from __future__ import annotations

from typing import Any, Protocol

from skills_learning.config import SkillAuthoringConfig, load_config


class EmbeddingClient(Protocol):
    def embed(self, text: str, *, model: str) -> list[float]:
        ...


class OpenAIEmbeddingClient:
    def __init__(self, *, transport: Any | None = None) -> None:
        self._transport = transport

    def embed(self, text: str, *, model: str) -> list[float]:
        client = self._client()
        response = client.embeddings.create(model=model, input=text)
        return [float(value) for value in response.data[0].embedding]

    def _client(self) -> Any:
        if self._transport is not None:
            return self._transport
        from openai import OpenAI

        self._transport = OpenAI()
        return self._transport


def embed_skill_text(
    text: str,
    *,
    client: EmbeddingClient | None = None,
    config: SkillAuthoringConfig | None = None,
) -> list[float] | None:
    settings = config or load_config()
    if not settings.enabled:
        return None
    try:
        embedding_client = client or OpenAIEmbeddingClient()
        return embedding_client.embed(text, model=settings.embedding_model)
    except Exception:
        return None