Update app.py

app.py

@@ -4,37 +4,52 @@ import requests
 import pandas as pd
 from smolagents import Agent
 
+# Config
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+MODEL_NAME = "google/flan-t5-small"
+SPACE_ID = os.getenv("SPACE_ID", "sirine1712/Final_Assignment_Template")
+HF_TOKEN = os.getenv("HF_TOKEN")
 
-# A simple agent using Hugging Face hosted inference API
+# Define a simple Hugging Face Inference Agent
 class HuggingFaceAPIAgent(Agent):
-    def __init__(self, model="google/flan-t5-small"):
+    def __init__(self, model=MODEL_NAME):
         self.model = model
         self.api_url = f"https://api-inference.huggingface.co/models/{model}"
-        self.headers = {"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"}
+        self.headers = {"Authorization": f"Bearer {HF_TOKEN}"}
 
     def __call__(self, question: str) -> str:
-        print(f"Calling HF inference API for: {question[:60]}")
-        response = requests.post(
-            self.api_url,
-            headers=self.headers,
-            json={"inputs": question},
-            timeout=10
-        )
-        if response.status_code != 200:
-            print(f"API error: {response.status_code} {response.text}")
-            return "API call failed."
-        return response.json()[0]["generated_text"]
+        print(f"⏳ Sending question to HF model: {question[:60]}")
+        try:
+            response = requests.post(
+                self.api_url,
+                headers=self.headers,
+                json={"inputs": question},
+                timeout=10
+            )
+            response.raise_for_status()
+            output = response.json()
+            if isinstance(output, list):
+                return output[0].get("generated_text", "No answer generated.")
+            else:
+                return output.get("generated_text", "No answer generated.")
+        except Exception as e:
+            print(f"⚠️ Error calling model: {e}")
+            return f"Error: {e}"
 
+# Function to run agent and submit to GAIA scoring API
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     if not profile:
-        return "Please log in first.", None
+        return "❌ Please log in first.", None
 
-    username = profile.username
-    agent_code = f"https://huggingface.co/spaces/{os.getenv('SPACE_ID')}/tree/main"
+    username = profile.username or "anonymous"
+    agent_code = f"https://huggingface.co/spaces/{SPACE_ID}/tree/main"
     agent = HuggingFaceAPIAgent()
 
-    questions = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15).json()
+    try:
+        questions = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15).json()
+    except Exception as e:
+        return f"❌ Failed to fetch questions: {e}", None
+
     answers, log = [], []
 
     for q in questions:
@@ -43,28 +58,40 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         except Exception as e:
             answer = f"Error: {e}"
         answers.append({"task_id": q["task_id"], "submitted_answer": answer})
-        log.append({"Task ID": q["task_id"], "Question": q["question"], "Submitted Answer": answer})
+        log.append({
+            "Task ID": q["task_id"],
+            "Question": q["question"],
+            "Submitted Answer": answer
+        })
 
-    result = requests.post(f"{DEFAULT_API_URL}/submit", json={
-        "username": username,
-        "agent_code": agent_code,
-        "answers": answers
-    }).json()
+    try:
+        result = requests.post(
+            f"{DEFAULT_API_URL}/submit",
+            json={
+                "username": username,
+                "agent_code": agent_code,
+                "answers": answers
+            },
+            timeout=10
+        ).json()
+    except Exception as e:
+        return f"❌ Submission failed: {e}", pd.DataFrame(log)
 
     message = (
-        f"✅ Submission complete!\n"
-        f"Score: {result.get('score')}%\n"
-        f"{result.get('correct_count')}/{result.get('total_attempted')} correct\n"
-        f"Message: {result.get('message')}"
+        f"✅ **Submission complete!**\n"
+        f"**Score:** {result.get('score')}%\n"
+        f"**Correct:** {result.get('correct_count')}/{result.get('total_attempted')}\n"
+        f"**Message:** {result.get('message')}"
     )
     return message, pd.DataFrame(log)
 
+# Gradio UI
 with gr.Blocks() as demo:
-    gr.Markdown("# 🤖 SmolAgent with Hugging Face Inference API")
+    gr.Markdown("# 🤖 HuggingFace Inference Agent\nA minimal agent using FLAN-T5 on HuggingFace Inference API.")
     gr.LoginButton()
-    btn = gr.Button("Run Agent & Submit")
-    status = gr.Textbox(label="Status")
-    results = gr.DataFrame(label="Results")
+    btn = gr.Button("🚀 Run Agent & Submit")
+    status = gr.Textbox(label="Status", lines=4)
+    results = gr.DataFrame(label="Agent Output Log")
     btn.click(fn=run_and_submit_all, outputs=[status, results])
 
-demo.launch()
+demo.launch()