# Technology Stack Reference

## Overview
This document provides comprehensive information about the technology stack used in the Chat App project, including core technologies, AI tools, development tools, and infrastructure components.

## Core Technology Stack

### Programming Languages

#### Python 3.11+
**Role**: Primary development language
**Justification**: 
- Excellent AI/ML ecosystem support
- Strong async/await capabilities for concurrent operations
- Rich standard library for system operations
- Extensive third-party package ecosystem

**Key Features Used**:
- Async/await for non-blocking I/O operations
- Type hints for better code documentation and IDE support
- Dataclasses for structured data representation
- Context managers for resource management

**Code Example**:
```python
from typing import Optional, Dict, List
from dataclasses import dataclass
import asyncio

@dataclass
class EventData:
    event_type: str
    payload: Dict
    timestamp: float

async def process_event(event: EventData) -> Optional[Dict]:
    """Process event asynchronously"""
    # Implementation
    pass
```

### Core Libraries and Frameworks

#### AsyncIO
**Version**: Built-in (Python 3.11+)
**Role**: Asynchronous programming foundation
**Usage**: 
- Event loop management
- Concurrent task execution
- Non-blocking I/O operations

```python
# Event loop management
async def main():
    tasks = [
        process_user_input(),
        handle_ai_responses(),
        update_terminal_display()
    ]
    await asyncio.gather(*tasks)
```

#### aiohttp
**Version**: 3.9.0+
**Role**: HTTP client for AI API communications
**Features**:
- Async HTTP requests
- Connection pooling
- Session management
- SSL/TLS support

```python
import aiohttp

async def call_ai_api(prompt: str) -> dict:
    async with aiohttp.ClientSession() as session:
        async with session.post(
            'https://api.anthropic.com/v1/messages',
            json={'prompt': prompt},
            headers={'Authorization': f'Bearer {api_key}'}
        ) as response:
            return await response.json()
```

#### SQLite3
**Version**: Built-in (Python 3.11+)
**Role**: Local data persistence
**Usage**:
- State management
- Configuration storage
- Conversation history
- Plugin data

```python
import sqlite3
import aiosqlite

async def store_conversation(message: ConversationMessage):
    async with aiosqlite.connect('state.db') as db:
        await db.execute(
            "INSERT INTO conversations (role, content, timestamp) VALUES (?, ?, ?)",
            (message.role, message.content, message.timestamp)
        )
        await db.commit()
```

## AI Technology Stack

### Primary AI Tools

#### Claude Code
**Provider**: Anthropic
**Version**: Latest
**Role**: Primary AI development assistant
**Capabilities**:
- Agentic coding assistance
- Codebase analysis and understanding
- Multi-tool orchestration
- Context-aware development

**Integration**:
```python
class ClaudeCodeIntegration:
    def __init__(self, api_key: str):
        self.api_key = api_key
        self.session = None
    
    async def start_session(self, project_context: dict):
        """Initialize Claude Code session with project context"""
        # Implementation
```

#### Claude AI API
**Provider**: Anthropic
**Models**: Claude-3 Sonnet, Claude-3 Opus
**Role**: LLM inference and conversation
**Features**:
- High-quality text generation
- Code analysis and generation
- Long context windows
- Tool use capabilities

**API Integration**:
```python
import anthropic

class ClaudeAPI:
    def __init__(self, api_key: str):
        self.client = anthropic.AsyncAnthropic(api_key=api_key)
    
    async def chat_completion(self, messages: List[dict]) -> dict:
        response = await self.client.messages.create(
            model="claude-3-sonnet-20240229",
            max_tokens=4000,
            messages=messages
        )
        return response
```

### Secondary AI Tools

#### GitHub Copilot
**Provider**: GitHub/Microsoft
**Role**: Code completion and suggestions
**Integration**: IDE-based, supplementary to Claude Code

#### OpenAI GPT-4
**Provider**: OpenAI
**Role**: Fallback LLM for specific tasks
**Use Cases**: When Claude is unavailable or for comparative analysis

```python
import openai

class OpenAIClient:
    def __init__(self, api_key: str):
        self.client = openai.AsyncOpenAI(api_key=api_key)
    
    async def create_completion(self, messages: List[dict]) -> dict:
        response = await self.client.chat.completions.create(
            model="gpt-4",
            messages=messages
        )
        return response
```

