my_voice_assistant_v3_jamulix/app/api/chat.py
Dieter Schlüter 68b02f42a1 feat(users): SSO-Nutzer-Personalisierung + Admin-Endpunkte
Hintergrund: SSO-Nutzer (va.linix.de) werden bereits beim ersten Besuch
automatisch registriert, hatten aber keinen echten Namen im LLM-Kontext
und konnten vom Admin nicht vorbereitet werden.

Änderungen:
- ws.py + chat.py: Nutzeridentität (display_name + Erinnerungen) wird als
  führende System-Message bei jeder Anfrage injiziert; für anonyme
  Dev-Nutzer (AUTH_ENABLED=false) wird diese Injection übersprungen
- store.py: update_display_name() im ABC und SQLiteStore
- schemas.py: UserUpdate (display_name)
- admin.py:
  - PUT /api/admin/users/{id}: Anzeigenamen eines SSO-Nutzers setzen
  - POST /api/admin/users/{id}/memories: initiale Erinnerungen vorbelegen
- BEDIENUNGSANLEITUNG §7.2: neuer Abschnitt "SSO-Nutzer — automatische
  Registrierung" mit vollständigem Workflow; §7.3/7.4 neu nummeriert;
  Anhang B.5 mit neuen Endpunkten ergänzt

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-06-18 17:55:05 +02:00

147 lines
5.2 KiB
Python

from io import BytesIO
from fastapi import APIRouter, Depends, HTTPException, Query
from fastapi.responses import JSONResponse, StreamingResponse
from app.config import settings
from app.errors import RoutingError
from app.auth import require_user
from app.store import ANONYMOUS_USER_ID, User, SessionOwnershipError
from app.dependencies import (
resolve_route,
build_orchestrator,
resolve_output_endpoint,
get_store,
)
from app.core.memory_extractor import maybe_schedule_extraction
from app.quota import enforce_quota, record_usage, QuotaExceededError
from app.safety.emergency import handle_emergency, schedule_llm_emergency_check
from app.schemas import ChatRequest
router = APIRouter()
def _route_headers(route) -> dict:
return {
"X-Input-Endpoint": route.input_endpoint,
"X-Output-Endpoint": route.output_endpoint,
"X-STT-Provider": route.stt_provider,
"X-LLM-Provider": route.llm_provider,
"X-TTS-Provider": route.tts_provider,
}
@router.post("/chat")
async def chat(
payload: ChatRequest,
debug: bool = Query(
default=False,
description="Return JSON trace instead of audio response",
),
session_id: str | None = Query(
default=None,
description="Optional session id to apply a stored route",
),
user: User = Depends(require_user),
):
overrides = {
"input_endpoint": payload.input_endpoint,
"output_endpoint": payload.output_endpoint,
"language": payload.language,
"stt_provider": payload.stt_provider,
"llm_provider": payload.llm_provider,
"tts_provider": payload.tts_provider,
}
# None -> der gewaehlte TTS-Provider nimmt seinen eigenen Default.
voice = payload.voice
store = get_store()
try:
route = resolve_route(user, session_id, overrides)
orchestrator = build_orchestrator(route)
output = await resolve_output_endpoint(route)
# Gespraechsverlauf laden (nur bei gesetzter session_id -> sonst zustandslos).
conversation = (
store.get_recent_messages(session_id, settings.history_max_messages)
if session_id
else []
)
# Langzeit-Erinnerungen sind nutzerbezogen und gelten auch ohne Session.
memories = store.get_memories(user.id)
except SessionOwnershipError as exc:
raise HTTPException(status_code=403, detail=str(exc))
except RoutingError as exc:
raise HTTPException(status_code=422, detail=str(exc))
llm_context = list(conversation)
user_context_parts = []
if user.id != ANONYMOUS_USER_ID:
user_context_parts.append(f"Du sprichst mit {user.display_name}.")
if memories:
user_context_parts.append(
"Was du ueber den Nutzer weisst:\n" + "\n".join(f"- {m.content}" for m in memories)
)
if user_context_parts:
llm_context = [{"role": "system", "content": "\n".join(user_context_parts)}] + llm_context
# Notfall-Erkennung zuerst (immer eskalieren, auch bei Quota-Limit).
emergency = handle_emergency(user, payload.text, store)
# Stufe 2: LLM-Klassifikation als Hintergrund-Task (nur wenn Stichwoerter nichts fanden).
schedule_llm_emergency_check(user, payload.text, store, emergency)
if emergency is None:
try:
enforce_quota(user, store)
except QuotaExceededError as exc:
raise HTTPException(status_code=429, detail=str(exc))
try:
trace, audio = await orchestrator.chat_text(
payload.text,
language=route.language,
voice=voice,
output=output,
history=llm_context,
)
except Exception as exc:
raise HTTPException(status_code=502, detail=str(exc))
record_usage(user, store, len(payload.text) + len(trace.semantic_response or ""))
# Turn persistieren (User-Eingabe + semantische Antwort) fuer das Gedaechtnis.
if session_id:
store.append_message(session_id, user.id, "user", payload.text)
store.append_message(session_id, user.id, "assistant", trace.semantic_response)
maybe_schedule_extraction(store, user.id, session_id)
if debug:
return JSONResponse(
content={
"ok": True,
"voice": voice,
"route": route.as_dict(),
"history_len": len(conversation),
"memories_len": len(memories),
"emergency": emergency,
"trace": {
"raw_transcript": trace.raw_transcript,
"cleaned_transcript": trace.cleaned_transcript,
"semantic_response": trace.semantic_response,
"spoken_response": trace.spoken_response,
"tts_ready_text": trace.tts_ready_text,
},
}
)
headers = {
"Content-Language": route.language,
"X-Audio-Format": "pcm",
"X-Audio-Sample-Rate": "24000",
"X-Audio-Channels": "1",
"X-Audio-Sample-Width": "16",
**_route_headers(route),
}
if emergency:
headers["X-Emergency"] = emergency["category"]
return StreamingResponse(BytesIO(audio), media_type="audio/pcm", headers=headers)