File size: 5,212 Bytes
2b967a2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166

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_001",
        "question": "What is the capital of France?",
        "expected_answer": "Paris",
        "has_file": False,
        "file_content": None
    }
]

SAMPLE_QUESTIONS_OUT = [
    {
        "task_id": "task_002",
        "question": "What is the square root of 144?",
        "expected_answer": "12",
        "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 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
    try:
        agent = QAgent()
    except Exception as e:
        print(f"Error instantiating agent for GAIA simulation: {e}")
        return f"Error initializing agent for GAIA simulation: {e}", None

    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