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| import os | |
| import sys | |
| import json | |
| import tempfile | |
| from typing import List, Dict, Any, Optional | |
| import traceback | |
| # vimport dotenv | |
| # Load environment variables from .env file | |
| # dotenv.load_dotenv() | |
| # Import our agent | |
| from agent import QAgent | |
| # Simulation of GAIA benchmark questions | |
| SAMPLE_QUESTIONS = [ | |
| { | |
| "task_id": "task_002", | |
| "question": "What is the square root of 144?", | |
| "expected_answer": "12", | |
| "has_file": False, | |
| "file_content": None | |
| } | |
| ] | |
| SAMPLE_QUESTIONS_OUT = [ | |
| { | |
| "task_id": "task_001", | |
| "question": "What is the capital of France?", | |
| "expected_answer": "Paris", | |
| "has_file": False, | |
| "file_content": None | |
| }, | |
| { | |
| "task_id": "task_003", | |
| "question": "If a train travels at 60 miles per hour, how far will it travel in 2.5 hours?", | |
| "expected_answer": "150 miles", | |
| "has_file": False, | |
| "file_content": None | |
| }, | |
| { | |
| "task_id": "task_004", | |
| "question": ".rewsna eht sa 'thgir' drow eht etirw ,tfel fo etisoppo eht si tahW", | |
| "expected_answer": "right", | |
| "has_file": False, | |
| "file_content": None | |
| }, | |
| { | |
| "task_id": "task_005", | |
| "question": "Analyze the data in the attached CSV file and tell me the total sales for the month of January.", | |
| "expected_answer": "$10,250.75", | |
| "has_file": True, | |
| "file_content": """Date,Product,Quantity,Price,Total | |
| 2023-01-05,Widget A,10,25.99,259.90 | |
| 2023-01-12,Widget B,5,45.50,227.50 | |
| 2023-01-15,Widget C,20,50.25,1005.00 | |
| 2023-01-20,Widget A,15,25.99,389.85 | |
| 2023-01-25,Widget B,8,45.50,364.00 | |
| 2023-01-28,Widget D,100,80.04,8004.50""" | |
| }, | |
| { | |
| "task_id": "task_006", | |
| "question": "I'm making a grocery list for my mom, but she's a picky eater. She only eats foods that don't contain the letter 'e'. List 5 common fruits and vegetables she can eat.", | |
| "expected_answer": "Banana, Kiwi, Corn, Fig, Taro", | |
| "has_file": False, | |
| "file_content": None | |
| }, | |
| { | |
| "task_id": "task_007", | |
| "question": "How many studio albums were published by Mercedes Sosa between 1972 and 1985?", | |
| "expected_answer": "12", | |
| "has_file": False, | |
| "file_content": None | |
| }, | |
| { | |
| "task_id": "task_008", | |
| "question": "In the video https://www.youtube.com/watch?v=L1vXC1KMRd0, what color is primarily associated with the main character?", | |
| "expected_answer": "Blue", | |
| "has_file": False, | |
| "file_content": None | |
| } | |
| ] | |
| def init_agent(): | |
| """Initialize the QAgent.""" | |
| print("Initializing QAgent...") | |
| try: | |
| agent = QAgent() | |
| return agent | |
| except Exception as e: | |
| print(f"Error instantiating agent for GAIA simulation: {e}") | |
| return None | |
| def save_test_file(task_id: str, content: str) -> str: | |
| """Save a test file to a temporary location.""" | |
| temp_dir = tempfile.gettempdir() | |
| file_path = os.path.join(temp_dir, f"test_file_{task_id}.csv") | |
| with open(file_path, 'w') as f: | |
| f.write(content) | |
| return file_path | |
| def run_GAIA_questions_simu(): | |
| """ | |
| Used only during development for test that simulate GAIA questions. | |
| """ | |
| # 1. Instantiate Agent | |
| agent = init_agent() | |
| results = [] | |
| correct_count = 0 | |
| total_count = len(SAMPLE_QUESTIONS) | |
| for idx, question_data in enumerate(SAMPLE_QUESTIONS): | |
| task_id = question_data["task_id"] | |
| question = question_data["question"] | |
| expected = question_data["expected_answer"] | |
| print(f"\n{'='*80}") | |
| print(f"Question {idx+1}/{total_count}: {question}") | |
| print(f"Expected: {expected}") | |
| # Process any attached file | |
| # file_path = None | |
| # if question_data["has_file"] and question_data["file_content"]: | |
| # file_path = save_test_file(task_id, question_data["file_content"]) | |
| # print(f"Created test file: {file_path}") | |
| # Get answer from agent | |
| try: | |
| answer = agent.invoke(question) # , file_path) | |
| print(f"Agent answer: {answer}") | |
| # Check if answer matches expected | |
| is_correct = answer.lower() == expected.lower() | |
| if is_correct: | |
| correct_count += 1 | |
| print(f"✅ CORRECT") | |
| else: | |
| print(f"❌ INCORRECT - Expected: {expected}") | |
| results.append({ | |
| "task_id": task_id, | |
| "question": question, | |
| "expected": expected, | |
| "answer": answer, | |
| "is_correct": is_correct | |
| }) | |
| except Exception as e: | |
| error_details = traceback.format_exc() | |
| print(f"Error processing question: {e}\n{error_details}") | |
| results.append({ | |
| "task_id": task_id, | |
| "question": question, | |
| "expected": expected, | |
| "answer": f"ERROR: {str(e)}", | |
| "is_correct": False | |
| }) | |
| # Print summary | |
| accuracy = (correct_count / total_count) * 100 | |
| print(f"\n{'='*80}") | |
| print(f"Test Results: {correct_count}/{total_count} correct ({accuracy:.1f}%)") | |
| return results | |