AI/Human task management system with file-based storage
Project description
Todozi - AI/Human Task Management System
Todozi is a comprehensive, AI-first task and knowledge management system that enables seamless collaboration between humans and AI agents. Built entirely in Python, Todozi combines powerful task management with semantic understanding, memory systems, and intelligent automation.
๐ฏ Core Philosophy
Todozi is designed around a TAG-FIRST approach where AI models can naturally embed structured information directly in conversations. This allows models to remember, organize, and manage tasks better than humans - capturing context, dependencies, and relationships automatically.
๐ Key Features
1. AI-Powered Task Management
- Intelligent task creation with automatic priority inference
- Semantic search across all content types
- AI/human/collaborative task assignment
- Project-based organization with automatic grouping
- Real-time progress tracking and analytics
2. Enhanced Terminal UI (TUI)
- Beautiful, feature-rich terminal interface with 8 comprehensive tabs
- Real-time analytics dashboard with completion tracking
- Modal dialogs for task editing and management
- Toast notifications and activity feed
- Live file watching for automatic updates
- Server management and API key controls
3. Chat Interface for AI Models ๐
The chat/ directory contains a revolutionary web-based chat interface that demonstrates Todozi's core value proposition:
- 20% Sidebar: Chat history with scrollable session list
- 40% Chat Interface: Real-time messaging with AI assistant
- 40% Todozi Panel: Dynamic task management with project filtering
Why This Matters: The chat interface shows how AI models can use Todozi tags (<todozi>, <memory>, <idea>, etc.) to naturally structure information during conversations. This allows models to:
- Remember context better than humans
- Automatically organize tasks and knowledge
- Maintain project continuity across sessions
- Capture insights and ideas in real-time
4. Training System ๐
The train/ directory contains powerful training scripts for fine-tuning AI models on Todozi data:
train-todozi-basic.py: Comprehensive BCO (Best-of-N) training script- Supports multiple batch strategies (balanced, bootstrap, k-fold, stratified, etc.)
- Integration with Hugging Face models (Gemma, Llama, etc.)
- Automatic dataset loading from batch files
- Configurable training parameters
Training Features:
- Multiple batch file formats and strategies
- BCO (Best-of-N) training with reference model
- Support for bf16/fp16 precision
- Automatic checkpointing and progress tracking
- Integration with TRL library for RLHF
5. Memory & Knowledge System
- Structured memory capture with importance levels
- Short-term and long-term memory retention
- Emotional memory tracking
- Secret/human/standard memory types
- Semantic memory search
6. Idea & Innovation Tracking
- Capture creative ideas with importance levels
- Team/public/private sharing options
- Breakthrough idea identification
- Tag-based organization
7. Advanced Features
- Error logging with severity classification
- Reminder system with overdue detection
- Training data collection for model improvement
- Code chunking for large projects
- Emotional state tracking
- Content summarization
๐ฆ Installation
pip install todozi
Or for development installation:
git clone https://github.com/cyber-boost/todozi.git
cd todozi/tdz_py
pip install -e .
๐ ๏ธ Quick Start
Terminal UI (TUI)
Launch the enhanced terminal interface:
todozi
# or
python -m todozi.tui
Keyboard Shortcuts:
1-8: Direct tab access (Projects, Tasks, Done, Find, More, API, Feed, Bye)a: Add new taske: Edit taskc: Complete taskd: Delete taskSpace: Task actions menuEnter: Task details modalCtrl+E: Modal task editingCtrl+R: Full refresh?: Help
Command Line Interface (CLI)
Use the tdz command for quick operations:
# Launch TUI (default)
tdz
# CLI commands
tdz task "Review quarterly budget"
tdz urgent "Fix critical security issue"
tdz find "authentication"
tdz stats
Python API
from todozi import Storage, Task, Priority, Status
# Initialize storage
storage = await Storage.new()
# Create a task
task = Task.new_full(
user_id="user123",
action="Implement user authentication",
time="4 hours",
priority=Priority.HIGH,
parent_project="web-app",
status=Status.TODO,
assignee=Assignee.AI,
tags=["backend", "security"],
context_notes="Use OAuth2 with JWT tokens"
)
# Add to project
await storage.add_task_to_project(task)
# List tasks
tasks = storage.list_tasks_across_projects(TaskFilters())
# Complete task
storage.complete_task_in_project(task.id)
๐ฌ Chat Interface
The chat interface demonstrates Todozi's tag-based approach for AI models:
cd chat
pip install -r requirements.txt
python chat.py
Then open http://localhost:8275 in your browser.
Example Conversation:
User: "I need to build a user authentication system for my web app"
AI: I'll help you organize this! <todozi>Build user authentication system; 4 hours; high; web-app; todo; ai; backend,security; none; Implement OAuth2 with JWT tokens; 0%</todozi>
<memory>standard; OAuth2 flows are complex; Need secure token handling; Important for web security; high; long; security,authentication</memory>
What specific authentication methods do you want to support?
