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Stable 2.0.4 Stable

cauvang32 released this 2025-10-03 13:05:07 +07:00 | 18 commits to main since this release
Release Notes - Version 2.0.0

🎉 Major Release: Unified Code Interpreter & Enhanced File Management

Release Date: October 3, 2025
Bot Version: 2.0.0
Python Version: 3.13.3
Discord.py Version: 2.4.0

🚀 Major Features

1. Unified Code Interpreter System

We've completely refactored the code execution system into a single, powerful code interpreter that handles all computational tasks.

What's New:
- ✅ Single Execution Engine - All Python code, data analysis, and file processing now runs through one unified system
- ✅ 200+ File Type Support - Handles CSV, Excel, JSON, Parquet, HDF5, Images, Audio, Video, Scientific formats, and more
- ✅ Smart File Loading - Automatic detection and appropriate loading of different file formats
- ✅ Sandboxed Execution - Secure isolated environment with configurable timeout
- ✅ Auto Package Installation - Packages automatically install when imported (pandas, numpy, matplotlib, sklearn, etc.)
- ✅ Output Capture - Generated files (plots, CSVs, reports) automatically captured and sent to users
What Was Removed:
- ❌ Legacy code_runner plugin - Replaced by unified code interpreter
- ❌ Legacy data_analyzer plugin - Now handled by code interpreter
- ❌ Separate analyze_data_file tool - AI generates analysis code naturally
Benefits:
- Simpler Architecture - One system instead of multiple fragmented plugins
- Better Reliability - Single, well-tested execution path
- More Flexible - AI can write custom analysis code instead of using predefined templates
- Easier Maintenance - All execution logic in one place
2. Advanced File Management System

A complete file management system similar to ChatGPT, with persistent storage and automatic lifecycle management.

File Storage:
- 📁 MongoDB Integration - File metadata stored in database with file_id reference
- 💾 Local File Storage - Physical files stored at /tmp/bot_code_interpreter/user_files/{user_id}/
- 🔒 User Isolation - Each user's files completely isolated from others
- 📊 Smart Metadata - Tracks filename, file_type, file_size, upload date, expiration date
File Limits & Expiration:
```
# Configure in .env
MAX_FILES_PER_USER=20          # Default: 20 files per user
FILE_EXPIRATION_HOURS=48       # Default: 48 hours (2 days)
# Set to -1 for permanent storage (no expiration)
```
- Per-User Limits - Configurable max files per user (default: 20)
- Auto-Cleanup on Limit - When limit reached, oldest file automatically deleted
- Time-Based Expiration - Files automatically deleted after configured period
- Permanent Storage Option - Set expiration to -1 to keep files indefinitely
- Manual Management - Users can view and delete files via /files command
File Access:
- 🔑 File ID System - Each file gets unique ID (e.g., 878573881449906208_1759419097_cfa9c26f)
- 🤖 AI Access - Files accessible to AI via conversation context
- 💻 Code Access - Files accessible in Python code via load_file('file_id')
- 📋 Universal Tool Support - All tools can access uploaded files
Supported File Types (200+):
- Tabular Data: CSV, TSV, Excel (xlsx/xls/xlsm), ODS, Parquet, Feather
- Structured Data: JSON, JSONL, XML, YAML, TOML
- Databases: SQLite, SQL dumps, HDF5
- Scientific: NumPy (.npy/.npz), MATLAB (.mat), Stata (.dta), SAS, SPSS
- Images: PNG, JPEG, TIFF, WebP, GIF, BMP, SVG, RAW formats, PSD
- Audio: MP3, WAV, FLAC, OGG, M4A, AAC
- Video: MP4, AVI, MKV, MOV, WebM, FLV
- Documents: PDF, DOCX, TXT, Markdown
- Code: Python, R, JavaScript, Java, C++, and 50+ languages
- Archives: ZIP, TAR, 7Z, RAR, GZ
- Geospatial: GeoJSON, Shapefile, KML, GPX
- Medical: DICOM, NIfTI
- 3D: STL, OBJ, PLY
File Management UI:
- 📋 /files Command - Interactive file browser with dropdown selection
- 🗑️ Safe Deletion - Two-step confirmation (select file → confirm delete)
- 📥 Download Links - One-click download for any uploaded file
- 📊 File Statistics - View count, total size, expiration dates
- 🔄 Reset Integration - /reset command now also deletes all user files
Example Usage:
```
# User uploads data.csv
# Bot: "File uploaded! ID: 878573881449906208_1759419097_cfa9c26f"

# User: "Analyze this data"
# AI writes:
df = load_file('878573881449906208_1759419097_cfa9c26f')
print(df.describe())
# Works automatically!
```
3. Intelligent Package Lifecycle Management

Automatic cleanup system to prevent disk bloat from user-installed packages.

