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Die Drafting-Engine (Dokument-Entwurf, v2-Pipeline, Validierung, Drafting-Chat, Vendor-Vertragspruefung) war auf prod doppelt tot: - RAG ueber bp-core-rag-service:8097 (existiert auf prod nicht) - LLM ueber OLLAMA_URL/api/chat mit qwen2.5vl (prod = ollama-embed, kein Chat-Modell) Fix (analog zum Compliance-Advisor): - rag-query.ts -> ai-compliance-sdk /sdk/v1/rag/search (bge-m3, prod-erreichbar). - Neue lib/sdk/drafting-engine/llm-cascade.ts: OVH/LiteLLM (gpt-oss-120b) zuerst, Ollama als Dev-Fallback; cascadeComplete (JSON) + cascadeStream. Das Backend nutzt OVH+JSON bereits erfolgreich auf prod (extract-datasheet). - 5 Aufrufstellen (draft-helpers, draft-helpers-v2, validate, chat, vendor-review) auf die Kaskade umgestellt; keine direkten Ollama-Calls mehr. - Tests: llm-cascade + rag-query aktualisiert. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
211 lines
6.7 KiB
TypeScript
211 lines
6.7 KiB
TypeScript
/**
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* Gemeinsame LLM-Kaskade fuer die Drafting-Engine.
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*
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* Reihenfolge: OVH/LiteLLM (gpt-oss-120b) zuerst — der prod-Chat-LLM; Ollama als
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* Dev-Fallback. Auf prod ist OLLAMA_URL embedding-only (kein Chat-Modell), daher
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* ist OVH dort der einzige funktionierende Pfad — genau wie beim Compliance-Advisor
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* (siehe lib/sdk/agents/advisor-llm). Das Backend nutzt OVH + JSON-Output bereits
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* erfolgreich auf prod (extract-datasheet), dieselbe Technik wird hier gespiegelt.
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*/
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const OLLAMA_URL = process.env.OLLAMA_URL || 'http://host.docker.internal:11434'
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const OLLAMA_MODEL = process.env.COMPLIANCE_LLM_MODEL || 'qwen2.5vl:32b'
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const OVH_URL = (process.env.OVH_LLM_URL || '').replace(/\/+$/, '')
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const OVH_MODEL = process.env.OVH_LLM_MODEL || ''
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const OVH_KEY = process.env.OVH_LLM_KEY || ''
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export interface ChatMessage {
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role: string
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content: string
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}
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export interface CascadeOpts {
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json?: boolean
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maxTokens?: number
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temperature?: number
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timeoutMs?: number
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}
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export interface CascadeResult {
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content: string
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tokensUsed: number
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provider: 'ovh' | 'ollama'
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}
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// --- Stream-Parser (pure, testbar) ---
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/** Text-Delta aus einer Ollama-NDJSON-Zeile (message.content). */
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export function parseOllamaLine(line: string): string | null {
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const t = line.trim()
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if (!t) return null
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try {
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return JSON.parse(t)?.message?.content || null
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} catch {
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return null
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}
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}
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/** Text-Delta aus einer OpenAI/OVH-SSE-Zeile (choices[0].delta.content). */
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export function parseSSELine(line: string): string | null {
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const t = line.trim()
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if (!t.startsWith('data:')) return null
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const payload = t.slice(5).trim()
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if (!payload || payload === '[DONE]') return null
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try {
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return JSON.parse(payload)?.choices?.[0]?.delta?.content || null
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} catch {
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return null
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}
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}
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// --- Non-Streaming (cascadeComplete) ---
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async function ovhComplete(messages: ChatMessage[], o: CascadeOpts): Promise<CascadeResult | null> {
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if (!OVH_URL || !OVH_MODEL) return null
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try {
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const headers: Record<string, string> = { 'Content-Type': 'application/json' }
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if (OVH_KEY) headers['Authorization'] = `Bearer ${OVH_KEY}`
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const payload: Record<string, unknown> = {
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model: OVH_MODEL,
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messages,
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stream: false,
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temperature: o.temperature ?? 0.15,
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max_tokens: o.maxTokens ?? 4096,
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}
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if (o.json) payload.response_format = { type: 'json_object' }
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const r = await fetch(`${OVH_URL}/v1/chat/completions`, {
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method: 'POST',
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headers,
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body: JSON.stringify(payload),
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signal: AbortSignal.timeout(o.timeoutMs ?? 120000),
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})
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if (!r.ok) return null
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const d = await r.json()
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const content = d?.choices?.[0]?.message?.content || ''
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if (!content) return null
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const usage = d?.usage || {}
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return { content, tokensUsed: usage.completion_tokens ?? usage.total_tokens ?? 0, provider: 'ovh' }
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} catch {
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return null
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}
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}
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async function ollamaComplete(messages: ChatMessage[], o: CascadeOpts): Promise<CascadeResult | null> {
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try {
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const body: Record<string, unknown> = {
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model: OLLAMA_MODEL,
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messages,
