Self Learning RAG With COT WIP

Overview

Self Learning RAG With COT is a project that implements Retrieval-Augmented Generation (RAG) combined with Chain of Thought (COT) reasoning. This project aims to enhance the performance of language models by enabling them to retrieve relevant information from external sources and reason through it step by step, mimicking human-like cognitive processes.

Features

• Retrieval-Augmented Generation (RAG): Leverages a retriever to access pertinent data from a large corpus.
• Chain of Thought (COT): Implements a reasoning mechanism that allows the model to articulate its thought process.
• Self-Learning Mechanism: Adapts the retrieval process based on feedback to improve accuracy and efficiency over time.

Installation

To get started, clone the repository and install the necessary dependencies:

git clone https://github.com/yourusername/Self_learning_RAG_With_COT.git
cd Self_learning_RAG_With_COT
pip install -r requirements.txt

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for more details.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements

• Transformers - For providing state-of-the-art pre-trained models.
• LangChain - For simplifying the implementation of the language model and retrieval mechanism.