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Paul Szabo edited this page Jun 28, 2026 · 12 revisions

The goal of this project is to stand up a self-hosted pipeline for "deep research".

Some assembly required

The parts to be assembled are:

  • Self-hosted "AI" (LLM) (Ollama in this case, which can expose OpenAI compliant models, provided you have the required hardware resources)
  • Workflow management platform (Apache Airflow), which contains modules to connect to your chosen model, any external tools, "skills", etc.
  • Directed acyclic graphs (pipelines), or workflows which are a representation in code (Python)

Why bother?

The pattern shared by mmajurski/(U.S.) NIST in the repo this project was forked from contains an example.py. You run this from a terminal. It generates a report.md containing the (annotated) resulted "deep research", along with citations in a separate file. Everything is designed to be machine readable.

The value of the shared pattern is that it contains everything required to do a whole lot more ..what that means to you is an exercise left to the reader.

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