- Removed the `analyze_data_file` function from tool definitions to streamline functionality. - Enhanced the `execute_python_code` function description to clarify auto-installation of packages and file handling. - Deleted the `python_executor.py` module to simplify the codebase and improve maintainability. - Introduced a new `token_counter.py` module for efficient token counting for OpenAI API requests, including support for Discord image links and cost estimation.
3.2 KiB
3.2 KiB
Data Analysis Fix - UnboundLocalError
🐛 Problem
UnboundLocalError: cannot access local variable 'file_path' where it is not associated with a value
Occurred at line 557 in message_handler.py during data file analysis.
🔍 Root Cause
Variable file_path was used before it was assigned:
# Line 557: Used here ❌
if file_path and not file_path.startswith('/tmp/bot_code_interpreter'):
# Line 583: Assigned here ❌
file_path = args.get("file_path", "")
The variable was referenced 26 lines before being defined!
✅ Solution
Fix 1: Reorder Variable Assignments
Before:
from src.utils.code_interpreter import execute_code
# ❌ Using file_path before assignment
if file_path and not file_path.startswith('/tmp/bot_code_interpreter'):
# migration code...
# ❌ Assignment comes too late
file_path = args.get("file_path", "")
After:
from src.utils.code_interpreter import execute_code
# ✅ Assign variables first
file_path = args.get("file_path", "")
analysis_type = args.get("analysis_type", "")
custom_analysis = args.get("custom_analysis", "")
# ✅ Now can safely use file_path
if file_path and not file_path.startswith('/tmp/bot_code_interpreter'):
# migration code...
Fix 2: Smart File Type Detection
Added automatic detection of file types for proper loading:
# Detect file type based on extension
file_ext = os.path.splitext(file_path)[1].lower()
if file_ext in ['.xlsx', '.xls']:
load_statement = f"df = pd.read_excel('{file_path}')"
elif file_ext == '.json':
load_statement = f"df = pd.read_json('{file_path}')"
elif file_ext == '.parquet':
load_statement = f"df = pd.read_parquet('{file_path}')"
else: # Default to CSV
load_statement = f"df = pd.read_csv('{file_path}')"
📊 Supported File Types
| Extension | Pandas Reader | Status |
|---|---|---|
.csv |
pd.read_csv() |
✅ Working |
.xlsx, .xls |
pd.read_excel() |
✅ Working |
.json |
pd.read_json() |
✅ Working |
.parquet |
pd.read_parquet() |
✅ Working |
| Other | pd.read_csv() |
✅ Default |
🔄 Execution Flow
User uploads data.xlsx
↓
Bot receives file
↓
Assigns file_path variable ✅
↓
Checks if migration needed
↓
Detects file type (.xlsx)
↓
Generates: df = pd.read_excel(file_path)
↓
Executes via code_interpreter
↓
Returns analysis results
🧪 Testing
Test Case 1: CSV File
1. Upload data.csv
2. Ask for analysis
3. ✅ Loads with pd.read_csv()
4. ✅ Shows statistics
Test Case 2: Excel File
1. Upload report.xlsx
2. Ask for analysis
3. ✅ Detects .xlsx extension
4. ✅ Loads with pd.read_excel()
5. ✅ Shows statistics
Test Case 3: JSON File
1. Upload data.json
2. Ask for analysis
3. ✅ Detects .json extension
4. ✅ Loads with pd.read_json()
5. ✅ Shows statistics
🎯 Result
✅ Fixed UnboundLocalError ✅ All file types supported ✅ Proper file type detection ✅ Clean execution through code_interpreter
Date: October 2, 2025
File: src/module/message_handler.py
Lines: 555-598
Status: ✅ Fixed