## Development Tools

### Version Control

#### Git
**Version**: 2.40+
**Role**: Source code version control
**Configuration**:
```bash
# .gitconfig optimizations for AI development
[core]
    editor = code --wait
    autocrlf = false
[pull]
    rebase = true
[merge]
    tool = vscode
```

#### Git LFS (Large File Storage)
**Role**: Managing large assets and AI model files
```bash
# .gitattributes
*.pkl filter=lfs diff=lfs merge=lfs -text
*.model filter=lfs diff=lfs merge=lfs -text
*.bin filter=lfs diff=lfs merge=lfs -text
```

### Testing Framework

#### unittest (Built-in)
**Role**: Primary testing framework
**Usage**: Unit tests, integration tests, mock testing

```python
import unittest
from unittest.mock import AsyncMock, patch

class TestEventBus(unittest.IsolatedAsyncioTestCase):
    async def test_event_publishing(self):
        event_bus = EventBus()
        result = await event_bus.publish_event("TEST", {"data": "test"})
        self.assertTrue(result.success)
```

#### pytest (Optional)
**Version**: 7.0+
**Role**: Advanced testing scenarios
**Plugins**:
- pytest-asyncio: Async test support
- pytest-mock: Enhanced mocking
- pytest-cov: Coverage reporting

### Code Quality Tools

#### Black (Code Formatter)
**Version**: 23.0+
**Configuration**:
```toml
# pyproject.toml
[tool.black]
line-length = 88
target-version = ['py311']
include = '\.pyi?$'
```

#### mypy (Type Checking)
**Version**: 1.0+
**Configuration**:
```toml
[tool.mypy]
python_version = "3.11"
warn_return_any = true
warn_unused_configs = true
disallow_untyped_defs = true
```

## Terminal and UI Technologies

### Terminal Interaction

#### ANSI Escape Sequences
**Role**: Terminal control and formatting
**Usage**: Color, cursor positioning, screen clearing, alternate buffer management

```python
class ANSIEscapes:
    CLEAR_SCREEN = '\033[2J'
    CURSOR_HOME = '\033[H'
    HIDE_CURSOR = '\033[?25l'
    SHOW_CURSOR = '\033[?25h'

    # Alternate Buffer Control (for fullscreen plugins)
    ENTER_ALT_BUFFER = '\033[?1049h'  # smcup
    EXIT_ALT_BUFFER = '\033[?1049l'   # rmcup

    @staticmethod
    def color(text: str, color_code: int) -> str:
        return f'\033[{color_code}m{text}\033[0m'

    @staticmethod
    def position(x: int, y: int) -> str:
        return f'\033[{y};{x}H'
```

#### Fullscreen Terminal Control
**Role**: Complete terminal takeover for immersive plugins
**Usage**: Matrix effects, games, visualizations

```python
class FullScreenRenderer:
    def setup_terminal(self) -> bool:
        """Enter alternate buffer and setup fullscreen mode"""
        sys.stdout.write('\033[?1049h')  # Enter alternate buffer
        sys.stdout.write('\033[?25l')    # Hide cursor
        return True

    def restore_terminal(self) -> bool:
        """Exit alternate buffer and restore normal mode"""
        sys.stdout.write('\033[?25h')    # Show cursor
        sys.stdout.write('\033[?1049l')  # Exit alternate buffer
        return True

    def write_at(self, x: int, y: int, text: str, color: str = None):
        """Write text at specific coordinates"""
        pos = f'\033[{y};{x}H'
        if color:
            text = f'\033[{color}m{text}\033[0m'
        sys.stdout.write(pos + text)
```

#### Terminfo/Termcap
**Role**: Terminal capability detection
**Usage**: Feature detection and compatibility

```python
import os
import subprocess

def detect_terminal_capabilities():
    """Detect terminal color and feature support"""
    term = os.environ.get('TERM', '')
    colors = subprocess.run(['tput', 'colors'], capture_output=True, text=True)
    return {
        'term_type': term,
        'color_support': int(colors.stdout.strip()) if colors.returncode == 0 else 8
    }
```

