DepressionCenter / DepressionCenter/extractium

Enrichment pass with a local language model

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enhancement
Dominant language
Python
Stars
1
Forks
1
Avg merge
1h 47m
Merged PRs (30d)
46

Description

Section 10 of `docs/extractium-spec.md` describes a deferred enrichment step: a small local instruct model, GPU-gated, delta-only, and parent-only, populating the reserved nullable fields (`summary`, `tags`, `keywords`, `enriched_at`, `enrich_ver`) through a `.kb_cache/enrichment/` layer, with no API calls ever. The fields are reserved in the container format and every adapter writes them when present and skips them when null, so the format needs no change.

Keyword extraction without a language model (YAKE plus embedding-similarity keywords) may ship earlier as a separate step, and would be a smaller first phase. Either way, plan it as a phase in `docs/implementation-plan.md` before building.

Contributor guide

No contributing guide indexed for this repository

Research direction

Read Section 10 of docs/extractium-spec.md and inspect docs/implementation-plan.md first. Document the enrichment phase, including the GPU gate, delta-only and parent-only scope, reserved nullable fields, .kb_cache/enrichment/ layer, and no-API constraint; clarify whether YAKE and embedding-similarity keywords are a separate earlier phase. Done means the implementation plan records an agreed sequence and boundaries before coding begins.

Written by the indexing model from the issue text.

Assessment

Domain
ai, documentation
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
45/100

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