deepset-ai / deepset-ai/haystack-core-integrations

New Converter Integration: OpenDataLoader PDF

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#3,693 3 comments 0 reactions 1 assignee View on GitHub

@kacperlukawski is already working on this.

Since Aug 27, 2026.

new integration P3
Dominant language
Python
Stars
203
Forks
332
Avg merge
2d 4h
Merged PRs (30d)
80

Description

Summary and motivation

OpenDataLoader PDF is a widely used PDF parser to prepare extract information to be used in AI/RAG systems. Currently no integration exists for haystack, but one does for langchain.

Detailed design

Create new OpenDataLoaderConverter that acts an interface supporting, input file paths (must be pdfs) as well as haystack ByteStream's and that returns list[Document]. This new component, should support various OpenDataLoader options, including modes and extraction settings.

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
  • An integration tile with a usage example has been added to https://github.com/deepset-ai/haystack-integrations
  • Docs are published at https://docs.haystack.deepset.ai/
  • The code is documented with docstrings and was merged in the main branch
  • 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
  • The integration has been listed in the Inventory section of this repo README
  • The feature was announced through social media

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Assessment

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