Files
ai-resume/content/ai/l3/ai-rag-corpus.md
Sam Rolfe a76882de67 visuals: technology marks, area icons, client wall, two diagrams
Phase 7 (AUD-149), cheapest first.

- internal/brand: vendored Simple Icons path data (CC0) for 50 marks, looked up
  by the technology label the content already uses. Inline SVG, 16 px,
  currentColor, no request and no font. tools/gen_brand_icons.sh regenerates it.
- Six hand-drawn area icons replace the two-letter badges in the nav and on the
  landing cards; the evidence index gets a seventh.
- TechChips renders a mark where one exists and plain text where one does not,
  so a missing icon reads as a decision rather than a broken image.
- Client wall: 45 names as one typeface, one size, one grid of equal tiles, and
  the reason for no logo collage written on the page. No mark invented.
- Two diagrams, authored in-repo: homelab topology (platform-network.md) and
  the RAG pipeline (ai-rag-corpus.md), each referenced from the page it explains.
- Content images now carry intrinsic width/height, loading="lazy" and
  decoding="async" at render time; a site test fails the build if an image
  ships without them.
- Topbar is two rows at desktop: the area names plus marks no longer overlap the
  search form (Lighthouse target-size was failing at 1440 px).
- Favicon, so the browser stops requesting a missing /favicon.ico.

Satisfies: logos on every area page, area icons in nav and cards, two diagrams
referenced from their pages, images sized and lazy, Lighthouse >= 95 held.

(cherry picked from commit a473e4738a3751418c2097df2bcf0568fb6d0208)
2026-10-28 15:56:11 +11:00

2.0 KiB
Raw Blame History

id, area, level, title, claim, confidence, period, tech, metrics, artefacts, public, last_verified, tags
id area level title claim confidence period tech metrics artefacts public last_verified tags
ai-rag-corpus ai 3 Artefact — Retrieval corpus and query graph Retrieval is filtered by metadata before it searches — a tagged corpus · a four-node LangGraph query graph · and a deliberate replacement of ChromaDB with Qdrant. running 2020–
Qdrant
LangGraph
Prefect
n8n
ChromaDB
label value
retrieval stores used over time 2
true 2026-10-26
ai
retrieval
rag
artefact

Ingest and index are live; the diagram below shows both sides, and the query path is labelled as the design it is until Phase 5 ships.

What the artefact is

The ingest and query path: documents are chunked and tagged with metadata at ingest, stored in Qdrant, and filtered on that metadata before a similarity search runs. The LangGraph graph has four nodes; the fourth decides whether the answer can be given from what was retrieved.

What it proves

Retrieval designed around payload filtering and a hard stop, plus the reasoning for moving off ChromaDB — heavier footprint and weaker filtering — recorded as a decision rather than a migration.

The pipeline

Two lanes. Ingest reads the content tree and estate notes, excludes secrets, chunks and tags every block, then embeds through the model gateway and upserts into the resume_corpus and resume_graph collections in Qdrant. The query lane runs classify, route, retrieve, compose and verify, and only composes from retrieved context.

The separating line is the design decision: metadata is written at ingest, so the query can filter by area, level and source before it pays for a similarity search. The fourth node is the hard stop — an answer that cannot be supported by what was retrieved is refused rather than improvised.

When it is delivered

Ingest is delivered and measured (this site's own corpus, Phase 4). The query path is delivered in Phase 5; the streaming console is the visitor-facing half of it.