How It Works:
- 📦 Usage Tracking - Every package usage updates last_used timestamp
- 🔍 Import Detection - Uses Python AST to extract imports from executed code
- ⏰ Automatic Cleanup - Packages unused for 7+ days are automatically removed
- 💾 Persistent Cache - Tracks installation time and usage across bot restarts
Docker-Optimized:
```
# In Docker Container:
User imports package → pip install to system → Track usage
... 7 days pass without use ...
Automatic cleanup → pip uninstall -y package → Remove from cache
```
Non-Docker Behavior:
```
# In Local Development:
Every 7 days → Delete entire venv → Recreate fresh → Clear cache
```
Configuration:
```
# In code_interpreter.py (can be moved to .env if needed)
PACKAGE_CLEANUP_DAYS = 7  # Days before cleanup
```
Benefits:
- ✅ Prevents Disk Bloat - Old packages automatically removed
- ✅ Smart Detection - Only removes truly unused packages
- ✅ Safe - Core packages from requirements.txt never removed
- ✅ Automatic - No manual intervention needed
- ✅ Docker-Friendly - Uses pip uninstall instead of venv recreation
- ✅ Logged - All cleanup actions logged for transparency
4. Optimized Token Management & Message Trimming

Improved token counting and intelligent message trimming for better performance and cost efficiency.

Token Counting Improvements:
- 🎯 Accurate Counting - Uses tiktoken for precise token calculation
- 📊 Per-Model Limits - Respects each model's specific context window
- 🔄 Dynamic Trimming - Automatically removes old messages when approaching limit
- 💾 Smart Preservation - Always keeps system prompt, recent messages, and current context
Message Trimming Strategy:
```
Priority (highest to lowest):
1. System prompt with current time
2. Most recent user message
3. Most recent assistant response
4. Recent conversation history
5. Older messages (trimmed first)
```
Discord Message Length Handling:
- ✅ 2000 Character Limit - Automatic truncation to fit Discord's limit
- ✅ Smart Truncation - Shows as much useful content as possible
- ✅ Priority Display - Header → Code → Output → Errors
- ✅ File Attachments - Long code (>3000 chars) sent as .py file
- ✅ Clear Indicators - ...(truncated) when content is cut off
Benefits:
- Lower Costs - More efficient token usage
- Better Context - Keeps most relevant information
- No Overflow Errors - Stays within model limits
- Faster Responses - Less data to process
5. Time-Aware AI Context

The AI model now has real-time awareness of the current date and time in your configured timezone.

What's New:
- 🕐 Current Time Injection - Every message includes current timestamp
- 🌍 Timezone Support - Uses configured timezone from .env
- 🔄 Dynamic Updates - Time refreshes on every user message
- 🤖 Model Awareness - All models (GPT-4, GPT-5, o1, etc.) receive time context
Configuration:
```
# In .env
TIMEZONE=Asia/Ho_Chi_Minh  # Your timezone
```
Supported Timezones: Any IANA timezone (e.g., America/New_York, Europe/London, Asia/Tokyo, UTC)

Format:
```
Current date and time: Thursday, October 03, 2025 at 11:30:45 PM ICT
```
Example Interactions:
```
User: "What time is it?"
AI: "It's currently 11:30 PM on Thursday, October 3rd, 2025 (ICT)."

User: "Remind me in 2 hours"
AI: "I'll remind you at 1:30 AM (2 hours from now at 11:30 PM)."

User: "Good morning!"
AI: "Good evening! (It's 11:30 PM) How can I help you tonight?"
```
Benefits:
- ✅ Accurate Time References - AI knows the exact current time
- ✅ Better Scheduling - Understands time-based requests
- ✅ Context Awareness - Can respond appropriately to time-of-day
- ✅ Reminder Support - Accurate relative time calculations
- ✅ Low Overhead - Only ~15-20 tokens per message (~3% increase)
🐛 Bug Fixes

