Skip to main content

A lightweight framework for building LLM-based agents

Project description

👋 join us on 𝕏 (Twitter), Discord and WeChat

Getting Started

Please see the overview for the general introduction of Lagent. Meanwhile, we provide extremely simple code for quick start. You may refer to examples for more details.

Installation

Install with pip (Recommended).

pip install lagent

Run a Web Demo

You need to install Streamlit first.

# pip install streamlit
streamlit run examples/internlm2_agent_web_demo.py

What's Lagent?

Lagent is a lightweight open-source framework that allows users to efficiently build large language model(LLM)-based agents. It also provides some typical tools to augment LLM. The overview of our framework is shown below:

image

Major Features

  • Stream Output: Provides the stream_chat interface for streaming output, allowing cool streaming demos right at your local setup.
  • Interfacing is unified, with a comprehensive design upgrade for enhanced extensibility, including:
    • Model: Whether it's the OpenAI API, Transformers, or LMDeploy inference acceleration framework, you can seamlessly switch between models.
    • Action: Simple inheritance and decoration allow you to create your own personal toolkit, adaptable to both InternLM and GPT.
    • Agent: Consistent with the Model's input interface, the transformation from model to intelligent agent only takes one step, facilitating the exploration and implementation of various agents.
  • Documentation has been thoroughly upgraded with full API documentation coverage.

💻Tech Stack

python

All Thanks To Our Contributors:

Citation

If you find this project useful in your research, please consider cite:

@misc{lagent2023,
    title={{Lagent: InternLM} a lightweight open-source framework that allows users to efficiently build large language model(LLM)-based agents},
    author={Lagent Developer Team},
    howpublished = {\url{https://github.com/InternLM/lagent}},
    year={2023}
}

License

This project is released under the Apache 2.0 license.

🔼 Back to top

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

xlagent-0.2.1.tar.gz (64.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

xlagent-0.2.1-py3-none-any.whl (83.8 kB view details)

Uploaded Python 3

File details

Details for the file xlagent-0.2.1.tar.gz.

File metadata

  • Download URL: xlagent-0.2.1.tar.gz
  • Upload date:
  • Size: 64.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.5

File hashes

Hashes for xlagent-0.2.1.tar.gz
Algorithm Hash digest
SHA256 f9f058328561fe388466b9b5705a45ef44f937a193a70231fa23fc3dc0d43405
MD5 19e17ddea1430af8d876080efba61e38
BLAKE2b-256 7312f25f9d8c2c87f802c015e945827231882286189a61707de8dae5a9fc02c6

See more details on using hashes here.

File details

Details for the file xlagent-0.2.1-py3-none-any.whl.

File metadata

  • Download URL: xlagent-0.2.1-py3-none-any.whl
  • Upload date:
  • Size: 83.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.5

File hashes

Hashes for xlagent-0.2.1-py3-none-any.whl
Algorithm Hash digest
SHA256 7f80e165f17abdc077b099b251bf17604ff2028290f13ec18c6d0c464656ef01
MD5 fa8c0abdae228edf439989f34fd75421
BLAKE2b-256 79df7d050831c368b5d52580772587874cc727e9a1c80153fd5d298e8a525b77

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page