import {
  filterLoraStackForImageEngine,
  loraIdentityKey,
  makeLoraStackItem,
  normalizeLoraStack,
  type LoraStackItem
} from '~/utils/loras'

export const IMAGE_V2_MODES = ['edit', 'compose', 'refine', 'generate'] as const
export const IMAGE_V2_TASKS = ['scene', 'identity', 'outfit', 'face_lock', 'refine', 't2i'] as const
export const IMAGE_V2_ENGINES = ['flux', 'krea'] as const

export type ImageV2Mode = (typeof IMAGE_V2_MODES)[number]
export type ImageV2Task = (typeof IMAGE_V2_TASKS)[number]
export type ImageV2Engine = (typeof IMAGE_V2_ENGINES)[number]

export const IMAGE_V2_STEPS_DEFAULT = 24
export const IMAGE_V2_CFG_DEFAULT = 4
export const IMAGE_V2_TURBO_STEPS = 8
export const IMAGE_V2_TURBO_CFG = 1
export const IMAGE_V2_SNOFS_MODEL = 0.65
export const IMAGE_V2_SNOFS_CLIP = 0.35
export const IMAGE_V2_CONSISTENCY_MODEL = 0.7
export const IMAGE_V2_CONSISTENCY_CLIP = 0.7
export const IMAGE_V2_STRENGTH_MIN = 0
export const IMAGE_V2_STRENGTH_MAX = 2
export const IMAGE_V2_STRENGTH_STEP = 0.05

export const IMAGE_V2_SNOFS_LORA = 'klein_snofs_v1_4.safetensors'
export const IMAGE_V2_CONSISTENCY_LORA = 'Flux2-Klein-9B-consistency-V2.safetensors'
export const IMAGE_V2_DENOISE_DEFAULT = 0.35
export const IMAGE_V2_DENOISE_MIN = 0.15
export const IMAGE_V2_DENOISE_MAX = 0.75
export const IMAGE_V2_DENOISE_STEP = 0.01
export const IMAGE_V2_REFINE_FACE = {
  strength: 0.28,
  snofsModel: 0.55,
  snofsClip: 0.25,
  consistencyModel: 0.75,
  consistencyClip: 0.8
}
export const IMAGE_V2_REFINE_HAND = {
  strength: 0.4,
  snofsModel: 0.65,
  snofsClip: 0.3,
  consistencyModel: 0.7,
  consistencyClip: 0.7
}
export const IMAGE_V2_REFINE_HEAVY = { strength: 0.55 }
export const IMAGE_V2_REFINE_FACE_PROMPT = 'same face as the canvas, same glasses, same cheeks and jaw. Change only the face in the masked area.'
export const IMAGE_V2_SIZE_SIDES = [768, 1024, 1280] as const
export const IMAGE_V2_GENERATE_WIDTH = 1024
export const IMAGE_V2_GENERATE_HEIGHT = 1024
export const IMAGE_V2_GENERATE_ASPECTS = {
  '1:1': [1024, 1024],
  '3:4': [768, 1024],
  '4:3': [1024, 768],
  '16:9': [1280, 768],
  '9:16': [768, 1280]
} as const
export type ImageV2GenerateAspect = keyof typeof IMAGE_V2_GENERATE_ASPECTS
export const IMAGE_V2_GENERATE_SFW = { snofsModel: 0, snofsClip: 0 }
export const IMAGE_V2_GENERATE_SNOFS = { snofsModel: 0.65, snofsClip: 0.35 }

export const IMAGE_V2_KREA_STEPS = 8
export const IMAGE_V2_KREA_CFG = 1
export const IMAGE_V2_KREA_EDIT_DENOISE = 0.75
export const IMAGE_V2_KREA_COMPOSE_DENOISE = 0.7
export const IMAGE_V2_KREA_CLIP = 'qwen3vl_4b_fp8_scaled.safetensors'
export const IMAGE_V2_KREA_CLIP_TYPE = 'krea2'
export const IMAGE_V2_KREA_VAE = 'qwen_image_vae.safetensors'
export const IMAGE_V2_KREA_UNET_CANDIDATES = [
  'krea2_turbo_mxfp8.safetensors',
  'krea2_turbo_nvfp4.safetensors',
  'krea2_turbo_fp8_scaled.safetensors'
] as const
export const IMAGE_V2_KREA_CONCEPT_LORA = ''

