init

.gitignore

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+.env
+*.mp3
+__pycache__/

app.py

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+import gradio as gr
+from pathlib import Path
+from openai import OpenAI
+import os
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Initialize the OpenAI client
+client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
+
+if not client.api_key:
+    raise ValueError("Please set the OPENAI_API_KEY in your .env file")
+
+def generate_versions(text):
+    prompt = f"""Given the original text: "{text}"
+    Generate two rephrased versions:
+    1. A slightly more emotional version (ex. "위험해요" -> "위험해요!!")
+    2. An exaggerated, highly emotional version (ex. "위험해요" -> "잠깐만요! 안돼, 위험해요!!")
+    Output format:
+    Original: [original text]
+    Emotional: [emotional version]
+    Exaggerated: [exaggerated version]"""
+
+    stream = client.chat.completions.create(
+        model="gpt-4o-mini",
+        messages=[{"role": "user", "content": prompt}],
+        stream=True,
+    )
+
+    full_response = ""
+    for chunk in stream:
+        if chunk.choices[0].delta.content is not None:
+            full_response += chunk.choices[0].delta.content
+
+    versions = full_response.split('\n')
+    return [v.split(': ', 1)[1] for v in versions if ': ' in v]
+
+def text_to_speech(text):
+    response = client.audio.speech.create(
+        model="tts-1",
+        voice="alloy",
+        input=text
+    )
+    return response.content
+
+def process_and_generate(text):
+    versions = generate_versions(text)
+    audio_contents = [text_to_speech(v) for v in versions]
+    return versions + audio_contents + ["All versions generated successfully!"]
+
+with gr.Blocks(title="Emotional TTS Comparison") as demo:
+    gr.Markdown("# Emotional TTS Comparison")
+    gr.Markdown("Enter text to generate three versions with varying emotional intensity.")
+    
+    input_text = gr.Textbox(label="Original Text", lines=3)
+    generate_btn = gr.Button("Generate Versions and Speech")
+    
+    with gr.Row():
+        text1 = gr.Textbox(label="Original Version")
+        text2 = gr.Textbox(label="Emotional Version")
+        text3 = gr.Textbox(label="Exaggerated Version")
+    
+    with gr.Row():
+        audio1 = gr.Audio(label="Original Speech")
+        audio2 = gr.Audio(label="Emotional Speech")
+        audio3 = gr.Audio(label="Exaggerated Speech")
+    
+    status = gr.Textbox(label="Status")
+    
+    generate_btn.click(
+        process_and_generate,
+        inputs=[input_text],
+        outputs=[text1, text2, text3, audio1, audio2, audio3, status]
+    )
+
+if __name__ == "__main__":
+    demo.launch()
+else:
+    demo.launch(share=True)

flagged/log.csv

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+Enter text to convert to speech,Status,flag,username,timestamp
+,,,,2024-09-27 13:12:27.212281

requirements.txt

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+gradio
+openai