> ## Documentation Index
> Fetch the complete documentation index at: https://slide.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Architecture overview

> Understanding the Slide framework architecture

## Slide Architecture

Slide is designed as a collection of modular packages that work seamlessly together while remaining independent. This architecture provides flexibility and allows you to use only what you need.

## Core Components

<img className="rounded-lg" src="https://mintlify.s3.us-west-1.amazonaws.com/slide/images/architecture-diagram.png" alt="Slide Architecture Overview" />

### Tyler - The Agent Core

Tyler is the heart of Slide, providing:

* Agent orchestration and LLM integration
* Tool execution framework
* Streaming and async support
* Model Context Protocol (MCP) compatibility
* Evaluation and testing framework

### Lye - The Tool Library

Lye provides ready-to-use tools organized by capability:

* **Web Tools**: Search, fetch, scrape
* **Image Tools**: Analyze, extract text, process
* **Audio Tools**: Transcribe, text-to-speech
* **File Tools**: Read, write, manipulate
* **Browser Tools**: Screenshots, extraction

### Narrator - The Persistence Layer

Narrator handles conversation and file persistence:

* Thread management (conversation history)
* File storage for attachments
* Support for multiple backends:
  * In-memory (testing)
  * SQLite (local development)
  * PostgreSQL (production)

### Space Monkey - The Slack Bridge

Space Monkey enables Slack deployment:

* Event handling and routing
* Message formatting
* Thread management
* File handling

## How Components Work Together

```python theme={null}
# Tyler provides the agent
from tyler import Agent, Thread, Message

# Lye provides tools
from lye import WEB_TOOLS, IMAGE_TOOLS

# Narrator provides persistence
from tyler import ThreadStore, FileStore

# They work together seamlessly
thread_store = await ThreadStore.create("sqlite+aiosqlite:///db.sqlite")
file_store = await FileStore.create("./files")

agent = Agent(
    name="my-agent",
    model_name="gpt-4",
    tools=[*WEB_TOOLS, *IMAGE_TOOLS],
    thread_store=thread_store,
    file_store=file_store
)
```

## Design Principles

### 1. Modularity

Each package is independent and can be used separately:

* Use Tyler alone for simple agents
* Use Lye in any Python project for tool utilities
* Use Narrator for any conversation management needs

### 2. Composability

Components are designed to work together:

* Tyler + Lye = Powerful agents with tools
* Tyler + Narrator = Agents with conversation persistence
* All together = Production-ready AI systems

### 3. Extensibility

Every component is designed for extension:

* Create custom tools
* Add new storage backends
* Integrate with any LLM provider
* Connect to MCP servers

### 4. Production-Ready

Built with real-world use in mind:

* Comprehensive error handling
* Structured logging
* Testing frameworks
* Performance optimization

## Data Flow

```mermaid theme={null}
graph LR
    User[User Input] --> Thread[Thread/Message]
    Thread --> Agent[Tyler Agent]
    Agent --> LLM[LLM Provider]
    LLM --> Tools{Tool Calls?}
    Tools -->|Yes| Lye[Lye Tools]
    Tools -->|No| Response[Response]
    Lye --> Agent
    Agent --> Narrator[Narrator Storage]
    Narrator --> Response
    Response --> User
```

## When to Use Each Component

### Just Tyler

Perfect for:

* Simple conversational agents
* Prototyping and experiments
* Custom tool implementations

### Tyler + Lye

Ideal for:

* Agents that interact with external systems
* Research and analysis tasks
* Automation workflows

### Tyler + Narrator

Best for:

* Customer service bots
* Long-running conversations
* Applications needing context persistence

### Tyler + Lye + Narrator

Recommended for:

* Production applications
* Complex agent systems
* Multi-user environments

### Space Monkey

Use when:

* Deploying to Slack
* Building team collaboration tools
* Integrating with existing Slack workflows

## Next steps

<CardGroup cols={2}>
  <Card title="How Agents Work" icon="robot" href="/concepts/how-agents-work">
    Deep dive into agent internals
  </Card>

  <Card title="Tool System" icon="wrench" href="/concepts/tools">
    Learn about the tool architecture
  </Card>
</CardGroup>