lionagi 0.0.209

Towards automated general intelligence.

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LionAGI

Towards Automated General Intelligence

LionAGI is an intelligent agent framework tailored for big data analysis with advanced machine learning tools. Designed for data-centric, production-level projects. Lionagi allows flexible and rapid design of agentic workflow, customed for your own data. Lionagi agents can manage and direct other agents, can also use multiple different tools in parallel.

Integrate any Advanced Model into your existing workflow.

Install LionAGI with pip:

pip install lionagi

Download the .env_template file, input your appropriate API_KEY, save the file, rename as .env and put in your project's root directory. by default we use OPENAI_API_KEY.

Intelligence Services

Provider	Type	Parallel Chat	Perform Action	Embeddings	MultiModal
OpenAI	API	✅	✅
OpenRouter	API	✅
Ollama	Local	✅
LiteLLM	Mixed	✅
HuggingFace	Local	✅
MLX	Local	✅
Anthropic	API
Azure	API
Amazon	API
Google	API
MistralAI	API

Quick Start

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

# 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}

# in interactive environment (.ipynb for example)
import lionagi as li

calculator = li.Session(system=system)
result = await calculator.chat(
  instruction=instruction, context=context, model="gpt-4-turbo-preview"
)

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

# or otherwise, you can use
import asyncio
from dotenv import load_dotenv

load_dotenv()

import lionagi as li

async def main():
    calculator = li.Session(system=system)
    result = await calculator.chat(
      instruction=instruction, context=context, model="gpt-4-turbo-preview"
    )
    print(f"Calculation Result: {result}")

if __name__ == "__main__":
    asyncio.run(main())

Visit our notebooks for examples.

LionAGI is designed to be asynchronous 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 1,000 requests, 100,000 tokens per miniute, 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

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},
}

Requirements

Python 3.9 or higher.