Overview

A development kit for manifesting AI agents with a complete lack of conventional limitations.

Build an agent with just a few lines of code.

import asyncio
from tyler import Agent, Thread, Message, EventType
from lye import WEB_TOOLS

# Create an AI agent that can browse the web
agent = Agent(
    name="web_summarizer",
    model_name="gpt-4o",
    purpose="To summarize web content clearly and concisely",
    tools=WEB_TOOLS
)

# Ask your agent to visit and summarize a webpage
thread = Thread()
thread.add_message(Message(
    role="user", 
    content="Why should I use https://slide.mintlify.app/?"
))

# Watch your agent work in real-time
async def main():
    async for event in agent.stream(thread):
        # Print content as it's generated
        if event.type == EventType.LLM_STREAM_CHUNK:
            print(event.data['content_chunk'], end="", flush=True)
        # Show when tools are being used
        elif event.type == EventType.TOOL_SELECTED:
            print(f"\n🔧 Using {event.data['tool_name']}...")

asyncio.run(main())

That’s it! Your agent can now search the web, analyze images, and complete complex tasks autonomously—and you can watch it happen in real-time.

Why use Slide?

Slide gives you everything you need to build, test, and deploy intelligent AI agents. It is:

• Extensible and open source: Built on a foundation you can inspect, customize, and contribute to
• Flexible with model support: Compatible with any LLM provider supported by LiteLLM (100+ providers including OpenAI, Anthropic, etc.)
• Real-time streaming enabled: Designed to build interactive applications with streaming responses from both agents and tools
• MCP and A2A compatible: Seamlessly integrated with Model Context Protocol (MCP) servers and Agent-to-Agent (A2A) protocol for multi-agent interoperability
• Agent delegation built-in: Create multi-agent systems where specialized agents collaborate to solve complex tasks
• Multimodal by design: Capable of processing and understanding images, audio, PDFs, and more out of the box
• Persistent with conversations: Equipped with built-in support for threads, messages, and attachments with flexible storage options (in-memory, SQLite, or PostgreSQL)
• Type-safe structured outputs: Get validated Pydantic models from your agents with automatic retry on validation failure—no more manual JSON parsing
• Ready-to-use with tools: Packed with built-in tools for web interaction, file handling, and browser automation—plus dependency injection via tool_context for custom tools
• Skills and project instructions: Progressively disclose reusable Open Agent Skills on-demand, and eagerly load project-level guidelines via AGENTS.md
• Transparent reasoning: Access model thinking tokens to see how agents arrive at decisions
• Interactive CLI included: Chat with your agents instantly using the built-in tyler chat command, or scaffold new projects with tyler init
• Evaluation-ready: Equipped with a framework to test agents safely with mock tools, prebuilt LLM judges, and multi-turn conversation scenarios
• Debuggable: Integrated with W&B Weave for powerful tracing and debugging capabilities

Ready to Build?

Quickstart Tutorial

Build your first agent in 5 minutes

Your First Agent

Step-by-step guide to building agents

What Can You Build?

AI Agents

Autonomous agents that can use tools, make decisions, and complete complex tasks

Multi-Agent Systems

Coordinate specialized agents that work together on complex problems

Slack Agents

Deploy your agents as Slack agents with built-in message handling

Research Assistants

Agents that can search, analyze, and synthesize information

Data Extraction Pipelines

Extract validated, type-safe structured data from documents and conversations

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