feat: Phase 2 — RAG integration in Requirements + DSFA Draft

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>

admin-compliance/app/api/sdk/drafting-engine/draft/route.ts

@@ -31,6 +31,7 @@ import { sanitizeAllowedFacts, validateNoRemainingPII, SanitizationError } from
 import { terminologyToPromptString, styleContractToPromptString } from '@/lib/sdk/drafting-engine/terminology'
 import { executeRepairLoop, type ProseBlockOutput, type RepairAudit } from '@/lib/sdk/drafting-engine/prose-validator'
 import { ProseCacheManager, computeChecksumSync, type CacheKeyParams } from '@/lib/sdk/drafting-engine/cache'
+import { queryRAG } from '@/lib/sdk/drafting-engine/rag-query'
 
 // ============================================================================
 // Shared State
@@ -103,9 +104,20 @@ async function handleV1Draft(body: Record<string, unknown>): Promise<NextRespons
     }, { status: 403 })
   }
 
+  // RAG: Fetch relevant legal context
+  const ragQuery = documentType === 'dsfa'
+    ? 'Datenschutz-Folgenabschaetzung Art. 35 DSGVO Risikobewertung'
+    : `${documentType} DSGVO Compliance Anforderungen`
+  const ragContext = await queryRAG(ragQuery)
+
+  let v1SystemPrompt = V1_SYSTEM_PROMPT
+  if (ragContext) {
+    v1SystemPrompt += `\n\n## Relevanter Rechtskontext\n${ragContext}`
+  }
+
   const draftPrompt = buildPromptForDocumentType(documentType, draftContext, instructions)
   const messages = [
-    { role: 'system', content: V1_SYSTEM_PROMPT },
+    { role: 'system', content: v1SystemPrompt },
     ...(existingDraft ? [{
       role: 'assistant',
       content: `Bisheriger Entwurf:\n${JSON.stringify(existingDraft.sections, null, 2)}`,
@@ -368,6 +380,12 @@ async function handleV2Draft(body: Record<string, unknown>): Promise<NextRespons
   // Compute prompt hash for audit
   const promptHash = computeChecksumSync({ factsString, tagsString, termsString, styleString, disallowedString })
 
+  // Step 5b: RAG Legal Context
+  const v2RagQuery = documentType === 'dsfa'
+    ? 'DSFA Art. 35 DSGVO Risikobewertung Massnahmen Datenschutz-Folgenabschaetzung'
+    : `${documentType} DSGVO Compliance`
+  const v2RagContext = await queryRAG(v2RagQuery)
+
   // Step 6: Generate Prose Blocks (with cache + repair loop)
   const proseBlocks = DOCUMENT_PROSE_BLOCKS[documentType] || DOCUMENT_PROSE_BLOCKS.tom
   const generatedBlocks: ProseBlockOutput[] = []
@@ -399,12 +417,15 @@ async function handleV2Draft(body: Record<string, unknown>): Promise<NextRespons
     }
 
     // Build prompts
-    const systemPrompt = buildV2SystemPrompt(
+    let systemPrompt = buildV2SystemPrompt(
       factsString, tagsString, termsString, styleString, disallowedString,
       sanitizedFacts.companyName,
       blockDef.blockId, blockDef.blockType, blockDef.sectionName,
       documentType, blockDef.targetWords
     )
+    if (v2RagContext) {
+      systemPrompt += `\n\nRECHTSKONTEXT (als Referenz, nicht woertlich uebernehmen):\n${v2RagContext}`
+    }
     const userPrompt = buildBlockSpecificPrompt(
       blockDef.blockType, blockDef.sectionName, documentType
     ) + (instructions ? `\n\nZusaetzliche Anweisungen: ${instructions}` : '')