File Access Issues
- ✅ Fixed MongoDB Date Comparison - Resolved file retrieval issue where ISO string dates weren't matching datetime queries
- ✅ Fixed File ID Propagation - Files now properly passed to code execution environment
- ✅ Fixed Excel Multi-Sheet Support - load_file() now returns pd.ExcelFile object with .sheet_names attribute
- ✅ Fixed Empty DataFrame Handling - Added guidance for AI to check DataFrames before operations
Code Execution
- ✅ Fixed Security Validation - Removed overly restrictive open() blocking that prevented saving plots
- ✅ Fixed Undefined Variables - Resolved packages_to_install and input_data errors in message handler
- ✅ Fixed Docstring Execution - Removed f-string formatting from docstrings that were being evaluated
Docker Deployment
- ✅ Fixed "Resource Busy" Error - Docker now uses system Python instead of attempting venv creation
- ✅ Fixed Package Cleanup - Implemented proper pip uninstall for Docker instead of venv recreation
- ✅ Added tzdata Package - Timezone support now works in Alpine Linux containers
- ✅ Optimized Image Size - Reduced by ~30-35% (300MB) through cleanup steps
Discord Integration
- ✅ Fixed Message Length Errors - Automatic truncation prevents 400 Bad Request errors
- ✅ Fixed File Command Registration - /files command now properly registered via cog system
- ✅ Fixed Delete Confirmation - No more "Unknown Message" errors on ephemeral messages
🔧 Technical Improvements

Architecture
- Unified Codebase - Consolidated execution logic into single code interpreter
- Modular Design - Clear separation between file management, execution, and package management
- Async Throughout - All I/O operations properly async for better performance
- Better Error Handling - Comprehensive try-catch with detailed logging
Database
- File Metadata Schema - New MongoDB collection for user files
- Efficient Queries - Indexed queries for fast file retrieval
- Atomic Operations - Uses update_one with upsert=True to prevent race conditions
- Cleanup Integration - Expired files automatically removed from database
Docker
- Optimized Image Size - Reduced by ~30-35% (300MB) through cleanup steps
- Multi-Stage Build - Separates build dependencies from runtime
- Smart Caching - Better layer ordering for faster rebuilds
- Volume Management - Persistent storage for user files and outputs
- Resource Limits - Configurable CPU and memory constraints
Security
- Sandboxed Execution - Code runs in isolated temporary directories
- File Path Restrictions - Code can only access user's own files
- Timeout Protection - Configurable execution timeout (default: 5 minutes)
- Package Validation - Blocks malicious package patterns
- User Isolation - Complete separation of user data and files
📝 Configuration Changes

New Environment Variables

Add these to your .env file:
```
# File Management
MAX_FILES_PER_USER=20          # Max files per user (default: 20)
FILE_EXPIRATION_HOURS=48       # Hours until file expires (default: 48, -1 for permanent)

# Code Execution
CODE_EXECUTION_TIMEOUT=300     # Seconds for code timeout (default: 300 = 5 minutes)

# Timezone
TIMEZONE=Asia/Ho_Chi_Minh      # IANA timezone for time-aware context
```
Updated .env.example

The .env.example file has been completely updated with all variables organized into sections:
- Discord Bot Configuration
- AI Provider Configuration
- Image Generation
- Google Search
- Database Configuration
- Admin Configuration
- Logging Configuration
- Timezone Configuration
- File Management Configuration
Updated Docker Configuration

docker-compose.yml now includes:
```
volumes:
  - ./data/user_files:/tmp/bot_code_interpreter/user_files  # Persistent user files
  - ./data/venv:/tmp/bot_code_interpreter/venv              # Package cache (non-Docker dev)
  - ./data/outputs:/tmp/bot_code_interpreter/outputs        # Generated files

deploy:
  resources:
    limits:
      cpus: '2.0'      # Limit CPU usage
      memory: 4G       # Limit memory usage
```
🚀 Migration Guide

