Load only the LoRAs the user picked on Klein; do not require snofs.

Co-authored-by: Cursor <cursoragent@cursor.com>

components/LoraSelect.vue

@@ -87,6 +87,7 @@ import {
   clampLoraStrength,
   formatLoraStrength,
   loraDisplayName,
+  loraIdentityKey,
   makeLoraStackItem,
   type LoraStackItem
 } from '~/utils/loras'
@@ -111,8 +112,8 @@ const props = withDefaults(defineProps<{
 const model = defineModel<LoraStackItem[]>({ default: () => [] })
 
 const availableNames = computed(() => {
-  const taken = new Set(model.value.map(item => item.name.replace(/\\/g, '/').toLowerCase()))
+  const taken = new Set(model.value.map(item => loraIdentityKey(item.name)))
-  return props.names.filter(name => !taken.has(name.replace(/\\/g, '/').toLowerCase()))
+  return props.names.filter(name => !taken.has(loraIdentityKey(name)))
 })
 
 function onAdd(event: Event) {
@@ -124,8 +125,8 @@ function onAdd(event: Event) {
 function addLora(name: string) {
   const item = makeLoraStackItem(name)
   if (!item || model.value.length >= LORA_STACK_MAX) return
-  const taken = new Set(model.value.map(entry => entry.name.replace(/\\/g, '/').toLowerCase()))
+  const taken = new Set(model.value.map(entry => loraIdentityKey(entry.name)))
-  if (taken.has(item.name.replace(/\\/g, '/').toLowerCase())) return
+  if (taken.has(loraIdentityKey(item.name))) return
   model.value = [...model.value, item]
 }
 

server/api/extend.post.ts

@@ -1,7 +1,7 @@
 import { copyFileSync, existsSync, readFileSync } from 'node:fs'
 import { join } from 'node:path'
 import { composeShotPrompt } from '~/utils/globalLocks'
-import { parsePostedLoraStack, listStudioLoras, persistLoraFields } from '~/server/utils/loras'
+import { parsePostedLoraStack, listStudioLoras, persistLoraFields, ensureComfyLoraNames } from '~/server/utils/loras'
 import { readLoraStack } from '~/utils/loras'
 import { clampVideoCfg } from '~/utils/generationPresets'
 import { defaultVideoSteps, isLtxWorkflow, LTX_DISABLED_MESSAGE, ltxWorkflowEnabled, parseVideoWorkflow } from '~/utils/videoModels'
@@ -213,6 +213,7 @@ async function runExtend(
   }
   emitJob(job, { type: 'status', message: 'Queueing extension on MiniMax H3...', progress: 6 })
   await waitForComfySocket(job, 4000)
+  await ensureComfyLoraNames('video')
 
   const graph = buildWorkflow({
     prompt: params.prompt,

server/assets/workflow_flux2_klein_edit.json

@@ -278,7 +278,7 @@
   },
   "75:131": {
     "inputs": {
-      "lora_name": "klein_snofs_v1_4.safetensors",
+      "lora_name": "",
       "strength_model": 1,
       "strength_clip": 1,
       "model": [
@@ -292,7 +292,7 @@
     },
     "class_type": "LoraLoader",
     "_meta": {
-      "title": "Load LoRA (Model and CLIP)"
+      "title": "User LoRA (optional)"
     }
   },
   "92:102": {
@@ -593,7 +593,7 @@
   },
   "92:132": {
     "inputs": {
-      "lora_name": "klein_snofs_v1_4.safetensors",
+      "lora_name": "",
       "strength_model": 1,
       "strength_clip": 1,
       "model": [
@@ -607,7 +607,7 @@
     },
     "class_type": "LoraLoader",
     "_meta": {
-      "title": "Load LoRA (Model and CLIP)"
+      "title": "User LoRA (optional)"
     }
   }
 }

