drop auto scan

src/lib/components/Pages/Scanner.svelte

@@ -1,8 +1,7 @@
 <script lang="ts">
   import PicletGenerator from '../PicletGenerator/PicletGenerator.svelte';
-  import AutoTrainerScanner from '../AutoTrainerScanner/AutoTrainerScanner.svelte';
   import type { GradioClient } from '$lib/types';
-  
+
   interface Props {
     fluxClient: GradioClient | null;
     joyCaptionClient: GradioClient | null;
@@ -14,14 +13,6 @@
 
 <div class="scanner-page">
   {#if fluxClient && joyCaptionClient && gptOssClient}
-    <!-- Auto Trainer Scanner -->
-    <AutoTrainerScanner
-      {joyCaptionClient}
-      {fluxClient}
-      {gptOssClient}
-    />
-
-    <!-- Manual Piclet Generator -->
     <PicletGenerator
       {fluxClient}
       {joyCaptionClient}

src/lib/components/PicletGenerator/PicletGenerator.svelte

@@ -12,20 +12,12 @@
   import { CanonicalService } from '$lib/services/canonicalService';
   // import { withQwenTimeout } from '$lib/utils/qwenTimeout'; // Unused since qwen is disabled
   
-  interface Props extends PicletGeneratorProps {
-    // Trainer mode props
-    isTrainerMode?: boolean;
-    onTrainerImageCompleted?: (imagePath: string, picletId: number) => void;
-    onTrainerImageFailed?: (imagePath: string, error: string) => void;
-  }
-  
+  interface Props extends PicletGeneratorProps {}
+
   let {
     joyCaptionClient,
     fluxClient,
-    gptOssClient,
-    isTrainerMode = false,
-    onTrainerImageCompleted,
-    onTrainerImageFailed
+    gptOssClient
   }: Props = $props();
   
   // GPT-OSS-120B text generation
@@ -83,9 +75,6 @@
   let imageQueue: File[] = $state([]);
   let currentImageIndex: number = $state(0);
   
-  // Track trainer image metadata when in trainer mode
-  let trainerImagePaths: string[] = $state([]);
-  
   const IMAGE_GENERATION_PROMPT = (concept: string) => `Extract ONLY the visual appearance from this monster concept and describe it in one concise sentence:
 "${concept}"
 
@@ -187,13 +176,6 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
     if (currentImageIndex < imageQueue.length) {
       // Process next image
       setTimeout(() => processCurrentImage(), 1000); // Small delay for better UX
-    } else if (isTrainerMode) {
-      // In trainer mode, don't reset - wait for scanner to queue next image
-      console.log('🔧 DEBUG: Trainer mode - waiting for next image to be queued');
-      // Reset current image index for next image
-      currentImageIndex = 0;
-      imageQueue = [];
-      // Don't call reset() - stay ready to process next trainer image
     } else {
       // Queue completed - reset to single image mode
       imageQueue = [];
@@ -230,8 +212,8 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
 
       workflowState.currentStep = 'complete';
 
-      // If processing a queue or in trainer mode, auto-advance to next image after a short delay
-      if (imageQueue.length > 1 || isTrainerMode) {
+      // If processing a queue, auto-advance to next image after a short delay
+      if (imageQueue.length > 1) {
         setTimeout(() => advanceToNextImage(), 2000); // 2 second delay to show completion
       }
     } catch (err) {
@@ -663,11 +645,6 @@ Create a concise visual description (1-3 sentences, max 100 words). Focus only o
       
       const picletId = await savePicletInstance(picletInstance);
       console.log('Piclet auto-saved as caught with ID:', picletId);
-      
-      // If in trainer mode, notify completion
-      if (isTrainerMode && onTrainerImageCompleted && trainerImagePaths[currentImageIndex]) {
-        onTrainerImageCompleted(trainerImagePaths[currentImageIndex], picletId);
-      }
     } catch (err) {
       console.error('Failed to auto-save piclet:', err);
       console.error('Piclet data that failed to save:', {
@@ -676,13 +653,7 @@ Create a concise visual description (1-3 sentences, max 100 words). Focus only o
         hasImageData: !!workflowState.picletImage?.imageData,
         hasStats: !!workflowState.picletStats
       });
-      
-      // If in trainer mode, notify failure
-      if (isTrainerMode && onTrainerImageFailed && trainerImagePaths[currentImageIndex]) {
-        const errorMessage = err instanceof Error ? err.message : 'Failed to save piclet';
-        onTrainerImageFailed(trainerImagePaths[currentImageIndex], errorMessage);
-      }
-      
+
       // Don't throw - we don't want to interrupt the workflow
     }
   }
@@ -715,21 +686,6 @@ Create a concise visual description (1-3 sentences, max 100 words). Focus only o
 
 <div class="piclet-generator">
   
-  <!-- Text Generation Client Selector (hidden since only HunyuanTurbos is active) -->
-  <!-- 
-  {#if !isTrainerMode}
-    <div class="client-selector">
-      <label for="text-client">Text Generator:</label>
-      <select id="text-client" bind:value={currentTextClient}>
-        <option value="hunyuan">HunyuanTurbos</option>
-        <option value="command">Command</option>
-        <option value="zephyr">Zephyr-7B</option>
-        <option value="qwen">Qwen3</option>
-        <option value="dots">Dots-Demo</option>
-      </select>
-    </div>
-  {/if}
-  -->
   
   {#if workflowState.currentStep !== 'upload'}
     <WorkflowProgress currentStep={workflowState.currentStep} error={workflowState.error} />