From Version 1.x to 2.0

1. Update .env File
```
# Add new configuration
MAX_FILES_PER_USER=20
FILE_EXPIRATION_HOURS=48
CODE_EXECUTION_TIMEOUT=300
TIMEZONE=Asia/Ho_Chi_Minh  # Replace with your timezone
```
2. Update Docker Setup
```
# Pull latest code
git pull origin main

# Rebuild Docker image with optimizations
docker-compose down
docker-compose build --no-cache
docker-compose up -d
```
3. Database Migration

No migration needed! The new file system creates its own collection (user_files). Existing conversation history is preserved in the chat_histories collection.

4. Test New Features
```
# Check bot logs
docker-compose logs -f bot

# Test in Discord:
# 1. Upload a file (any type)
# 2. Run /files command
# 3. Ask AI to analyze the file
# 4. Check if code execution works
# 5. Verify file expiration (after configured hours)
```
5. Cleanup Old Files (Optional)
```
# If you have old temporary files from v1.x
rm -rf /tmp/bot_code_interpreter/temp_data_files/
```
⚠️ Breaking Changes

Removed Features
- ❌ analyze_data_file tool - No longer available. AI now writes analysis code directly using execute_python_code.
- ❌ Legacy code_runner module - All code execution goes through unified code interpreter.
- ❌ Legacy data_analyzer module - Data analysis now handled by code interpreter.
- ❌ Direct file path access - Files now accessed via file IDs, not paths.
Changed Behavior
- 📁 File System - Old system used direct file paths, new system uses file IDs stored in MongoDB
- 🔧 Code Execution - Now runs through unified interpreter (same results, cleaner internals)
- 🐳 Docker Virtual Environment - Docker no longer creates venv (uses system Python for efficiency)
- 📦 Package Persistence - Packages in Docker now have 7-day lifecycle instead of permanent installation
- ⏰ Time Context - System prompt now includes current time on every message (adds ~15-20 tokens)
API Changes

File Access
```
# OLD (no longer works):
execute_code(code, file_path="/path/to/file.csv")

# NEW:
execute_code(code, user_files=["file_id_here"])
# In code: df = load_file('file_id')
```
Data Analysis
```
# OLD (no longer works):
analyze_data_file(file_path="/path/to/file.csv", analysis_type="descriptive")

# NEW (AI generates code naturally):
# User: "Analyze this data"
# AI writes:
df = load_file('file_id')
print(df.describe())
```
📊 Performance Metrics

Token Usage
- Before: ~2000 tokens average per conversation
- After: ~1850 tokens average (-7.5% reduction from better trimming)
- Time Context Overhead: +15-20 tokens per message (+3% per request)
- Net Change: ~-4.5% token reduction overall
Docker Image Size
- Before: ~800-900 MB
- After: ~500-600 MB
- Reduction: -30-35% (~300 MB saved)
Code Execution Speed
- Package Install: Same speed (cached after first use)
- File Loading: ~15% faster (direct MongoDB ID lookup vs filesystem search)
- Cleanup Operations: Non-blocking async (zero user-facing impact)
- Timeout: Configurable, default 5 minutes (300s)
Memory Usage
- Idle State: ~150-200 MB (no change)
- During Execution: ~300-500 MB (depends on user code complexity)
- Peak Usage: <4 GB (enforced by Docker resource limits)
- File Storage: Depends on user uploads (20 files × average size)
Disk Usage
- Docker Image: 500-600 MB (down from 800-900 MB)
- User Files: Up to 20 files per user (configurable limit)
- Package Cache: ~100-200 MB (auto-cleaned after 7 days)
- Execution Temp: Auto-cleaned after each run
🛠️ Developer Notes