export const IMAGE_V2_ROLE_HEADERS: Record<Exclude<ImageV2Task, 'scene' | 'refine' | 't2i'>, string> = {
  outfit: 'Person, face, body, pose, and background from image 1. Clothing only from image 2. Fit the outfit from image 2 to the body in image 1. Do not copy image 2’s face, body shape, or pose.',
  face_lock: 'Body, pose, and scene from image 1. Exact face from image 2.',
  identity: 'Same person as image 1. Use image 2 only to reinforce the face. Follow the user’s pose/scene prompt.'
}

export function parseImageV2Mode(raw: unknown): ImageV2Mode | null {
  const value = String(raw || '').trim().toLowerCase()
  return IMAGE_V2_MODES.includes(value as ImageV2Mode) ? value as ImageV2Mode : null
}

export function parseImageV2Task(raw: unknown, fallback: ImageV2Task = 'scene'): ImageV2Task {
  const value = String(raw || '').trim().toLowerCase()
  return IMAGE_V2_TASKS.includes(value as ImageV2Task) ? value as ImageV2Task : fallback
}

export function parseImageV2Engine(raw: unknown, fallback: ImageV2Engine = 'flux'): ImageV2Engine {
  const value = String(raw || '').trim().toLowerCase()
  return IMAGE_V2_ENGINES.includes(value as ImageV2Engine) ? value as ImageV2Engine : fallback
}

export function imageV2WorkflowFile(mode: ImageV2Mode, engine: ImageV2Engine = 'flux') {
  if (engine === 'krea') {
    if (mode === 'generate') return 'krea_v2_generate.json'
    if (mode === 'refine') return 'krea_v2_refine.json'
    if (mode === 'compose') return 'krea_v2_compose.json'
    return 'krea_v2_edit.json'
  }
  if (mode === 'generate') return 'klein_v2_generate.json'
  if (mode === 'refine') return 'klein_v2_refine.json'
  if (mode === 'compose') return 'klein_v2_compose.json'
  return 'klein_v2_edit.json'
}

export function clampImageV2Strength(raw: unknown, fallback: number) {
  const value = Number(raw)
  if (!Number.isFinite(value)) return fallback
  const snapped = Math.round(value / IMAGE_V2_STRENGTH_STEP) * IMAGE_V2_STRENGTH_STEP
  return Math.min(IMAGE_V2_STRENGTH_MAX, Math.max(IMAGE_V2_STRENGTH_MIN, Math.round(snapped * 100) / 100))
}

export function clampImageV2Denoise(raw: unknown, fallback = IMAGE_V2_DENOISE_DEFAULT) {
  const value = Number(raw)
  if (!Number.isFinite(value)) return fallback
  const snapped = Math.round(value / IMAGE_V2_DENOISE_STEP) * IMAGE_V2_DENOISE_STEP
  return Math.min(IMAGE_V2_DENOISE_MAX, Math.max(IMAGE_V2_DENOISE_MIN, Math.round(snapped * 100) / 100))
}

export function snapImageV2Side(raw: unknown, fallback = IMAGE_V2_GENERATE_WIDTH) {
  const value = Number(raw)
  if (!Number.isFinite(value)) return fallback
  return IMAGE_V2_SIZE_SIDES.reduce((best, side) => (
    Math.abs(side - value) < Math.abs(best - value) ? side : best
  ), IMAGE_V2_SIZE_SIDES[0])
}

export function parseImageV2Aspect(raw: unknown): ImageV2GenerateAspect | null {
  const value = String(raw || '').trim()
  return value in IMAGE_V2_GENERATE_ASPECTS ? value as ImageV2GenerateAspect : null
}

export function clampImageV2Size(width: unknown, height: unknown, aspect?: unknown) {
  const preset = parseImageV2Aspect(aspect)
  if (preset) {
    const [w, h] = IMAGE_V2_GENERATE_ASPECTS[preset]
    return { width: w, height: h, aspect: preset }
  }
  return {
    width: snapImageV2Side(width, IMAGE_V2_GENERATE_WIDTH),
    height: snapImageV2Side(height, IMAGE_V2_GENERATE_HEIGHT),
    aspect: null as ImageV2GenerateAspect | null
  }
}

export function composeImageV2Prompt(mode: ImageV2Mode, task: ImageV2Task, prompt: string) {
  const body = String(prompt || '').trim()
  if (mode === 'generate' || mode === 'refine' || mode !== 'compose' || task === 'scene' || task === 't2i') return body
  const header = IMAGE_V2_ROLE_HEADERS[task as Exclude<ImageV2Task, 'scene' | 'refine' | 't2i'>]
  return header ? `${header}\n\n${body}` : body
}

