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import json |
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from fastapi import FastAPI |
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from starlette.middleware.sessions import SessionMiddleware |
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from starlette.responses import HTMLResponse, RedirectResponse |
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from starlette.requests import Request |
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import gradio as gr |
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import uvicorn |
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from fastapi.responses import HTMLResponse |
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from fastapi.responses import RedirectResponse |
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import spotipy |
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from spotipy import oauth2 |
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PORT_NUMBER = 8080 |
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SPOTIPY_CLIENT_ID = 'c087fa97cebb4f67b6f08ba841ed8378' |
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SPOTIPY_CLIENT_SECRET = 'ae27d6916d114ac4bb948bb6c58a72d9' |
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SPOTIPY_REDIRECT_URI = 'https://hf-hackathon-2023-01-spotify.hf.space' |
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SCOPE = 'user-library-read' |
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sp_oauth = oauth2.SpotifyOAuth(SPOTIPY_CLIENT_ID, SPOTIPY_CLIENT_SECRET, SPOTIPY_REDIRECT_URI, scope=SCOPE) |
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app = FastAPI() |
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app.add_middleware(SessionMiddleware, secret_key="w.o.w") |
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@app.get('/', response_class=HTMLResponse) |
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async def homepage(request: Request): |
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token = request.session.get('token') |
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if token: |
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return RedirectResponse("/gradio") |
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url = str(request.url) |
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code = sp_oauth.parse_response_code(url) |
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if code != url: |
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token_info = sp_oauth.get_access_token(code) |
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request.session['token'] = token_info['access_token'] |
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return RedirectResponse("/gradio") |
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auth_url = sp_oauth.get_authorize_url() |
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return "<a href='" + auth_url + "'>Login to Spotify</a>" |
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from vega_datasets import data |
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iris = data.iris() |
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def scatter_plot_fn(dataset, request: gr.Request): |
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token = request.request.session.get('token') |
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if token: |
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sp = spotipy.Spotify(token) |
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results = sp.current_user() |
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print(f"Welcome to Gradio, {name}!\n{results}") |
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return gr.ScatterPlot( |
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value=iris |
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) |
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def get_started(): |
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return |
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with gr.Blocks() as demo: |
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gr.Markdown(" ## Spotify Analyzer 🥳🎉") |
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gr.Markdown("This app analyzes how cool your music taste is. We dare you to take this challenge!") |
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with gr.Row(): |
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get_started_btn = gr.Button("Get Started") |
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with gr.Row(): |
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with gr.Column(): |
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with gr.Row(): |
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with gr.Column(): |
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plot = gr.ScatterPlot(show_label=False).style(container=True) |
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with gr.Column(): |
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plot = gr.ScatterPlot(show_label=False).style(container=True) |
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with gr.Row(): |
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with gr.Column(): |
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plot = gr.ScatterPlot(show_label=False).style(container=True) |
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with gr.Column(): |
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plot = gr.ScatterPlot(show_label=False).style(container=True) |
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with gr.Row(): |
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gr.Markdown(" ### We have recommendations for you!") |
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with gr.Row(): |
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gr.Dataframe( |
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headers=["Song", "Album", "Artist"], |
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datatype=["str", "str", "str"], |
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label="Reccomended Songs", |
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) |
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demo.load(fn=scatter_plot_fn, outputs=plot) |
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gradio_app = gr.mount_gradio_app(app, demo, "/gradio") |
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uvicorn.run(app, host="0.0.0.0", port=7860) |
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