big client swap

src/App.svelte

@@ -18,8 +18,13 @@
   // Gradio client instances
   let fluxClient: GradioClient | null = $state(null);
   let joyCaptionClient: GradioClient | null = $state(null);
-  let zephyrClient: GradioClient | null = $state(null);
-  let qwenClient: GradioClient | null = $state(null);
+  let hunyuanClient: GradioClient | null = $state(null);
+  
+  // Unused clients (kept for future use but not initialized)
+  // let zephyrClient: GradioClient | null = $state(null);
+  // let qwenClient: GradioClient | null = $state(null);
+  // let commandClient: GradioClient | null = $state(null);
+  // let dotsClient: GradioClient | null = $state(null);
   
   // Navigation state
   let activeTab: TabId = $state('scanner');
@@ -97,7 +102,7 @@
     try {
       const opts = hfToken ? { hf_token: hfToken } : {};
       
-      // Connect to all three spaces
+      // Connect to essential spaces only
       fluxClient = await gradioClient.Client.connect(
         "black-forest-labs/FLUX.1-schnell",
         opts
@@ -108,27 +113,43 @@
         opts
       );
       
-      zephyrClient = await gradioClient.Client.connect(
-        "Fraser/zephyr-7b",
+      hunyuanClient = await gradioClient.Client.connect(
+        "tencent/hunyuan-turbos",
         opts
       );
       
-      qwenClient = await gradioClient.Client.connect(
-        "Qwen/Qwen3-Demo",
-        opts
-      );
+      // Unused clients (commented out to save resources)
+      // zephyrClient = await gradioClient.Client.connect(
+      //   "Fraser/zephyr-7b",
+      //   opts
+      // );
+      
+      // qwenClient = await gradioClient.Client.connect(
+      //   "Qwen/Qwen3-Demo",
+      //   opts
+      // );
+      
+      // commandClient = await gradioClient.Client.connect(
+      //   "Fraser/command-a-vision",
+      //   opts
+      // );
+      
+      // dotsClient = await gradioClient.Client.connect(
+      //   "Fraser/dots-demo",
+      //   opts
+      // );
       
       authStore.setBannerMessage("");
       
-      // Set up qwen client reset function
-      setQwenClientResetter(async () => {
-        console.log('🔄 Resetting qwen client connection...');
-        const opts = hfToken ? { hf_token: hfToken } : {};
-        qwenClient = await gradioClient.Client.connect(
-          "Qwen/Qwen3-Demo",
-          opts
-        );
-      });
+      // Qwen client reset function (commented out since qwen is not used)
+      // setQwenClientResetter(async () => {
+      //   console.log('🔄 Resetting qwen client connection...');
+      //   const opts = hfToken ? { hf_token: hfToken } : {};
+      //   qwenClient = await gradioClient.Client.connect(
+      //     "Qwen/Qwen3-Demo",
+      //     opts
+      //   );
+      // });
       
     } catch (err) {
       console.error(err);
@@ -152,8 +173,7 @@
       <Scanner 
         {fluxClient}
         {joyCaptionClient}
-        {zephyrClient}
-        {qwenClient}
+        {hunyuanClient}
       />
     {:else if activeTab === 'encounters'}
       <Encounters />

src/lib/components/AutoTrainerScanner/AutoTrainerScanner.svelte

@@ -11,12 +11,17 @@
   
   interface Props {
     joyCaptionClient: GradioClient;
-    zephyrClient: GradioClient;
     fluxClient: GradioClient;
-    qwenClient: GradioClient;
+    hunyuanClient: GradioClient;
+    
+    // Unused clients (kept for future use)
+    // zephyrClient: GradioClient;
+    // qwenClient: GradioClient;
+    // commandClient: GradioClient;
+    // dotsClient: GradioClient;
   }
   
-  let { joyCaptionClient, zephyrClient, fluxClient, qwenClient }: Props = $props();
+  let { joyCaptionClient, fluxClient, hunyuanClient }: Props = $props();
   
   // Scanner state
   let scanState = $state({
@@ -47,7 +52,7 @@
   
   // Initialize trainer paths on component mount
   $effect(() => {
-    if (joyCaptionClient && zephyrClient && fluxClient) {
+    if (joyCaptionClient && fluxClient && hunyuanClient) {
       loadInitialState();
     }
   });
@@ -332,9 +337,8 @@
   <PicletGenerator 
     bind:this={picletGenerator}
     {joyCaptionClient}
-    {zephyrClient}
     {fluxClient}
-    {qwenClient}
+    {hunyuanClient}
     isTrainerMode={true}
     onTrainerImageCompleted={onTrainerImageCompleted}
     onTrainerImageFailed={onTrainerImageFailed}

src/lib/components/Pages/Scanner.svelte

@@ -6,29 +6,32 @@
   interface Props {
     fluxClient: GradioClient | null;
     joyCaptionClient: GradioClient | null;
-    zephyrClient: GradioClient | null;
-    qwenClient: GradioClient | null;
+    hunyuanClient: GradioClient | null;
+    
+    // Unused clients (kept for future use)
+    // zephyrClient: GradioClient | null;
+    // qwenClient: GradioClient | null;
+    // commandClient: GradioClient | null;
+    // dotsClient: GradioClient | null;
   }
   
