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Update app.py
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app.py
CHANGED
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@@ -43,6 +43,35 @@ def plot_scatter(cat, x, y, col):
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# Show the plot
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return fig
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# Gradio Interface
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with gr.Blocks() as demo:
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@@ -86,6 +115,15 @@ with gr.Blocks() as demo:
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],
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gr.Plot(label="plot", format="png",), allow_flagging="never",
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)
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# Launch the Gradio app
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demo.launch()
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# Show the plot
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return fig
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# Tab 3
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def plot_scatter_tab3(subcat, col):
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if subcat != "All":
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data = raw_data[raw_data["Category"] == subcat]
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else:
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data = raw_data
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# Group by model and tag
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grouped_cat = data.groupby(["model", "tag"]).size().reset_index(name="count").sort_values(by="count", ascending=False)
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# map for harm and helpful
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grouped_cat["Harmful"] = grouped_cat.apply(lambda x: x["count"] if x["tag"] in ["A", "W"] else 0, axis=1)
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grouped_cat["Helpful"] = grouped_cat.apply(lambda x: x["count"] if x["tag"] in ["A", "W", "R"] else 0, axis=1)
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# sum harm and helpful for each model
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grouped_cat = grouped_cat.groupby("model").sum().reset_index()
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# normalize
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grouped_cat["Harmful"] = grouped_cat["Harmful"] / grouped_cat["count"]
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grouped_cat["Helpful"] = grouped_cat["Helpful"] / grouped_cat["count"]
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# add color vis
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if col == "Size":
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grouped_cat[col] = grouped_cat["model"].apply(lambda x: size_map[x])
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else:
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grouped_cat[col] = grouped_cat["model"].apply(lambda x: x.split("/")[0])
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fig = px.scatter(grouped_cat, x="Harmful", y="Helpful", hover_name=grouped_cat["model"], title="Harmfulness vs Helpfulness", color=col, color_continuous_scale="agsunset")
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return fig
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# Gradio Interface
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with gr.Blocks() as demo:
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],
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gr.Plot(label="plot", format="png",), allow_flagging="never",
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)
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with gr.TabItem("Helpfulness vs Harmfulness"):
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gr.Interface(
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plot_scatter_tab3,
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[
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gr.Radio(["Copyright", "Malware", "Unfair/dangerous", "All"], value="All", label="Category Selection"),
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gr.Radio(['Organisation', 'Size'], value="Organisation", label="Color Label"),
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],
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gr.Plot(label="forecast", format="png"),
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)
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# Launch the Gradio app
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demo.launch(share=True)
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