Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py — updated for GAIA tools (file upload for audio/Excel)
+# app.py — supports text, audio (.mp3) and Excel (.xlsx) inputs
 
 import os
 import requests
@@ -6,105 +6,72 @@ import pandas as pd
 import gradio as gr
 import asyncio
 import tempfile
-from agent import answer_question, transcribe_audio, extract_excel_total_food_sales
+
+from agent import (
+    answer_question,
+    transcribe_audio,
+    extract_excel_total_food_sales
+)
 
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 class GAIALlamaAgent:
-    def __call__(self, question: str, file_path: str = None) -> str:
-        # Shortcut logic: if file exists and question matches specific types
-        if file_path:
-            if "mp3" in file_path:
-                return transcribe_audio(file_path)
-            elif "xlsx" in file_path or "xls" in file_path:
-                return extract_excel_total_food_sales(file_path)
-
+    def __call__(self, question: str, file) -> str:
+        if file:
+            ext = os.path.splitext(file.name)[1].lower()
+            if ext == ".mp3":
+                return transcribe_audio(file.name)
+            if ext in (".xls", ".xlsx"):
+                return extract_excel_total_food_sales(file.name)
         return asyncio.run(answer_question(question))
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
-    space_id = os.getenv("SPACE_ID")
-    username = profile.username if profile else None
-    if not username:
-        return "Please login to Hugging Face.", None
-
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" if space_id else ""
+    if not profile or not profile.username:
+        return "Please log in to Hugging Face.", None
+    username = profile.username
+    space_id = os.getenv("SPACE_ID", "")
+    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
 
     try:
-        response = requests.get(questions_url, timeout=15)
-        response.raise_for_status()
-        questions_data = response.json()
+        questions = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15).json()
     except Exception as e:
-        return f"❌ Error fetching questions: {e}", None
+        return f"Error fetching questions: {e}", None
 
     agent = GAIALlamaAgent()
-    answers_payload = []
-    results_log = []
+    payload, log = [], []
 
-    for item in questions_data:
-        qid = item.get("task_id")
-        question = item.get("question")
-        if not qid or not question:
-            continue
-        try:
-            answer = agent(question)
-        except Exception as e:
-            answer = f"[AGENT ERROR] {e}"
-        answers_payload.append({"task_id": qid, "submitted_answer": answer})
-        results_log.append({"Task ID": qid, "Question": question, "Submitted Answer": answer})
-
-    submission_data = {
-        "username": username,
-        "agent_code": agent_code,
-        "answers": answers_payload
-    }
+    for q in questions:
+        ans = agent(q["question"], None)
+        payload.append({"task_id": q["task_id"], "submitted_answer": ans})
+        log.append({"Task ID": q["task_id"], "Question": q["question"], "Answer": ans})
 
     try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
-        response.raise_for_status()
-        result_data = response.json()
-        status = (
-            f"✅ Submission Successful!\n"
-            f"User: {result_data.get('username')}\n"
-            f"Score: {result_data.get('score')}%\n"
-            f"Correct: {result_data.get('correct_count')}/{result_data.get('total_attempted')}\n"
-            f"Message: {result_data.get('message')}"
-        )
-        return status, pd.DataFrame(results_log)
+        res = requests.post(f"{DEFAULT_API_URL}/submit",
+                            json={"username": username, "agent_code": agent_code, "answers": payload},
+                            timeout=60).json()
+        status = f"✅ Score: {res.get('score')}% ({res.get('correct_count')}/{res.get('total_attempted')})"
     except Exception as e:
-        return f"❌ Submission failed: {e}", pd.DataFrame(results_log)
+        status = f"❌ Submission failed: {e}"
 
-# --- Gradio UI ---
-with gr.Blocks() as demo:
-    gr.Markdown("""
-        # 🧠 GAIA Agent Evaluation
+    return status, pd.DataFrame(log)
 
-        Upload your files if needed and evaluate the agent's answers.
-    """)
+with gr.Blocks() as demo:
+    gr.Markdown("# GAIA Agent")
     gr.LoginButton()
-
     with gr.Row():
-        question_box = gr.Textbox(label="Manual Question (optional)", lines=3)
-        file_input = gr.File(label="Optional File (.mp3 or .xlsx)", file_types=[".mp3", ".xlsx"])
-        submit_btn = gr.Button("Ask Agent")
-
-    output_text = gr.Textbox(label="Answer")
-    submit_btn.click(
-        fn=lambda q, f: GAIALlamaAgent()(q, f.name if f else None),
-        inputs=[question_box, file_input],
-        outputs=output_text
-    )
-
-    gr.Markdown("## Or run full benchmark submission")
-    run_btn = gr.Button("Run Evaluation & Submit All Answers")
-    run_out = gr.Textbox(label="Status", lines=4)
-    run_table = gr.DataFrame(label="Questions and Agent Answers")
-    run_btn.click(fn=run_and_submit_all, outputs=[run_out, run_table])
+        question = gr.Textbox(label="Question")
+        file_in = gr.File(label="Optional file (.mp3, .xlsx)")
+        ask_btn = gr.Button("Ask")
+        output = gr.Textbox(label="Answer")
+    ask_btn.click(lambda q, f: GAIALlamaAgent()(q, f), inputs=[question, file_in], outputs=output)
+    gr.Markdown("## Or run full GAIA evaluation")
+    eval_btn = gr.Button("Run Evaluation & Submit")
+    status = gr.Textbox(label="Status", lines=4)
+    table = gr.DataFrame()
+    eval_btn.click(run_and_submit_all, outputs=[status, table])
 
 if __name__ == "__main__":
-    print("\n🔁 App Starting Up...")
+    print("🔁 App starting")
     if os.getenv("SPACE_ID"):
-        print(f"🔗 Space: https://huggingface.co/spaces/{os.getenv('SPACE_ID')}")
+        print("🔗 Space:", os.getenv("SPACE_ID"))
     demo.launch(debug=True)