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openvoice_app.py

@@ -6,88 +6,45 @@ import langid
 from openvoice import se_extractor
 from openvoice.api import BaseSpeakerTTS, ToneColorConverter
 from dotenv import load_dotenv
+from openai import OpenAI
+from elevenlabs.client import ElevenLabs
+from elevenlabs import play,save
+load_dotenv()
 
 # Argument parsing
 parser = argparse.ArgumentParser()
 parser.add_argument("--share", action='store_true', default=False, help="make link public")
 args = parser.parse_args()
-load_dotenv()
-
-# Paths and device setup
-en_ckpt_base = 'base_speakers/EN'
-zh_ckpt_base = 'base_speakers/ZH'
-ckpt_converter = 'converter'
+client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
+client = ElevenLabs(api_key=os.environ.get("ELEVENLABS_API_KEY"))
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
 output_dir = 'outputs'
 os.makedirs(output_dir, exist_ok=True)
 
-# Load models
-en_base_speaker_tts = BaseSpeakerTTS(f'{en_ckpt_base}/config.json', device=device)
-en_base_speaker_tts.load_ckpt(f'{en_ckpt_base}/checkpoint.pth')
-zh_base_speaker_tts = BaseSpeakerTTS(f'{zh_ckpt_base}/config.json', device=device)
-zh_base_speaker_tts.load_ckpt(f'{zh_ckpt_base}/checkpoint.pth')
-tone_color_converter = ToneColorConverter(f'{ckpt_converter}/config.json', device=device)
-tone_color_converter.load_ckpt(f'{ckpt_converter}/checkpoint.pth')
-
-# Load speaker embeddings
-en_source_default_se = torch.load(f'{en_ckpt_base}/en_default_se.pth').to(device)
-en_source_style_se = torch.load(f'{en_ckpt_base}/en_style_se.pth').to(device)
-zh_source_se = torch.load(f'{zh_ckpt_base}/zh_default_se.pth').to(device)
 
-# Supported languages
 supported_languages = ['zh', 'en']
 
 def predict(prompt, style, audio_file_pth):
     text_hint = ''
-
-    # Detect the input language
-    language_predicted = langid.classify(prompt)[0].strip()
-    print(f"Detected language: {language_predicted}")
-
-    if language_predicted not in supported_languages:
-        text_hint += f"[ERROR] The detected language {language_predicted} is not supported. Supported languages: {supported_languages}\n"
-        return text_hint, None, None
-
-    if language_predicted == "zh":
-        tts_model = zh_base_speaker_tts
-        source_se = zh_source_se
-        language = 'Chinese'
-        if style != 'default':
-            text_hint += f"[ERROR] The style {style} is not supported for Chinese. Supported style: 'default'\n"
-            return text_hint, None, None
-    else:
-        tts_model = en_base_speaker_tts
-        source_se = en_source_default_se if style == 'default' else en_source_style_se
-        language = 'English'
-        if style not in ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']:
-            text_hint += f"[ERROR] The style {style} is not supported for English. Supported styles: ['default', 'whispering', 'shouting', 'excited', 'cheerful', 'terrified', 'angry', 'sad', 'friendly']\n"
-            return text_hint, None, None
-
     if len(prompt) < 2:
         text_hint += "[ERROR] Please provide a longer prompt text.\n"
         return text_hint, None, None
     if len(prompt) > 200:
         text_hint += "[ERROR] Text length limited to 200 characters. Please try shorter text.\n"
         return text_hint, None, None
-
-    try:
-        target_se, audio_name = se_extractor.get_se(audio_file_pth, tone_color_converter, target_dir='processed', vad=True)
-    except Exception as e:
-        text_hint += f"[ERROR] Error extracting tone color: {str(e)}\n"
-        return text_hint, None, None
-
-    src_path = f'{output_dir}/tmp.wav'
-    tts_model.tts(prompt, src_path, speaker=style, language=language)
-
-    save_path = f'{output_dir}/output.wav'
-    encode_message = "@MyShell"
-    tone_color_converter.convert(audio_src_path=src_path, src_se=source_se, tgt_se=target_se, output_path=save_path, message=encode_message)
-
-    text_hint += "Response generated successfully.\n"
+    
+    print(audio_file_pth)
+    voice = client.clone(
+        name="TrialVoice",
+        description="A trial voice model for testing",
+        files=[audio_file_pth],
+    )
+    #text should be prompt
+    audio = client.generate(text=prompt, voice=voice)
+    save(audio, "result.mp3")
+    save_path="result.mp3"
     return text_hint, save_path, audio_file_pth
 
-title = "MyShell OpenVoice"
-
 # Gradio interface setup
 with gr.Blocks(gr.themes.Glass()) as demo:
     with gr.Row():
@@ -123,3 +80,4 @@ demo.launch(debug=True, show_api=False, share=args.share)
 
 # Hide Gradio footer
 css = "footer {visibility: hidden}"
+