lionagi 0.0.112

Towards automated general intelligence.

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LionAGI

Towards Automated General Intelligence

LionAGI is a cutting-edge intelligent agent framework. It integrates data manipulation with advanced machine learning tools, such as Large Language Models (i.e. OpenAI's GPT).

• Designed for data-centric, production-level projects,
• dramatically lowers the barrier in creating intelligent, automated systems
• that can understand and interact meaningfully with large volumes of data.

Install LionAGI with pip:

pip install lionagi

Download the .env_template file, input your OPENAI_API_KEY, save the file, rename as .env and put in your project's root directory.

Features

• Robust performance
• Efficient data operations for reading, chunking, binning, writing, storing and managing data.
• Fast interaction with LLM services like OpenAI with configurable rate limiting concurrent API calls for maximum throughput.
• Create a production ready LLM application in hours. Intuitive workflow management to streamline the process from idea to market.
• (Work In Progress): verstile intergration with most API and local LLM services.

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LionAGI is designed to be async only, please check python official documentation on how async work: here

Notice:

• calling API with maximum throughput over large set of data with advanced models i.e. gpt-4 can get EXPENSIVE IN JUST SECONDS,
• please know what you are doing, and check the usage on OpenAI regularly
• default rate limits are set to be tier 1 of OpenAI model gpt-4-1104-preview, please check the OpenAI usage limit documentation you can modify token rate parameters to fit different use cases.
• if you would like to build from source, please download the latest release, main is under development and will be changed without notice

Quick Start

The following example shows how to use LionAGI's Session object to interact with gpt-4 model:

import lionagi as li

# define system messages, context and user instruction
system = "You are a helpful assistant designed to perform calculations."
instruction = {"Addition":"Add the two numbers together i.e. x+y"}
context = {"x": 10, "y": 5}

# Initialize a session with a system message
calculator = li.Session(system=system)

# run a LLM API call
result = await calculator.initiate(instruction=instruction,
                                   context=context,
                                   model="gpt-4-1106-preview")

print(f"Calculation Result: {result}")

Visit our notebooks for our examples.

Community

We encourage contributions to LionAGI and invite you to enrich its features and capabilities. Engage with us and other community members Join Our Discord

Citation

When referencing LionAGI in your projects or research, please cite:

@software{Li_LionAGI_2023,
  author = {Haiyang Li},
  month = {12},
  year = {2023},
  title = {LionAGI: Towards Automated General Intelligence},
  url = {https://github.com/lion-agi/lionagi},
}

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Requirements

Python 3.9 or higher.