# Paniki Architecture

## Overview

Paniki is built on a modular, pipeline-based architecture that enables flexible integration of various components for voice and multimodal applications.

## Core Components

### 1. Transport Layer

The transport layer handles the communication between the client and server. It supports:
- WebRTC for real-time audio/video
- WebSocket for web-based applications
- Custom transport implementations

### 2. Audio Processing

Audio processing components include:
- Voice Activity Detection (VAD)
- Audio normalization
- Noise reduction
- Format conversion

### 3. Pipeline System

The pipeline system is the core of Paniki's architecture:
- Modular design for easy component integration
- Sequential processing of data
- Event-driven architecture
- Support for async/await operations

```python
pipeline = Pipeline([
    input_component,
    processing_component,
    output_component,
])
```

### 4. AI Service Integration

Paniki supports various AI services:
- OpenAI (GPT models)
- Google (Gemini)
- Anthropic (Claude)
- Azure Cognitive Services
- Custom model integration

### 5. Context Management

The context management system:
- Maintains conversation history
- Handles state management
- Provides context aggregation
- Supports different conversation strategies

## Data Flow

1. Input Processing:
   - Audio/video capture
   - Voice activity detection
   - Input preprocessing

2. AI Processing:
   - Speech-to-text conversion
   - Context aggregation
   - AI model processing
   - Text-to-speech conversion

3. Output Handling:
   - Audio/video output
   - Response formatting
   - Client communication

## Extension Points

Paniki can be extended through:
1. Custom Transport Implementations
2. Custom AI Service Integrations
3. Custom Audio Processors
4. Pipeline Component Development
5. Context Management Strategies

## Best Practices

1. Error Handling:
   - Implement proper error handling in pipeline components
   - Use appropriate logging
   - Handle network failures gracefully

2. Resource Management:
   - Clean up resources properly
   - Handle connection lifecycle events
   - Implement proper shutdown procedures

3. Performance:
   - Use async/await for I/O operations
   - Implement proper buffering strategies
   - Consider resource limitations

4. Security:
   - Implement proper authentication
   - Secure API key handling
   - Input validation