"""Offline, lazy CPU runtime; one encoder call per process, with a fast busy response."""

from functools import lru_cache
from threading import Lock

from fastapi import HTTPException

from app.core.config import settings
from app.services.embedding import LOCAL_MODELS, EmbeddingSpec, LocalEmbeddingProvider


class EmbeddingRuntime:
    def __init__(self, spec: EmbeddingSpec, cache_dir, batch_size: int, threads: int):
        self.spec = spec
        self.cache_dir, self.batch_size, self.threads = cache_dir, batch_size, threads
        self._provider = None
        self._lock = Lock()

    def encode(self, texts: list[str], *, query: bool = False) -> list[list[float]]:
        if not self._lock.acquire(blocking=False):
            raise HTTPException(503, "本地编码器忙，请稍后重试")
        try:
            if self._provider is None:
                self._provider = LocalEmbeddingProvider(
                    self.spec,
                    cache_dir=self.cache_dir,
                    batch_size=self.batch_size,
                    threads=self.threads,
                    offline=True,
                )
            return self._provider.encode(texts, query=query)
        finally:
            self._lock.release()


@lru_cache(maxsize=1)
def runtime(spec, cache_dir, batch_size, threads):
    return EmbeddingRuntime(spec, cache_dir, batch_size, threads)


def get_embedding_provider():
    if not settings.embedding_enabled:
        raise HTTPException(503, "本地 Embedding 未启用，请先完成模型缓存和运行环境配置")
    return runtime(
        LOCAL_MODELS[settings.embedding_model],
        settings.embedding_cache_dir,
        settings.embedding_batch_size,
        settings.embedding_threads,
    )