This is a collection of simple applications/code snippets that demonstrates the use of a LLM with a Retrieval-Augmented Generator (LLM RAG) for text generation tasks. This uses most of the popular LLMs like OpenAI's ChatGPT and Meta's Llama-2
LLM RAG is a powerful tool that combines the capabilities of a language model with retrieval-based methods to generate text responses. This application showcases how to use LLM RAG for various text generation tasks, such as question answering, summarization, and dialogue generation.
- Question Answering: Utilize the LLM RAG model to answer questions based on provided context.
- Summarization: Generate summaries of text passages using LLM RAG.
- Dialogue Generation: Engage in conversational exchanges by leveraging the LLM RAG model.
Contributions are welcome! Please feel free to submit pull requests or open issues for any improvements or bug fixes.
This project is licensed under the MIT license. Feel free to modify it according to your specific application needs or add more details as necessary.