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app.py

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+import os
+import io
+from typing_extensions import Literal
+
+import gradio as gr
+import tempfile
+import numpy as np
+
+from dotenv import load_dotenv
+from elevenlabs.client import ElevenLabs
+from elevenlabs import play, stream, save
+from elevenlabs import Voice, VoiceSettings
+from pydub import AudioSegment
+from pydub.playback import play
+import imageio_ffmpeg as ffmpeg
+import requests
+from audiostretchy.stretch import AudioStretch
+
+
+load_dotenv()
+
+def verify_auth(username, password):
+    if username == USER and password == PASSWORD:
+
+        return True
+    else:
+        return False
+
+ELE_API_KEY = os.getenv("ELE_API_KEY")
+USER = os.getenv("USER")
+PASSWORD = os.getenv("PASSWORD")
+
+MODEL = "eleven_multilingual_v2"
+
+ele_client = ElevenLabs(api_key=ELE_API_KEY)
+
+VOICE = [
+    "승현",
+    "우승"
+]
+
+KEY_MAPPING = {
+    "승현": "0RBbbgk6KUJxHmWzPiHz", # 승현+제시카(2:1)
+    "우승": "ASwOiisDbuaP2R1jUQU6", # 우승+TTS_KKC(1:1)
+}
+
+
+AudioSegment.converter = ffmpeg.get_ffmpeg_exe()
+
+
+def change_pitch(audio_segment, pitch_shift):
+    new_sample_rate = int(audio_segment.frame_rate * (2.0 ** pitch_shift))
+    pitched_audio = audio_segment._spawn(audio_segment.raw_data, overrides={'frame_rate': new_sample_rate})    
+    return pitched_audio.set_frame_rate(audio_segment.frame_rate)
+
+
+def predict(
+        text: str,
+        voice: str,
+        output_file_format: Literal["mp3"] = "",
+        speed: float = 1.0,
+        pitch_shift: float = 0.0,
+        stability: float = 0.5,
+        similarity: float = 0.7,
+        style_exaggeration: float = 0.,
+        speaker_boost: bool = True     
+):
+    
+    try:                        
+        voice_setup=Voice(
+            voice_id=KEY_MAPPING[voice],
+            settings=VoiceSettings(stability=stability, similarity_boost=similarity, style=style_exaggeration, use_speaker_boost=speaker_boost)
+        )
+        
+        audio = ele_client.generate(
+            text = text,
+            voice = voice_setup,
+            model=MODEL
+        )            
+        audio_data = b''.join(audio)
+
+    except Exception as e:
+        raise requests.exceptions.RequestException(f"An error occurred while generating speech. Please check your API key and come back try again. {str(e)}")   
+        
+    print(f"[Text] {text}")
+    
+    audio_stretch = AudioStretch()
+    audio_stretch.open_mp3(io.BytesIO(audio_data))
+    audio_stretch.stretch(ratio=1/speed) # speed 0.5 -> 2.0\
+
+    # Export the final audio to a temporary file
+    with tempfile.NamedTemporaryFile(suffix=f".{output_file_format}", delete=False) as temp_file:
+        audio_stretch.save(path=temp_file.name)
+        audio = AudioSegment.from_file(temp_file.name)
+        
+        # Adjust pitch if needed
+        if pitch_shift != 0.0:
+            audio = change_pitch(audio, pitch_shift)
+        
+        audio.export(temp_file.name, format=output_file_format)
+        temp_file_path = temp_file.name
+
+    return temp_file_path
+
+          
+with gr.Blocks() as demo:
+    gr.Markdown("# <center> Letsur Text-To-Speech API with Gradio </center>")
+    with gr.Row(variant="panel"):        
+        voice = gr.Dropdown(choices=VOICE, label="Voice Options", value="승현")
+        output_file_format = gr.Dropdown(choices=["mp3"], label="Output Options", value="mp3")
+
+    text = gr.Textbox(label="Input text",
+                      value="안녕하세요.",
+                      placeholder="안녕하세요.")
+    
+    # Additional parameters
+    with gr.Accordion("Advanced Settings", open=False):
+        speed = gr.Slider(label="speed", minimum=0.8, maximum=1.2, step=0.1, value=1.0)
+        pitch_shift = gr.Slider(label="pitch_shift", minimum=-0.1, maximum=0.1, step=0.05, value=0.0) # 범위: 0~1
+        stability = gr.Slider(label="stability", minimum=0., maximum=1., step=0.1, value=1.0) # 범위: 0~1
+        similarity = gr.Slider(label="similarity", minimum=0., maximum=1., step=0.1, value=1.0) # 범위: 0~1
+        style_exaggeration = gr.Slider(label="style_exaggeration", minimum=0., maximum=1., step=0.1, value=0.) # 범위: 0~1
+        speaker_boost = gr.Checkbox(label="speaker_boost", value=True) # True or False            
+    
+    btn = gr.Button("Text-To-Speech")
+    output_audio = gr.Audio(label="Speech Output")
+
+    inputs = [text, voice, output_file_format] + [speed, pitch_shift, stability, similarity, style_exaggeration, speaker_boost]
+    
+    text.submit(fn=predict, inputs=inputs, outputs=output_audio, api_name="predict")
+    btn.click(fn=predict, inputs=inputs, outputs=output_audio, api_name=False)
+
+demo.queue().launch()

requirements.txt

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+gradio==4.36.1
+python-dotenv==1.0.0
+typing_extensions==4.8.0
+pydub==0.25.1
+audiostretchy==1.3.5
+elevenlabs
+ffprobe
+imageio[ffmpeg]
+numpy==1.26.4