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97 lines
3.3 KiB
Markdown
97 lines
3.3 KiB
Markdown
# Component Architecture
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This document describes the component architecture of LangBot, which is designed to be modular and extensible.
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## Overview
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LangBot is built around a component-based architecture that allows for easy extension and customization. The main components are:
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1. **Bots**: Interface with messaging platforms
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2. **Pipelines**: Process messages and generate responses
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3. **Models**: Connect to LLM providers
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4. **Plugins**: Extend functionality
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## Bots
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Bots are responsible for connecting to messaging platforms and handling message events. Each bot implements a specific platform adapter that translates between the platform's API and LangBot's internal event system.
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Key classes:
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- `MessageSourceAdapter`: Base class for all platform adapters
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- `EventConverter`: Converts platform-specific events to LangBot events
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- `MessageConverter`: Converts platform-specific messages to LangBot messages
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## Pipelines
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Pipelines process messages through a series of components:
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1. **Trigger**: Determines whether to process a message
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2. **Moderation**: Filters and processes messages before sending to the model
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3. **AI**: Sends the message to the LLM and receives a response
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4. **Output**: Processes the model's response before sending it back to the user
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Each component in the pipeline can be configured and customized.
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## Models
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The Models component manages connections to various LLM providers, such as OpenAI, Anthropic, and others. It provides a unified interface for sending requests to these providers and handling their responses.
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Key classes:
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- `ModelProvider`: Base class for all model providers
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- `ModelRequest`: Represents a request to a model
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- `ModelResponse`: Represents a response from a model
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## Plugins
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The plugin system allows for extending LangBot's functionality without modifying the core code. Plugins can:
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- Register event handlers
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- Add new commands
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- Provide functions that can be called by the LLM
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- Extend core components
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Key concepts:
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- `@handler`: Decorator for registering event handlers
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- `@llm_func`: Decorator for registering functions that can be called by the LLM
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- `APIHost`: Provides access to LangBot's API from plugins
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- `manifest.yaml`: Configuration file for plugins
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## Event System
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LangBot uses an event-driven architecture where different components communicate through events. Events include:
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- Message events (received, sent)
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- Group events (joined, left, invited)
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- System events (startup, shutdown)
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- Custom events defined by plugins
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## Configuration System
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The configuration system uses a YAML-based approach with the main configuration file at `data/config.yaml`. The configuration is structured around the component architecture:
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```yaml
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bots:
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# Bot configurations
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pipelines:
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# Pipeline configurations
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providers:
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# Model provider configurations
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plugins:
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# Plugin configurations
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system:
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# System configurations
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```
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## Development Workflow
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When developing for LangBot, follow these steps:
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1. Understand the component you want to modify or extend
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2. Create a plugin if you're adding new functionality
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3. Implement the necessary classes and methods
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4. Test your changes
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5. Submit a pull request
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For more detailed information on development, see the [Development Configuration](/en/develop/dev-config) page.
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