The AI automatically:
- Creates structured tasks with proper fields
- Captures important memories
- Maintains project context
- Organizes information semantically
๐ Training AI Models
Train models on Todozi data using the training scripts:
cd train
pip install -r requirements.txt
# Basic training
python pure/train-todozi-basic.py
# Advanced training (if available)
python pure/train-todozi-advanced.py
Training Script Features:
- Automatic batch file selection
- BCO (Best-of-N) training configuration
- Support for multiple model architectures
- Configurable training parameters
- Progress tracking and checkpointing
Available Batch Strategies:
balanced/: Balanced sampling across categoriesbootstrap/: Bootstrap resamplingkfold/: K-fold cross-validation splitsstratified/: Stratified samplingprogressive/: Progressive training setsml/: Machine learning optimized splitscustom/: Custom batch configurations
๐ Todozi Tags
Todozi uses XML-like tags that AI models can naturally embed in conversations:
Task Creation
<todozi>action; time; priority; project; status; assignee; tags; dependencies; context; progress%</todozi>
Example:
<todozi>Fix login bug; 2 hours; high; auth-system; in_progress; ai; bug,security; none; JWT validation issue; 25%</todozi>
Memory Capture
<memory>type; moment; meaning; reason; importance; term; tags</memory>
Example:
<memory>standard; Discovered async patterns in Rust; Makes concurrent code cleaner; Will use for API calls; high; long; rust,async,patterns</memory>
Idea Capture
<idea>idea; share; importance; tags; context</idea>
Example:
<idea>Voice-controlled task management; team; breakthrough; innovation,product,ai; Could revolutionize productivity</idea>
Error Logging
<error>title; description; severity; category; source; context; tags</error>
Example:
<error>Database timeout; Connection failed after 30s; critical; database; postgres; Need connection pooling; performance,database</error>
๐๏ธ Project Structure
tdz_py/
โโโ todozi/ # Main package
โ โโโ tui.py # Enhanced Terminal UI
โ โโโ cli.py # Command-line interface
โ โโโ storage.py # File-based storage
โ โโโ models.py # Data models
โ โโโ server.py # REST API server
โ โโโ ...
โโโ chat/ # Chat interface for AI models
โ โโโ chat.py # Flask chat server
โ โโโ system.py # AI system prompts
โ โโโ tdz.html # Web interface
โ โโโ requirements.txt
โโโ train/ # Training scripts
โ โโโ pure/ # Pure training scripts
โ โ โโโ train-todozi-basic.py
โ โ โโโ train-todozi-advanced.py
โ โโโ batches/ # Training batch files
โ โโโ requirements.txt
โโโ tests/ # Test suite
โโโ tdz.py # CLI entry point
โโโ pyproject.toml # Package configuration
โโโ py.sh # Build & publish script
๐ง Development
Building the Package
Use the automated build script:
./py.sh # Build only
./py.sh --upload # Build and upload to PyPI
The script automatically:
- Increments version number (patch version)
- Cleans old build artifacts
- Builds source distribution and wheel
- Optionally uploads to PyPI
Running Tests
pytest
# or
python -m pytest
Development Installation
pip install -e ".[dev]"
๐ Features Overview
Terminal UI Tabs
- ๐ Projects: Manage and organize projects
- ๐ Tasks: View, filter, and manage tasks with analytics
- โ Done: Completed tasks with sorting and filtering
- ๐ Find: Semantic search across all content
- ๐ฎ More: Extended data (Ideas, Memories, Feelings, Errors, Training, Queue, Reminders, Analytics)
- ๐ API: Server management and API key administration
- ๐ฐ Feed: Live activity feed with real-time updates
- ๐ Bye: Exit screen
API Server
Start the REST API server:
from todozi.server import start_server
# Start server on default port
await start_server()
Key Endpoints:
GET /tasks- List all tasksPOST /tasks- Create new taskGET /tasks/search?q={query}- Semantic searchGET /agents- List AI agentsPOST /chat/process- Process chat with Todozi tags
๐ฏ Use Cases
For Developers
- Project task management
- Code review tracking
- Bug tracking and resolution
- Documentation tasks
- Learning and knowledge capture
For AI Researchers
- Training data collection
- Model fine-tuning workflows
- Experiment tracking
- Knowledge base building
- Multi-agent coordination
For Teams
- Collaborative task management
- Shared knowledge base
- Project planning and tracking
- Meeting notes and action items
- Innovation capture
๐ Links
- Website: https://todozi.com
- GitHub: https://github.com/cyber-boost/todozi
- Documentation: https://todozi.com
- Issues: https://github.com/cyber-boost/todozi/issues
๐ License
MIT License - see LICENSE file for details.
๐ค Contributing
Contributions welcome! Please see CONTRIBUTING.md for guidelines.
๐ Acknowledgments
Built with love for the AI and developer communities. Special thanks to all contributors and users who help make Todozi better every day.
Todozi - Where AI and humans collaborate seamlessly. ๐
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