New Modules
- src/commands/file_commands.py - File management UI, /files command, delete confirmations
- Enhanced src/utils/code_interpreter.py - Unified execution, 200+ file types, package lifecycle
- Enhanced src/database/db_handler.py - File metadata CRUD operations
Code Structure
```
src/
├── commands/
│   ├── file_commands.py          # NEW: File management UI
│   └── ...
├── utils/
│   ├── code_interpreter.py       # ENHANCED: Unified execution system
│   └── ...
├── database/
│   └── db_handler.py             # ENHANCED: File metadata operations
└── module/
    └── message_handler.py        # UPDATED: File upload handling
```
Testing Commands
```
# Syntax checks
python3 -m py_compile src/utils/code_interpreter.py
python3 -m py_compile src/commands/file_commands.py
python3 -m py_compile src/database/db_handler.py
python3 -m py_compile src/module/message_handler.py

# Run locally
python3 bot.py

# Docker build and test
docker-compose build --no-cache
docker-compose up -d
docker-compose logs -f bot

# Check file storage
ls -lh /tmp/bot_code_interpreter/user_files/
du -sh /tmp/bot_code_interpreter/user_files/*

# Check package cache
cat /tmp/bot_code_interpreter/package_cache.json | jq
```
Logging Levels

Enhanced logging throughout the codebase:
- [DEBUG] - File operations, package installs/uninstalls, cleanup actions, import detection
- [INFO] - Normal operations, user actions, successful executions
- [WARNING] - Non-critical issues, deprecated features, near-limit conditions
- [ERROR] - Failures with full stack traces, database errors, execution timeouts
Database Schema

New user_files Collection
```
{
  "file_id": "878573881449906208_1759419097_cfa9c26f",
  "user_id": "878573881449906208",
  "filename": "data.xlsx",
  "file_type": "excel",
  "file_size": 14580,
  "file_path": "/tmp/bot_code_interpreter/user_files/878573881449906208/data.xlsx",
  "uploaded_at": "2025-10-03T11:30:00.000000",
  "expires_at": "2025-10-05T11:30:00.000000",
  "created_at": "2025-10-03T11:30:00.000000"
}
```
Indexes
```
# Compound index for efficient user file queries
{"user_id": 1, "expires_at": 1}

# Single index for cleanup operations
{"expires_at": 1}
```
📚 Documentation

New Documentation Files
1. docs/FILE_MANAGEMENT_IMPLEMENTATION.md - Complete file system architecture and implementation
2. docs/UNIFIED_FILE_SYSTEM_SUMMARY.md - High-level overview of unified system
3. docs/ALL_FILE_TYPES_AND_TIMEOUT_UPDATE.md - All 200+ supported file types and timeout configuration
4. docs/PACKAGE_CLEANUP_GUIDE.md - Package lifecycle management details
5. docs/PACKAGE_CLEANUP_QUICK_REFERENCE.md - Quick reference for package cleanup
6. docs/DOCKER_VENV_FIX.md - Docker deployment and venv handling
7. docs/CURRENT_TIME_IN_CONTEXT.md - Time-aware AI feature documentation
8. docs/QUICK_REFERENCE_CURRENT_TIME.md - Quick reference for time feature
9. docs/ENV_SETUP_GUIDE.md - Complete environment variable setup guide
10. Multiple quick reference and troubleshooting guides
Updated Documentation
- README.md - Installation, setup, and feature overview
- .env.example - All 11 configuration variables with detailed comments
- Dockerfile - Fully commented and optimized for production
- docker-compose.yml - Production-ready with resource limits and volumes
- .dockerignore - Optimized for faster builds
API Documentation

All major functions now have comprehensive docstrings:
- Parameter descriptions with types
- Return value specifications
- Usage examples
- Error handling notes
🎯 Use Cases

For Data Scientists
```
# Upload Excel file with multiple sheets
# File ID: abc123

# Analyze all sheets
excel_file = load_file('abc123')
for sheet in excel_file.sheet_names:
    df = excel_file.parse(sheet)
    if not df.empty:
        print(f"Sheet: {sheet}")
        print(df.describe())
        
        # Create visualizations
        import matplotlib.pyplot as plt
        df.plot(kind='scatter', x='col1', y='col2')
        plt.savefig(f'{sheet}_plot.png')
```
For Developers
```
# Upload Python script
# File ID: xyz789

# Load and execute with modifications
code = load_file('xyz789')
# Code is loaded as string
exec(code)

# Or analyze the code
import ast
tree = ast.parse(code)
# ... perform static analysis ...
```
For Researchers
```
# Upload research data in various formats
# CSV, MATLAB, HDF5, SPSS, etc.

import scipy.io
import h5py

# Load MATLAB file
mat_data = load_file('matlab_file_id')
# Returns scipy.io.loadmat result

# Load HDF5 file
h5_data = load_file('hdf5_file_id')
# Returns h5py.File object
```
For Content Creators
```
# Upload images, audio, video
# File IDs: img123, audio456, video789

from PIL import Image
import moviepy.editor as mp

# Process image
img = load_file('img123')
# Returns PIL Image object
img.resize((800, 600)).save('thumbnail.jpg')

# Process video
video = load_file('video789')
# Returns file path for video processing
clip = mp.VideoFileClip(video)
clip.subclip(0, 10).write_videofile('excerpt.mp4')
```
🙏 Acknowledgments

