deepset-ai / deepset-ai/haystack-core-integrations
Add new Gotenberg Integration
@sjrl is already working on this.
Since Aug 23, 2026.
- Dominant language
- Python
- Stars
- 203
- Forks
- 332
- Avg merge
- 2d 4h
- Merged PRs (30d)
- 80
Description
Summary and motivation
Add a Gotenberg integration for remotely converting Office, OpenDocument, HTML, Markdown, and other supported formats into PDFs for ingestion in Haystack pipelines.
This provides a production-friendly alternative to the LibreOffice integration, allowing document conversion to be deployed and scaled as a separate service.
Adoption signals
Every integration we merge has to be maintained, tested nightly, and released, so we prioritise integrations for
technologies with a healthy and growing user base. Please share adoption signals for the software you want to integrate with. The more info you provide, the easier it is for us to decide.
- GitHub stars of the main repository: 12.9k
- PyPI downloads in the last 30 days of the Python client/SDK (see pypistats.org): N/A as gotenburg is a docker container - ~7.7 million pulls per month
- Release activity: date of the latest release and rough release cadence: v8.36.0 released in August 2026; releases are frequent, typically every few weeks.
- Maintenance: Actively maintained, with regular releases, commits, issue activity, and security fixes.
- Haystack community demand: links to Discord threads, GitHub issues, or other requests asking for this
integration: This is the first issue. - Anything else that shows adoption (enterprise usage, conference talks, blog posts, comparable integrations in
other frameworks): Gotenberg reports 82M+ Docker pulls and states that it is used in production by thousands of companies.
Detailed design
Introduce a GotenbergFileConverter component configured with a Gotenberg endpoint.
The component should accept Haystack-compatible Path and ByteStream sources and:
- Send supported Office/OpenDocument files to Gotenberg's LibreOffice conversion endpoint.
- Support Chromium conversion for formats such as HTML and Markdown where appropriate.
- Parse the resulting PDF into Haystack Document objects using Haystack's existing PDF conversion functionality.
- Preserve source metadata and support both
runandrun_async.
Checklist
If the request is accepted, ensure the following checklist is complete before closing this issue.
Follow the instructions in https://github.com/deepset-ai/haystack-core-integrations/blob/main/CONTRIBUTING.md#create-a-new-integration and use our scaffolding script for the implementation.
Tasks
- The code is documented with docstrings and was merged in the
mainbranch - Docs are published at https://docs.haystack.deepset.ai/
- There is a Github workflow running the tests for the integration nightly and at every PR
- A new label named like
integration:<your integration name>has been added to the list of labels for this repository - The labeler.yml file has been updated
- The package has been released on PyPI
- An integration tile with a usage example has been added to https://github.com/deepset-ai/haystack-integrations
- The integration has been listed in the Inventory section of this repo README
- The feature was announced through social media
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Assessment
This issue has not been assessed yet.