dschlueter/my_voice_assistant_v2
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

fix(llm): LLM antwortet jetzt in der konfigurierten Systemsprache

Browse source 
Bisher wurde `language` zwar an STT/TTS übergeben, aber nie an den LLM.
Lokales Modell antwortete deshalb immer auf Englisch/Deutsch, egal ob
Französisch, Spanisch o.a. eingestellt war.

Lösung: `language`-Parameter durch die gesamte LLM-Schicht gezogen:
- base.py: `lang_instruction()` helper + Signatur erweitert
- local_openai_compatible.py: Sprachanweisung ("Respond in Français.")
  wird als letzter System-Part in den Message-Stack eingefügt
- openrouter.py: Explizite Sprachanweisung ergänzt den bestehenden
  "Answer in the same language as the user"-Prompt
- fallback.py: FallbackLLMProvider leitet `language` durch
- orchestrator.py: alle 3 LLM-Aufrufstellen übergeben `language`
- Tests: alle Stub-LLMs um `language=None` ergänzt

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Dieter Schlüter 2026-06-19 14:12:16 +02:00
commit 81d4cf6fd8
14 changed files with 89 additions and 44 deletions
Download patch file Download diff file Expand all files Collapse all files

5
app/core/orchestrator.py
View file

@ -99,6 +99,7 @@ class Orchestrator:
trace.semantic_response = await self.llm.complete(
trace.cleaned_transcript or "",
history=history,
language=language,
)
if not trace.semantic_response:
raise RuntimeError("LLM returned an empty response")
@ -158,7 +159,7 @@ class Orchestrator:
parts: list[str] = []
stream_fn = getattr(self.llm, "stream", None)
if stream_fn is not None:
async for delta in stream_fn(trace.cleaned_transcript or "", history=history):
async for delta in stream_fn(trace.cleaned_transcript or "", history=history, language=language):
parts.append(delta)
if on_token:
await on_token(delta)
@ -167,7 +168,7 @@ class Orchestrator:
await _emit_sentence(sentence)
else:
# Provider ohne Streaming -> komplette Antwort als ein Token.
result = await self.llm.complete(trace.cleaned_transcript or "", history=history)
result = await self.llm.complete(trace.cleaned_transcript or "", history=history, language=language)
parts.append(result)
if on_token:
await on_token(result)

12
app/providers/fallback.py
View file

@ -37,11 +37,13 @@ class FallbackSTTProvider(_Chain):
class FallbackLLMProvider(_Chain):
async def complete(self, text, history=None, session_id=None) -> str:
async def complete(self, text, history=None, session_id=None, language=None) -> str:
last_exc = None
for index, (name, provider) in enumerate(self.entries):
try:
result = await provider.complete(text, history=history, session_id=session_id)
result = await provider.complete(
text, history=history, session_id=session_id, language=language
)
if index > 0:
self._on_fallback()
return result
@ -50,12 +52,14 @@ class FallbackLLMProvider(_Chain):
self._on_error(name)
raise last_exc
async def stream(self, text, history=None, session_id=None) -> AsyncIterator[str]:
async def stream(self, text, history=None, session_id=None, language=None) -> AsyncIterator[str]:
last_exc = None
for index, (name, provider) in enumerate(self.entries):
produced = False
try:
async for delta in provider.stream(text, history=history, session_id=session_id):
async for delta in provider.stream(
text, history=history, session_id=session_id, language=language
):
produced = True
yield delta
if index > 0:

24
app/providers/llm/base.py
View file

@ -2,6 +2,26 @@ import json
from abc import ABC, abstractmethod
from collections.abc import AsyncIterator
_LANG_NAMES: dict[str, str] = {
"de": "Deutsch",
"en": "English",
"fr": "Français",
"es": "Español",
"it": "Italiano",
"nl": "Nederlands",
"ru": "Русский",
"zh": "中文",
"cmn": "中文",
}
def lang_instruction(language: str | None) -> str | None:
"""'Respond in X.' instruction for the given ISO language code, or None."""
if not language:
return None
name = _LANG_NAMES.get(language, language)
return f"Respond in {name}."
def sse_delta(line: str) -> str | None:
"""Extrahiert das Token-Delta aus einer OpenAI-kompatiblen SSE-Zeile (oder None)."""
@ -24,6 +44,7 @@ class LLMProvider(ABC):
text: str,
history: list[dict] | None = None,
session_id: str | None = None,
language: str | None = None,
) -> str: ...
async def stream(
@ -31,9 +52,10 @@ class LLMProvider(ABC):
text: str,
history: list[dict] | None = None,
session_id: str | None = None,
language: str | None = None,
) -> AsyncIterator[str]:
"""Token-Stream. Default: kein echtes Streaming -> komplette Antwort als ein Chunk.
Provider mit SSE-Unterstuetzung ueberschreiben diese Methode.
"""
yield await self.complete(text, history=history, session_id=session_id)
yield await self.complete(text, history=history, session_id=session_id, language=language)

