Create app.py

app.py

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+import streamlit as st
+import torch
+from parler_tts import ParlerTTSForConditionalGeneration
+from transformers import AutoTokenizer
+import soundfile as sf
+
+# Set up the device
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+# Load the model and tokenizer
+model = ParlerTTSForConditionalGeneration.from_pretrained("parler-tts/parler-tts-large-v1").to(device)
+tokenizer = AutoTokenizer.from_pretrained("parler-tts/parler-tts-large-v1")
+
+# Neon-themed styling
+st.markdown("""
+    <style>
+    body {
+        background-color: #0f0f0f;
+        color: #0fff0f;
+    }
+    .stTextInput, .stTextArea {
+        background-color: #333333;
+        color: #0fff0f;
+    }
+    .stButton > button {
+        background-color: #0fff0f;
+        color: #0f0f0f;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+st.title("🎤 Neon TTS Converter")
+
+# Predefined voice options
+voices = {
+    "Smooth Female": "A female speaker delivers a slightly expressive and animated speech with a moderate speed and pitch.",
+    "Monotone Male": "Jon's voice is monotone yet slightly fast in delivery, with a very close recording that almost has no background noise.",
+    "Energetic Youth": "An energetic young speaker with a lively tone and rapid speech, creating a sense of excitement.",
+    "Calm Elderly": "An elderly speaker with a calm and slow-paced voice, bringing wisdom and serenity to the speech.",
+    "Robotic": "A robotic, artificial voice with a consistent pitch and no variation in tone.",
+    "Narrator": "A deep and clear voice, with a strong presence and a slightly slower pace, suitable for narrations.",
+    "Whisper": "A soft, whispered voice, with very low volume and an intimate tone.",
+    "Formal": "A formal, authoritative voice with clear articulation and a steady pace.",
+    "Happy": "A cheerful, upbeat voice with a positive tone and lively intonation.",
+    "Mysterious": "A mysterious and low-pitched voice, with slow delivery and a sense of intrigue."
+}
+
+# Sidebar for voice selection
+st.sidebar.header("Select Voice")
+voice_choice = st.sidebar.selectbox("Choose a Voice", list(voices.keys()))
+
+# Display the selected voice description
+st.sidebar.markdown(f"**Description:** {voices[voice_choice]}")
+
+# Input for custom prompt
+st.sidebar.header("Custom Prompt")
+prompt = st.sidebar.text_area("Enter your custom prompt", value="Hey, how are you doing today?")
+
+# Error handling
+try:
+    # Generate the TTS output
+    if st.sidebar.button("Generate Speech"):
+        description = voices[voice_choice]
+        input_ids = tokenizer(description, return_tensors="pt").input_ids.to(device)
+        prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
+
+        generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
+        audio_arr = generation.cpu().numpy().squeeze()
+
+        # Save the audio file
+        output_file = "parler_tts_out.wav"
+        sf.write(output_file, audio_arr, model.config.sampling_rate)
+
+        # Display the audio player
+        st.audio(output_file)
+        st.success("Speech generation complete!")
+except Exception as e:
+    st.error(f"An error occurred: {e}")