TODO.md - Echo Bot Implementation

This document outlines the missing core functionality needed to implement the "Echo" bot as described in the README.md.

Core Echo Functionality (Not Yet Implemented)

1. Echo Commands (/echo slash command group)

Missing Implementation:

• /echo @user dd.mm.yyyy - Analyze user messages before cutoff date
• /echo online - Activate echo bot in current channel
• /echo offline - Deactivate echo bot in current channel

Implementation Details:

• Create new cog cogs/echo.py with slash command group
• Implement date parsing for dd.mm.yyyy format
• Add user mention parsing and validation
• Create channel state management for online/offline status

2. Message Data Collection & Storage

Missing Implementation:

• Historical message scraping from Discord channels
• Message filtering by user and date cutoff
• Secure local storage of collected messages
• Data preprocessing for LLM training

Implementation Details:

• Add database schema for storing user messages:

  CREATE TABLE user_messages (
    id INTEGER PRIMARY KEY,
    user_id VARCHAR(20),
    server_id VARCHAR(20),
    channel_id VARCHAR(20),
    message_content TEXT,
    timestamp DATETIME,
    message_id VARCHAR(20)
  );
  

• Implement message history fetching using Discord API
• Add data cleaning and tokenization utilities
• Create secure file storage for processed datasets

3. Ollama Integration

Missing Implementation:

• Ollama client integration for local LLM operations
• Model fine-tuning pipeline
• Model management (loading, unloading, switching)
• Error handling for Ollama service connectivity

Implementation Details:

• Add ollama-python to requirements.txt
• Create services/ollama_client.py for LLM operations
• Implement model fine-tuning workflow:
  • Dataset preparation in Ollama format
  • Model fine-tuning execution
  • Model validation and testing
• Add model state management

4. Echo Bot Personality System

Missing Implementation:

• User personality profile creation
• Context-aware response generation
• Message pacing and timing simulation
• Conversation initiation logic

Implementation Details:

• Create services/personality_engine.py
• Implement user writing style analysis
• Add conversation context management
• Create natural message timing algorithms
• Implement proactive conversation starters

5. Database Extensions

Missing Implementation:

• User echo profiles storage
• Active echo sessions tracking
• Message generation history
• Model training status tracking

Implementation Details:

• Extend database schema:

  CREATE TABLE echo_profiles (
    id INTEGER PRIMARY KEY,
    user_id VARCHAR(20),
    server_id VARCHAR(20),
    cutoff_date DATE,
    model_path VARCHAR(255),
    training_status VARCHAR(50),
    created_at TIMESTAMP
  );
  
  CREATE TABLE echo_sessions (
    id INTEGER PRIMARY KEY,
    profile_id INTEGER,
    channel_id VARCHAR(20),
    is_active BOOLEAN,
    started_at TIMESTAMP,
    FOREIGN KEY (profile_id) REFERENCES echo_profiles(id)
  );
  

6. Background Tasks & Processing

Missing Implementation:

• Asynchronous message processing
• Model training job queue
• Periodic model updates
• Session cleanup and management

Implementation Details:

• Create services/background_tasks.py
• Implement asyncio task management
• Add job queue for long-running operations
• Create cleanup routines for expired sessions

7. Configuration & Settings

Missing Implementation:

• Echo-specific configuration options
• Model parameters and training settings
• Rate limiting and usage controls
• Privacy and data retention policies

Implementation Details:

• Extend config.json with echo settings:

  {
    "echo": {
      "max_messages_per_analysis": 10000,
      "model_training_timeout": 3600,
      "max_active_sessions_per_server": 5,
      "message_generation_cooldown": 2.0,
      "data_retention_days": 30
    }
  }
  

8. Error Handling & Logging

Missing Implementation:

• Echo-specific error handling
• Training progress logging
• Model performance monitoring
• User feedback collection

Implementation Details:

• Add echo-specific log levels and formatting
• Implement training progress tracking
• Create error recovery mechanisms
• Add user notification system for failures

9. Security & Privacy

Missing Implementation:

• Message data encryption at rest
• User consent management
• Data deletion capabilities
• Access control for echo profiles

Implementation Details:

• Implement message encryption before storage
• Add user consent tracking system
• Create data deletion utilities
• Implement profile access controls

10. Performance Optimization

Missing Implementation:

• Message processing optimization
• Model loading/unloading strategies
• Resource usage monitoring
• Concurrent session management

Implementation Details:

• Add async processing for large datasets
• Implement model caching strategies
• Create resource monitoring utilities
• Add concurrent session limits

File Structure Extensions Needed

cogs/
├── echo.py                    # Main echo commands
services/
├── __init__.py
├── ollama_client.py          # Ollama integration
├── personality_engine.py     # AI personality system
├── message_processor.py      # Message data processing
├── background_tasks.py       # Async task management
└── security.py              # Data encryption/privacy
utils/
├── __init__.py
├── date_parser.py           # Date parsing utilities
├── text_processor.py        # Text cleaning/tokenization
└── validation.py            # Input validation

Dependencies to Add

ollama-python>=0.3.0
cryptography>=41.0.0
aiofiles>=23.0.0
python-dateutil>=2.8.0

Testing Requirements

• Unit tests for all new services
• Integration tests for Ollama communication
• Discord API interaction tests
• Database operation tests
• End-to-end echo workflow tests

Documentation Needed

• API documentation for new services
• User guide for echo functionality
• Privacy policy for data handling
• Troubleshooting guide for common issues