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Multi-agent framework for generative AI. Build LLM agents with tools, memory, reasoning, and planning. Fast, extensible, and developer-friendly.

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TinyGent Logo

Tiny platform for amazing agents.

Tinygent is a tiny agentic framework - lightweight, easy to use (hopefully), and efficient (also hopefully ;-0) library for building and deploying generative AI applications. It provides a simple interface for working with various models and tools, making it ideal for developers who want to quickly prototype and deploy AI solutions.

Create an agent

# uv sync --extra openai

from tinygent.tools import tool
from tinygent.core.factory import build_agent

@tool
def get_weather(location: str) -> str:
    """Get the current weather in a given location."""
    return f'The weather in {location} is sunny with a high of 75°F.'

agent = build_agent(
    'react',
    llm='openai:gpt-4o-mini',
    tools=[get_weather],
)

print(agent.run('What is the weather like in Prague?'))

Getting Started

Prerequisites

Before you begin using tinygent, ensure that you meet the following software prerequisites.

Install From Source

  1. Clone the tinygent repository to your local machine.

    git clone git@github.com:filchy/tinygent.git tinygent
    cd tinygent
  2. Create a Python environment.

    uv venv --seed .venv
    source .venv/bin/activate
  3. Install the tinygent library. To install only the core tinygent library without any optional dependencies, run the following:

    uv sync

    To install the tinygent library along with all of the optional dependencies. Including developer tools (--all-groups), additional packages and all of the dependencies needed for profiling and plugins (--all-extras) in the source repository, run the following:

    uv sync --all-groups --all-extras

    [!NOTE] Not all packages are included in the default installation to keep the library lightweight. You can customize your installation by specifying the optional dependencies you need.

  4. Install tinygent in editable mode (development mode), so that changes in the source code are immediately reflected:

    uv pip install -e .

Examples (Quick Start)

  1. Ensure you have set the OPENAI_API_KEY environment variable to allow the example to use OpenAI's API. An API key can be obtained from openai.com.

    export OPENAI_API_KEY="your_openai_api_key"
  2. Run the examples using uv:

    uv run examples/agents/multi-step/main.py
  3. Explore more examples below:

Basics

  1. Tool Usage
  2. LLM Usage
  3. Function Calling

Memory

  1. Chat Buffer Memory
  2. Summary Buffer Memory
  3. Window Buffer Memory
  4. Combined Memory

Tools

  1. Basic Tools
  2. Reasoning Tools
  3. JIT Tools

Agents

  1. Middlewares in Agents
  2. ReAct Agent
  3. Multi-Step Agent
  4. Squad Agent
  5. Modular Agentic Planner Agent

Packages

  1. Brave Tools
  2. Tiny Chat
  3. Tiny OpenAI
  4. Tiny MistralAI
  5. Tiny Gemini
  6. Tiny Anthropic
  7. Tiny VoyageAI
  8. Tiny Graph

Linting & Formatting

To ensure code quality, formatting consistency, and type safety, run:

uv run fmt   # Format code Ruff
uv run lint  # Run Ruff linter and Mypy type checks

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Multi-agent framework for generative AI. Build LLM agents with tools, memory, reasoning, and planning. Fast, extensible, and developer-friendly.

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