learning_ai_clock/backend
saravanakumardb1 229ce4f00f feat(backend): wire Ollama LLM for context messages (TODO-005)
Dual-path LLM enrichment for AI context prep messages:
1. extraction-service (if EXTRACTION_SERVICE_URL set)
2. Ollama direct (if OLLAMA_URL set) — non-streaming /api/generate
3. Keyword rules fallback
4. Generic fallback

New env vars: OLLAMA_URL, OLLAMA_MODEL (default: gemma3:4b)
Both LLM paths use 5s timeout and null-return-on-error pattern.
Feature-gated behind ai_context_messages.enabled flag.
2026-04-13 17:00:24 -07:00
..
src feat(backend): wire Ollama LLM for context messages (TODO-005) 2026-04-13 17:00:24 -07:00
.env.example fix(backend): harden Phase A endpoints — Zod validation, feature flag gate, state filtering 2026-03-31 23:56:35 -07:00
.gitignore feat(backend): scaffold product-specific Fastify backend (port 4011) 2026-03-01 20:39:08 -08:00
Dockerfile fix(docker): .docker-deps COPY + optional secret + .npmrc.docker simplification 2026-04-13 14:05:54 -07:00
eslint.config.js chore(backend): add eslint config and lint script 2026-03-26 22:59:50 -07:00
package.json feat(backend): add domain event bus + webhook dispatch 2026-04-13 11:28:38 -07:00
tsconfig.json feat(backend): scaffold product-specific Fastify backend (port 4011) 2026-03-01 20:39:08 -08:00
vitest.config.ts feat(backend): scaffold product-specific Fastify backend (port 4011) 2026-03-01 20:39:08 -08:00