Readability already reads og:site_name and JSON-LD publisher.name; carry
that through Page and Extracted and store it in articles.publication, the
same way the page byline is kept. `publication_label` is what the readers
will see after the feed name: the site name, else the domain, and nothing
when it would only repeat the feed's own title.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01YWmCpUojfHXhSZ2129Z7Nv
The article dashboard page gains a "Nearest articles (any)" table: the
ten closest stored embeddings by cosine, regardless of rating or run,
via a brute-force scan of article_embeddings. The deep-assessment format
facet grows from 5 to 14 values (code_repository, documentation_reference,
tool_or_product_page, discussion_thread, paper_or_report,
interview_or_transcript, video_or_podcast, fiction_or_humor, other) and
the triage kind from 10 to 16 (repo, docs, discussion, paper, media,
fiction), so a GitHub repository is no longer forced into analysis_essay.
Both prompt versions bump to 2.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01QVPagF6jfDv78CC5Jv2wp4
DeepSeek's content filter rejects a whole request (400 "Content Exists
Risk") when one article trips it, which cost the other articles in the
batch their assessment and retried them every run. New curate/batch.rs
runs both stages through a bisecting runner: a rejected batch is split
until the offending article is isolated, that article is retried once on
the editor provider when it is a different one, and a still-rejected
article is recorded as a provider_rejected assessment row so it is not
retried for assessment_reuse_days. Cache reuse accepts rows from either
configured model. Each stage logs reused/requested/rejected counts, the
curation: line shows rejections when non-zero, explain prints them, and
the llm_assess span reports the deep-set size.
Implemented by a Claude agent from an orchestrator brief; verified
fmt/clippy(-W dead_code)/test green (354 lib tests).
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A1rCLQeKBgnBo3oTgHuTMe
- embedding.rs: EmbeddingBackend + VoyageBackend, batched bounded-concurrency
client with its own UsageMeter, f32 BLOB codec, article/interest embedding
cache keyed by model, dimension and sha256 of the embedded text.
- signals.rs: z-scored interest match, decayed rated-neighbour preference
with the knn gate, feed affinity with the feed gate, social, text heuristic
without social terms, mid-rank percentile normalizer, preliminary blend.
- telemetry.rs: candidate_runs writer with §7.5 signals_json, explain and
near-misses renderers, prune.
- [voyage] and the full [curation.ranking] config with validation.
- CLI: explain, features backfill|prune, generate --skip-embeddings.
- Pipeline: hygiene rows, embed and signals stages before the old prefilter;
same-date regeneration no longer excludes its own picks.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01A1rCLQeKBgnBo3oTgHuTMe
thalladaandClaude Fable 5.1