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stream: false,
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think: false,
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options: { temperature: o.temperature ?? 0.15, num_predict: o.maxTokens ?? 4096, num_ctx: 8192 },
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}
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if (o.json) body.format = 'json'
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const r = await fetch(`${OLLAMA_URL}/api/chat`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(body),
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signal: AbortSignal.timeout(o.timeoutMs ?? 120000),
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})
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if (!r.ok) return null
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const d = await r.json()
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const content = d?.message?.content || ''
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if (!content) return null
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return { content, tokensUsed: d?.eval_count ?? 0, provider: 'ollama' }
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} catch {
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return null
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}
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}
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/**
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* Nicht-streamender LLM-Aufruf mit Kaskade. Liefert Inhalt + Token + Provider,
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* oder null wenn weder OVH noch Ollama antworten.
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*/
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export async function cascadeComplete(messages: ChatMessage[], opts: CascadeOpts = {}): Promise<CascadeResult | null> {
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return (await ovhComplete(messages, opts)) ?? (await ollamaComplete(messages, opts))
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}
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// --- Streaming (cascadeStream) ---
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const encoder = new TextEncoder()
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function textStream(upstream: Response, parseLine: (line: string) => string | null): ReadableStream<Uint8Array> {
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return new ReadableStream({
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async start(controller) {
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const reader = upstream.body!.getReader()
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const decoder = new TextDecoder()
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let buf = ''
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try {
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for (;;) {
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const { done, value } = await reader.read()
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if (done) break
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buf += decoder.decode(value, { stream: true })
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const lines = buf.split('\n')
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buf = lines.pop() || ''
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for (const line of lines) {
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const delta = parseLine(line)
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if (delta) controller.enqueue(encoder.encode(delta))
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}
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}
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const tail = parseLine(buf)
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if (tail) controller.enqueue(encoder.encode(tail))
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} finally {
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controller.close()
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}
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},
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})
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}
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async function ovhStream(messages: ChatMessage[], o: CascadeOpts): Promise<Response | null> {
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if (!OVH_URL || !OVH_MODEL) return null
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try {
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const headers: Record<string, string> = { 'Content-Type': 'application/json' }
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if (OVH_KEY) headers['Authorization'] = `Bearer ${OVH_KEY}`
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const r = await fetch(`${OVH_URL}/v1/chat/completions`, {
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method: 'POST',
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headers,
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body: JSON.stringify({
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model: OVH_MODEL,
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messages,
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stream: true,
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temperature: o.temperature ?? 0.3,
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max_tokens: o.maxTokens ?? 4096,
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}),
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signal: AbortSignal.timeout(o.timeoutMs ?? 120000),
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})
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return r.ok && r.body ? r : null
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} catch {
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return null
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}
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}
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async function ollamaStream(messages: ChatMessage[], o: CascadeOpts): Promise<Response | null> {
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try {
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const r = await fetch(`${OLLAMA_URL}/api/chat`, {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify({
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model: OLLAMA_MODEL,
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messages,
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stream: true,
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think: false,
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options: { temperature: o.temperature ?? 0.3, num_predict: o.maxTokens ?? 4096, num_ctx: 8192 },
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}),
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signal: AbortSignal.timeout(o.timeoutMs ?? 120000),
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})
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return r.ok && r.body ? r : null
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} catch {
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return null
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}
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}
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/**
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* Streamender LLM-Aufruf mit Kaskade -> Plain-Text-Stream. null = kein LLM erreichbar.
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*/
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export async function cascadeStream(messages: ChatMessage[], opts: CascadeOpts = {}): Promise<ReadableStream<Uint8Array> | null> {
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const ovh = await ovhStream(messages, opts)
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if (ovh) return textStream(ovh, parseSSELine)
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const ollama = await ollamaStream(messages, opts)
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if (ollama) return textStream(ollama, parseOllamaLine)
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return null
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}
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