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Browse files- Dockerfile +12 -0
- app.py +47 -0
- requirements.txt +8 -0
Dockerfile
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FROM python:3.9
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WORKDIR /code
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COPY ./requirements.txt /code/requirements.txt
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RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
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COPY . .
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#CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]
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CMD ["panel", "serve", "/code/app.py", "--address", "0.0.0.0", "--port", "7860", "--allow-websocket-origin", "nongae-Panel_Test_Docker.hf.space"]
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app.py
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import panel as pn
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import hvplot.pandas
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# Load Data
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from bokeh.sampledata.autompg import autompg_clean as df
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# Make DataFrame Pipeline Interactive
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idf = df.interactive()
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# Define Panel widgets
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cylinders = pn.widgets.IntSlider(name='Cylinders', start=4, end=8, step=2)
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mfr = pn.widgets.ToggleGroup(
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name='MFR',
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options=['ford', 'chevrolet', 'honda', 'toyota', 'audi'],
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value=['ford', 'chevrolet', 'honda', 'toyota', 'audi'],
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button_type='success')
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yaxis = pn.widgets.RadioButtonGroup(
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name='Y axis',
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options=['hp', 'weight'],
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button_type='success'
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)
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# Combine pipeline and widgets
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ipipeline = (
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idf[
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(idf.cyl == cylinders) &
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(idf.mfr.isin(mfr))
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]
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.groupby(['origin', 'mpg'])[yaxis].mean()
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.to_frame()
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.reset_index()
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.sort_values(by='mpg')
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.reset_index(drop=True)
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)
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# Pipe to hvplot
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ihvplot = ipipeline.hvplot(x='mpg', y=yaxis, by='origin', color=["#ff6f69", "#ffcc5c", "#88d8b0"], line_width=6, height=400)
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# Layout using Template
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template = pn.template.FastListTemplate(
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title='Interactive DataFrame Dashboards with hvplot .interactive',
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sidebar=[cylinders, 'Manufacturers', mfr, 'Y axis' , yaxis],
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main=[ihvplot.panel()],
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accent_base_color="#88d8b0",
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header_background="#88d8b0",
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)
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template.servable()
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requirements.txt
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langchain
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openai
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chromadb
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pypdf
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tiktoken
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panel
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notebook
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hvplot
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