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DeepDoc

Local deep-research tool where Jev reranks Qdrant chunks and checks evidence coverage per report section before an LLM writes it; project has 305 GitHub stars (author).

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The source publishes no measured number.
Use
Search, ranking and matching
Industry
Education and research
Form
Open-source tool
Stage
Beta
Plugs into
Qdrant
Listed
2026-09-26
Found via
github
Repository
Oqura-ai/deepdoc
Stars
312
Forks
47
Last push
2026-09-26
Language
Python
License
MIT
DeepDoc screenshot
assets/workflow.png in the Oqura-ai/deepdoc README, MIT; shown from GitHub.

The README opens with

Oqura's deepdoc is a local deep-research tool that turns your own files into a structured Markdown report. It extracts and indexes the content, plans the report, researches every section against the local collection, and combines the results into one final document.

DeepDoc uses TypeSafe's Jev model to improve the research process without replacing the generative LLM. Jev checks and reranks the chunks returned by Qdrant, then checks whether the collected evidence covers every required subsection. The configured LLM still handles planning, query generation, synthesis, and report writing, while Python uses Jev's probabilities to make explicit filtering and retry decisions.

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For the project's own README, linking back here:

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