21
app/providers/llm/local_openai_compatible.py
View file

@ -2,7 +2,7 @@ from collections.abc import AsyncIterator
import httpx
from app.providers.llm.base import LLMProvider, sse_delta
from app.providers.llm.base import LLMProvider, lang_instruction, sse_delta
class LocalOpenAICompatibleLLM(LLMProvider):
@ -24,7 +24,9 @@ class LocalOpenAICompatibleLLM(LLMProvider):
self.max_tokens = max_tokens
self.temperature = temperature
def _build_messages(self, text: str, history: list[dict] | None) -> list[dict]:
def _build_messages(
self, text: str, history: list[dict] | None, language: str | None = None
) -> list[dict]:
# Manche Chat-Templates (z. B. Qwen3) erlauben nur EINE System-Nachricht,
# ganz am Anfang. Daher den Sprach-System-Prompt und etwaige System-
# Nachrichten aus der History (z. B. Nutzer-Erinnerungen) zu einer einzigen
@ -40,6 +42,9 @@ class LocalOpenAICompatibleLLM(LLMProvider):
system_parts.append(content)
else:
rest.append(msg)
instr = lang_instruction(language)
if instr:
system_parts.append(instr)
messages: list[dict] = []
if system_parts:
@ -48,10 +53,12 @@ class LocalOpenAICompatibleLLM(LLMProvider):
messages.append({"role": "user", "content": text})
return messages
def _payload(self, text: str, history: list[dict] | None, stream: bool) -> dict:
def _payload(
self, text: str, history: list[dict] | None, stream: bool, language: str | None = None
) -> dict:
payload: dict = {
"model": self.model,
"messages": self._build_messages(text, history),
"messages": self._build_messages(text, history, language=language),
"temperature": self.temperature,
}
if stream:
@ -68,12 +75,13 @@ class LocalOpenAICompatibleLLM(LLMProvider):
text: str,
history: list[dict] | None = None,
session_id: str | None = None,
language: str | None = None,
) -> str:
async with httpx.AsyncClient(timeout=120) as client:
response = await client.post(
f"{self.base_url}/chat/completions",
headers={"Authorization": f"Bearer {self.api_key}"},
json=self._payload(text, history, stream=False),
json=self._payload(text, history, stream=False, language=language),
)
response.raise_for_status()
data = response.json()
@ -84,13 +92,14 @@ class LocalOpenAICompatibleLLM(LLMProvider):
text: str,
history: list[dict] | None = None,
session_id: str | None = None,
language: str | None = None,
) -> AsyncIterator[str]:
async with httpx.AsyncClient(timeout=120) as client:
async with client.stream(
"POST",
f"{self.base_url}/chat/completions",
headers={"Authorization": f"Bearer {self.api_key}"},
json=self._payload(text, history, stream=True),
json=self._payload(text, history, stream=True, language=language),
) as response:
if response.status_code >= 400:
body = await response.aread()

19
app/providers/llm/openrouter.py
View file

@ -2,7 +2,7 @@ from collections.abc import AsyncIterator
import httpx
from app.providers.llm.base import LLMProvider, sse_delta
from app.providers.llm.base import LLMProvider, lang_instruction, sse_delta
SYSTEM_PROMPT = """
@ -51,7 +51,9 @@ class OpenRouterLLMProvider(LLMProvider):
self.api_key = (api_key or "").strip()
self.model = (model or "").strip()
def _build_messages(self, text: str, history: list[dict] | None) -> list[dict]:
def _build_messages(
self, text: str, history: list[dict] | None, language: str | None = None
) -> list[dict]:
if not self.api_key:
raise ValueError("OPENROUTER_API_KEY is empty")
if not self.model:
@ -59,7 +61,12 @@ class OpenRouterLLMProvider(LLMProvider):
if not text or not text.strip():
raise ValueError("LLM input text is empty")
messages = [{"role": "system", "content": SYSTEM_PROMPT}]
system_content = SYSTEM_PROMPT
instr = lang_instruction(language)
if instr:
system_content = f"{SYSTEM_PROMPT}\n\n{instr}"
messages = [{"role": "system", "content": system_content}]
if history:
messages.extend(history)
messages.append({"role": "user", "content": text.strip()})
@ -70,10 +77,11 @@ class OpenRouterLLMProvider(LLMProvider):
text: str,
history: list[dict] | None = None,
session_id: str | None = None,
language: str | None = None,
) -> str:
payload = {
"model": self.model,
"messages": self._build_messages(text, history),
"messages": self._build_messages(text, history, language=language),
}
timeout = httpx.Timeout(connect=10.0, read=120.0, write=30.0, pool=10.0)
@ -115,10 +123,11 @@ class OpenRouterLLMProvider(LLMProvider):
text: str,
history: list[dict] | None = None,
session_id: str | None = None,
language: str | None = None,
) -> AsyncIterator[str]:
payload = {
"model": self.model,
"messages": self._build_messages(text, history),
"messages": self._build_messages(text, history, language=language),
"stream": True,
}
timeout = httpx.Timeout(connect=10.0, read=120.0, write=30.0, pool=10.0)