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Web Frontend

The web frontend provides a UI on top of the RAG chat server APIs.

  • Users can chat with the LLM and see responses streamed back for different examples.
  • By selecting “Use knowledge base,” the chatbot returns responses augmented with the data that’s been stored in the vector database.
  • To store content in the vector database, change the window to “Knowledge Base” in the upper right corner and upload documents.

Diagram

Frontend structure

At its core, llm-playground is a FastAPI server written in Python. This FastAPI server hosts two Gradio applications, one for conversing with the model and another for uploading documents. These Gradio pages are wrapped in a static frame created with the Kaizen UI React+Next.js framework and compiled down to static pages. Iframes are used to mount the Gradio applications into the outer frame.

Running the web UI

If the web frontend needs to be stood up manually for development purposes, run the following commands:

  • Build the web UI container from source
  source deploy/compose/compose.env
  docker compose -f deploy/compose/docker-compose.yaml build frontend
  • Run the container which will start the server
  source deploy/compose/compose.env
  docker compose -f deploy/compose/docker-compose.yaml up frontend
  • Open the web application at http://host-ip:8090

Note:

  • If multiple pdf files are being uploaded the expected time of completion as shown in the UI may not be correct.