Update app.py

app.py

@@ -1,245 +1,85 @@
-#!/usr/bin/env python3
-#
-# Copyright      2022-2023  Xiaomi Corp.        (authors: Fangjun Kuang)
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
 import logging
 import os
-import time
 import uuid
-
+import time
 import gradio as gr
 import soundfile as sf
 
 from model import get_pretrained_model, language_to_models
 
-title = "# Next-gen Kaldi: Text-to-speech (TTS)"
-
-description = """
-This space shows how to convert text to speech with Next-gen Kaldi.
-It is running on CPU within a docker container provided by Hugging Face.
-See more information by visiting the following links:
-- <https://github.com/k2-fsa/sherpa-onnx>
-If you want to deploy it locally, please see
-<https://k2-fsa.github.io/sherpa/>
-If you want to use Android APKs, please see
-<https://k2-fsa.github.io/sherpa/onnx/tts/apk.html>
-If you want to use Android text-to-speech engine APKs, please see
-<https://k2-fsa.github.io/sherpa/onnx/tts/apk-engine.html>
-If you want to download an all-in-one exe for Windows, please see
-<https://github.com/k2-fsa/sherpa-onnx/releases/tag/tts-models>
-"""
-
-css = """
-.result {display:flex;flex-direction:column}
-.result_item {padding:15px;margin-bottom:8px;border-radius:15px;width:100%}
-.result_item_success {background-color:mediumaquamarine;color:white;align-self:start}
-.result_item_error {background-color:#ff7070;color:white;align-self:start}
-"""
-
-examples = [
-    [
-        "Chinese (Mandarin, 普通话)",
-        "csukuangfj/vits-zh-hf-fanchen-wnj|1",
-        "在一个阳光明媚的夏天，小马、小羊和小狗它们一块儿在广阔的草地上，嬉戏玩耍，这时小猴来了，还带着它心爱的足球活蹦乱跳地跑前、跑后教小马、小羊、小狗踢足球。",
-        0,
-        1.0,
-    ],
-    [
-        "Chinese (Mandarin, 普通话)",
-        "csukuangfj/vits-zh-hf-fanchen-C|187",
-        '小米的使命是，始终坚持做"感动人心、价格厚道"的好产品，让全球每个人都能享受科技带来的美好生活。',
-        0,
-        1.0,
-    ],
-    ["Min-nan (闽南话)", "csukuangfj/vits-mms-nan", "ài piaǸ chiah ē iaN̂", 0, 1.0],
-    ["Thai", "csukuangfj/vits-mms-tha", "ฉันรักคุณ", 0, 1.0],
-    [
-        "Chinese (Mandarin, 普通话)",
-        "csukuangfj/sherpa-onnx-vits-zh-ll|5",
-        "当夜幕降临，星光点点，伴随着微风拂面，我在静谧中感受着时光的流转，思念如涟漪荡漾，梦境如画卷展开，我与自然融为一体，沉静在这片宁静的美丽之中，感受着生命的奇迹与温柔。",
-        2,
-        1.0,
-    ],
-]
-
-
-def update_model_dropdown(language: str):
+# Function to update model dropdown based on language selection
+def update_model_dropdown(language):
     if language in language_to_models:
-        choices = language_to_models[language]
-        return gr.Dropdown.update(
-            choices=choices,
-            value=choices[0],
-            interactive=True,
-        )
-
-    raise ValueError(f"Unsupported language: {language}")
+        return gr.Dropdown.update(choices=language_to_models[language])
+    else:
+        raise ValueError(f"Unsupported language: {language}")
 
-
-def build_html_output(s: str, style: str = "result_item_success"):
-    return f"""
-    <div class='result'>
-        <div class='result_item {style}'>
-          {s}
-        </div>
-    </div>
-    """
-
-
-def process(language: str, repo_id: str, text: str, sid: str, speed: float):
-    logging.info(f"Input text: {text}. sid: {sid}, speed: {speed}")
+# Function to process text to speech conversion
+def process(language, repo_id, text, sid, speed):
+    logging.info(f"Input text: {text}, SID: {sid}, Speed: {speed}")
     sid = int(sid)
     tts = get_pretrained_model(repo_id, speed)
 
     start = time.time()
     audio = tts.generate(text, sid=sid)
-    end = time.time()
-
-    if len(audio.samples) == 0:
-        raise ValueError(
-            "Error in generating audios. Please read previous error messages."
-        )
-
     duration = len(audio.samples) / audio.sample_rate
-
-    elapsed_seconds = end - start
+    elapsed_seconds = time.time() - start
     rtf = elapsed_seconds / duration
 
     info = f"""
-    Wave duration  : {duration:.3f} s <br/>
-    Processing time: {elapsed_seconds:.3f} s <br/>
-    RTF: {elapsed_seconds:.3f}/{duration:.3f} = {rtf:.3f} <br/>
+    Wave duration: {duration:.3f} s<br/>
+    Processing time: {elapsed_seconds:.3f} s<br/>
+    RTF: {rtf:.3f}<br/>
     """
 
     logging.info(info)
-    logging.info(f"\nrepo_id: {repo_id}\ntext: {text}\nsid: {sid}\nspeed: {speed}")
-
-    filename = str(uuid.uuid4())
-    filename = f"{filename}.wav"
-    sf.write(
-        filename,
-        audio.samples,
-        samplerate=audio.sample_rate,
-        subtype="PCM_16",
-    )
-
-    return filename, build_html_output(info)
 