-  let { fluxClient, joyCaptionClient, zephyrClient, qwenClient }: Props = $props();
+  let { fluxClient, joyCaptionClient, hunyuanClient }: Props = $props();
 </script>
 
 <div class="scanner-page">
-  {#if fluxClient && joyCaptionClient && zephyrClient && qwenClient}
+  {#if fluxClient && joyCaptionClient && hunyuanClient}
     <!-- Auto Trainer Scanner -->
     <AutoTrainerScanner 
       {joyCaptionClient}
-      {zephyrClient}
       {fluxClient}
-      {qwenClient}
+      {hunyuanClient}
     />
     
     <!-- Manual Piclet Generator -->
     <PicletGenerator 
       {fluxClient}
       {joyCaptionClient}
-      {zephyrClient}
-      {qwenClient}
+      {hunyuanClient}
     />
   {:else}
     <div class="loading-state">

src/lib/components/PicletGenerator/PicletGenerator.svelte

@@ -21,15 +21,106 @@
   
   let { 
     joyCaptionClient, 
-    zephyrClient, 
     fluxClient, 
-    qwenClient,
+    hunyuanClient,
+    
+    // Unused clients (kept for future use)
+    // zephyrClient, 
+    // qwenClient,
+    // commandClient,
+    // dotsClient,
+    
     isTrainerMode = false,
     onTrainerImageCompleted,
     onTrainerImageFailed
   }: Props = $props();
   
-  let state: PicletWorkflowState = $state({
+  // Text generation client management - simplified to only use HunyuanTurbos
+  type TextGenerationClient = 'hunyuan' | 'command' | 'zephyr' | 'qwen' | 'dots';
+  let currentTextClient: TextGenerationClient = $workflowState('hunyuan'); // Fixed to HunyuanTurbos only
+  
+  // Get the active text generation client (now only returns HunyuanTurbos)
+  const getActiveTextClient = () => {
+    return hunyuanClient; // Only HunyuanTurbos is active
+    
+    // Unused client switching (kept for future use)
+    // switch (currentTextClient) {
+    //   case 'hunyuan': return hunyuanClient;
+    //   case 'command': return commandClient;
+    //   case 'zephyr': return zephyrClient;
+    //   case 'qwen': return qwenClient;
+    //   case 'dots': return dotsClient;
+    //   default: return hunyuanClient;
+    // }
+  };
+  
+  // Unified text generation function (simplified to only use HunyuanTurbos)
+  const generateText = async (prompt: string): Promise<string> => {
+    const client = getActiveTextClient();
+    if (!client) {
+      throw new Error(`HunyuanTurbos client is not available`);
+    }
+    
+    console.log(`Generating text with HunyuanTurbos...`);
+    
+    // Use HunyuanTurbos client only
+    const hunyuanResult = await client.predict("/chat", [prompt]);
+    return hunyuanResult.data[0] || '';
+    
+    // Unused client handling (kept for future use)
+    // switch (currentTextClient) {
+    //   case 'hunyuan':
+    //     // HunyuanTurbos client (assuming similar API to other simple clients)
+    //     const hunyuanResult = await client.predict("/chat", [prompt]);
+    //     return hunyuanResult.data[0] || '';
+    //     
+    //   case 'command':
+    //   case 'dots':
+    //     // Command and dots clients use direct predict call (assuming similar to zephyr)
+    //     const result = await client.predict("/chat", [prompt]);
+    //     return result.data[0] || '';
+    //     
+    //   case 'zephyr':
+    //     // Zephyr client uses direct predict call
+    //     const zephyrResult = await client.predict("/chat", [prompt]);
+    //     return zephyrResult.data[0] || '';
+    //     
+    //   case 'qwen':
+    //     // Qwen client uses the complex API with settings and workflowState
+    //     const defaultSettings = {
+    //       "system_prompt": "",
+    //       "max_new_tokens": 2048,
+    //       "temperature": 0.7,
+    //       "top_p": 0.9,
+    //       "top_k": 50,
+    //       "repetition_penalty": 1.05
+    //     };
+    //     
+    //     const defaultState = {
+    //       "messages": [],
+    //       "system": "",
+    //       "tools": null
+    //     };
+    //     
+    //     const thinkingBtnState = {
+    //       "enable_thinking": true
+    //     };
+    //     
+    //     const output = await withQwenTimeout(() => client.predict(13, [
+    //       prompt,
+    //       defaultSettings,
+    //       thinkingBtnState,
+    //       defaultState
+    //     ]));
+    //     
+    //     return output.data[0] || '';
+    //     
+    //   default:
+    //     throw new Error(`Unsupported text client: ${currentTextClient}`);
+    // }
+  };
+  
+  let workflowState: PicletWorkflowState = $state({
     currentStep: 'upload',
     userImage: null,
     imageCaption: null,
@@ -55,15 +146,15 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
   
