Metadata-Version: 2.1
Name: agential
Version: 0.1.0
Summary: A flexible agent library.
Home-page: https://github.com/alckasoc/agential
License: MIT
Keywords: agent,LLM,poetry
Author: Vincent Tu
Author-email: tuvincent0106@gmail.com
Requires-Python: >=3.11,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
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Requires-Dist: func-timeout (>=4.3.5,<5.0.0)
Requires-Dist: google-api-python-client (>=2.100.0)
Requires-Dist: langchain (>=0.2.1,<0.3.0)
Requires-Dist: langchain-community (>=0.2.1,<0.3.0)
Requires-Dist: langchain-core (>=0.2.3,<0.3.0)
Requires-Dist: litellm (>=1.42.12,<2.0.0)
Requires-Dist: scipy (>=1.13.1,<2.0.0)
Requires-Dist: sentence-transformers (>=2.2.2,<3.0.0)
Requires-Dist: tiktoken (>=0.7.0,<0.8.0)
Requires-Dist: torch (==2.2.0)
Requires-Dist: wikipedia (>=1.4.0,<2.0.0)
Project-URL: Repository, https://github.com/alckasoc/agential
Description-Content-Type: text/markdown


<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"
  />
</h3>


<h3 align="center">Language agent experimentation made easy.</h3>

<h3 align="center">

[![codecov](https://codecov.io/gh/agential-ai/agential/branch/main/graph/badge.svg)](https://codecov.io/gh/agential-ai/agential)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](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)
```


## 🧭 Project Organization

------------

    ├── agential                           <- Source code for this project.
    │   ├── cog   
    │   │   ├── agent                      <- Model/agent-related modules.
    │   │   │     ├── strategies           <- Strategies encapsulate agent logic for each benchmark/benchmark type.
    │   │   │     │       ├── base.py  
    │   │   │     │       ├── qa.py
    │   │   │     │       ├── math.py
    │   │   │     │       └── code.py
    │   │   │     │
    │   │   │     ├── agent.py             <- Agent class responsible for selecting the correct strategy, prompts/few-shots, and generating responses.
    │   │   │     ├── functional.py        <- Functional methods for agent. The lowest level of abstraction.
    │   │   │     ├── output.py            <- Output class responsible for formatting the response from the agents.
    │   │   │     ├── prompts.py           <- Prompt templates.
    │   │   │     └── <modules>.py         <- Any additional modules you may have for the strategies. Agnostic to benchmarks/benchmark-types.
    │   │
    │   ├── eval                           <- Evaluation-related modules.
    │   │
    │   ├── llm                            <- LLM class.
    │   │
    │   └── utils                          <- Utility methods.
    │       
    ├── docs                               <- An mkdocs project.
    │
    ├── notebooks                          <- Jupyter notebooks. Naming convention is a number 
    │                                         (for ordering), the creator's initials, and a short `-` delimited │ description, e.g. `1.0-jqp-initial-data-exploration`.
    │  
    ├── references                         <- Data dictionaries, manuals, and all other explanatory materials.
    │
    ├── reports                            <- Generated analysis as HTML, PDF, LaTeX, etc.
    │   └── figures                        <- Generated graphics and figures to be used in reporting.
    │
    └── tests                              <- Tests.

---------

## 🙏 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!