Add legal context enrichment from Qdrant vector corpus to the two
highest-priority modules (Requirements AI assistant and DSFA drafting
engine).
Go SDK:
- Add SearchCollection() with collection override + whitelist validation
- Refactor Search() to delegate to shared searchInternal()
Python backend:
- New ComplianceRAGClient proxying POST /sdk/v1/rag/search (error-tolerant)
- AI assistant: enrich interpret_requirement() and suggest_controls() with RAG
- Requirements API: add ?include_legal_context=true query parameter
Admin (Next.js):
- Extract shared queryRAG() utility from chat route
- Inject RAG legal context into v1 and v2 draft pipelines
Tests for all three layers (Go, Python, TypeScript shared utility).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