 
   async function importPiclet(picletData: PicletInstance) {
-    state.isProcessing = true;
-    state.currentStep = 'complete';
+    workflowState.isProcessing = true;
+    workflowState.currentStep = 'complete';
     
     try {
       // Save the imported piclet
       const savedId = await savePicletInstance(picletData);
       
-      // Create a success state similar to generation
-      state.picletImage = {
+      // Create a success workflowState similar to generation
+      workflowState.picletImage = {
         imageUrl: picletData.imageUrl,
         imageData: picletData.imageData,
         seed: 0,
@@ -71,20 +162,20 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
       };
       
       // Show import success
-      state.isProcessing = false;
+      workflowState.isProcessing = false;
       alert(`Successfully imported ${picletData.nickname || picletData.typeId}!`);
       
       // Reset to allow another import/generation
       setTimeout(() => reset(), 2000);
     } catch (error) {
-      state.error = `Failed to import piclet: ${error}`;
-      state.isProcessing = false;
+      workflowState.error = `Failed to import piclet: ${error}`;
+      workflowState.isProcessing = false;
     }
   }
 
   async function handleImageSelected(file: File) {
     if (!joyCaptionClient || !fluxClient) {
-      state.error = "Services not connected. Please wait...";
+      workflowState.error = "Services not connected. Please wait...";
       return;
     }
     
@@ -92,8 +183,8 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
     imageQueue = [];
     currentImageIndex = 0;
     
-    state.userImage = file;
-    state.error = null;
+    workflowState.userImage = file;
+    workflowState.error = null;
     
     // Check if this is a piclet card with metadata
     const picletData = await extractPicletMetadata(file);
@@ -108,7 +199,7 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
   
   async function handleImagesSelected(files: File[]) {
     if (!joyCaptionClient || !fluxClient) {
-      state.error = "Services not connected. Please wait...";
+      workflowState.error = "Services not connected. Please wait...";
       return;
     }
     
@@ -127,8 +218,8 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
     }
     
     const currentFile = imageQueue[currentImageIndex];
-    state.userImage = currentFile;
-    state.error = null;
+    workflowState.userImage = currentFile;
+    workflowState.error = null;
     
     // Check if this is a piclet card with metadata
     const picletData = await extractPicletMetadata(currentFile);
@@ -165,24 +256,24 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
   }
   
   async function startWorkflow() {
-    state.isProcessing = true;
+    workflowState.isProcessing = true;
     
     try {
       // Step 1: Generate detailed object description with joy-caption
       await captionImage();
-      await new Promise(resolve => setTimeout(resolve, 100)); // Small delay for state update
+      await new Promise(resolve => setTimeout(resolve, 100)); // Small delay for workflowState update
       
       // Step 2: Generate free-form monster concept with qwen3
       await generateConcept();
-      await new Promise(resolve => setTimeout(resolve, 100)); // Small delay for state update
+      await new Promise(resolve => setTimeout(resolve, 100)); // Small delay for workflowState update
       
       // Step 3: Generate structured monster stats based on both caption and concept
       await generateStats();
-      await new Promise(resolve => setTimeout(resolve, 100)); // Small delay for state update
+      await new Promise(resolve => setTimeout(resolve, 100)); // Small delay for workflowState update
       
       // Step 4: Generate image prompt with qwen3
       await generateImagePrompt();
-      await new Promise(resolve => setTimeout(resolve, 100)); // Small delay for state update
+      await new Promise(resolve => setTimeout(resolve, 100)); // Small delay for workflowState update
       
       // Step 5: Generate monster image
       await generateMonsterImage();
@@ -190,7 +281,7 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
       // Step 6: Auto-save the piclet as uncaught
       await autoSavePiclet();
       