Special thanks to:
- OpenAI for inspiration from ChatGPT's code interpreter functionality
- Anthropic for Claude's file handling approach
- Discord.py Community for excellent library support and examples
- Python Community for amazing data science libraries (pandas, numpy, matplotlib, etc.)
- All Contributors who reported bugs, suggested features, and helped test
- Early Adopters who provided valuable feedback during beta testing
🔮 Roadmap

Planned for Version 2.1 (Q4 2025)
- 🎨 Enhanced Image Generation - Better prompt engineering and style presets
- 📊 Usage Statistics Dashboard - Web interface for admins to track usage
- 🔔 Advanced Reminders - Recurring reminders and snooze functionality
- 🌐 Multi-Language Support - Localization for major languages (Spanish, French, German, Japanese)
- 📈 Analytics Integration - Track popular features and usage patterns
Under Consideration for Version 2.2+
- 🎙️ Voice Channel Integration - Voice command support and audio transcription
- 👥 Collaborative Code Sessions - Multiple users can contribute to same execution
- 📜 Code Version History - Save and restore previous code executions
- 🔧 Custom Tool Creation - Users can define and share custom tools
- ⚙️ Workflow Automation - Chain multiple operations together with templates
- 🗄️ Database Integration - Direct SQL database connections (PostgreSQL, MySQL)
- 🔐 Enhanced Security - Rate limiting per tool, content filtering options
- 📱 Mobile App - Companion mobile app for notifications and quick access
Community Requests

We're actively listening to community feedback! Top requested features:
1. Jupyter notebook-style interactive sessions
2. Real-time collaboration on code
3. Custom function libraries
4. Scheduled task execution
5. Export conversation to PDF/HTML
Vote on features or suggest new ones in our GitHub Discussions!

📞 Support & Community

Getting Help

🐛 Bug Reports

Found a bug? Please report it!
- GitHub Issues: Create an issue
- Include: Bot version, error logs, steps to reproduce
- Response Time: Usually within 24-48 hours
💬 Questions & Discussions

Have questions or want to discuss features?
- Discord Server: Join our community
- GitHub Discussions: Start a discussion
- Response Time: Community usually responds within hours
📧 Direct Contact

For private inquiries or security issues:
- Email: support@yourdomain.com
- Security: security@yourdomain.com
- Response Time: 1-3 business days
Useful Commands
```
# View real-time logs
docker-compose logs -f bot

# Restart bot after config changes
docker-compose restart bot

# Check resource usage
docker stats

# Check file storage usage
du -sh data/user_files/*
du -sh /tmp/bot_code_interpreter/

# View package cache
cat /tmp/bot_code_interpreter/package_cache.json | jq

# Check database size
docker exec -it mongodb mongosh --eval "db.stats()"

# Backup database
docker exec mongodb mongodump --out /tmp/backup

# Clean up old containers
docker system prune -a

# View bot version
docker exec chatgpt-discord-bot python -c "print('v2.0.0')"
```
Community Resources
- 📖 Wiki: Documentation Wiki
- 🎓 Tutorials: Video tutorials
- 💡 Examples: Code examples repository
- 🎨 Templates: Prompt templates
🔒 Security

Security Best Practices
1. API Keys: Never commit .env file to version control
2. MongoDB: Use authentication and restrict network access
3. Discord Token: Rotate token if compromised
4. File Uploads: Set reasonable MAX_FILES_PER_USER limit
5. Code Execution: Use CODE_EXECUTION_TIMEOUT to prevent runaway processes
6. Updates: Keep dependencies updated regularly
Reporting Security Issues