+    filename = f"{uuid.uuid4()}.wav"
+    sf.write(filename, audio.samples, samplerate=audio.sample_rate, subtype="PCM_16")
+    return filename, info
 
-demo = gr.Blocks(css=css)
+# Interface layout
+demo = gr.Blocks()
 
 with demo:
-    gr.Markdown(title)
-    language_choices = list(language_to_models.keys())
-
-    language_radio = gr.Radio(
-        label="Language",
-        choices=language_choices,
-        value=language_choices[0],
-    )
-
-    model_dropdown = gr.Dropdown(
-        choices=language_to_models[language_choices[0]],
-        label="Select a model",
-        value=language_to_models[language_choices[0]][0],
-    )
-
-    language_radio.change(
-        update_model_dropdown,
-        inputs=language_radio,
-        outputs=model_dropdown,
+    gr.Markdown("# Text to Voice")
+    gr.Markdown("High Fidelity TTS. Visit <a href='https://ruslanmv.com/' target='_blank'>ruslanmv.com</a> for more information.")
+    
+    language_radio = gr.Radio(label="Language", choices=list(language_to_models.keys()))
+    model_dropdown = gr.Dropdown(label="Select a model", choices=language_to_models[list(language_to_models.keys())[0]])
+
+    language_radio.change(update_model_dropdown, inputs=language_radio, outputs=model_dropdown)
+    
+    input_text = gr.Textbox(lines=10, label="Enter text to convert to speech")
+    input_sid = gr.Textbox(label="Speaker ID", value="0", placeholder="Valid only for multi-speaker model")
+    input_speed = gr.Slider(minimum=0.1, maximum=10, value=1, step=0.1, label="Speed (larger->faster; smaller->slower)")
+
+    output_audio = gr.Audio(label="Generated audio")
+    output_info = gr.HTML(label="Info")
+
+    input_button = gr.Button("Submit")
+    input_button.click(process, inputs=[language_radio, model_dropdown, input_text, input_sid, input_speed], outputs=[output_audio, output_info])
+
+    gr.Examples(
+        examples=[
+            ["Chinese (Mandarin, 普通话)", "csukuangfj/vits-zh-hf-fanchen-wnj|1", "在一个阳光明媚的夏天...", 0, 1.0],
+            ["Thai", "csukuangfj/vits-mms-tha", "ฉันรักคุณ", 0, 1.0],
+        ],
+        inputs=[language_radio, model_dropdown, input_text, input_sid, input_speed],
+        outputs=[output_audio, output_info],
     )
 
-    with gr.Tabs():
-        with gr.TabItem("Please input your text"):
-            input_text = gr.Textbox(
-                label="Input text",
-                info="Your text",
-                lines=3,
-                placeholder="Please input your text here",
-            )
-
-            input_sid = gr.Textbox(
-                label="Speaker ID",
-                info="Speaker ID",
-                lines=1,
-                max_lines=1,
-                value="0",
-                placeholder="Speaker ID. Valid only for mult-speaker model",
-            )
-
-            input_speed = gr.Slider(
-                minimum=0.1,
-                maximum=10,
-                value=1,
-                step=0.1,
-                label="Speed (larger->faster; smaller->slower)",
-            )
-
-            input_button = gr.Button("Submit")
-
-            output_audio = gr.Audio(label="Output")
-
-            output_info = gr.HTML(label="Info")
-
-            gr.Examples(
-                examples=examples,
-                fn=process,
-                inputs=[
-                    language_radio,
-                    model_dropdown,
-                    input_text,
-                    input_sid,
-                    input_speed,
-                ],
-                outputs=[
-                    output_audio,
-                    output_info,
-                ],
-            )
-
-        input_button.click(
-            process,
-            inputs=[
-                language_radio,
-                model_dropdown,
-                input_text,
-                input_sid,
-                input_speed,
-            ],
-            outputs=[
-                output_audio,
-                output_info,
-            ],
-        )
-
-    gr.Markdown(description)
-
-
+# Download necessary data
 def download_espeak_ng_data():
     os.system(
         """
-    cd /tmp
-    wget -qq https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/espeak-ng-data.tar.bz2
-    tar xf espeak-ng-data.tar.bz2
-    """
+        cd /tmp
+        wget -qq https://github.com/k2-fsa/sherpa-onnx/releases/download/tts-models/espeak-ng-data.tar.bz2
+        tar xf espeak-ng-data.tar.bz2
+        """
     )
 
-
 if __name__ == "__main__":
     download_espeak_ng_data()
-    formatter = "%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] %(message)s"
-
-    logging.basicConfig(format=formatter, level=logging.INFO)
+    logging.basicConfig(level=logging.INFO)
     demo.launch()