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Update app.py
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app.py
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import streamlit as st
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import torch
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
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import urllib.parse
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# Set Streamlit page configuration
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st.set_page_config(
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page_title="Text-to-Music Generator 🎵",
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page_icon="🎵",
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layout="wide",
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initial_sidebar_state="expanded",
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)
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# Add custom CSS for styling
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st.markdown("""
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<style>
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body {
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background-color: #eaf6fb;
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color: #003366;
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font-family: 'Arial', sans-serif;
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}
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.stButton>button {
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background-color: #4dabf5;
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color: white;
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font-weight: bold;
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border-radius: 12px;
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padding: 10px 20px;
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}
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.stButton>button:hover {
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background-color: #007bb5;
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}
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.stTextArea textarea {
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border: 2px solid #4dabf5;
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border-radius: 8px;
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}
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iframe {
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border: 2px solid #4dabf5;
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border-radius: 8px;
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}
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.title {
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text-align: center;
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font-size: 36px;
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font-weight: bold;
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color: #003366;
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}
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.description {
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text-align: center;
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font-size: 18px;
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color: #005792;
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}
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</style>
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""", unsafe_allow_html=True)
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# Initialize the Hugging Face model and tokenizer
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@st.cache_resource
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def load_model():
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tokenizer = AutoTokenizer.from_pretrained('sander-wood/text-to-music')
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model = AutoModelForSeq2SeqLM.from_pretrained('sander-wood/text-to-music')
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return tokenizer, model
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# Load model and tokenizer
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tokenizer, model = load_model()
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# Streamlit App UI
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st.markdown("<div class='title'>🎵 Text-to-Music Generator 🎵</div>", unsafe_allow_html=True)
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st.markdown("""
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<div class='description'>
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Enter a textual description, and the model will generate music in ABC notation.
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You can use tools like [abc2midi](http://abc.sourceforge.net/abcMIDI/) to convert the notation into a playable file.
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</div>
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""", unsafe_allow_html=True)
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# Input Fields
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with st.container():
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text_input = st.text_area(
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"Enter a description for the music:",
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placeholder="e.g., This is a traditional Irish dance music.",
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)
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max_length = st.slider(
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"Maximum Length of Generated Music:", min_value=128, max_value=2048, value=1024, step=128
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)
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top_p = st.slider(
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"Top-p (Nucleus Sampling):", min_value=0.1, max_value=1.0, value=0.9, step=0.05
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)
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temperature = st.slider(
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"Temperature (Sampling Diversity):", min_value=0.1, max_value=2.0, value=1.0, step=0.1
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)
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# Generate Music Button
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if st.button("Generate Music 🎶"):
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if not text_input.strip():
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st.error("Please enter a valid description!")
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else:
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st.info("Generating music... This might take a few seconds.")
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try:
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# Tokenize input
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input_ids = tokenizer(text_input, return_tensors='pt', truncation=True, max_length=max_length)['input_ids']
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# Generate music using efficient beam search sampling
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generated_ids = model.generate(
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input_ids,
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max_length=max_length,
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do_sample=True,
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top_p=top_p,
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temperature=temperature,
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eos_token_id=tokenizer.eos_token_id,
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)
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# Decode generated music
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tune = tokenizer.decode(generated_ids[0], skip_special_tokens=True)
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tune = "X:1\n" + tune
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st.success("Music generated successfully!")
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# Display raw generated music in the app
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st.text_area("Generated Music (ABC Notation):", value=tune, height=300)
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# Encode tune for URL and embed ABCJS Editor
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encoded_tune = urllib.parse.quote(tune)
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editor_url = f"https://www.abcjs.net/abcjs-editor?abc={encoded_tune}"
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st.markdown(f"""
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### ABCJS Editor Preview
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You can edit or play the music below:
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<iframe src="{editor_url}" width="100%" height="500" style="border:none;"></iframe>
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""", unsafe_allow_html=True)
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except Exception as e:
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st.error(f"An error occurred: {e}")
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