379e002460
- LLMProvider.stream: Basis-Default (Fallback über complete) + SSE-Streaming
fuer OpenRouter und lokalen OpenAI-kompatiblen Provider; gemeinsamer Parser sse_delta
- Orchestrator.chat_stream: LLM-Token live via on_token-Callback, danach
Spoken-Adapter/Normalizer/TTS/Output; Fallback fuer Provider ohne stream
- WS /ws/chat: opt-in {"stream":true} -> ack -> token* -> semantic -> audio -> done
- Tests: 43 gruen (+5: SSE-Parsing, Default-Fallback, WS-Token-Flow)
- Doku aktualisiert; .gitignore: *.wav (generierte Audio-Ausgaben)
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
39 lines
1.1 KiB
Python
39 lines
1.1 KiB
Python
import json
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from abc import ABC, abstractmethod
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from collections.abc import AsyncIterator
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def sse_delta(line: str) -> str | None:
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"""Extrahiert das Token-Delta aus einer OpenAI-kompatiblen SSE-Zeile (oder None)."""
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if not line.startswith("data:"):
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return None
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data = line[len("data:"):].strip()
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if not data or data == "[DONE]":
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return None
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try:
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obj = json.loads(data)
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return obj["choices"][0]["delta"].get("content")
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except (ValueError, KeyError, IndexError, TypeError):
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return None
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class LLMProvider(ABC):
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@abstractmethod
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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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) -> str: ...
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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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) -> AsyncIterator[str]:
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"""Token-Stream. Default: kein echtes Streaming -> komplette Antwort als ein Chunk.
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Provider mit SSE-Unterstuetzung ueberschreiben diese Methode.
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"""
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yield await self.complete(text, history=history, session_id=session_id)
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