Reflexion: Language Agents with Verbal Reinforcement Learning

Overview

Reflexion is an open-source AI tool designed for developing language agents that utilize verbal reinforcement learning techniques. Developed by a team including Noah Shinn and Karthik Narasimhan, Reflexion leverages advanced reasoning capabilities to enhance the performance of language models in various tasks.

Preview

The repository includes comprehensive code, demos, and log files to facilitate experimentation with language agents. Users can explore different agent types and reflexion strategies through Jupyter notebooks, making it easy to visualize and analyze results.

How to Use

To get started with Reflexion, clone the repository and navigate to the HotPotQA directory:

git clone https://github.com/noahshinn/reflexion && cd ./hotpotqa_runs
pip install -r requirements.txt
export OPENAI_API_KEY=<your key>

Select from various agent types such as ReAct, CoT_context, and CoT_no_context, and specify your desired reflexion strategy in the notebooks provided.

Purposes

Reflexion is primarily aimed at researchers and developers looking to create sophisticated language agents capable of improved reasoning and interaction. It is particularly useful in tasks involving question answering and complex decision-making.

Reviews

Users have praised Reflexion for its flexibility and the depth of its research-oriented features. The ability to test multiple agent types and strategies has made it a valuable resource for the AI community.

Alternatives

While Reflexion stands out, alternatives like Hugging Face Transformers and OpenAI's GPT series offer robust frameworks for language processing tasks.

Benefits for Users

• Open Source: Free to use and modify.
• Research-Driven: Built on