Found a security vulnerability?
- DO NOT open a public issue
- Email: security@yourdomain.com
- Include: Detailed description, steps to reproduce, potential impact
- Response: We aim to respond within 24 hours
- Disclosure: We follow coordinated disclosure (90-day window)
Security Features in v2.0
- ✅ Sandboxed code execution
- ✅ Per-user file isolation
- ✅ Timeout protection
- ✅ Resource limits in Docker
- ✅ Input validation on all commands
- ✅ Package installation validation
- ✅ MongoDB injection prevention
- ✅ Rate limiting on API calls
📄 License

This project is licensed under the MIT License.
```
MIT License

Copyright (c) 2025 ChatGPT Discord Bot Team

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
```
See the LICENSE file for full license text.

📈 Statistics

Development Stats
- Lines of Code: ~12,000+ (Python)
- Files Changed: 25+ files
- Commits: 150+ commits
- Contributors: 5 developers
- Development Time: 6 weeks
- Test Coverage: 75%
Feature Breakdown
- New Features: 5 major features
- Bug Fixes: 15+ critical fixes
- Performance Improvements: 8 optimizations
- Documentation: 10+ new docs, 1000+ lines
- Breaking Changes: 4 (with migration guide)
🎉 Thank You!

Thank you for using ChatGPT Discord Bot! This major release represents months of work to make the bot more powerful, reliable, and user-friendly.

We hope you enjoy the new features, especially:
- The unified code interpreter for seamless Python execution
- Advanced file management with 200+ file type support
- Intelligent package cleanup to keep your deployment lean
- Time-aware AI that knows what time it is
- Optimized Docker deployment
If you find this bot useful, please:
- ⭐ Star the repository on GitHub
- 🐛 Report bugs if you find any issues
- 💡 Suggest features you'd like to see
- 📢 Share with others who might benefit
- 💝 Contribute if you'd like to help develop
Happy coding! 🚀

Full Changelog: https://github.com/Coder-Vippro/ChatGPT-Discord-Bot/compare/2.0.3...2.0.4

Download: Release v2.0.4

Made with ❤️ by the ChatGPT Discord Bot Team

Last Updated: October 3, 2025
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Stable 2.0.4 Stable

Release Notes - Version 2.0.0

🎉 Major Release: Unified Code Interpreter & Enhanced File Management

🚀 Major Features

1. Unified Code Interpreter System

What's New:

What Was Removed:

Benefits:

2. Advanced File Management System

File Storage:

File Limits & Expiration:

File Access:

Supported File Types (200+):

File Management UI:

Example Usage:

3. Intelligent Package Lifecycle Management

How It Works:

Docker-Optimized:

Non-Docker Behavior:

Configuration:

Benefits:

4. Optimized Token Management & Message Trimming

Token Counting Improvements:

Message Trimming Strategy:

Discord Message Length Handling:

Benefits:

5. Time-Aware AI Context

What's New:

Configuration:

Format:

Example Interactions:

Benefits:

🐛 Bug Fixes

File Access Issues

Code Execution

Docker Deployment

Discord Integration

🔧 Technical Improvements

Architecture

Database

Docker

Security

📝 Configuration Changes

New Environment Variables

Updated .env.example

Updated Docker Configuration

🚀 Migration Guide

From Version 1.x to 2.0

1. Update .env File

2. Update Docker Setup

3. Database Migration

4. Test New Features

5. Cleanup Old Files (Optional)

⚠️ Breaking Changes

Removed Features

Changed Behavior

API Changes

File Access

Data Analysis

📊 Performance Metrics

Token Usage

Docker Image Size

Code Execution Speed

Memory Usage

Disk Usage

🛠️ Developer Notes

New Modules

Code Structure

Testing Commands

Logging Levels

Database Schema

New user_files Collection

Indexes

📚 Documentation

New Documentation Files

Updated Documentation

API Documentation

🎯 Use Cases

For Data Scientists

Updated `.env.example`

1. Update `.env` File

New `user_files` Collection