import { Injectable } from '@nestjs/common';
import OpenAI from 'openai';
import { EMBEDDING_DIM, env } from '../config/env';
import { EmbedKind, EmbeddingProvider } from './types';

@Injectable()
export class OpenAiEmbeddingProvider extends EmbeddingProvider {
  readonly name = `openai:${env.llm.embeddingModel}`;
  readonly dimensions = EMBEDDING_DIM;
  private readonly client = new OpenAI({ apiKey: env.llm.apiKey });

  async embed(texts: string[], _kind: EmbedKind = 'passage'): Promise<number[][]> {
    if (texts.length === 0) return [];
    const res = await this.client.embeddings.create({
      model: env.llm.embeddingModel,
      input: texts,
      dimensions: EMBEDDING_DIM, // 스키마와 차원을 맞춘다
    });
    return res.data.map((d) => d.embedding as number[]);
  }
}