-      state.currentStep = 'complete';
+      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) {
@@ -203,17 +294,17 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
       if (err && typeof err === 'object' && 'message' in err) {
         const errorMessage = String(err.message);
         if (errorMessage.includes('exceeded your GPU quota') || errorMessage.includes('GPU quota')) {
-          state.error = 'GPU quota exceeded! You need to sign in with Hugging Face for free GPU time, or upgrade to Hugging Face Pro for more quota.';
+          workflowState.error = 'GPU quota exceeded! You need to sign in with Hugging Face for free GPU time, or upgrade to Hugging Face Pro for more quota.';
         } else {
-          state.error = errorMessage;
+          workflowState.error = errorMessage;
         }
       } else if (err instanceof Error) {
-        state.error = err.message;
+        workflowState.error = err.message;
       } else {
-        state.error = 'An unknown error occurred';
+        workflowState.error = 'An unknown error occurred';
       }
     } finally {
-      state.isProcessing = false;
+      workflowState.isProcessing = false;
     }
   }
   
@@ -242,15 +333,15 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
   }
   
   async function captionImage() {
-    state.currentStep = 'captioning';
+    workflowState.currentStep = 'captioning';
     
-    if (!joyCaptionClient || !state.userImage) {
+    if (!joyCaptionClient || !workflowState.userImage) {
       throw new Error('Caption service not available or no image provided');
     }
     
     try {
       const output = await joyCaptionClient.predict("/stream_chat", [
-        state.userImage,  // input_image
+        workflowState.userImage,  // input_image
         "Descriptive",  // caption_type
         "long",  // caption_length
         [],  // extra_options
@@ -260,7 +351,7 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
       
       const [, caption] = output.data;
       // Store the detailed object description
-      state.imageCaption = caption;
+      workflowState.imageCaption = caption;
       console.log('Detailed object description generated:', caption);
     } catch (error) {
       handleAPIError(error);
@@ -268,15 +359,16 @@ Focus on: colors, body shape, eyes, limbs, mouth, and key visual features. Omit
   }
   
   async function generateConcept() {
-    state.currentStep = 'conceptualizing';
+    workflowState.currentStep = 'conceptualizing';
     
-    if (!qwenClient || !state.imageCaption) {
-      throw new Error('Qwen service not available or no image caption provided');
+    const activeClient = getActiveTextClient();
+    if (!activeClient || !workflowState.imageCaption) {
+      throw new Error(`${currentTextClient} service not available or no image caption provided`);
     }
     
     const conceptPrompt = `Based on this detailed object description, create a Pokémon-style monster that transforms the object into an imaginative creature. The monster should clearly be inspired by the object's appearance but reimagined as a living monster.
 
-Object description: "${state.imageCaption}"
+Object description: "${workflowState.imageCaption}"
 
 Guidelines:
 - Take the object's key visual elements (colors, shapes, materials) incorporating all of them into a single creature design
@@ -297,7 +389,7 @@ Format your response exactly as follows:
 {Detailed physical description showing how the object becomes a creature. Ensure the creature uses all the unique attributes of the object. Include colors, shapes, materials, eyes, limbs, mouth, and distinctive features. This section should be comprehensive as it will be used for both stats generation and image creation.}`;
     
     try {
-      // Create the required state structure based on qwen.html
+      // Create the required workflowState structure based on qwen.html
       const defaultState = {
         "conversation_contexts": {},
         "conversations": [],
@@ -311,56 +403,18 @@ Format your response exactly as follows:
         "thinking_budget": 1
       };
       
-      // Create thinking button state
+      // Create thinking button workflowState
       const thinkingBtnState = {
         "enable_thinking": true
       };
       
-      console.log('Generating monster concept with qwen3...');
-      
-      // Call the add_message function (fn_index 13)
-      const output = await withQwenTimeout(() => qwenClient.predict(13, [
-        conceptPrompt,          // input_value
-        defaultSettings,        // settings_form_value  
-        thinkingBtnState,       // thinking_btn_state_value
-        defaultState            // state_value
-      ]));
-      
-      console.log('Qwen3 concept response:', output);
-      
-      // Extract the response text from the output
-      let responseText = "";
-      if (output && output.data && Array.isArray(output.data)) {
-        // The chatbot response is at index 5 in the outputs array
-        const chatbotUpdate = output.data[5];
-        
-        if (chatbotUpdate && chatbotUpdate.value && Array.isArray(chatbotUpdate.value)) {
-          const chatHistory = chatbotUpdate.value;
-          
-          if (chatHistory.length > 0) {
-            // Get the last message (assistant's response)
-            const lastMessage = chatHistory[chatHistory.length - 1];
-            
-            if (lastMessage && lastMessage.content && Array.isArray(lastMessage.content)) {
-              // Extract text content from the message
-              const textContents = lastMessage.content
-                .filter((item: any) => item.type === "text")
-                .map((item: any) => item.content)
-                .join("\n");
-              responseText = textContents || "Response received but no text content found";
-            } else if (lastMessage && lastMessage.role === "assistant") {
-              // Fallback - if content structure is different
-              responseText = JSON.stringify(lastMessage, null, 2);
-            }
-          }
-        }
-      }
+      const responseText = await generateText(conceptPrompt);
       
       if (!responseText || responseText.trim() === '') {
         throw new Error('Failed to generate monster concept');
       }
       