server/utils/imageChain.ts

@@ -3,6 +3,7 @@ import { ensureComfyReady } from '~/server/utils/comfyLifecycle'
 import { getComfyHost, uploadImage, queuePrompt, purgeComfyArtifacts } from '~/server/utils/comfy'
 import { withImageComfyHost, waitForImageEdit, downloadEditedImage } from '~/server/utils/imageComfy'
 import { buildEditWorkflow } from '~/server/utils/imageWorkflow'
+import { ensureComfyLoraNames } from '~/server/utils/loras'
 import { imageDimensions } from '~/server/utils/resolution'
 import { emitChainJob } from '~/server/utils/watch'
 import { saveStill, stillChainName } from '~/server/utils/library'
@@ -91,6 +92,7 @@ export async function runEdit(job: Job, params: EditRunParams) {
             : 'Queueing Flux.2 Klein edit on Beast...',
           progress: 12
         })
+        await ensureComfyLoraNames('image')
         const graph = buildEditWorkflow({
           prompt,
           negative: params.negative,

server/utils/imageWorkflow.ts

@@ -1,5 +1,5 @@
 import template from '../assets/workflow_flux2_klein_edit.json'
-import { applyUserLoraToGraph } from '~/server/utils/loras'
+import { applyOptionalLoraLoaders } from '~/server/utils/loras'
 import type { LoraStackItem } from '~/utils/loras'
 
 const IMAGE1 = '76'
@@ -65,7 +65,8 @@ export function buildEditWorkflow(params: EditParams) {
     if (dual ? singleNode : dualNode) delete graph[id]
   }
 
-  applyUserLoraToGraph(graph, params.loraStack || params.loraName)
+  // User LoRAs only. Empty stack bypasses the optional LoraLoader (no snofs default).
+  applyOptionalLoraLoaders(graph, params.loraStack || params.loraName, 'image')
   return graph
 }
 

server/utils/loras.ts

@@ -2,15 +2,18 @@ import { comfyConfigured, comfyFetch, getComfyHost } from '~/server/utils/comfy'
 import { getBeastImageHost, imageComfyFetch, sameImageHost } from '~/server/utils/imageComfy'
 import {
   XAIGEN_LORA_MESSAGE,
+  MINIMAX_TURBO_LORA,
   filterLorasForStudio,
   isXaigenOnlyLora,
+  loraIdentityKey,
   normalizeLoraName,
   normalizeLoraStack,
   persistLoraFields,
+  resolveComfyLoraName,
   type LoraKind,
   type LoraStackItem
 } from '~/utils/loras'
-import { isXaigenStudio } from '~/utils/videoModels'
+import { isXaigenStudio, LTX_DISTILLED_LORA } from '~/utils/videoModels'
 
 type WorkflowNode = { class_type: string; inputs: Record<string, unknown>; _meta?: { title?: string } }
 type WorkflowGraph = Record<string, WorkflowNode>
@@ -28,6 +31,7 @@ const OBJECT_INFO_NODES = [
 ]
 const MODEL_FEED_CLASSES = new Set(['BasicGuider', 'CFGGuider', 'KSampler', 'KSamplerAdvanced'])
 const CACHE_MS = 20_000
+const SYSTEM_LORA_PREFERRED = [MINIMAX_TURBO_LORA, LTX_DISTILLED_LORA]
 
 type LoraCache = {
   at: number
@@ -150,11 +154,10 @@ async function loadLoraCache(): Promise<LoraCache> {
     const image = imageHost && !same
       ? await discoverFromHost('image').catch(() => ({ image: [] as string[], video: [] as string[] }))
       : video
-    const xaigen = isXaigenStudio()
     const next: LoraCache = {
       at: Date.now(),
-      image: filterLorasForStudio(uniqueNames([...image.image, ...video.image]), xaigen),
+      image: uniqueNames([...image.image, ...video.image]),
-      video: filterLorasForStudio(uniqueNames([...video.video, ...image.video]), xaigen)
+      video: uniqueNames([...video.video, ...image.video])
     }
     cache = next
     return next
@@ -166,22 +169,74 @@ async function loadLoraCache(): Promise<LoraCache> {
 
 export async function listStudioLoras() {
   try {
-    return await loadLoraCache()
+    const listed = await loadLoraCache()
+    const xaigen = isXaigenStudio()
+    return {
+      at: listed.at,
+      image: filterLorasForStudio(listed.image, xaigen),
+      video: filterLorasForStudio(listed.video, xaigen)
+    }
   } catch {
     return { at: 0, image: [] as string[], video: [] as string[] }
   }
 }
 
