b3012b8320
- ai-service: Ollama 기반 AI 서비스 (분류, 시맨틱 검색, RAG Q&A, 패턴 분석) - AI 어시스턴트 페이지: 채팅형 Q&A, 시맨틱 검색, 패턴 분석, 분류 테스트 - 권한 시스템에 ai_assistant 페이지 등록 (기본 비활성) - 기존 페이지에 AI 기능 통합 (대시보드, 수신함, 관리함) - docker-compose, gateway, nginx 설정 업데이트 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
58 lines
2.1 KiB
Python
58 lines
2.1 KiB
Python
import httpx
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from config import settings
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class OllamaClient:
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def __init__(self):
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self.base_url = settings.OLLAMA_BASE_URL
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self.timeout = httpx.Timeout(float(settings.OLLAMA_TIMEOUT), connect=10.0)
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async def generate_embedding(self, text: str) -> list[float]:
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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response = await client.post(
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f"{self.base_url}/api/embeddings",
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json={"model": settings.OLLAMA_EMBED_MODEL, "prompt": text},
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)
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response.raise_for_status()
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return response.json()["embedding"]
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async def batch_embeddings(self, texts: list[str]) -> list[list[float]]:
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results = []
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for text in texts:
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emb = await self.generate_embedding(text)
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results.append(emb)
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return results
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async def generate_text(self, prompt: str, system: str = None) -> str:
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messages = []
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if system:
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messages.append({"role": "system", "content": system})
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messages.append({"role": "user", "content": prompt})
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async with httpx.AsyncClient(timeout=self.timeout) as client:
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response = await client.post(
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f"{self.base_url}/api/chat",
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json={
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"model": settings.OLLAMA_TEXT_MODEL,
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"messages": messages,
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"stream": False,
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"options": {"temperature": 0.3, "num_predict": 2048},
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},
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)
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response.raise_for_status()
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return response.json()["message"]["content"]
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async def check_health(self) -> dict:
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try:
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async with httpx.AsyncClient(timeout=httpx.Timeout(5.0)) as client:
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response = await client.get(f"{self.base_url}/api/tags")
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models = response.json().get("models", [])
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return {
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"status": "connected",
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"models": [m["name"] for m in models],
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}
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except Exception:
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return {"status": "disconnected"}
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ollama_client = OllamaClient()
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