-      state.picletConcept = responseText;
+      workflowState.picletConcept = responseText;
       console.log('Monster concept generated:', responseText);
     } catch (error) {
       handleAPIError(error);
@@ -368,18 +422,19 @@ Format your response exactly as follows:
   }
   
   async function generateImagePrompt() {
-    state.currentStep = 'promptCrafting';
+    workflowState.currentStep = 'promptCrafting';
     
-    if (!qwenClient || !state.picletConcept || !state.imageCaption) {
-      throw new Error('Qwen service not available or no concept/caption available for prompt generation');
+    const activeClient = getActiveTextClient();
+    if (!activeClient || !workflowState.picletConcept || !workflowState.imageCaption) {
+      throw new Error(`HunyuanTurbos service not available or no concept/caption available for prompt generation`);
     }
     
     // Extract the Monster Visual Description from the structured concept
-    const visualDescMatch = state.picletConcept.match(/## Monster Visual Description\s*\n([\s\S]*?)(?=##|$)/);
+    const visualDescMatch = workflowState.picletConcept.match(/## Monster Visual Description\s*\n([\s\S]*?)(?=##|$)/);
     
     if (visualDescMatch && visualDescMatch[1]) {
-      state.imagePrompt = visualDescMatch[1].trim();
-      console.log('Extracted visual description for image generation:', state.imagePrompt);
+      workflowState.imagePrompt = visualDescMatch[1].trim();
+      console.log('Extracted visual description for image generation:', workflowState.imagePrompt);
       return; // Skip qwen3 call since we have the description
     }
     
@@ -388,13 +443,13 @@ Format your response exactly as follows:
 
 MONSTER CONCEPT:
 """
-${state.picletConcept}
+${workflowState.picletConcept}
 """
 
 Create a concise visual description (1-3 sentences, max 100 words). Focus only on colors, shapes, materials, eyes, limbs, mouth, and distinctive features. Omit all non-visual information like abilities and backstory.`;
     
     try {
-      // Create the required state structure based on qwen.html
+      // Create the required workflowState structure based on qwen.html
       const defaultState = {
         "conversation_contexts": {},
         "conversations": [],
@@ -408,73 +463,35 @@ Create a concise visual description (1-3 sentences, max 100 words). Focus only o
         "thinking_budget": 1
       };
       
-      // Create thinking button state
+      // Create thinking button workflowState
       const thinkingBtnState = {
         "enable_thinking": true
       };
       
-      console.log('Generating image prompt with qwen3...');
-      
-      // Call the add_message function (fn_index 13)
-      const output = await withQwenTimeout(() => qwenClient.predict(13, [
-        imagePromptPrompt,      // input_value
-        defaultSettings,        // settings_form_value  
-        thinkingBtnState,       // thinking_btn_state_value
-        defaultState            // state_value
-      ]));
-      
-      console.log('Qwen3 image prompt response:', output);
-      
-      // Extract the response text from the output using the same pattern as generateConcept
-      let responseText = "";
-      if (output && output.data && Array.isArray(output.data)) {
-        // The chatbot response is at index 5 in the outputs array
-        const chatbotUpdate = output.data[5];
-        
-        if (chatbotUpdate && chatbotUpdate.value && Array.isArray(chatbotUpdate.value)) {
-          const chatHistory = chatbotUpdate.value;
-          
-          if (chatHistory.length > 0) {
-            // Get the last message (assistant's response)
-            const lastMessage = chatHistory[chatHistory.length - 1];
-            
-            if (lastMessage && lastMessage.content && Array.isArray(lastMessage.content)) {
-              // Extract text content from the message
-              const textContents = lastMessage.content
-                .filter((item: any) => item.type === "text")
-                .map((item: any) => item.content)
-                .join("\n");
-              responseText = textContents || "Response received but no text content found";
-            } else if (lastMessage && lastMessage.role === "assistant") {
-              // Fallback - if content structure is different
-              responseText = JSON.stringify(lastMessage, null, 2);
-            }
-          }
-        }
-      }
+      const responseText = await generateText(imagePromptPrompt);
       
       if (!responseText || responseText.trim() === '') {
         throw new Error('Failed to generate image prompt');
       }
       
