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>
This commit is contained in:
@@ -4,8 +4,17 @@
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"type": "ollama",
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"url": "http://host.docker.internal:11434",
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"models": [
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{ "id": "qwen3.5:9b-q8_0", "capabilities": ["chat"], "priority": 1 },
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{ "id": "qwen3-vl:8b", "capabilities": ["chat", "vision"], "priority": 1 }
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{ "id": "bge-m3", "capabilities": ["embed"], "priority": 1 }
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],
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"access": "all",
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"rate_limit": null
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},
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{
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"id": "mlx-mac",
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"type": "openai-compat",
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"url": "http://192.168.1.122:8800",
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"models": [
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{ "id": "qwen3.5:35b-a3b", "capabilities": ["chat"], "priority": 1 }
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],
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"access": "all",
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"rate_limit": null
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@@ -5,7 +5,7 @@ from fastapi.responses import JSONResponse, StreamingResponse
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from pydantic import BaseModel
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from middleware.rate_limit import check_backend_rate_limit
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from services import proxy_ollama
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from services import proxy_ollama, proxy_openai
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from services.registry import registry
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router = APIRouter(prefix="/v1", tags=["chat"])
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@@ -79,7 +79,24 @@ async def chat_completions(body: ChatRequest, request: Request):
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)
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return JSONResponse(content=result)
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# Placeholder for other backend types
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if backend.type == "openai-compat":
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if body.stream:
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return StreamingResponse(
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proxy_openai.stream_chat(
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backend.url, body.model, messages, **kwargs
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),
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media_type="text/event-stream",
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headers={
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"Cache-Control": "no-cache",
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"X-Accel-Buffering": "no",
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},
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)
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else:
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result = await proxy_openai.complete_chat(
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backend.url, body.model, messages, **kwargs
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)
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return JSONResponse(content=result)
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raise HTTPException(
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status_code=501,
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detail={
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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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@@ -0,0 +1,83 @@
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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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