+/** Unfiltered Comfy filenames for graph system LoRAs (MiniMax turbo, LTX distilled). Reuses the listing cache. */
+export function cachedComfyLoraNames(kind?: LoraKind) {
+  if (!cache) return [] as string[]
+  if (kind === 'image') return uniqueNames([...cache.image, ...cache.video])
+  if (kind === 'video') return uniqueNames([...cache.video, ...cache.image])
+  return uniqueNames([...cache.image, ...cache.video])
+}
+
+export async function ensureComfyLoraNames(kind?: LoraKind) {
+  try {
+    await loadLoraCache()
+  } catch {
+    /* keep whatever was cached */
+  }
+  return cachedComfyLoraNames(kind)
+}
+
+export function resolveGraphLoraNames(graph: WorkflowGraph, kind?: LoraKind) {
+  const names = cachedComfyLoraNames(kind)
+  for (const node of Object.values(graph)) {
+    if (node.class_type !== LORA_LOADER && node.class_type !== LORA_MODEL_ONLY) continue
+    const current = String(node.inputs.lora_name || '').trim()
+    if (!current) continue
+    const preferred = SYSTEM_LORA_PREFERRED.find(item => loraIdentityKey(item) === loraIdentityKey(current)) || current
+    node.inputs.lora_name = names.length ? resolveComfyLoraName(preferred, names) : preferred
+  }
+}
+
+function allowedLoraNames(kind?: LoraKind) {
+  return filterLorasForStudio(cachedComfyLoraNames(kind), isXaigenStudio())
+}
+
+function resolveUserLoraName(name: string, kind?: LoraKind) {
+  const allowed = allowedLoraNames(kind)
+  if (!allowed.length) return name
+  return resolveComfyLoraName(name, allowed)
+}
+
 export function assertLoraAllowed(raw: unknown, kind: LoraKind) {
   const name = normalizeLoraName(raw)
   if (!name) return ''
   if (isXaigenOnlyLora(name) && !isXaigenStudio()) {
     throw createError({ statusCode: 400, statusMessage: XAIGEN_LORA_MESSAGE })
   }
-  const known = cache?.[kind]
+  const allowed = allowedLoraNames(kind)
-  if (known?.length && !known.includes(name) && !known.some(item => item.replace(/\\/g, '/') === name)) {
+  if (allowed.length) {
+    const identity = loraIdentityKey(name)
+    const listed = allowed.some((item) => {
+      const path = item.replace(/\\/g, '/')
+      return path === name || path.toLowerCase() === name.toLowerCase() || loraIdentityKey(item) === identity
+    })
+    if (!listed) {
       throw createError({ statusCode: 400, statusMessage: `Unknown ${kind} LoRA` })
     }
+    return resolveUserLoraName(name, kind)
+  }
   return name
 }
 
@@ -225,10 +280,11 @@ function linkSource(value: unknown): string | null {
 }
 
 function alreadyHasLora(graph: WorkflowGraph, name: string) {
-  const wanted = name.replace(/\\/g, '/').toLowerCase()
+  const wanted = loraIdentityKey(name)
+  if (!wanted) return false
   return Object.values(graph).some((node) => {
     if (node.class_type !== LORA_LOADER && node.class_type !== LORA_MODEL_ONLY) return false
-    return String(node.inputs.lora_name || '').replace(/\\/g, '/').toLowerCase() === wanted
+    return loraIdentityKey(String(node.inputs.lora_name || '')) === wanted
   })
 }
 
@@ -260,8 +316,74 @@ function findModelFeed(graph: WorkflowGraph) {
   return ''
 }
 