-      state.imagePrompt = responseText.trim();
-      console.log('Image prompt generated:', state.imagePrompt);
+      workflowState.imagePrompt = responseText.trim();
+      console.log('Image prompt generated:', workflowState.imagePrompt);
     } catch (error) {
       handleAPIError(error);
     }
   }
   
   async function generateMonsterImage() {
-    state.currentStep = 'generating';
+    workflowState.currentStep = 'generating';
     
-    if (!fluxClient || !state.imagePrompt || !state.picletStats) {
+    if (!fluxClient || !workflowState.imagePrompt || !workflowState.picletStats) {
       throw new Error('Image generation service not available or no prompt/stats');
     }
     
     // The image prompt should already be generated by generateImagePrompt() in the workflow
     
     // Get tier for image quality enhancement
-    const tier = state.picletStats.tier || 'medium';
+    const tier = workflowState.picletStats.tier || 'medium';
     const tierDescriptions = {
       low: 'simple and basic design',
       medium: 'detailed and well-crafted design', 
@@ -484,7 +501,7 @@ Create a concise visual description (1-3 sentences, max 100 words). Focus only o
     
     try {
       const output = await fluxClient.predict("/infer", [
-        `${state.imagePrompt}\nNow generate a Pokémon-Anime-style image of the monster in an idle pose with a plain white background. This is a ${tier} tier monster with ${tierDescriptions[tier as keyof typeof tierDescriptions]}. The monster should not be attacking or in motion. The full monster must be visible within the frame.`,
+        `${workflowState.imagePrompt}\nNow generate a Pokémon-Anime-style image of the monster in an idle pose with a plain white background. This is a ${tier} tier monster with ${tierDescriptions[tier as keyof typeof tierDescriptions]}. The monster should not be attacking or in motion. The full monster must be visible within the frame.`,
         0,      // seed
         true,   // randomizeSeed
         1024,   // width
@@ -504,20 +521,20 @@ Create a concise visual description (1-3 sentences, max 100 words). Focus only o
         console.log('Processing image for background removal...');
         try {
           const transparentBase64 = await removeBackground(url);
-          state.picletImage = {
+          workflowState.picletImage = {
             imageUrl: url,
             imageData: transparentBase64,
             seed: usedSeed,
-            prompt: state.imagePrompt
+            prompt: workflowState.imagePrompt
           };
           console.log('Background removal completed successfully');
         } catch (processError) {
           console.error('Failed to process image for background removal:', processError);
           // Fallback to original image
-          state.picletImage = {
+          workflowState.picletImage = {
             imageUrl: url,
             seed: usedSeed,
-            prompt: state.imagePrompt
+            prompt: workflowState.imagePrompt
           };
         }
       } else {
@@ -529,30 +546,31 @@ Create a concise visual description (1-3 sentences, max 100 words). Focus only o
   }
   
   async function generateStats() {
-    state.currentStep = 'statsGenerating';
+    workflowState.currentStep = 'statsGenerating';
     
-    if (!qwenClient || !state.picletConcept || !state.imageCaption) {
-      throw new Error('Qwen service not available or no concept/caption available for stats generation');
+    const activeClient = getActiveTextClient();
+    if (!activeClient || !workflowState.picletConcept || !workflowState.imageCaption) {
+      throw new Error(`${currentTextClient} service not available or no concept/caption available for stats generation`);
     }
     
     // Default tier (will be set from the generated stats)
     let tier: 'low' | 'medium' | 'high' | 'legendary' = 'medium';
     
     // Extract monster name and rarity from the structured concept
-    const monsterNameMatch = state.picletConcept.match(/# Monster Name\s*\n([\s\S]*?)(?=^##|$)/m);
+    const monsterNameMatch = workflowState.picletConcept.match(/# Monster Name\s*\n([\s\S]*?)(?=^##|$)/m);
     const monsterName = monsterNameMatch ? monsterNameMatch[1].trim() : 'Unknown Monster';
     
-    const rarityMatch = state.picletConcept.match(/# Object Rarity\s*\n([\s\S]*?)(?=^#)/m);
+    const rarityMatch = workflowState.picletConcept.match(/# Object Rarity\s*\n([\s\S]*?)(?=^#)/m);
     const objectRarity = rarityMatch ? rarityMatch[1].trim().toLowerCase() : 'common';
     
     // Create comprehensive battle-ready monster prompt
     const statsPrompt = `Based on this detailed object description and monster concept, create a complete battle-ready monster for the Pictuary Battle System:
 
 ORIGINAL OBJECT DESCRIPTION:
-"${state.imageCaption}"
+"${workflowState.imageCaption}"
 
