Update app.py

app.py

@@ -1,32 +1,32 @@
-# app.py
+# app.py — updated for GAIA tools (file upload for audio/Excel)
 
 import os
 import requests
 import pandas as pd
 import gradio as gr
-from agent import answer_question
 import asyncio
+import tempfile
+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 __init__(self):
-        print("✅ LangChain/LlamaIndex Agent initialized.")
+    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) -> str:
-        print(f"📨 Agent received: {question[:50]}...")
-        try:
-            return asyncio.run(answer_question(question))
-        except Exception as e:
-            return f"[ERROR] {str(e)}"
+        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 log in to Hugging Face.", None
+        return "Please login to Hugging Face.", None
 
-    print(f"👤 User: {username}")
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
     submit_url = f"{api_url}/submit"
@@ -36,7 +36,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         response = requests.get(questions_url, timeout=15)
         response.raise_for_status()
         questions_data = response.json()
-        print(f"📥 Fetched {len(questions_data)} questions")
     except Exception as e:
         return f"❌ Error fetching questions: {e}", None
 
@@ -56,9 +55,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         answers_payload.append({"task_id": qid, "submitted_answer": answer})
         results_log.append({"Task ID": qid, "Question": question, "Submitted Answer": answer})
 
-    if not answers_payload:
-        return "No answers to submit.", pd.DataFrame(results_log)
-
     submission_data = {
         "username": username,
         "agent_code": agent_code,
@@ -80,23 +76,32 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     except Exception as e:
         return f"❌ Submission failed: {e}", pd.DataFrame(results_log)
 
-# --- Build Gradio Interface using Blocks ---
+# --- Gradio UI ---
 with gr.Blocks() as demo:
     gr.Markdown("""
         # 🧠 GAIA Agent Evaluation
 
-        This app runs a LlamaIndex + LangChain powered agent through the GAIA benchmark.
-
-        1. Login to Hugging Face below
-        2. Click **Run Evaluation** to test all questions
-        3. Answers will be submitted and scored
-        """)
+        Upload your files if needed and evaluate the agent's answers.
+    """)
     gr.LoginButton()
-    run_button = gr.Button("Run Evaluation & Submit All Answers")
-    status_output = gr.Textbox(label="Status", lines=5, interactive=False)
-    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
-    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
+    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])
 
 if __name__ == "__main__":
     print("\n🔁 App Starting Up...")