+function bypassLoraNode(graph: WorkflowGraph, id: string) {
+  const node = graph[id]
+  if (!node) return
+  const model = Array.isArray(node.inputs.model) ? node.inputs.model : null
+  const clip = Array.isArray(node.inputs.clip) ? node.inputs.clip : null
+  for (const [otherId, other] of Object.entries(graph)) {
+    if (otherId === id) continue
+    for (const [key, value] of Object.entries(other.inputs)) {
+      const src = linkSource(value)
+      if (src !== id || !Array.isArray(value)) continue
+      const slot = value[1]
+      if (slot === 0 && model) other.inputs[key] = [model[0], model[1]]
+      else if (slot === 1 && clip) other.inputs[key] = [clip[0], clip[1]]
+    }
+  }
+  delete graph[id]
+}
+
+/** Optional Klein-style LoraLoader: user stack only. Empty stack bypasses model/CLIP around the loader. */
+export function applyOptionalLoraLoaders(graph: WorkflowGraph, stack?: unknown, kind: LoraKind = 'image') {
+  const loaders = Object.entries(graph).filter(([, node]) => node.class_type === LORA_LOADER)
+  const xaigen = isXaigenStudio()
+  const items = normalizeLoraStack(stack)
+    .filter(item => xaigen || !isXaigenOnlyLora(item.name))
+    .map(item => ({
+      ...item,
+      name: resolveUserLoraName(item.name, kind)
+    }))
+    .filter(item => item.name && (xaigen || !isXaigenOnlyLora(item.name)))
+  if (!loaders.length) {
+    applyUserLoraToGraph(graph, items)
+    return
+  }
+  if (!items.length) {
+    for (const [id] of loaders) bypassLoraNode(graph, id)
+    return
+  }
+  for (const [id] of loaders) {
+    const first = items[0]
+    graph[id].inputs.lora_name = first.name
+    graph[id].inputs.strength_model = first.strengthModel
+    graph[id].inputs.strength_clip = first.strengthClip
+    graph[id]._meta = { title: items.length === 1 ? 'User LoRA' : 'User LoRA 1' }
+    let sourceId = id
+    for (const [index, item] of items.slice(1).entries()) {
+      const nodeId = `user:lora:${id}:${index + 1}`
+      injectAfter(graph, sourceId, nodeId, {
+        class_type: LORA_LOADER,
+        inputs: {
+          lora_name: item.name,
+          strength_model: item.strengthModel,
+          strength_clip: item.strengthClip,
+          model: [sourceId, 0],
+          clip: [sourceId, 1]
+        },
+        _meta: { title: `User LoRA ${index + 2}` }
+      })
+      sourceId = nodeId
+    }
+  }
+}
+
 export function applyUserLoraToGraph(graph: WorkflowGraph, stack?: unknown) {
-  const items = normalizeLoraStack(stack).filter(item => !alreadyHasLora(graph, item.name))
+  const xaigen = isXaigenStudio()
+  const items = normalizeLoraStack(stack)
+    .filter(item => xaigen || !isXaigenOnlyLora(item.name))
+    .map(item => ({ ...item, name: resolveUserLoraName(item.name) }))
+    .filter(item => item.name && (xaigen || !isXaigenOnlyLora(item.name)) && !alreadyHasLora(graph, item.name))
   if (!items.length) return
 
   const clipLoaders = Object.entries(graph).filter(([, node]) => node.class_type === LORA_LOADER)

server/utils/videoChain.ts

@@ -21,7 +21,7 @@ import {
   updateShotQueue
 } from '~/server/utils/shotQueue'
 import { composeShotPrompt, allowIdentityRefs, type PermanenceRef } from '~/utils/globalLocks'
-import { persistLoraFields } from '~/server/utils/loras'
+import { persistLoraFields, ensureComfyLoraNames } from '~/server/utils/loras'
 import { readLoraStack, resolveLoraStack } from '~/utils/loras'
 import type { LoraStackItem } from '~/utils/loras'
 
@@ -180,6 +180,7 @@ export async function queueMiniMax(
   }
   emitChainJob(job, { type: 'status', message: queueing, progress: 6 })
   await waitForComfySocket(job, 4000)
+  await ensureComfyLoraNames('video')
 
   const shotIndex = job.library?.chainIndex || 0
   const composedPrompt = composeShotPrompt({

server/utils/workflow.ts

@@ -3,7 +3,7 @@ import workflowV1 from '../assets/workflow_minimax_video.json'
 import workflowV2 from '../assets/workflow_minimax_video_v2.json'
 import workflowLtx from '../assets/workflow_ltx_video.json'
 import { buildIdentityPrompt } from '~/utils/identityPrompt'
-import { applyUserLoraToGraph } from '~/server/utils/loras'
+import { applyUserLoraToGraph, resolveGraphLoraNames } from '~/server/utils/loras'
 import type { LoraStackItem } from '~/utils/loras'
 import {
   isLtxWorkflow,
@@ -225,6 +225,7 @@ export function buildWorkflow(params: GenerateParams) {
     if (graph['105:104']?.inputs) delete graph['105:104'].inputs.audio_vae
   }
 
