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Open WebUI

Kreuzberg

Open WebUI supports pluggable content extraction backends. Kreuzberg implements two of those backend APIs — the docling-serve endpoint and the external document loader endpoint, so it works as a drop-in replacement without patching Open WebUI.

How it works

  1. A user uploads a document (PDF, DOCX, image, etc.) in Open WebUI.
  2. Open WebUI sends the file to Kreuzberg's API endpoint.
  3. Kreuzberg extracts the content — running OCR where needed and returns markdown.
  4. Open WebUI stores the markdown in its vector database for retrieval-augmented generation.

Kreuzberg supports 90+ file formats and requires no GPU.

Prerequisites

  • Docker and Docker Compose (v2)
  • Open WebUI running or ready to deploy
  • No GPU required — Kreuzberg runs entirely on CPU

Setup with Docker Compose

This is the fastest way to get both services running together.

docker-compose.yaml
services:
  kreuzberg:
    image: ghcr.io/kreuzberg-dev/kreuzberg:latest-core
    ports:
      - "8000:8000"
    command: ["serve", "--host", "0.0.0.0", "--port", "8000"]
    volumes:
      - kreuzberg-cache:/app/.kreuzberg
    healthcheck:
      test: ["CMD", "kreuzberg", "version"]
      interval: 10s
      timeout: 5s
      retries: 5

  open-webui:
    image: ghcr.io/open-webui/open-webui:main
    ports:
      - "3000:8080"
    environment:
      CONTENT_EXTRACTION_ENGINE: "docling"
      DOCLING_SERVER_URL: "http://kreuzberg:8000"
    depends_on:
      kreuzberg:
        condition: service_healthy

volumes:
  kreuzberg-cache:

Start both services in detached mode:

docker compose up -d

Open http://localhost:3000, create an account, and upload a document. The extracted text will appear in the chat context.

Cache volume

The kreuzberg-cache volume persists OCR models and embedding weights across restarts. Without it, models re-download on every container restart (~90 MB–1.2 GB depending on configuration).

Already running Open WebUI?

Start Kreuzberg separately, then point Open WebUI to that Kreuzberg URL.

docker run -d \
  --name kreuzberg \
  -p 8000:8000 \
  -v kreuzberg-cache:/app/.kreuzberg \
  ghcr.io/kreuzberg-dev/kreuzberg:latest-core \
  serve --host 0.0.0.0 --port 8000

kreuzberg serve --host 0.0.0.0 --port 8000

Then configure Open WebUI using one of the two engine modes below.

Choosing an engine mode

Kreuzberg exposes two Open WebUI–compatible APIs. Both return the same extracted content. So pick whichever fits your setup.

Docling (recommended) External
Endpoint POST /v1/convert/file PUT /process
Engine setting docling external
URL variable DOCLING_SERVER_URL EXTERNAL_DOCUMENT_LOADER_URL

Set these environment variables on the Open WebUI container:

environment:
  CONTENT_EXTRACTION_ENGINE: "docling"
  DOCLING_SERVER_URL: "http://kreuzberg:8000"

Or via the Admin UI: Settings → Documents → Content Extraction Engine → select Docling → set server URL to http://kreuzberg:8000.

Set these environment variables on the Open WebUI container:

environment:
  CONTENT_EXTRACTION_ENGINE: "external"
  EXTERNAL_DOCUMENT_LOADER_URL: "http://kreuzberg:8000"

Or via the Admin UI: Settings → Documents → Content Extraction Engine → select External → set URL to http://kreuzberg:8000.

Tip

If Kreuzberg runs on a different host or port, replace http://kreuzberg:8000 with the actual address. Inside Docker Compose, use the service name (kreuzberg). Outside Docker, use the host IP or localhost.

Verify it works

Test the endpoints directly before debugging through Open WebUI.

curl -s -F "files=@invoice.pdf" http://localhost:8000/v1/convert/file | jq .
Expected response
{
  "document": {
    "md_content": "# Invoice\n\nDate: 2026-01-15\n..."
  },
  "status": "success"
}

curl -s -X PUT \
  -H "Content-Type: application/pdf" \
  -H "X-Filename: invoice.pdf" \
  --data-binary @invoice.pdf \
  http://localhost:8000/process | jq .
Expected response
{
  "page_content": "# Invoice\n\nDate: 2026-01-15\n...",
  "metadata": {
    "source": "invoice.pdf"
  }
}

If the endpoint returns extracted text, the integration is working. Upload a document through Open WebUI to confirm end-to-end.

Next steps