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Build an agent with just a few lines of code. 
import asyncio
from tyler import Agent, Thread, Message
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()
message = Message(
    role="user", 
    content="Why should I use https://slide.mintlify.app/?"
)
thread.add_message(message)

# The agent will visit the page and provide a summary
result = asyncio.run(agent.go(thread))

# Print the agent's response
print(f"ASSISTANT: {result.content}")
That’s it! Your agent can now search the web, analyze images, and complete complex tasks autonomously.

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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.)
  • 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)
  • Ready-to-use with tools: Packed with built-in tools for web interaction, file handling, and browser automation with support for custom tools
  • Real-time streaming enabled: Designed to build interactive applications with streaming responses from both agents and tools
  • 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

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Ready to Build?

Quickstart Tutorial

Build your first agent in 5 minutes

Your First Agent

Step-by-step guide to building agents

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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