+  resolveGraphLoraNames(graph, 'video')
   applyUserLoraToGraph(graph, params.loraStack || params.loraName)
   return graph
 }
@@ -298,6 +299,7 @@ function buildLtxWorkflow(params: GenerateParams, version: VideoWorkflowId) {
     if (graph['12']?.inputs) graph['12'].inputs.latent = ['8', 0]
     if (graph['14']?.inputs) graph['14'].inputs.latent_image = ['8', 0]
   }
+  resolveGraphLoraNames(graph, 'video')
   applyUserLoraToGraph(graph, params.loraStack || params.loraName)
   return graph
 }

utils/loras.ts

@@ -16,16 +16,52 @@ export const LORA_STRENGTH_DEFAULT = 1
 export const LORA_STRENGTH_STEP = 0.05
 export const LORA_STACK_MAX = 8
 
+/** Graph system LoRA for MiniMax turbo. Not a user pick. */
+export const MINIMAX_TURBO_LORA = 'minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors'
+
 export function loraBasename(name: string) {
   const trimmed = String(name || '').trim().replace(/\\/g, '/')
   const parts = trimmed.split('/').filter(Boolean)
   return parts[parts.length - 1] || trimmed
 }
 
+export function loraIdentityKey(name: string) {
+  return loraBasename(name).replace(/^xaigen-?/i, '').toLowerCase()
+}
+
 export function isXaigenOnlyLora(name: string) {
   return /^xaigen/i.test(loraBasename(name))
 }
 
+/** Pick the real Comfy filename: exact path, then same basename ignoring `xaigen-`, then suffix/contains. */
+export function resolveComfyLoraName(wanted: string, available: string[]) {
+  const target = String(wanted || '').trim().replace(/\\/g, '/')
+  if (!target) return ''
+  if (!available.length) return target
+  const targetLower = target.toLowerCase()
+  const exact = available.find(item => item.replace(/\\/g, '/') === target)
+  if (exact) return exact
+  const exactCi = available.find(item => item.replace(/\\/g, '/').toLowerCase() === targetLower)
+  if (exactCi) return exactCi
+
+  const identity = loraIdentityKey(target)
+  const identityHit = available.find(item => loraIdentityKey(item) === identity)
+  if (identityHit) return identityHit
+
+  const stem = identity.replace(/\.(safetensors|sft|ckpt|pt|bin)$/i, '')
+  if (!stem) return target
+  const containsHits = available.filter((item) => {
+    const base = loraBasename(item).toLowerCase()
+    return base.includes(stem) || loraIdentityKey(item).includes(stem)
+  })
+  if (!containsHits.length) return target
+  const suffix = containsHits.find((item) => {
+    const base = loraBasename(item).toLowerCase()
+    return base.endsWith(identity) || base.endsWith(stem) || loraIdentityKey(item).endsWith(identity)
+  })
+  return suffix || containsHits[0]
+}
+
 export function loraDisplayName(name: string) {
   return loraBasename(name).replace(/\.(safetensors|sft|ckpt|pt|bin)$/i, '')
 }
@@ -106,7 +142,7 @@ export function normalizeLoraStack(raw: unknown): LoraStackItem[] {
     if (out.length >= LORA_STACK_MAX) break
     const item = parseStackEntry(entry)
     if (!item) continue
-    const key = loraKey(item.name)
+    const key = loraIdentityKey(item.name)
     if (seen.has(key)) continue
     seen.add(key)
     out.push(item)
@@ -159,6 +195,7 @@ export function loraStacksEqual(a?: unknown, b?: unknown) {
   ))
 }
 
+/** User LoRA picker only. `xaigen-*` names are visible only on xAIGen. */
 export function filterLorasForStudio(names: string[], xaigenStudio: boolean) {
   const seen = new Set<string>()
   const out: string[] = []