christian/grant-outreach-engine
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity
Files
master
grant-outreach-engine/packages/outreach-ai/README.md
Croissant Le Doux 14200edb60 feat: scaffold outreach engine monorepo on the novelpad-desktop stack 
Workspaces: config (copied), outreach-core (schema + actions/queries +
hard gates), outreach-ai (Gemini client + embeddings copies, profiler and
mission-fit-judge agent stubs), outreach-worker (DBOS executor with
nightly ingest + hourly expiry workflows), outreach-review (RR7 review
queue v0). Initial drizzle migration incl. pgvector extension.

Stack contract: Yarn 4.5.0 + Turbo, Node 22.16, Drizzle 0.44.6 +
pgvector, DBOS 4.17.6, @google/genai on Vertex, gemini-embedding-001
@1536, React Router v7. Files copied from novelpad-desktop carry
provenance headers @ 62c56b87.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-07-16 11:08:24 -04:00

2.7 KiB
Raw Permalink Blame History

@novelpad/outreach-ai

LLM access layer for the HelmDocs grant-match outreach engine. Modeled on novelpad-desktop's packages/ai, trimmed to what this engine needs: a Vertex/Gemini client, an embeddings helper, model-tier constants, and two structured-output agents (org profiler, mission-fit judge).

Provenance

src/gemini.ts and src/embeddings.ts are copied near-verbatim from novelpad-desktop at commit 62c56b87 (see the header comment in each file for the exact source path). They are kept as close to the original as compiles standalone in this workspace — do not "clean up" drift between them and the source without checking whether the source has moved on too.

src/agents/*/run.ts follow the structured-JSON-output pattern from novelpad-desktop's packages/ai/src/agents/grant/section-drafter/run.ts (prompt builder + generateContent with responseMimeType: 'application/json' and a hand-written responseSchema), but are new code for this repo's domain, not copies — both are currently NOT IMPLEMENTED stubs pending the source-fetching / hard-gate scoring infrastructure they depend on. Each stub's doc comment shows the intended call shape.

Never mix embedding models

generateQueryEmbedding / generateDocumentEmbedding / generateDocumentEmbeddings are pinned to gemini-embedding-001 at outputDimensionality: 1536. Do not change either value, and do not add a second embedding model/dimensionality into this package. Every vector this package produces has to remain comparable (same model, same dimensionality) against every other vector already stored in the HelmDocs RAG index — switching models or dimensions silently corrupts similarity search for anything embedded before the switch, with no error at write time. If a better embedding model becomes available, that's a deliberate, full-reindex migration, not a constant change here.

Model tiering

See src/models.ts: BULK_MODEL (gemini-2.5-flash) for high-volume mechanical work (classification, effort estimates, first-pass org-profile extraction); JUDGE_MODEL (gemini-2.5-pro) for anything a wrong answer could put in front of a real prospect (mission-fit judge, email personalization QA).

Layout

  • src/gemini.ts — getAi() Vertex client singleton + CHAT_MODEL.
  • src/embeddings.ts — query/document embedding helpers.
  • src/models.ts — BULK_MODEL / JUDGE_MODEL constants.
  • src/agents/org-profiler/ — OrgProfileSchema (per-field source URL + confidence) and the profiler agent stub.
  • src/agents/mission-fit-judge/ — MissionFitVerdictSchema (fit, citedOrgProgram, citedGrantPriority, reasoning) and the judge agent stub.
  • src/index.ts — barrel export.