Update app.py

app.py

@@ -4,10 +4,8 @@ import os
 import gradio as gr
 import requests
 import pandas as pd
-
-import google.generativeai as genai
+from openai import OpenAI
 from smolagents import CodeAgent, DuckDuckGoSearchTool
-from smolagents.model.base import ModelOutput  # import ModelOutput if available
 
 # System prompt used by the agent
 SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question.
@@ -18,64 +16,36 @@ If you're asked for a string, don’t use articles or abbreviations (e.g. for ci
 
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-# Gemini model wrapper
 class GeminiFlashModel:
-    def __init__(self, model_id="gemini-1.5-flash", api_key=None):
-        genai.configure(api_key=api_key or os.getenv("GEMINI_API_KEY"))
-        self.model = genai.GenerativeModel(model_id)
+    def __init__(self, model_id="gemini-1.5-flash"):
+        self.client = OpenAI(
+            api_key=os.getenv("GEMINI_API_KEY"),
+            base_url="https://generativelanguage.googleapis.com/v1beta/openai/"
+        )
+        self.model_id = model_id
         self.system_prompt = SYSTEM_PROMPT
 
-    def generate(self, messages, stop_sequences=None, **kwargs):
-        if not isinstance(messages, list) or not all(isinstance(m, dict) for m in messages):
-            raise TypeError("Expected 'messages' to be a list of dicts")
-
+    def generate(self, messages):
+        # Ensure system prompt is present
         if not any(m.get("role") == "system" for m in messages):
             messages = [{"role": "system", "content": self.system_prompt}] + messages
 
-        prompt = ""
-        for m in messages:
-            role = m["role"].capitalize()
-            content = m["content"]
-            prompt += f"{role}: {content}\n"
+        response = self.client.chat.completions.create(
+            model=self.model_id,
+            messages=messages
+        )
+        # Return the generated content string directly
+        return response.choices[0].message.content
 
-        try:
-            response = self.model.generate_content(prompt)
-            return ModelOutput(
-                content=response.text.strip(),
-                input_tokens=0,
-                output_tokens=0,
-                token_usage={}
-            )
-        except Exception as e:
-            return ModelOutput(
-                content=f"GENERATION ERROR: {e}",
-                input_tokens=0,
-                output_tokens=0,
-                token_usage={}
-            )
-
-# Agent wrapper
 class MyAgent:
     def __init__(self):
-        self.model = GeminiFlashModel(model_id="gemini-1.5-flash")
+        self.model = GeminiFlashModel()
         self.agent = CodeAgent(tools=[DuckDuckGoSearchTool()], model=self.model)
 
     def __call__(self, question: str) -> str:
-        result = self.agent.run(question)
-        print(f"[DEBUG] Agent run result type: {type(result)}; value: {result}")
-
-        # Return string content only
-        if hasattr(result, "content"):
-            return result.content
-        elif isinstance(result, dict):
-            return result.get("content", str(result))
-        else:
-            return str(result)
-
-# Main evaluation function
-def run_and_submit_all(profile: gr.OAuthProfile | None):
-    print("Starting run_and_submit_all...")
+        return self.agent.run(question)
 
+def run_and_submit_all(profile: gr.OAuthProfile | None):
     space_id = os.getenv("SPACE_ID")
 
     if profile:
@@ -108,20 +78,15 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         question_text = item.get("question")
         if not task_id or question_text is None:
             continue
-
-        print(f"Running agent on question: {question_text}")
         try:
             submitted_answer = agent(question_text)
-            print(f"Agent answer: {submitted_answer} (type: {type(submitted_answer)})")
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
         except Exception as e:
-            error_msg = f"AGENT ERROR: {e}"
-            print(error_msg)
             results_log.append({
                 "Task ID": task_id,
                 "Question": question_text,
-                "Submitted Answer": error_msg
+                "Submitted Answer": f"AGENT ERROR: {e}"
             })
 
     if not answers_payload:
@@ -148,7 +113,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     except Exception as e:
         return f"Submission failed: {e}", pd.DataFrame(results_log)
 
-# Gradio UI setup
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
     gr.Markdown("""
@@ -173,5 +137,3 @@ if __name__ == "__main__":
 
 
 
-
-