Update app.py

app.py

@@ -1,38 +1,73 @@
 import os
 import gradio as gr
 import requests
-import inspect
 import pandas as pd
+from openai import OpenAI
+from ddgs import DDGS
 
-# (Keep Constants as is)
-# --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
+        print("OpenAI Agent initialized.")
+        self.client = OpenAI(api_key="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")
+
+    def web_search(self, query, max_results=5):
+        try:
+            with DDGS() as ddgs:
+                results = list(ddgs.text(query, max_results=max_results))
+            return "\n".join([
+                f"{r.get('title')}: {r.get('body')}"
+                for r in results
+            ])
+        except Exception as e:
+            print("SEARCH ERROR:", e)
+            return ""
+
+    def clean(self, ans):
+        ans = str(ans).strip()
+        for x in ["FINAL ANSWER:", "Final Answer:", "Answer:"]:
+            ans = ans.replace(x, "")
+        return ans.split("\n")[0].strip()
+
     def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+        context = self.web_search(question)
+
+        prompt = f"""
+Return ONLY the exact final answer.
+No explanation.
+No extra words.
+Do not write FINAL ANSWER.
+Question:
+{question}
+Search context:
+{context}
+"""
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+        try:
+            response = self.client.chat.completions.create(
+                model="gpt-4o-mini",
+                messages=[
+                    {"role": "system", "content": "Return exact final answers only."},
+                    {"role": "user", "content": prompt}
+                ],
+                temperature=0
+            )
+            return self.clean(response.choices[0].message.content)
+        except Exception as e:
+            print("AGENT ERROR:", e)
+            return "unknown"
+            
+def run_and_submit_all(profile):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
+    space_id = os.getenv("SPACE_ID")
 
-    if profile:
-        username= f"{profile.username}"
-        print(f"User logged in: {username}")
-    else:
-        print("User not logged in.")
-        return "Please Login to Hugging Face with the button.", None
+    username = os.getenv("SPACE_AUTHOR_NAME", "ahmer64")
+    print(f"Using username: {username}")
 
     api_url = DEFAULT_API_URL
     questions_url = f"{api_url}/questions"
@@ -51,23 +86,35 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     # 2. Fetch Questions
     print(f"Fetching questions from: {questions_url}")
     try:
-        response = requests.get(questions_url, timeout=15)
+        import time
+
+        for attempt in range(3):
+            response = requests.get(questions_url, timeout=15)
+            if response.status_code != 429:
+                break
+            print("Rate limited. Waiting 30 seconds...")
+            time.sleep(30)
+
         response.raise_for_status()
         questions_data = response.json()
+
         if not questions_data:
-             print("Fetched questions list is empty.")
-             return "Fetched questions list is empty or invalid format.", None
+            print("Fetched questions list is empty.")
+            return "Fetched questions list is empty or invalid format.", None
+
         print(f"Fetched {len(questions_data)} questions.")
+
     except requests.exceptions.RequestException as e:
         print(f"Error fetching questions: {e}")
         return f"Error fetching questions: {e}", None
+
     except requests.exceptions.JSONDecodeError as e:
-         print(f"Error decoding JSON response from questions endpoint: {e}")
-         print(f"Response text: {response.text[:500]}")
-         return f"Error decoding server response for questions: {e}", None
+        print(f"Error decoding JSON response: {e}")
+        return f"Error decoding server response: {e}", None
+
     except Exception as e:
-        print(f"An unexpected error occurred fetching questions: {e}")
-        return f"An unexpected error occurred fetching questions: {e}", None
+        print(f"Unexpected error: {e}")
+        return f"Unexpected error: {e}", None
 
     # 3. Run your Agent
     results_log = []
@@ -146,11 +193,9 @@ with gr.Blocks() as demo:
     gr.Markdown(
         """
         **Instructions:**
-
         1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
         2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
         3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.
-
         ---
         **Disclaimers:**
         Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).