Update app.py

app.py

@@ -1,3 +1,5 @@
+# app.py
+
 import os
 import time
 import requests
@@ -5,22 +7,21 @@ import pandas as pd
 import gradio as gr
 
 # --- Config from Env ---
-API_URL  = os.getenv("API_URL", "https://agents-course-unit4-scoring.hf.space")
-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")
+API_URL      = os.getenv("API_URL", "https://agents-course-unit4-scoring.hf.space")
+SPACE_ID     = os.getenv("SPACE_ID")                     # e.g. "user/your-space"
+MODEL_ID     = os.getenv("MODEL_ID", "meta-llama/Llama-2-7b-instruct")
+# HF token: either from Secrets or from login profile
+HF_TOKEN_ENV = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 
-if not all([SPACE_ID, HF_TOKEN]):
+if not SPACE_ID:
     raise RuntimeError(
-        "❌ Please set these in your Space Secrets:\n"
-        " • SPACE_ID       (e.g. user/your-space)\n"
-        " • HUGGINGFACEHUB_API_TOKEN"
+        "❌ Please set SPACE_ID in your Space Secrets: e.g. user/your-space"
     )
 
 WELCOME = """
 ## GAIA Benchmark Runner 🎉
 
-Build your agent, score **≥30%** to earn the Certificate of Completion,  
+Build your agent, score **≥30%** to earn your Certificate,  
 and see where you land on the Student Leaderboard!
 """
 
@@ -42,7 +43,7 @@ class GAIAAgent:
         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: "..."}
+        # data is 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)
@@ -52,6 +53,13 @@ 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
+    hf_token = HF_TOKEN_ENV or getattr(profile, "access_token", None)
+    if not hf_token:
+        return (
+            "❌ No Hugging Face token found.\n"
+            "Set HUGGINGFACEHUB_API_TOKEN in Secrets or log in via the button.",
+            pd.DataFrame()
+        )
 
     # 1) Fetch GAIA questions
     q_resp = requests.get(f"{API_URL}/questions", timeout=15)
@@ -61,15 +69,14 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         return "❌ No questions found. Check your API_URL.", pd.DataFrame()
 
     # 2) Init agent
-    agent = GAIAAgent(MODEL_ID, HF_TOKEN)
+    agent = GAIAAgent(MODEL_ID, hf_token)
 
     # 3) Answer each
     results = []
     payload = []
     for item in questions:
         tid  = item.get("task_id")
-        qtxt = item.get("question","")
-        # Some tasks include a file path; you can fetch and append it if you like.
+        qtxt = item.get("question", "")
         try:
             ans = agent.answer(qtxt)
         except Exception as e:
@@ -101,15 +108,15 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 # --- Gradio UI ---
 with gr.Blocks() as demo:
     gr.Markdown(WELCOME)
-    login = gr.LoginButton()
-    run_btn   = gr.Button("▶️ Run GAIA Benchmark")
-    status_md = gr.Markdown()
-    table_df  = gr.Dataframe(headers=["Task ID","Question","Answer"], wrap=True)
+    login    = gr.LoginButton()
+    run_btn  = gr.Button("▶️ Run GAIA Benchmark")
+    status   = 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_md, table_df]
+        outputs=[status, table_df]
     )
 
 if __name__ == "__main__":