<h3 align="center">
<img
src="https://raw.githubusercontent.com/agential-ai/.github/main/profile/banner_dark.svg#gh-dark-mode-only"
/>
<img
src="https://raw.githubusercontent.com/agential-ai/.github/main/profile/banner_light.svg#gh-light-mode-only"
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</h3>
<h3 align="center">Language agent experimentation made easy.</h3>
<h3 align="center">
[](https://codecov.io/gh/agential-ai/agential)
[](https://opensource.org/licenses/MIT)
</h3>
Agential provides clear implementations of popular LLM-based agents across a variety of reasoning/decision-making and language agent benchmarks, making it easy for researchers to evaluate and compare different agents.
## 🤔 Getting Started
First, install the library with `pip`:
```
pip install agential
```
Next, let's query the `ReActAgent`!
```python
from agential.llm.llm import LLM
from agential.cog.react.agent import ReActAgent
question = 'Who was once considered the best kick boxer in the world, however he has been involved in a number of controversies relating to his "unsportsmanlike conducts" in the sport and crimes of violence outside of the ring?'
llm = LLM("gpt-3.5-turbo")
agent = ReActAgent(llm=llm, benchmark="hotpotqa")
out = agent.generate(question=question)
```
## 🙏 Acknowledgement
## 😀 Contributing
If you want to contribute, please check the [contributing.md](https://github.com/alckasoc/agential/blob/main/CONTRIBUTING.md) for guidelines!
Please check out the [project document timeline](https://equatorial-jobaria-9ad.notion.site/Project-Lifecycle-Management-70d65e9a76eb4c86b6aed007f717aa41?pvs=4) on Notion and reach out to us if you have any questions!
## 😶🌫️ Contact Us!
If you have any questions or suggestions, please feel free to reach out to tuvincent0106@gmail.com!
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