Update app.py

app.py

@@ -3,24 +3,29 @@ import time
 import gradio as gr
 import requests
 import pandas as pd
-import tiktoken  # For token length
 
 from smolagents import CodeAgent, OpenAIServerModel
-from smolagents.tools import code_tools  # Includes WebSearchTool and more
+from smolagents.tools.web_search import WebSearchTool
 
 # Constants
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-MAX_TOKENS = 3000  # Limit to avoid GPT-4 token overflow
-
-# Token counting helper
-def token_length(text: str, model: str = "gpt-4") -> int:
-    try:
-        encoding = tiktoken.encoding_for_model(model)
-        return len(encoding.encode(text))
-    except Exception:
-        return len(text) // 4  # fallback estimate
-
-# Main agent class
+MAX_QUESTION_LENGTH = 4000
+
+# Retryable search tool
+class ReliableWebSearchTool(WebSearchTool):
+    def run(self, query: str) -> str:
+        for attempt in range(3):
+            try:
+                return super().run(query)
+            except Exception as e:
+                if "rate" in str(e).lower():
+                    print(f"[WebSearch] Rate limit, retry {attempt+1}/3")
+                    time.sleep(2 * (attempt + 1))
+                else:
+                    raise
+        raise RuntimeError("Web search failed after retries")
+
+# Agent definition
 class SmartGAIAAgent:
     def __init__(self):
         key = os.getenv("OPENAI_API_KEY")
@@ -28,53 +33,42 @@ class SmartGAIAAgent:
             raise ValueError("Missing OPENAI_API_KEY")
         model = OpenAIServerModel(model_id="gpt-4", api_key=key)
         self.agent = CodeAgent(
-            tools=code_tools(),  # Includes WebSearchTool, Code Interpreter, etc.
-            model=model
+            tools=[ReliableWebSearchTool()],
+            model=model,
+            add_base_tools=True
         )
 
     def __call__(self, question: str) -> str:
+        q = question[:MAX_QUESTION_LENGTH]
         try:
-            return self.agent.run(question).strip()
+            return self.agent.run(q).strip()
         except Exception as e:
             print("Agent error:", e)
             return "error"
 
-# Run agent + submit answers to API
+# Submission logic
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     username = profile.username if profile else None
     if not username:
-        return "Please login to Hugging Face", None
+        return "Please Login to Hugging Face", None
 
     try:
         agent = SmartGAIAAgent()
     except Exception as e:
         return f"Error initializing agent: {e}", None
 
-    # Fetch questions
-    try:
-        resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
-        resp.raise_for_status()
-        questions = resp.json()
-    except Exception as e:
-        return f"Failed to fetch questions: {e}", None
+    resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
+    resp.raise_for_status()
+    questions = resp.json()
 
-    skip_kw = ['.mp3', '.wav', '.png', '.jpg', 'youtube', 'video', 'watch', 'listen']
     payload, logs = [], []
-
+    skip_kw = ['.mp3','.wav','.png','.jpg','youtube','video','watch','listen']
     for item in questions:
         tid = item.get("task_id")
         q = item.get("question", "")
-        if not tid or not q:
+        if not tid or not q or len(q) > MAX_QUESTION_LENGTH or any(k in q.lower() for k in skip_kw):
             continue
-        if token_length(q) > MAX_TOKENS or any(k in q.lower() for k in skip_kw):
-            continue
-
-        try:
-            ans = agent(q)
-        except Exception as e:
-            print(f"[Error Task {tid}] {e}")
-            ans = "error"
-
+        ans = agent(q)
         payload.append({"task_id": tid, "submitted_answer": ans})
         logs.append({"Task ID": tid, "Question": q, "Submitted Answer": ans})
 
@@ -86,26 +80,18 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         "agent_code": f"https://huggingface.co/spaces/{os.getenv('SPACE_ID')}/tree/main",
         "answers": payload
     }
-
-    try:
-        resp = requests.post(f"{DEFAULT_API_URL}/submit", json=sub, timeout=60)
-        resp.raise_for_status()
-        result = resp.json()
-        score = result.get("score")
-        correct = result.get("correct_count")
-        attempted = result.get("total_attempted")
-        status = f"Score: {score}% ({correct}/{attempted})"
-    except Exception as e:
-        status = f"Submission failed: {e}"
-
+    resp = requests.post(f"{DEFAULT_API_URL}/submit", json=sub, timeout=60)
+    resp.raise_for_status()
+    result = resp.json()
+    status = f"Score: {result.get('score')}% ({result.get('correct_count')}/{result.get('total_attempted')})"
     return status, pd.DataFrame(logs)
 
-# Gradio UI
+# UI
 with gr.Blocks() as demo:
     gr.Markdown("# GAIA Agent")
     gr.LoginButton()
     run_btn = gr.Button("Run & Submit")
-    status = gr.Textbox(lines=4, label="Result")
+    status = gr.Textbox(lines=5)
     table = gr.DataFrame()
     run_btn.click(run_and_submit_all, outputs=[status, table])