Update app.py

app.py

@@ -2,59 +2,42 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
-
-# ---- LangChain & Tools (OpenAI‑only) ----
-from langchain.chat_models import ChatOpenAI
-from langchain.agents import initialize_agent, Tool
-from langchain.utilities import WikipediaAPIWrapper
-from langchain.tools.python.tool import PythonREPLTool
+import openai
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# --- GaiaAgent using only OpenAI ---
+# --- Simple OpenAI‑based Agent ---
 class GaiaAgent:
     def __init__(self, model_name: str = "gpt-4"):
-        key = os.getenv("OPENAIAPI")
+        # Load your API key (no underscore)
+        key = os.getenv("OPENAIAPIKEY")
         if not key:
-            raise ValueError("Set OPENAIAPI in your Space secrets!")
-        self.llm = ChatOpenAI(
-            model_name=model_name,
-            temperature=0,
-            openai_api_key=key,
-        )
-
-        # Python REPL tool for calculations & parsing
-        python_tool = PythonREPLTool()
-
-        # DuckDuckGo instant answers for basic web search
-        def web_search(query: str) -> str:
-            resp = requests.get(
-                "https://api.duckduckgo.com/",
-                params={"q": query, "format": "json", "t": "hf_agent"}
-            )
-            data = resp.json()
-            return data.get("AbstractText") or "No instant answer available."
-        search_tool = Tool(
-            name="web_search",
-            func=web_search,
-            description="Query the web for up‑to‑date information."
-        )
-
-        # Build agent: zero‑shot React, capped at 4 steps
-        self.agent = initialize_agent(
-            tools=[wiki_tool, python_tool, search_tool],
-            llm=self.llm,
-            agent="zero-shot-react-description",
-            verbose=False,
-            max_iterations=4,
-        )
+            raise ValueError("Please set OPENAIAPIKEY in your Space secrets!")
+        openai.api_key = key
+        self.model = model_name
 
     def __call__(self, question: str) -> str:
-        return self.agent.run(question)
-
+        """
+        Sends the question to OpenAI and returns the assistant's response.
+        """
+        prompt = [
+            {"role": "system", "content": "You are a helpful assistant answering GAIA Level 1 questions. Be concise and return just the final answer."},
+            {"role": "user",   "content": question}
+        ]
+        resp = openai.ChatCompletion.create(
+            model=self.model,
+            messages=prompt,
+            temperature=0.0,
+            max_tokens=256,
+        )
+        return resp.choices[0].message.content.strip()
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
+    """
+    Fetches GAIA questions, runs GaiaAgent on each, submits answers,
+    and returns a status message + results DataFrame.
+    """
     if not profile:
         return "Please log in to Hugging Face with the button.", None
 
@@ -62,84 +45,76 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID", "unknown-space")
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
 
-    # Instantiate our new agent
+    # Instantiate our OpenAI agent
     try:
         agent = GaiaAgent(model_name=os.getenv("OPENAI_MODEL", "gpt-4"))
     except Exception as e:
         return f"Error initializing GaiaAgent: {e}", None
 
-    # Fetch questions
+    # 1) Fetch questions
     try:
         resp = requests.get(f"{DEFAULT_API_URL}/questions", timeout=15)
         resp.raise_for_status()
-        questions_data = resp.json()
-        if not questions_data:
-            return "Fetched questions list is empty or invalid.", None
+        questions = resp.json()
+        if not questions:
+            return "Server returned no questions.", None
     except Exception as e:
         return f"Error fetching questions: {e}", None
 
-    # Run agent on each question
-    results_log = []
-    answers_payload = []
-    for item in questions_data:
+    # 2) Run agent on each question
+    results = []
+    payload = []
+    for item in questions:
         tid = item.get("task_id")
         q   = item.get("question")
         if not tid or q is None:
             continue
         try:
             ans = agent(q)
-        except Exception as e:
-            ans = f"AGENT_ERROR: {e}"
-        results_log.append({
-            "Task ID": tid,
-            "Question": q,
-            "Submitted Answer": ans
-        })
-        answers_payload.append({
-            "task_id": tid,
-            "submitted_answer": ans
-        })
+        except Exception as ee:
+            ans = f"AGENT_ERROR: {ee}"
+        results.append({"Task ID": tid, "Question": q, "Submitted Answer": ans})
+        payload.append({"task_id": tid, "submitted_answer": ans})
 
-    if not answers_payload:
-        return "Agent produced no answers.", pd.DataFrame(results_log)
+    if not payload:
+        return "Agent produced no answers.", pd.DataFrame(results)
 
-    # Submit
+    # 3) Submit all answers
     submission = {
         "username": username,
         "agent_code": agent_code,
-        "answers": answers_payload
+        "answers": payload
     }
     try:
-        resp = requests.post(f"{DEFAULT_API_URL}/submit", json=submission, timeout=60)
-        resp.raise_for_status()
-        res = resp.json()
+        post = requests.post(f"{DEFAULT_API_URL}/submit", json=submission, timeout=60)
+        post.raise_for_status()
+        res = post.json()
         status = (
             f"✅ Submission Successful!\n"
             f"User: {res.get('username')}\n"
-            f"Score: {res.get('score', 'N/A')}% "
-            f"({res.get('correct_count', '?')}/"
-            f"{res.get('total_attempted', '?')} correct)\n"
+            f"Score: {res.get('score','N/A')}% "
+            f"({res.get('correct_count','?')}/"
+            f"{res.get('total_attempted','?')} correct)\n"
             f"{res.get('message','')}"
         )
     except Exception as e:
         status = f"❌ Submission Failed: {e}"
 
-    return status, pd.DataFrame(results_log)
-
+    return status, pd.DataFrame(results)
 
-# --- Gradio App ---
+# --- Gradio Interface ---
 with gr.Blocks() as demo:
-    gr.Markdown("# GAIA Level 1 Agent Evaluation")
+    gr.Markdown("# GAIA Level 1 Agent (OpenAI‑only)")
     gr.Markdown(
         """
-        1. Make sure `OPENAI_API_KEY` is set in your Space secrets.  
-        2. Log in with the HF button.  
-        3. Click **Run Evaluation & Submit All Answers**.
+        1. Add your OpenAI key (no underscore) as `OPENAIAPIKEY` in Space secrets.  
+        2. (Optional) Override model with `OPENAI_MODEL` (default: `gpt-4`).  
+        3. Log in with the button, then click **Run Evaluation & Submit All Answers**.
         """
     )
     gr.LoginButton()
     run_btn    = gr.Button("Run Evaluation & Submit All Answers")
-    status_out = gr.Textbox(label="Status / Submission Result", lines=5, interactive=False)
+    status_out = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
     results_tbl= gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
     run_btn.click(fn=run_and_submit_all, outputs=[status_out, results_tbl])