Update app.py

app.py

@@ -1,67 +1,55 @@
-api_key = "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"
-
 import os
 import gradio as gr
 import requests
-from huggingface_hub import InferenceClient, login
-from dotenv import load_dotenv
 import pandas as pd
+from crewai import Crew, Process
+from dotenv import load_dotenv
 
 # Load environment variables
 load_dotenv()
 
 # Constants
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-MODEL_NAME = "meta-llama/llama-4-maverick-17b-128e-instruct"
 
-# Initialize the Llama Maverick client
-class MaverickAgent:
+# CrewAI components (would normally be in separate files)
+class ResearchAgent:
     def __init__(self):
-        try:
-            self.client = InferenceClient(
-                model=MODEL_NAME,
-                token=os.getenv("HUGGINGFACE_TOKEN")
-            )
-            print("MaverickAgent initialized successfully")
-        except Exception as e:
-            print(f"Error initializing MaverickAgent: {e}")
-            raise
+        self.role = "Researcher"
+        self.goal = "Research information thoroughly"
+    
+    def research(self, question):
+        # Implement research logic here
+        return f"Researched information about: {question}"
+
+class WritingAgent:
+    def __init__(self):
+        self.role = "Writer"
+        self.goal = "Write clear and accurate answers"
+    
+    def write(self, research_data):
+        # Implement writing logic here
+        return f"Comprehensive answer based on: {research_data}"
+
+# Enhanced Agent Definition
+class CrewAIAgent:
+    def __init__(self):
+        print("Initializing CrewAI agents...")
+        self.researcher = ResearchAgent()
+        self.writer = WritingAgent()
+        print("CrewAI agents initialized.")
 
     def __call__(self, question: str) -> str:
+        print(f"Processing question: {question[:50]}...")
+        
+        # Create and execute crew
         try:
-            print(f"Processing question: {question[:100]}...")
-            
-            # Custom prompt template for the Maverick model
-            prompt = f"""<|begin_of_text|>
-            <|start_header_id|>system<|end_header_id|>
-            You are an AI assistant that provides accurate and concise answers to questions.
-            Be factual and respond with just the answer unless asked to elaborate.
-            <|eot_id|>
-            <|start_header_id|>user<|end_header_id|>
-            {question}
-            <|eot_id|>
-            <|start_header_id|>assistant<|end_header_id|>"""
-            
-            response = self.client.text_generation(
-                prompt,
-                max_new_tokens=256,
-                temperature=0.7,
-                do_sample=True,
-            )
-            
-            # Clean up the response
-            answer = response.split("<|eot_id|>")[0].strip()
-            print(f"Generated answer: {answer[:200]}...")
-            return answer
+            research_data = self.researcher.research(question)
+            final_answer = self.writer.write(research_data)
+            print(f"Generated answer: {final_answer[:100]}...")
+            return final_answer
         except Exception as e:
-            print(f"Error processing question: {e}")
-            return f"Error: {str(e)}"
-
-# Authentication
-try:
-    login(token=os.getenv("HUGGINGFACE_TOKEN"))
-except Exception as e:
-    print(f"Authentication error: {e}")
+            print(f"CrewAI error: {e}")
+            return f"CrewAI Error: {str(e)}"
 
 def run_and_submit_all(profile: gr.OAuthProfile | None):
     if not profile:
@@ -69,7 +57,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
     # Initialize agent
     try:
-        agent = MaverickAgent()
+        agent = CrewAIAgent()  # Using CrewAI instead of BasicAgent
     except Exception as e:
         return f"Agent initialization failed: {e}", None
 
@@ -85,7 +73,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     # Process questions
     results = []
     answers = []
-    for i, item in enumerate(questions_data):
+    for item in questions_data:
         task_id = item.get("task_id")
         question = item.get("question")
         if not task_id or not question:
@@ -120,7 +108,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             f"✅ Submitted {len(answers)} answers\n"
             f"📊 Score: {result.get('score', 'N/A')}%\n"
             f"🔢 Correct: {result.get('correct_count', 0)}/{len(answers)}\n"
-            f"🤖 Model: {MODEL_NAME}",
+            f"🤖 Using CrewAI agents",
             pd.DataFrame(results)
         )
     except Exception as e:
@@ -128,8 +116,11 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
 # Gradio Interface
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🦙 Llama 4 Maverick Agent")
-    gr.Markdown(f"Using `{MODEL_NAME}` for evaluation")
+    gr.Markdown("# 🚀 CrewAI Evaluation Runner")
+    gr.Markdown("""
+    This combines CrewAI agents with the evaluation framework.
+    The agents will research and write answers to evaluation questions.
+    """)
     
     gr.LoginButton()
     
@@ -146,6 +137,4 @@ with gr.Blocks(theme=gr.themes.Soft()) as demo:
     )
 
 if __name__ == "__main__":
-    demo.launch()
-
-
+    demo.launch()