 MONSTER CONCEPT:
-"${state.picletConcept}"
+"${workflowState.picletConcept}"
 
 The object rarity has been assessed as: ${objectRarity}
 
@@ -758,7 +776,7 @@ Write your response within \`\`\`json\`\`\``;
     console.log('Generating monster stats with qwen3');
     
     try {
-      // Create the required state structure based on qwen.html
+      // Create the required workflowState structure based on qwen.html
       const defaultState = {
         "conversation_contexts": {},
         "conversations": [],
@@ -772,58 +790,12 @@ Write your response within \`\`\`json\`\`\``;
         "thinking_budget": 1
       };
       
-      // Create thinking button state
+      // Create thinking button workflowState
       const thinkingBtnState = {
         "enable_thinking": true
       };
       
-      // Call the add_message function (fn_index 13)
-      const output = await withQwenTimeout(() => qwenClient.predict(13, [
-        statsPrompt,            // input_value
-        defaultSettings,        // settings_form_value  
-        thinkingBtnState,       // thinking_btn_state_value
-        defaultState            // state_value
-      ]));
-      
-      console.log('Qwen3 stats response:', output);
-      
-      // Extract the response text from the output using the same pattern as generateConcept
-      let responseText = "";
-      if (output && output.data && Array.isArray(output.data)) {
-        // The chatbot response is at index 5 in the outputs array
-        const chatbotUpdate = output.data[5];
-        
-        if (chatbotUpdate && chatbotUpdate.value && Array.isArray(chatbotUpdate.value)) {
-          const chatHistory = chatbotUpdate.value;
-          
-          if (chatHistory.length > 0) {
-            // Get the last message (assistant's response)
-            const lastMessage = chatHistory[chatHistory.length - 1];
-            
-            console.log('Full message structure:', JSON.stringify(lastMessage, null, 2));
-            
-            if (lastMessage && lastMessage.content && Array.isArray(lastMessage.content)) {
-              // Extract ALL text content from the message more robustly
-              const textContents = lastMessage.content
-                .filter((item: any) => item.type === "text")
-                .map((item: any) => {
-                  console.log('Content item:', item);
-                  return item.content || '';
-                })
-                .join("");  // Join without separator to avoid breaking JSON
-              responseText = textContents || "Response received but no text content found";
-              console.log('Extracted text length:', responseText.length);
-              console.log('Extracted text preview:', responseText.substring(0, 200) + '...');
-            } else if (lastMessage && typeof lastMessage === 'string') {
-              // Handle case where the message is a plain string
-              responseText = lastMessage;
-            } else if (lastMessage && lastMessage.role === "assistant") {
-              // Fallback - if content structure is different
-              responseText = JSON.stringify(lastMessage, null, 2);
-            }
-          }
-        }
-      }
+      const responseText = await generateText(statsPrompt);
       
       if (!responseText || responseText.trim() === '') {
         throw new Error('Failed to generate monster stats');
@@ -939,7 +911,7 @@ Write your response within \`\`\`json\`\`\``;
         }
         
         const stats: PicletStats = parsedStats;
-        state.picletStats = stats;
+        workflowState.picletStats = stats;
         console.log('Monster stats generated:', stats);
         console.log('Monster stats JSON:', JSON.stringify(stats, null, 2));
       } catch (parseError) {
@@ -952,22 +924,22 @@ Write your response within \`\`\`json\`\`\``;
   }
   
   async function autoSavePiclet() {
-    if (!state.picletImage || !state.imageCaption || !state.picletConcept || !state.imagePrompt || !state.picletStats) {
+    if (!workflowState.picletImage || !workflowState.imageCaption || !workflowState.picletConcept || !workflowState.imagePrompt || !workflowState.picletStats) {
       console.error('Cannot auto-save: missing required data');
       return;
     }
     
     try {
       // Create a clean copy of stats to ensure it's serializable
-      const cleanStats = JSON.parse(JSON.stringify(state.picletStats));
+      const cleanStats = JSON.parse(JSON.stringify(workflowState.picletStats));
       
       const picletData = {
-        name: state.picletStats.name,
-        imageUrl: state.picletImage.imageUrl,
-        imageData: state.picletImage.imageData,
-        imageCaption: state.imageCaption,
-        concept: state.picletConcept,
-        imagePrompt: state.imagePrompt,
+        name: workflowState.picletStats.name,
+        imageUrl: workflowState.picletImage.imageUrl,
+        imageData: workflowState.picletImage.imageData,
+        imageCaption: workflowState.imageCaption,
+        concept: workflowState.picletConcept,
+        imagePrompt: workflowState.imagePrompt,
         stats: cleanStats,
         createdAt: new Date()
       };
@@ -994,10 +966,10 @@ Write your response within \`\`\`json\`\`\``;
     } catch (err) {
       console.error('Failed to auto-save piclet:', err);
       console.error('Piclet data that failed to save:', {
-        name: state.picletStats?.name,
-        hasImageUrl: !!state.picletImage?.imageUrl,
-        hasImageData: !!state.picletImage?.imageData,
-        hasStats: !!state.picletStats
+        name: workflowState.picletStats?.name,
+        hasImageUrl: !!workflowState.picletImage?.imageUrl,
+        hasImageData: !!workflowState.picletImage?.imageData,
+        hasStats: !!workflowState.picletStats
       });
       
