3794afff95
GPU 서버 중앙 AI 라우팅 서비스 초기 구현: - OpenAI 호환 API (/v1/chat/completions, /v1/models, /v1/embeddings) - 모델 레지스트리 + 백엔드 헬스체크 (30초 루프) - Ollama SSE 프록시 (NDJSON → OpenAI SSE 변환) - JWT 인증 이중 경로 (httpOnly 쿠키 + Bearer 토큰) - owner/guest 역할 분리, 로그인 rate limiting - 백엔드별 rate limiting (NanoClaude 대비) - SQLite 스키마 사전 정의 (aiosqlite + WAL) - Docker Compose + Caddy 리버스 프록시 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
68 lines
1.9 KiB
Python
68 lines
1.9 KiB
Python
from typing import List, Union
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from fastapi import APIRouter, HTTPException, Request
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from pydantic import BaseModel
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from services import proxy_ollama
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from services.registry import registry
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router = APIRouter(prefix="/v1", tags=["embeddings"])
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class EmbeddingRequest(BaseModel):
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model: str
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input: Union[str, List[str]]
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@router.post("/embeddings")
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async def create_embedding(body: EmbeddingRequest, request: Request):
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role = getattr(request.state, "role", "anonymous")
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if role == "anonymous":
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raise HTTPException(
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status_code=401,
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detail={"error": {"message": "Authentication required", "type": "auth_error", "code": "unauthorized"}},
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)
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result = registry.resolve_model(body.model, role)
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if not result:
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raise HTTPException(
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status_code=404,
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detail={
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"error": {
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"message": f"Model '{body.model}' not found or not available",
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"type": "invalid_request_error",
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"code": "model_not_found",
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}
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},
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)
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backend, model_info = result
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if "embed" not in model_info.capabilities:
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raise HTTPException(
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status_code=400,
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detail={
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"error": {
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"message": f"Model '{body.model}' does not support embeddings",
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"type": "invalid_request_error",
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"code": "capability_mismatch",
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}
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},
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)
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if backend.type == "ollama":
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return await proxy_ollama.generate_embedding(
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backend.url, body.model, body.input
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)
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raise HTTPException(
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status_code=501,
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detail={
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"error": {
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"message": f"Embedding not supported for backend type '{backend.type}'",
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"type": "api_error",
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"code": "not_implemented",
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}
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},
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)
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