The authors map the landscape of frameworks for abstracting interactions with and between large language models, and suggest two systems of organization for reasoning about the various approaches to, and philosophies of, LLM abstraction.
- Introduces embeviz - a simple side project for exploring text embeddings
- Uses backend API with GoFiber framework and frontend UI with React and React Router
- Provides interactive charts for visualizing computed projections
- Can label texts and select options for both projections and chunking
- Offers swagger docs for the API, in-memory data store, and persistent data store with QDrant
- Uses backend API with GoFiber framework and frontend UI with React and React Router
- Provides interactive charts for visualizing computed projections
- Can label texts and select options for both projections and chunking
- Offers swagger docs for the API, in-memory data store, and persistent data store with QDrant
llama-cpp-python offers a web server which aims to act as a drop-in replacement for the OpenAI API. This allows you to use llama.cpp compatible models with any OpenAI compatible client (language libraries, services, etc).
