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πŸ””πŸ§  Easily experiment with popular language agents across diverse reasoning/decision-making benchmarks!

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Language agent experimentation made easy.

codecov License: MIT

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.

πŸ€” Getting Started

First, install the library with pip:

pip install agential

Next, let's query the ReActAgent!

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)

πŸ™ Acknowledgement

πŸ˜€ Contributing

If you want to contribute, please check the contributing.md for guidelines! Please check out the project document timeline on Notion and reach out to us if you have any questions!

πŸ˜Άβ€πŸŒ«οΈ Contact Us!

If you have any questions or suggestions, please feel free to reach out to [email protected]!

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πŸ””πŸ§  Easily experiment with popular language agents across diverse reasoning/decision-making benchmarks!

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