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GitHub - talkdai/dialog: RAG LLM Ops App for easy deployment and testing

May 28, 2024 - github.com
Talkd/dialog is an application designed to simplify the deployment of Language Models (LLMs), particularly for programmers interested in AI but lacking knowledge in server maintenance. The app allows users to deploy any LLM based on the structure provided by dialog-lib, reducing coding time and increasing model training time. The repository serves an API focused on LLM deployment, initially aimed at humanizing RAGs (Retrieval-Augmented Generators), but now expanding to broader approaches for better RAG deployment and maintenance.

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.
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