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breakpilot-compliance/admin-compliance/app/api/sdk/compliance-advisor/chat/route.ts
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fix(llm): qwen3.5 think:false + num_ctx 8192 in allen Chat/Draft-Routen
Compliance Advisor, Drafting Agent und Validator haben nicht geantwortet
weil qwen3.5 standardmaessig im Thinking-Mode laeuft (interne Chain-of-
Thought > 2min Timeout). Keiner der Agenten benoetigt Thinking-Mode —
alle Aufgaben sind Chat/Textgenerierung/JSON-Validierung ohne tiefes
Reasoning. think:false sorgt fuer direkte schnelle Antworten.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-03-06 08:35:53 +01:00

249 lines
7.9 KiB
TypeScript

/**
* Compliance Advisor Chat API
*
* Connects the ComplianceAdvisorWidget to:
* 1. Multi-Collection RAG search (rag-service) for context across 6 collections
* 2. Ollama LLM (32B) for generating answers
*
* Supports country-specific filtering (DE, AT, CH, EU).
* Streams the LLM response back as plain text.
*/
import { NextRequest, NextResponse } from 'next/server'
import { readSoulFile } from '@/lib/sdk/agents/soul-reader'
const RAG_SERVICE_URL = process.env.RAG_SERVICE_URL || 'http://rag-service:8097'
const OLLAMA_URL = process.env.OLLAMA_URL || 'http://host.docker.internal:11434'
const LLM_MODEL = process.env.COMPLIANCE_LLM_MODEL || 'qwen2.5vl:32b'
// All compliance-relevant collections (without NiBiS)
const COMPLIANCE_COLLECTIONS = [
'bp_compliance_gesetze',
'bp_compliance_ce',
'bp_compliance_datenschutz',
'bp_dsfa_corpus',
'bp_compliance_recht',
'bp_legal_templates',
] as const
type Country = 'DE' | 'AT' | 'CH' | 'EU'
// Fallback SOUL prompt (used when .soul.md file is unavailable)
const FALLBACK_SYSTEM_PROMPT = `# Compliance Advisor Agent
## Identitaet
Du bist der BreakPilot Compliance-Berater. Du hilfst Nutzern des AI Compliance SDK,
Datenschutz- und Compliance-Fragen in verstaendlicher Sprache zu beantworten.
## Kernprinzipien
- Quellenbasiert: Verweise auf DSGVO-Artikel, BDSG-Paragraphen
- Verstaendlich: Einfache, praxisnahe Sprache
- Ehrlich: Bei Unsicherheit empfehle Rechtsberatung
- Deutsch als Hauptsprache`
const COUNTRY_LABELS: Record<Country, string> = {
DE: 'Deutschland',
AT: 'Oesterreich',
CH: 'Schweiz',
EU: 'EU-weit',
}
interface RAGSearchResult {
content: string
source_name?: string
source_code?: string
attribution_text?: string
score: number
collection?: string
metadata?: Record<string, unknown>
}
/**
* Query multiple RAG collections in parallel, with optional country filter
*/
async function queryMultiCollectionRAG(query: string, country?: Country): Promise<string> {
try {
const searchPromises = COMPLIANCE_COLLECTIONS.map(async (collection) => {
const searchBody: Record<string, unknown> = {
query,
collection,
top_k: 3,
}
// Apply country filter for gesetze collection
if (collection === 'bp_compliance_gesetze' && country && country !== 'EU') {
searchBody.metadata_filter = {
must: [
{
key: 'country',
match: { any: [country, 'EU'] },
},
],
}
}
const res = await fetch(`${RAG_SERVICE_URL}/api/v1/search`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(searchBody),
signal: AbortSignal.timeout(10000),
})
if (!res.ok) return []
const data = await res.json()
return (data.results || []).map((r: RAGSearchResult) => ({
...r,
collection,
}))
})
const settled = await Promise.allSettled(searchPromises)
const allResults: RAGSearchResult[] = []
for (const result of settled) {
if (result.status === 'fulfilled') {
allResults.push(...result.value)
}
}
// Sort by score descending, take top 8
allResults.sort((a, b) => b.score - a.score)
const topResults = allResults.slice(0, 8)
if (topResults.length === 0) return ''
return topResults
.map((r, i) => {
const source = r.source_name || r.source_code || 'Unbekannt'
return `[Quelle ${i + 1}: ${source}]\n${r.content || ''}`
})
.join('\n\n---\n\n')
} catch (error) {
console.warn('Multi-collection RAG query error (continuing without context):', error)
return ''
}
}
export async function POST(request: NextRequest) {
try {
const body = await request.json()
const { message, history = [], currentStep = 'default', country } = body
if (!message || typeof message !== 'string') {
return NextResponse.json({ error: 'Message is required' }, { status: 400 })
}
// Validate country parameter
const validCountry = ['DE', 'AT', 'CH', 'EU'].includes(country) ? (country as Country) : undefined
// 1. Query RAG across all collections
const ragContext = await queryMultiCollectionRAG(message, validCountry)
// 2. Build system prompt with RAG context + country
const soulPrompt = await readSoulFile('compliance-advisor')
let systemContent = soulPrompt || FALLBACK_SYSTEM_PROMPT
if (validCountry) {
const countryLabel = COUNTRY_LABELS[validCountry]
systemContent += `\n\n## Laenderspezifische Auskunft
Der Nutzer hat "${countryLabel} (${validCountry})" gewaehlt.
