97840e25ab
7 curated knowledge cards extracted from RFCs and docs: - architecture: core pipeline, extension points, process isolation - sense: compute behavior, Sense→Workflow, config - workflow: engine, threads, WorkflowSpec - adapter: AgentFn protocol, available adapters, extract layer - coding-conventions: functional-first, Result type, naming - monorepo: package structure, dependency rules - knowledge-layer: sync/query CLI, embedding service knowledge.yaml indexes .knowledge/**/*.md only.
1.2 KiB
1.2 KiB
Knowledge Layer (RFC-003 Phase 6)
Local-first, repo-scoped knowledge base for project context.
Files
knowledge.yaml— repo root, defines include/exclude globsknowledge.db— SQLite, stores chunks + embeddings.knowledge/— curated knowledge cards (indexed by sync)
Commands
nerve knowledge sync # chunk files, compute embeddings, write to knowledge.db
nerve knowledge query "query" # search by cosine similarity (or word overlap fallback)
nerve knowledge query -g "query" # global search across all indexed repos
nerve knowledge query --repo /path "query" # search specific repo
Embedding
- Remote service:
embed.shazhou.workers.dev(Cloudflare Worker + KV cache) - Model: Dashscope text-embedding-v3 (1024 dims)
- Cache: content-addressable (sha256 of model+text), never expires
- Fallback: word-overlap scoring when embed service not configured
Chunking
- Markdown: split by headings, large sections split further by paragraphs (max 24)
- TypeScript/JS: split by function declarations, fallback to paragraphs
- Other files: single chunk
Env Config
EMBED_SERVICE_URL=https://embed.shazhou.workers.dev
EMBED_AUTH_TOKEN=<token>