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src/streamlit_app.py

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  1. src/streamlit_app.py +25 -39
src/streamlit_app.py CHANGED
@@ -1,40 +1,26 @@
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- import altair as alt
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- import numpy as np
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- import pandas as pd
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  import streamlit as st
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-
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- """
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- # Welcome to Streamlit!
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-
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- Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
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- If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
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- forums](https://discuss.streamlit.io).
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-
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- In the meantime, below is an example of what you can do with just a few lines of code:
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- """
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-
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- num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
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- num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
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-
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- indices = np.linspace(0, 1, num_points)
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- theta = 2 * np.pi * num_turns * indices
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- radius = indices
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-
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- x = radius * np.cos(theta)
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- y = radius * np.sin(theta)
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-
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- df = pd.DataFrame({
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- "x": x,
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- "y": y,
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- "idx": indices,
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- "rand": np.random.randn(num_points),
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- })
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-
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- st.altair_chart(alt.Chart(df, height=700, width=700)
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- .mark_point(filled=True)
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- .encode(
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- x=alt.X("x", axis=None),
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- y=alt.Y("y", axis=None),
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- color=alt.Color("idx", legend=None, scale=alt.Scale()),
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- size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
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- ))
 
 
 
 
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  import streamlit as st
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+ from huggingface_hub import hf_hub_download
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+ import torch
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+
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+ # Télécharger le modèle
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+ model_path = hf_hub_download(
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+ repo_id="tencent/SongGeneration",
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+ filename="ckpt/songgeneration_base_zh/model.pt"
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+ )
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+
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+ # Charger le modèle
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+ model = torch.load(model_path)
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+ model.eval()
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+
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+ # Interface Streamlit
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+ st.title("🎵 Générateur de Chansons")
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+
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+ description = st.text_area("Décrivez l'ambiance de la chanson")
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+
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+ if st.button("Générer la chanson"):
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+ if description:
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+ # Génération de la chanson (à adapter selon le modèle)
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+ chanson = model.generate(description)
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+ st.audio(chanson)
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+ else:
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+ st.warning("Veuillez fournir une description.")