- Beziehe dich AUSSCHLIESSLICH auf ${validCountry}-Recht + anwendbares EU-Recht
- Nenne IMMER explizit das Land in deiner Antwort
- Verwende NIEMALS Gesetze eines anderen Landes
- Bei ${validCountry === 'EU' ? 'EU-weiten Fragen: Beziehe dich auf EU-Verordnungen und -Richtlinien' : `${countryLabel}: Beziehe nationale Gesetze (${validCountry === 'DE' ? 'BDSG, TDDDG, TKG, UWG' : validCountry === 'AT' ? 'AT DSG, ECG, TKG, KSchG, MedienG' : 'CH DSG, DSV, OR, UWG, FMG'}) mit ein`}`
}
if (ragContext) {
systemContent += `\n\n## Relevanter Kontext aus dem RAG-System\n\nNutze die folgenden Quellen fuer deine Antwort. Verweise in deiner Antwort auf die jeweilige Quelle:\n\n${ragContext}`
}
systemContent += `\n\n## Aktueller SDK-Schritt\nDer Nutzer befindet sich im SDK-Schritt: ${currentStep}`
// 3. Build messages array (limit history to last 6 messages)
const messages = [
{ role: 'system', content: systemContent },
...history.slice(-6).map((h: { role: string; content: string }) => ({
role: h.role === 'user' ? 'user' : 'assistant',
content: h.content,
})),
{ role: 'user', content: message },
]
// 4. Call Ollama with streaming
const ollamaResponse = await fetch(`${OLLAMA_URL}/api/chat`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model: LLM_MODEL,
messages,
stream: true,
think: false,
options: {
temperature: 0.3,
num_predict: 8192,
num_ctx: 8192,
},
}),
signal: AbortSignal.timeout(120000),
})
if (!ollamaResponse.ok) {
const errorText = await ollamaResponse.text()
console.error('Ollama error:', ollamaResponse.status, errorText)
return NextResponse.json(
{ error: `LLM nicht erreichbar (Status ${ollamaResponse.status}). Ist Ollama mit dem Modell ${LLM_MODEL} gestartet?` },
{ status: 502 }
)
}
// 5. Stream response back as plain text
const encoder = new TextEncoder()
const stream = new ReadableStream({
async start(controller) {
const reader = ollamaResponse.body!.getReader()
const decoder = new TextDecoder()
try {
while (true) {
const { done, value } = await reader.read()
if (done) break
const chunk = decoder.decode(value, { stream: true })
const lines = chunk.split('\n').filter((l) => l.trim())
for (const line of lines) {
try {
const json = JSON.parse(line)
if (json.message?.content) {
controller.enqueue(encoder.encode(json.message.content))
}
} catch {
// Partial JSON line, skip
}
}
}
} catch (error) {
console.error('Stream read error:', error)
} finally {
controller.close()
}
},
})
return new NextResponse(stream, {
headers: {
'Content-Type': 'text/plain; charset=utf-8',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
},
})
} catch (error) {
console.error('Compliance advisor chat error:', error)
return NextResponse.json(
{ error: 'Verbindung zum LLM fehlgeschlagen. Bitte pruefen Sie ob Ollama laeuft.' },
{ status: 503 }
)
}
}