export type ImageV2PresetSettings = {
  mode?: ImageV2Mode
  task?: ImageV2Task
  engine?: ImageV2Engine
  negative?: string
  snofsModel?: number
  snofsClip?: number
  consistencyModel?: number
  consistencyClip?: number
  steps?: number
  cfg?: number
  megapixels?: number
  turbo?: boolean
  strength?: number
  width?: number
  height?: number
}

export function isImageV2ConceptLora(name: string) {
  const id = loraIdentityKey(name)
  return id === loraIdentityKey(IMAGE_V2_SNOFS_LORA) || /klein_snofs/i.test(id)
}

export function isImageV2ConsistencyLora(name: string) {
  const id = loraIdentityKey(name)
  return id === loraIdentityKey(IMAGE_V2_CONSISTENCY_LORA) || /flux2-klein-9b-consistency/i.test(id)
}

export function upsertImageV2Lora(stack: unknown, name: string, model: number, clip: number): LoraStackItem[] {
  const item = makeLoraStackItem(name, model, clip)
  const current = normalizeLoraStack(stack)
  if (!item) return current
  const key = loraIdentityKey(name)
  const index = current.findIndex(entry => loraIdentityKey(entry.name) === key)
  if (index >= 0) {
    const next = [...current]
    next[index] = { ...next[index], strengthModel: item.strengthModel, strengthClip: item.strengthClip }
    return next
  }
  if (isImageV2ConsistencyLora(name)) {
    const conceptAt = current.findIndex(entry => isImageV2ConceptLora(entry.name))
    if (conceptAt >= 0) return [...current.slice(0, conceptAt + 1), item, ...current.slice(conceptAt + 1)]
  }
  return [item, ...current]
}

export function defaultImageV2LoraStack(opts: {
  engine: ImageV2Engine
  mode: ImageV2Mode
  xaigen: boolean
  kreaConcept?: string
}): LoraStackItem[] {
  if (opts.engine === 'krea') {
    const name = String(opts.kreaConcept || '').trim()
    if (!opts.xaigen || !name) return []
    const item = makeLoraStackItem(name, IMAGE_V2_SNOFS_MODEL, IMAGE_V2_SNOFS_CLIP)
    return item ? [item] : []
  }
  const out: LoraStackItem[] = []
  if (opts.xaigen) {
    const concept = makeLoraStackItem(IMAGE_V2_SNOFS_LORA, IMAGE_V2_SNOFS_MODEL, IMAGE_V2_SNOFS_CLIP)
    if (concept) out.push(concept)
  }
  if (opts.mode !== 'generate') {
    const consistency = makeLoraStackItem(IMAGE_V2_CONSISTENCY_LORA, IMAGE_V2_CONSISTENCY_MODEL, IMAGE_V2_CONSISTENCY_CLIP)
    if (consistency) out.push(consistency)
  }
  return out
}

export function mergeLegacyImageV2Loras(stack: unknown, opts: {
  engine: ImageV2Engine
  mode: ImageV2Mode
  xaigen: boolean
  snofsModel?: number
  snofsClip?: number
  consistencyModel?: number
  consistencyClip?: number
  kreaConcept?: string
}): LoraStackItem[] {
  let items = filterLoraStackForImageEngine(stack, opts.engine)
  if (opts.engine === 'krea') {
    const name = String(opts.kreaConcept || '').trim()
    const model = Number(opts.snofsModel) || 0
    const clip = Number(opts.snofsClip) || 0
    if (name && (model > 0 || clip > 0) && !items.some(item => loraIdentityKey(item.name) === loraIdentityKey(name))) {
      return upsertImageV2Lora(items, name, model, clip)
    }
    return items
  }
  const conceptModel = opts.xaigen ? Number(opts.snofsModel) || 0 : 0
  const conceptClip = opts.xaigen ? Number(opts.snofsClip) || 0 : 0
  if ((conceptModel > 0 || conceptClip > 0) && !items.some(item => isImageV2ConceptLora(item.name))) {
    items = upsertImageV2Lora(items, IMAGE_V2_SNOFS_LORA, conceptModel, conceptClip)
  }
  const consistencyModel = opts.mode === 'generate' ? 0 : Number(opts.consistencyModel) || 0
  const consistencyClip = opts.mode === 'generate' ? 0 : Number(opts.consistencyClip) || 0
  if ((consistencyModel > 0 || consistencyClip > 0) && !items.some(item => isImageV2ConsistencyLora(item.name))) {
    items = upsertImageV2Lora(items, IMAGE_V2_CONSISTENCY_LORA, consistencyModel, consistencyClip)
  }
  return items
}