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>
160 lines
5.8 KiB
Python
160 lines
5.8 KiB
Python
from collections.abc import AsyncIterator
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import httpx
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from app.providers.llm.base import LLMProvider, lang_instruction, sse_delta
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SYSTEM_PROMPT = """
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You are a voice assistant for spoken conversations with older adults.
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Speak naturally, clearly, and calmly.
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Use short, simple sentences.
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Prefer plain everyday language over technical wording.
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Answer in the same language as the user, unless the user asks to switch languages.
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Important response rules:
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- Output plain text only.
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- No markdown.
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- No bullet points.
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- No numbered lists.
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- No tables.
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- No code.
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- No emojis.
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- No URLs unless the user explicitly asks for one.
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- Do not use asterisks, hashtags, or formatting symbols.
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- Do not write headings.
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- Do not use long disclaimers.
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Voice style rules:
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- Sound helpful, warm, and patient.
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- Keep answers brief by default: 1 to 3 short sentences.
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- If more detail is needed, explain step by step in natural spoken sentences.
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- Ask at most one follow-up question at a time.
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- If the answer contains several items, present them as natural speech, not as a list.
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- Use wording that sounds good when spoken aloud.
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- Avoid abbreviations when possible.
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- Avoid symbols when words are better.
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- Prefer complete spoken forms for dates, times, and numbers when useful.
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Safety and honesty rules:
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- If you are unsure, say so briefly and clearly.
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- Do not invent facts.
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- If current real-world information is needed and unavailable, say that clearly.
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Always optimize your answer for listening, not for reading.
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""".strip()
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class OpenRouterLLMProvider(LLMProvider):
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def __init__(self, api_key: str, model: str):
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self.api_key = (api_key or "").strip()
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self.model = (model or "").strip()
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def _build_messages(
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self, text: str, history: list[dict] | None, language: str | None = None
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) -> list[dict]:
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if not self.api_key:
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raise ValueError("OPENROUTER_API_KEY is empty")
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if not self.model:
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raise ValueError("OPENROUTER_LLM_MODEL is empty")
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if not text or not text.strip():
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raise ValueError("LLM input text is empty")
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system_content = SYSTEM_PROMPT
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instr = lang_instruction(language)
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if instr:
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system_content = f"{SYSTEM_PROMPT}\n\n{instr}"
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messages = [{"role": "system", "content": system_content}]
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if history:
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messages.extend(history)
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messages.append({"role": "user", "content": text.strip()})
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return messages
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async def complete(
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self,
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text: str,
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history: list[dict] | None = None,
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session_id: str | None = None,
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language: str | None = None,
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) -> str:
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payload = {
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"model": self.model,
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"messages": self._build_messages(text, history, language=language),
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}
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timeout = httpx.Timeout(connect=10.0, read=120.0, write=30.0, pool=10.0)
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async with httpx.AsyncClient(timeout=timeout) as client:
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try:
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response = await client.post(
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"https://openrouter.ai/api/v1/chat/completions",
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headers={
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json",
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},
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json=payload,
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)
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response.raise_for_status()
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except httpx.HTTPStatusError as exc:
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raise RuntimeError(
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f"OpenRouter LLM error {exc.response.status_code}: {exc.response.text}"
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) from exc
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except httpx.TimeoutException as exc:
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raise RuntimeError("OpenRouter LLM timeout") from exc
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except httpx.HTTPError as exc:
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raise RuntimeError(f"OpenRouter LLM transport error: {exc}") from exc
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data = response.json()
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try:
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content = data["choices"][0]["message"]["content"]
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except (KeyError, IndexError, TypeError) as exc:
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raise RuntimeError(f"Unexpected OpenRouter LLM response: {data}") from exc
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if not content or not str(content).strip():
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raise RuntimeError("OpenRouter LLM returned empty content")
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return str(content).strip()
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async def stream(
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self,
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text: str,
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history: list[dict] | None = None,
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session_id: str | None = None,
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language: str | None = None,
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) -> AsyncIterator[str]:
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payload = {
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"model": self.model,
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"messages": self._build_messages(text, history, language=language),
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"stream": True,
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}
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timeout = httpx.Timeout(connect=10.0, read=120.0, write=30.0, pool=10.0)
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async with httpx.AsyncClient(timeout=timeout) as client:
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try:
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async with client.stream(
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"POST",
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"https://openrouter.ai/api/v1/chat/completions",
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headers={
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"Authorization": f"Bearer {self.api_key}",
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"Content-Type": "application/json",
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},
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json=payload,
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) as response:
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if response.status_code >= 400:
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body = await response.aread()
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raise RuntimeError(
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f"OpenRouter LLM error {response.status_code}: "
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f"{body.decode(errors='replace')}"
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)
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async for line in response.aiter_lines():
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delta = sse_delta(line)
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if delta:
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yield delta
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except httpx.TimeoutException as exc:
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raise RuntimeError("OpenRouter LLM timeout") from exc
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except httpx.HTTPError as exc:
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raise RuntimeError(f"OpenRouter LLM transport error: {exc}") from exc
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