   = gr.Button("▶️ Run GAIA Benchmark")
+    status_md = gr.Markdown()
+    table_df  = gr.Dataframe(headers=["Task ID","Question","Answer"], wrap=True)
 
     run_btn.click(
         fn=run_and_submit_all,
         inputs=[login],
-        outputs=[status_out, table_out]
+        outputs=[status_md, table_df]
     )
 
 if __name__ == "__main__":