- adapters/huggingface.py: HF API adapter (models + datasets)
- Dual fetch: sort=likes (popularity) + sort=lastModified (fresh)
- AI relevance filter: pipeline_tag, library_name, tag matching
- Score: adoption (likes/downloads log-scale) + relevance (pipeline/library/tags)
- score_type: actual (real likes/downloads from HF API)
- Cross-source signal: GLM-5.2 top on both HN and HF
- Wired into ENABLED_SOURCES + verification in pipeline.py
- Live verify: DB likes match live API exactly (GLM-5.2: 3607, DeepSeek-R1: 13448)
- 99 total entries across 5 sources, all pipeline green
- adapters/hackernews.py: HN Firebase API adapter with AI keyword filtering
- Word-boundary matching to avoid substring traps (Britain/Guinea)
- Score: log(points) + log(comments), actual HN scores
- Wired into ENABLED_SOURCES + verification in pipeline.py
- Live test: 10 AI/ML stories fetched, all clean
- oracle-pipeline.sh: single cron entry point (pipeline -> summarize -> archive)
- archive.py: soft-cap archival to entries_archive (preserve, not delete)
- pipeline.py: record zero-fetch (rate-limited) runs as degraded in run_log.notes
Verified: full script runs exit 0, run_log captures per-source status.
Epictetus