File size: 3,271 Bytes
86c2b0f | 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 | import sys
import os
from src.routes.code_routes import fix_code_with_dspy, extract_code_blocks
from scripts.format_response import execute_code_from_markdown
import pandas as pd
import logging
# Configure logging
logging.basicConfig(level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
def read_code_file(file_path):
"""Read the code file content"""
with open(file_path, 'r') as f:
return f.read()
def demo_code_fixing():
"""Demonstrate the code fixing functionality using sample code with errors"""
print("\n===== CODE ERROR FIXING DEMONSTRATION =====\n")
# Sample dataset
sample_data = {
'price': [10000, 12000, 13000, 15000, 18000],
'area': [1000, 1200, 1300, 1500, 1800],
'bedrooms': [2, 3, 3, 4, 4],
'bathrooms': [1, 1, 2, 2, 3],
'stories': [1, 1, 2, 2, 3],
'mainroad': ['yes', 'yes', 'no', 'yes', 'yes'],
'guestroom': ['no', 'no', 'yes', 'no', 'yes'],
'basement': ['no', 'no', 'yes', 'no', 'yes'],
'hotwaterheating': ['no', 'yes', 'no', 'yes', 'yes'],
'airconditioning': ['yes', 'yes', 'no', 'yes', 'yes'],
'parking': [1, 1, 2, 2, 3],
'prefarea': ['yes', 'no', 'yes', 'no', 'yes'],
'furnishingstatus': ['furnished', 'semi-furnished', 'unfurnished', 'furnished', 'semi-furnished']
}
df = pd.DataFrame(sample_data)
# 1. Load the sample code with errors
sample_code_path = "sample_code.py"
original_code = read_code_file(sample_code_path)
# Introduce an error in the statistical analytics agent
# Change numpy import from np to pd (conflict with pandas)
modified_code = original_code.replace("import numpy as np", "import numpy as pd")
print("Original code has been modified to introduce an error (numpy import conflict)")
# 2. Execute the code to get the error
print("\n=== EXECUTING CODE WITH ERROR... ===\n")
output, _ = execute_code_from_markdown(modified_code, df)
print(output)
# 3. Fix the code using our error fixing function
print("\n=== FIXING THE CODE... ===\n")
dataset_context = f"DataFrame with {len(df)} rows and columns: {', '.join(df.columns)}"
fixed_code = fix_code_with_dspy(modified_code, output, dataset_context)
# 4. Execute the fixed code to verify it works
print("\n=== EXECUTING FIXED CODE... ===\n")
fixed_output, _ = execute_code_from_markdown(fixed_code, df)
print(fixed_output)
# 5. Show what changes were made
print("\n=== ANALYZING FIXES MADE ===\n")
original_blocks = extract_code_blocks(modified_code)
fixed_blocks = extract_code_blocks(fixed_code)
for block_name in original_blocks:
if block_name in fixed_blocks:
print(f"Block: {block_name}")
# Very simple diff - just check if they're different
if original_blocks[block_name] != fixed_blocks[block_name]:
print(f" - This block was modified during fixing")
else:
print(f" - No changes to this block")
print("\n===== DEMONSTRATION COMPLETE =====")
if __name__ == "__main__":
demo_code_fixing() |