feat: 맥미니 MLX 연동 — OpenAI-compat 프록시 + 모델 배치 정정
- proxy_openai.py 추가: MLX 서버 SSE 패스스루 - chat.py: openai-compat 백엔드 타입 라우팅 추가 - backends.json: GPU=embed(bge-m3)만, 맥미니MLX=채팅(qwen3.5:35b-a3b) - LAN IP(192.168.1.122) 사용 (같은 서브넷, Tailscale 불필요) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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83
hub-api/services/proxy_openai.py
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83
hub-api/services/proxy_openai.py
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"""OpenAI-compatible proxy (MLX server, vLLM, etc.) — SSE passthrough."""
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from __future__ import annotations
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import json
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import logging
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from collections.abc import AsyncGenerator
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import httpx
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logger = logging.getLogger(__name__)
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async def stream_chat(
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base_url: str,
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model: str,
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messages: list[dict],
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**kwargs,
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) -> AsyncGenerator[str, None]:
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"""Proxy OpenAI-compatible chat streaming. SSE passthrough with model field override."""
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payload = {
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"model": model,
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"messages": messages,
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"stream": True,
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**{k: v for k, v in kwargs.items() if v is not None},
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}
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async with httpx.AsyncClient(timeout=120.0) as client:
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async with client.stream(
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"POST",
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f"{base_url}/v1/chat/completions",
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json=payload,
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) as resp:
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if resp.status_code != 200:
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body = await resp.aread()
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error_msg = body.decode("utf-8", errors="replace")
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yield _error_event(f"Backend error ({resp.status_code}): {error_msg}")
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return
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async for line in resp.aiter_lines():
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if not line.strip():
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continue
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# Pass through SSE lines as-is (already in OpenAI format)
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if line.startswith("data: "):
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yield f"{line}\n\n"
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elif line == "data: [DONE]":
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yield "data: [DONE]\n\n"
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async def complete_chat(
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base_url: str,
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model: str,
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messages: list[dict],
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**kwargs,
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) -> dict:
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"""Non-streaming OpenAI-compatible chat."""
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payload = {
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"model": model,
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"messages": messages,
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"stream": False,
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**{k: v for k, v in kwargs.items() if v is not None},
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}
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async with httpx.AsyncClient(timeout=120.0) as client:
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resp = await client.post(f"{base_url}/v1/chat/completions", json=payload)
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resp.raise_for_status()
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return resp.json()
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def _error_event(message: str) -> str:
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error = {
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"id": "chatcmpl-gateway",
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"object": "chat.completion.chunk",
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"model": "error",
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"choices": [
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{
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"index": 0,
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"delta": {"content": f"[Error] {message}"},
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"finish_reason": "stop",
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}
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],
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}
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return f"data: {json.dumps(error)}\n\ndata: [DONE]\n\n"
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