import test from 'brittle'
import { readFileSync } from 'node:fs'
import vm from 'node:vm'

const SRC = readFileSync(new URL('../lib/agent/agent-models.js', import.meta.url), 'utf8')

function load() {
  const sandbox = { console }
  vm.createContext(sandbox)
  vm.runInContext(SRC, sandbox, { filename: 'agent-models.js' })
  return sandbox
}

test('QVAC catalog covers profiles and extra chat ids', async (t) => {
  const s = load()
  const ids = s.BARE_AGENT_QVAC_CHAT_MODELS.map((m) => m.id)
  t.ok(ids.includes('QWEN3_1_7B_INST_Q4'))
  t.ok(ids.includes('QWEN3_8B_INST_Q4_K_M'))
  t.ok(ids.includes('LLAMA_TOOL_CALLING_1B_INST_Q4_K'))
  t.ok(ids.includes('GEMMA4_2B_MULTIMODAL_Q4_K_M'))
  t.is(s.bareAgentQvacModelForProfile('recommended').id, 'QWEN3_1_7B_INST_Q4')
  t.is(s.bareAgentQvacModelForProfile('strong').id, 'QWEN3_4B_INST_Q4_K_M')
  for (const m of s.BARE_AGENT_QVAC_CHAT_MODELS) {
    t.ok(m.ctxSize >= 8192, m.id + ' missing ctxSize')
  }
  t.is(s.bareAgentQvacFindChatModel('QWEN3_5_4B_MULTIMODAL_Q4_K_M').ctxSize, 262144)
  t.is(s.bareAgentQvacFindChatModel('GEMMA4_2B_MULTIMODAL_Q4_K_M').ctxSize, 131072)
})

test('parse OpenAI models skips embeddings and sorts', async (t) => {
  const s = load()
  const list = s.bareAgentParseOpenAiModels({
    data: [
      { id: 'llama-3.3-70b-versatile', owned_by: 'meta' },
      { id: 'text-embedding-3-large', owned_by: 'openai' },
      { id: 'whisper-large-v3', owned_by: 'openai' },
      { id: 'gpt-4.1', owned_by: 'openai' }
    ]
  })
  t.is(list.length, 2)
  t.is(list[0].id, 'gpt-4.1')
  t.is(list[1].id, 'llama-3.3-70b-versatile')
})

test('fetch REST models uses /models and falls back on empty', async (t) => {
  const s = load()
  const live = await s.bareAgentFetchRestModels(
    async () => ({
      ok: true,
      status: 200,
      json: async () => ({ data: [{ id: 'grok-4' }, { id: 'grok-3-mini' }] })
    }),
    { baseUrl: 'https://api.x.ai/v1', apiKey: 'x' }
  )
  t.is(live.length, 2)
  t.is(live[0].id, 'grok-3-mini')
  await t.exception(() =>
    s.bareAgentFetchRestModels(async () => ({ ok: false, status: 401 }), {
      baseUrl: 'https://api.groq.com/openai/v1'
    })
  )
  t.ok(s.bareAgentRestModelsFallback('groq').some((m) => m.id === 'llama-3.3-70b-versatile'))
})

test('honor explicit QVAC model does not fall back to profile default', async (t) => {
  const s = load()
  const next = s.bareAgentHonorExplicitQvacModel(
    {
      qvac_profile: 'recommended',
      qvac_model: 'QWEN3_8B_INST_Q4_K_M',
      model: 'QWEN3_8B_INST_Q4_K_M'
    },
    { chatModel: 'QWEN3_1_7B_INST_Q4' }
  )
  t.is(next.qvac_model, 'QWEN3_8B_INST_Q4_K_M')
  t.is(next.model, 'QWEN3_8B_INST_Q4_K_M')
})

test('apply live model switches QVAC and REST independently', async (t) => {
  const s = load()
  const qvac = s.bareAgentApplyLiveModel(
    { backend: 'qvac', qvac_profile: 'recommended', qvac_model: 'QWEN3_1_7B_INST_Q4' },
    'QWEN3_600M_INST_Q4'
  )
  t.is(qvac.qvac_model, 'QWEN3_600M_INST_Q4')
  t.is(qvac.qvac_profile, 'lite')
  const rest = s.bareAgentApplyLiveModel(
    {
      backend: 'rest',
      provider: 'groq',
      rest_api_key: 'gsk',
      rest_base_url: 'https://api.groq.com/openai/v1',
      model: 'old'
    },
    'llama-3.1-8b-instant'
  )
  t.is(rest.backend, 'rest')
  t.is(rest.model, 'llama-3.1-8b-instant')
})