The project assumes familiarity with Docker and provides a quick start guide for setting up and running the services. The guide includes steps for cloning the repository, creating a '.env' file, setting the OPENAI_API_KEY value, and building and starting the services with Docker. The project also offers tutorials, a partnership with Open-WebUI for front-end use, and customization options for prompts and data. The maintaining team includes avelino, vmesel, walison17, and lgabs.
Key takeaways:
- Dialog is an app designed to simplify LLM deploys for programmers deploying RAGs without server maintenance knowledge, allowing them to focus more on training their model.
- The project is run using Docker and includes two services: a PostgresSQL database for chat history and document retrieval for RAG, and a service with the API.
- Users can get started quickly with the project by cloning the repository, creating a .env file, setting the OPENAI_API_KEY value, and building and starting the services with Docker.
- The project can be customized with a .csv file for the knowledge base and a .toml file for prompt configuration, and it also allows for the use of Open-WebUI as a front-end.