       // If in trainer mode, notify failure
@@ -1011,7 +983,7 @@ Write your response within \`\`\`json\`\`\``;
   }
   
   function reset() {
-    state = {
+    workflowState = {
       currentStep: 'upload',
       userImage: null,
       imageCaption: null,
@@ -1030,7 +1002,7 @@ Write your response within \`\`\`json\`\`\``;
     trainerImagePaths.push(imagePath);
     
     // If this is the first image and we're not processing, start processing
-    if (imageQueue.length === 1 && !state.isProcessing) {
+    if (imageQueue.length === 1 && !workflowState.isProcessing) {
       processCurrentImage();
     }
   }
@@ -1038,33 +1010,49 @@ Write your response within \`\`\`json\`\`\``;
 
 <div class="piclet-generator">
   
-  {#if state.currentStep !== 'upload'}
-    <WorkflowProgress currentStep={state.currentStep} error={state.error} />
+  <!-- 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} />
   {/if}
   
-  {#if state.currentStep === 'upload'}
+  {#if workflowState.currentStep === 'upload'}
     <UploadStep 
       onImageSelected={handleImageSelected}
       onImagesSelected={handleImagesSelected}
-      isProcessing={state.isProcessing}
+      isProcessing={workflowState.isProcessing}
       imageQueue={imageQueue}
       currentImageIndex={currentImageIndex}
     />
-  {:else if state.currentStep === 'complete'}
-    <PicletResult workflowState={state} onReset={reset} />
+  {:else if workflowState.currentStep === 'complete'}
+    <PicletResult workflowState={workflowState} onReset={reset} />
   {:else}
     <div class="processing-container">
       <div class="spinner"></div>
       <p class="processing-text">
-        {#if state.currentStep === 'captioning'}
+        {#if workflowState.currentStep === 'captioning'}
           Analyzing your image...
-        {:else if state.currentStep === 'conceptualizing'}
+        {:else if workflowState.currentStep === 'conceptualizing'}
           Creating Piclet concept...
-        {:else if state.currentStep === 'statsGenerating'}
+        {:else if workflowState.currentStep === 'statsGenerating'}
           Generating battle stats...
-        {:else if state.currentStep === 'promptCrafting'}
+        {:else if workflowState.currentStep === 'promptCrafting'}
           Creating image prompt...
-        {:else if state.currentStep === 'generating'}
+        {:else if workflowState.currentStep === 'generating'}
           Generating your Piclet...
         {/if}
       </p>
@@ -1080,6 +1068,34 @@ Write your response within \`\`\`json\`\`\``;
     padding: 2rem;
   }
   
+  /* Client selector styles (hidden since only HunyuanTurbos is active) */
+  /*
+  .client-selector {
+    display: flex;
+    align-items: center;
+    gap: 0.5rem;
+    margin-bottom: 1rem;
+    padding: 0.75rem;
+    background: #f8f9fa;
+    border-radius: 8px;
+    border: 1px solid #dee2e6;
+  }
+  
+  .client-selector label {
+    font-weight: 500;
+    color: #495057;
+  }
+  
+  .client-selector select {
+    padding: 0.25rem 0.5rem;
+    border: 1px solid #ced4da;
+    border-radius: 4px;
+    background: white;
+    color: #495057;
+    font-size: 0.9rem;
+  }
+  */
+  
   
   .processing-container {
     display: flex;

src/lib/types/index.ts

@@ -98,9 +98,14 @@ export interface PicletWorkflowState {
 
 export interface PicletGeneratorProps {
   joyCaptionClient: GradioClient | null;
-  zephyrClient: GradioClient | null;
   fluxClient: GradioClient | null;
-  qwenClient: GradioClient | null;
+  hunyuanClient: GradioClient | null;
+  
+  // Unused clients (kept for future use)
+  // zephyrClient: GradioClient | null;
+  // qwenClient: GradioClient | null;
+  // commandClient: GradioClient | null;
+  // dotsClient: GradioClient | null;
 }
 
 // Piclet Stats Types - now compatible with battle engine