import { CreateEmbeddingResponse } from 'openai/resources';
import { DyFM_AI_Provider } from '@futdevpro/fsm-dynamo/ai';
import { DyFM_Error } from '@futdevpro/fsm-dynamo';

import { DyNTS_LMStudio_Embedding_ControlService } from './lmstudio-embedding.control-service';
import { DyNTS_AI_CostEvent } from '../_models/interfaces/dynts-ai-cost-event.interface';

describe('| DyNTS_LMStudio_Embedding_ControlService', () => {

  const baseUrl: string = 'http://localhost:1234/v1';
  const issuer: string = 'test-issuer';

  /** Egy OpenAI-kompatibilis embeddings-válasz JSON-string-é csomagolva, fetch-mockhoz. */
  function okResponse(embeddings: number[][], usage?: { prompt_tokens: number; total_tokens: number }): Response {
    const body: string = JSON.stringify({
      object: 'list',
      data: embeddings.map((embedding, index) => ({ object: 'embedding', embedding: embedding, index: index })),
      usage: usage,
    });
    return {
      ok: true,
      status: 200,
      text: () => Promise.resolve(body),
    } as Response;
  }

  /** Egy hibás (non-2xx) válasz fetch-mockhoz. */
  function errorResponse(status: number, body: string): Response {
    return {
      ok: false,
      status: status,
      text: () => Promise.resolve(body),
    } as Response;
  }

  let fetchSpy: jasmine.Spy;

  beforeEach(() => {
    fetchSpy = spyOn(globalThis, 'fetch');
  });

  describe('| constructor', () => {
    it('| should throw a DyFM_Error if baseUrl is empty', () => {
      expect(() => new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: '' })).toThrowMatching(
        (error: unknown) => error instanceof DyFM_Error,
      );
    });

    it('| should set provider to LocalAI', () => {
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: baseUrl });
      expect(service.aiProvider).toBe(DyFM_AI_Provider.LocalAI);
      expect(service.capabilities.embeddings).toBe(true);
    });
  });

  describe('| createEmbeddings', () => {
    it('| should POST to ${baseUrl}/embeddings and return vectors in order', async () => {
      fetchSpy.and.returnValue(Promise.resolve(okResponse([[0.1, 0.2], [0.3, 0.4]])));

      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: baseUrl });
      const result: number[][] | CreateEmbeddingResponse = await service.createEmbeddings({
        texts: ['hello', 'world'],
        model: 'nomic-embed-text-v1.5',
        issuer: issuer,
      });

      expect(result).toEqual([[0.1, 0.2], [0.3, 0.4]]);
      expect(fetchSpy).toHaveBeenCalledTimes(1);
      const url: string = fetchSpy.calls.mostRecent().args[0] as string;
      expect(url).toBe('http://localhost:1234/v1/embeddings');
      const init: RequestInit = fetchSpy.calls.mostRecent().args[1] as RequestInit;
      expect(init.method).toBe('POST');
      const sentBody: { model: string; input: string[] } = JSON.parse(init.body as string);
      expect(sentBody.model).toBe('nomic-embed-text-v1.5');
      expect(sentBody.input).toEqual(['hello', 'world']);
    });

    it('| should trim trailing slashes from baseUrl', async () => {
      fetchSpy.and.returnValue(Promise.resolve(okResponse([[0.5]])));
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({
        baseUrl: 'http://localhost:1234/v1///',
      });
      await service.createEmbeddings({ texts: ['x'], model: 'm', issuer: issuer });
      expect(fetchSpy.calls.mostRecent().args[0]).toBe('http://localhost:1234/v1/embeddings');
    });

    it('| should add a Bearer header when apiKey is provided', async () => {
      fetchSpy.and.returnValue(Promise.resolve(okResponse([[0.5]])));
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({
        baseUrl: baseUrl,
        apiKey: 'secret-token',
      });
      await service.createEmbeddings({ texts: ['x'], model: 'm', issuer: issuer });
      const init: RequestInit = fetchSpy.calls.mostRecent().args[1] as RequestInit;
      const headers: { [key: string]: string } = init.headers as { [key: string]: string };
      expect(headers.Authorization).toBe('Bearer secret-token');
    });

