fix: pass language parameter to Qwen TTS models and sync form with profile language

Both PyTorch and MLX backends silently dropped the language parameter —
it was accepted by generate() but never forwarded to the underlying
Qwen3-TTS model, causing it to default to auto-detection which
frequently confuses similar languages (e.g. Portuguese for Spanish).

- Add LANGUAGE_CODE_TO_NAME mapping (ISO 639-1 to full name) to both backends
- PyTorch: pass language= to generate_voice_clone()
- MLX: pass lang_code= to all 4 model.generate() call sites
- Frontend: auto-sync generation form language with selected voice profile

Closes #97

app/src/components/Generation/FloatingGenerateBox.tsx

@@ -13,7 +13,7 @@ import {
 } from '@/components/ui/select';
 import { Textarea } from '@/components/ui/textarea';
 import { useToast } from '@/components/ui/use-toast';
-import { getLanguageOptionsForEngine } from '@/lib/constants/languages';
+import { getLanguageOptionsForEngine, type LanguageCode } from '@/lib/constants/languages';
 import { useGenerationForm } from '@/lib/hooks/useGenerationForm';
 import { useProfile, useProfiles } from '@/lib/hooks/useProfiles';
 import { useAddStoryItem, useStory } from '@/lib/hooks/useStories';
@@ -112,6 +112,13 @@ export function FloatingGenerateBox({
     }
   }, [selectedProfileId, profiles, setSelectedProfileId]);
 
+  // Sync generation form language with selected profile's language
+  useEffect(() => {
+    if (selectedProfile?.language) {
+      form.setValue('language', selectedProfile.language as LanguageCode);
+    }
+  }, [selectedProfile, form]);
+
   // Auto-resize textarea based on content (only when expanded)
   useEffect(() => {
     if (!isExpanded) {
@@ -344,9 +351,7 @@ export function FloatingGenerateBox({
                               : 'bg-card border border-border hover:bg-background/50',
                           )}
                           aria-label={
-                            isInstructMode
-                              ? 'Fine tune instructions, on'
-                              : 'Fine tune instructions'
+                            isInstructMode ? 'Fine tune instructions, on' : 'Fine tune instructions'
                           }
                         >
                           <SlidersHorizontal className="h-4 w-4" />

backend/backends/mlx_backend.py

@@ -21,6 +21,12 @@ from ..utils.progress import get_progress_manager
 from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
 from ..utils.tasks import get_task_manager
 
+LANGUAGE_CODE_TO_NAME = {
+    "zh": "chinese", "en": "english", "ja": "japanese", "ko": "korean",
+    "de": "german", "fr": "french", "ru": "russian", "pt": "portuguese",
+    "es": "spanish", "it": "italian",
+}
+
 
 class MLXTTSBackend:
     """MLX-based TTS backend using mlx-audio."""
@@ -343,7 +349,8 @@ class MLXTTSBackend:
             # MLX generate() returns a generator yielding GenerationResult objects
             audio_chunks = []
             sample_rate = 24000
-            
+            lang = LANGUAGE_CODE_TO_NAME.get(language, "auto")
+
             # Set seed if provided (MLX uses numpy random)
             if seed is not None:
                 import mlx.core as mx
@@ -371,23 +378,23 @@ class MLXTTSBackend:
                     sig = inspect.signature(self.model.generate)
                     if "ref_audio" in sig.parameters:
                         # Generate with voice cloning
-                        for result in self.model.generate(text, ref_audio=ref_audio, ref_text=ref_text):
+                        for result in self.model.generate(text, ref_audio=ref_audio, ref_text=ref_text, lang_code=lang):
                             audio_chunks.append(np.array(result.audio))
                             sample_rate = result.sample_rate
                     else:
                         # Fallback: generate without voice cloning
-                        for result in self.model.generate(text):
+                        for result in self.model.generate(text, lang_code=lang):
                             audio_chunks.append(np.array(result.audio))
                             sample_rate = result.sample_rate
                 else:
                     # No voice prompt, generate normally
-                    for result in self.model.generate(text):
+                    for result in self.model.generate(text, lang_code=lang):
                         audio_chunks.append(np.array(result.audio))
                         sample_rate = result.sample_rate
             except Exception as e:
                 # If voice cloning fails, try without it
                 print(f"Warning: Voice cloning failed, generating without voice prompt: {e}")
-                for result in self.model.generate(text):
+                for result in self.model.generate(text, lang_code=lang):
                     audio_chunks.append(np.array(result.audio))
                     sample_rate = result.sample_rate
             

backend/backends/pytorch_backend.py

@@ -15,6 +15,12 @@ from ..utils.progress import get_progress_manager
 from ..utils.hf_progress import HFProgressTracker, create_hf_progress_callback
 from ..utils.tasks import get_task_manager
 
+LANGUAGE_CODE_TO_NAME = {
+    "zh": "chinese", "en": "english", "ja": "japanese", "ko": "korean",
+    "de": "german", "fr": "french", "ru": "russian", "pt": "portuguese",
+    "es": "spanish", "it": "italian",
+}
+
 
 class PyTorchTTSBackend:
     """PyTorch-based TTS backend using Qwen3-TTS."""
@@ -359,6 +365,7 @@ class PyTorchTTSBackend:
             wavs, sample_rate = self.model.generate_voice_clone(
                 text=text,
                 voice_clone_prompt=voice_prompt,
+                language=LANGUAGE_CODE_TO_NAME.get(language, "auto"),
                 instruct=instruct,
             )
             return wavs[0], sample_rate