Purpose and audience The tool extracts and indexes document content in Qdrant, plans an outline and researches each section against the local collection.
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How Jev fits Jev judges and reranks retrieved chunks and scores missing coverage; a separate LLM plans, queries and writes while Python controls retries.
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Using the project Supply a topic, outline and resource directory through the CLI; default configuration needs OpenAI and TypeSafe keys and saves reports in output_folder.
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Scope and limits Jev thresholds are starting points to validate on your documents. Section writing can begin when the configured retry limit is reached.
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Evidence checked: Sep 30, 2026
Project facts
Relationship to Jev Jev application
Evidence Documented
Language Python
License MIT
Origin Original repository
Repository status Not archived
Created 2025-08-15
Last code update 2026-09-26
GitHub stars 305
Evidence checked Sep 30, 2026
Metadata checked Sep 28, 2026
Check status Up to date Stars measure the whole repository, including work unrelated to Jev.
Evidence and scope Documented records the linked documentation or source. JevHunt has not independently run or benchmarked this project.
Evidence commit: 42c8758292cacb619680bde23f77826f0419c4f2
Discovered through: github-search.
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