### Input Handling

#### Terminal Raw Mode
**Role**: Character-by-character input processing
**Implementation**: Custom input handler with async processing

```python
import tty
import sys
import termios

class RawInputHandler:
    def __init__(self):
        self.original_settings = None
    
    def enter_raw_mode(self):
        """Enter raw terminal mode"""
        self.original_settings = termios.tcgetattr(sys.stdin)
        tty.setraw(sys.stdin.fileno())
    
    def exit_raw_mode(self):
        """Restore normal terminal mode"""
        if self.original_settings:
            termios.tcsetattr(sys.stdin, termios.TCSADRAIN, self.original_settings)
```

## Infrastructure and Deployment

### Local Development

#### Python Virtual Environment
```bash
# Environment setup
python3.11 -m venv venv
source venv/bin/activate  # Unix/macOS
# or
venv\Scripts\activate     # Windows

pip install -r requirements.txt
```

#### Requirements Management
```python
# requirements.txt
aiohttp>=3.9.0
anthropic>=0.25.0
sqlite3  # Built-in
typing-extensions>=4.0.0

# requirements-dev.txt
pytest>=7.0.0
pytest-asyncio>=0.21.0
black>=23.0.0
mypy>=1.0.0
```

### Configuration Management

#### Environment Variables
```bash
# .env file
ANTHROPIC_API_KEY=your_api_key_here
OPENAI_API_KEY=your_openai_key_here
LOG_LEVEL=INFO
DEVELOPMENT_MODE=true
```

#### Configuration Files
```python
# config/default.json
{
  "terminal": {
    "render_fps": 20,
    "color_support": "auto"
  },
  "ai": {
    "primary_provider": "anthropic",
    "fallback_provider": "openai"
  },
  "plugins": {
    "auto_discovery": true,
    "plugin_directory": "plugins/"
  }
}
```

## Security Technologies

### API Key Management
```python
import keyring
import os

class SecureAPIKeyManager:
    @staticmethod
    def get_api_key(service: str) -> str:
        """Get API key from secure storage"""
        # Try environment variable first
        key = os.getenv(f'{service.upper()}_API_KEY')
        if key:
            return key
        
        # Fall back to keyring
        return keyring.get_password('chat_app', service)
```

### Input Sanitization
```python
import html
import re

class InputSanitizer:
    @staticmethod
    def sanitize_user_input(input_text: str) -> str:
        """Sanitize user input for security"""
        # Remove potentially dangerous characters
        sanitized = html.escape(input_text)
        # Remove control characters except newlines and tabs
        sanitized = re.sub(r'[\x00-\x08\x0b\x0c\x0e-\x1f\x7f]', '', sanitized)
        return sanitized
```

## Performance Monitoring

### Built-in Profiling
```python
import cProfile
import pstats
from functools import wraps

def profile_function(func):
    """Decorator to profile function performance"""
    @wraps(func)
    async def wrapper(*args, **kwargs):
        profiler = cProfile.Profile()
        profiler.enable()
        result = await func(*args, **kwargs)
        profiler.disable()
        
        stats = pstats.Stats(profiler)
        stats.sort_stats('cumulative')
        # Log or store stats as needed
        
        return result
    return wrapper
```

### Memory Monitoring
```python
import psutil
import asyncio

class ResourceMonitor:
    @staticmethod
    async def get_system_metrics():
        """Get current system resource usage"""
        process = psutil.Process()
        return {
            'cpu_percent': process.cpu_percent(),
            'memory_usage': process.memory_info().rss / 1024 / 1024,  # MB
            'memory_percent': process.memory_percent(),
            'open_files': len(process.open_files()),
            'threads': process.num_threads()
        }
```

## Future Technology Considerations

### Potential Additions
- **WebAssembly**: For performance-critical components
- **gRPC**: For high-performance API communications
- **Redis**: For distributed caching and pub/sub
- **Docker**: For containerized deployment
- **Kubernetes**: For orchestrated cloud deployment

### AI Technology Evolution
- **Local LLM Integration**: Support for local model inference
- **Specialized AI Models**: Domain-specific fine-tuned models
- **Multi-modal AI**: Support for vision and audio AI capabilities
- **AI Agent Orchestration**: Advanced multi-agent coordination

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*This technology stack reference provides comprehensive information about all technologies used in the Chat App project, enabling informed decisions about development, maintenance, and future enhancements.*