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import gradio as gr |
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import pandas as pd |
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import tsai |
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import Generate |
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example_df_aircomp=pd.read_csv('D:/project/aircompressordata.csv') |
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example_df_ener=pd.read_csv('D:/project/energymeter.csv') |
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example_df_boiler=pd.read_csv('D:/project/Boiler1.csv') |
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demo=gr.Blocks(title="EcoForecast") |
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def pred_air(date): |
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preds=Generate.inference_Aircomp(date,example_df_aircomp) |
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return preds |
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def pred_ener(date): |
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preds=Generate.inference_Energy(date,example_df_ener) |
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return preds |
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def pred_boiler(date): |
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preds=Generate.inference_boiler(date,example_df_boiler) |
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return preds |
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def plotgraphs(dataframe): |
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plots=0 |
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return plots |
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with demo: |
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gr.Markdown("Tool for predicting the next seven days of data in the future using the last 200 points of data incoming") |
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with gr.Tabs(): |
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with gr.TabItem("Air compressor data"): |
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with gr.Row(): |
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Air_input=gr.Text(placeholder="Enter date and like the example only",show_label=False) |
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air_dataframe_input=gr.Dataframe(example_df_aircomp.head(100)) |
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Air_dataframe_output=gr.Dataframe() |
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Air_plots=gr.Plot() |
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with gr.Column(): |
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Aircomp_output_btn=gr.Button("Forecast") |
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Air_plot_forecast=gr.Button("Plot") |
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with gr.TabItem("Energymeter data"): |
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with gr.Row(): |
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ener_input=gr.Text(placeholder="Enter the date and time in example format only",show_label=False) |
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ener_dataframe_input=gr.Dataframe(example_df_ener.head(100)) |
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Ener_dataframe_output=gr.Dataframe() |
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Ener_plots=gr.Plot() |
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with gr.Column(): |
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Energy_output_btn=gr.Button("Forecast") |
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Ener_plot_forecast=gr.Button("Plot") |
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with gr.TabItem("Boiler data"): |
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with gr.Row(): |
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boiler_input=gr.Text(placeholder="Enter the date and time in example format only",show_label=False) |
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ener_dataframe_input=gr.Dataframe(example_df_boiler.head(100)) |
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boiler_dataframe_output=gr.Dataframe() |
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boil_plots=gr.Plot() |
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with gr.Column(): |
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Boiler_output_btn=gr.Button("Forecast") |
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boiler_plot_forecast=gr.Button("Plot") |
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Aircomp_output_btn.click(pred_air,inputs=Air_input,outputs=Air_dataframe_output) |
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Energy_output_btn.click(pred_ener,inputs=ener_input,outputs=Ener_dataframe_output) |
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Boiler_output_btn.click(pred_boiler,inputs=boiler_input,outputs=boiler_dataframe_output) |
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Air_plot_forecast.click() |
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demo.launch(share=True) |