Update app.py

app.py

@@ -1,46 +1,32 @@
 import os
 import gradio as gr
 import requests
-import openai
 import pandas as pd
+from huggingface_hub import InferenceClient
 
 # Constants
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")  # Assuming you're using OpenAI's GPT model for the agent.
 
-# Basic Agent Definition
+# Basic Agent Definition using HF Inference API
 class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
-        openai.api_key = OPENAI_API_KEY  # Set OpenAI API key for GPT
+        self.client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.1")
 
     def __call__(self, question: str) -> str:
         print(f"Agent received question: {question[:50]}...")
-        
-        # Use OpenAI GPT to generate a response for the question
         try:
-            response = openai.Completion.create(
-                engine="text-davinci-003",  # or another GPT engine
-                prompt=question,
-                max_tokens=150,
-                n=1,
-                stop=None,
-                temperature=0.7,
-            )
-            fixed_answer = response.choices[0].text.strip()
-            print(f"Agent returning answer: {fixed_answer}")
-            return fixed_answer
+            prompt = f"[INST] {question.strip()} [/INST]"
+            response = self.client.text_generation(prompt=prompt, max_new_tokens=300, temperature=0.7)
+            answer = response.strip()
+            print(f"Agent returning answer: {answer}")
+            return answer
         except Exception as e:
-            print(f"Error while fetching response from GPT: {e}")
+            print(f"Error while querying HF model: {e}")
             return f"Error: {e}"
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
-    """
-    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}"
@@ -103,7 +89,11 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
     # 4. Prepare Submission 
-    submission_data = {"username": username.strip(), "agent_code": f"https://huggingface.co/spaces/{space_id}/tree/main", "answers": answers_payload}
+    submission_data = {
+        "username": username.strip(),
+        "agent_code": f"https://huggingface.co/spaces/{space_id}/tree/main",
+        "answers": answers_payload
+    }
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
 
@@ -134,7 +124,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
 
-
 # Gradio Interface
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")