    it('| should throw a DyFM_Error on a non-ok HTTP response', async () => {
      fetchSpy.and.returnValue(Promise.resolve(errorResponse(500, 'boom')));
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: baseUrl });

      await expectAsync(
        service.createEmbeddings({ texts: ['x'], model: 'm', issuer: issuer }),
      ).toBeRejectedWith(jasmine.any(DyFM_Error));
    });

    it('| should throw a DyFM_Error if the vector count does not match the text count', async () => {
      fetchSpy.and.returnValue(Promise.resolve(okResponse([[0.1]])));
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: baseUrl });

      await expectAsync(
        service.createEmbeddings({ texts: ['a', 'b'], model: 'm', issuer: issuer }),
      ).toBeRejectedWith(jasmine.any(DyFM_Error));
    });

    it('| should emit an embedding-batch cost-event with provider lm-studio', async () => {
      fetchSpy.and.returnValue(Promise.resolve(okResponse([[0.1], [0.2]], { prompt_tokens: 7, total_tokens: 7 })));
      const events: DyNTS_AI_CostEvent[] = [];
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({
        baseUrl: baseUrl,
        onCostEvent: (event: DyNTS_AI_CostEvent) => events.push(event),
      });

      await service.createEmbeddings({ texts: ['a', 'b'], model: 'm', issuer: issuer });

      expect(events.length).toBe(1);
      expect(events[0].callType).toBe('embedding-batch');
      expect(events[0].provider).toBe('lm-studio');
      expect(events[0].model).toBe('m');
      expect(events[0].tokensUsed.input).toBe(7);
      expect(events[0].issuer).toBe(issuer);
    });

    it('| should estimate tokens when the endpoint provides no usage', async () => {
      fetchSpy.and.returnValue(Promise.resolve(okResponse([[0.1]])));
      const events: DyNTS_AI_CostEvent[] = [];
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({
        baseUrl: baseUrl,
        onCostEvent: (event: DyNTS_AI_CostEvent) => events.push(event),
      });

      await service.createEmbeddings({ texts: ['abcdefgh'], model: 'm', issuer: issuer });

      // 8 chars / 4 = 2 estimated tokens.
      expect(events[0].tokensUsed.input).toBe(2);
    });
  });

  describe('| createEmbedding (single)', () => {
    it('| should emit an embedding-single cost-event and return a single vector', async () => {
      fetchSpy.and.returnValue(Promise.resolve(okResponse([[0.9, 0.8, 0.7]], { prompt_tokens: 3, total_tokens: 3 })));
      const events: DyNTS_AI_CostEvent[] = [];
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({
        baseUrl: baseUrl,
        onCostEvent: (event: DyNTS_AI_CostEvent) => events.push(event),
      });

      const result: number[] | CreateEmbeddingResponse = await service.createEmbedding({
        text: 'one',
        model: 'm',
        issuer: issuer,
      });

      expect(result).toEqual([0.9, 0.8, 0.7]);
      expect(events[0].callType).toBe('embedding-single');
    });

    it('| should throw a DyFM_Error if text is empty', async () => {
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: baseUrl });
      await expectAsync(
        service.createEmbedding({ text: '', model: 'm', issuer: issuer }),
      ).toBeRejectedWith(jasmine.any(DyFM_Error));
    });
  });

  describe('| testConnection', () => {
    it('| should return true when the probe succeeds', async () => {
      fetchSpy.and.returnValue(Promise.resolve(okResponse([[0.1, 0.2]])));
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: baseUrl });
      expect(await service.testConnection(issuer)).toBe(true);
    });

    it('| should return false (never throw) when the probe fails', async () => {
      fetchSpy.and.returnValue(Promise.reject(new Error('connection refused')));
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: baseUrl });
      expect(await service.testConnection(issuer)).toBe(false);
    });
  });

  describe('| getEmbeddingInfo', () => {
    it('| should report the LocalAI provider and the given model', () => {
      const service: DyNTS_LMStudio_Embedding_ControlService = new DyNTS_LMStudio_Embedding_ControlService({ baseUrl: baseUrl });
      expect(service.getEmbeddingInfo('my-model')).toEqual({ provider: DyFM_AI_Provider.LocalAI, model: 'my-model' });
    });
  });
});