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@ -159,6 +159,7 @@ class TextVectorizer:
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# Generate a list of colors for each data point based on the document path
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point_colors = [document_path_colors["_".join(path.split("_")[:-1])] for path in ref]
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# Create a scatter plot using Seaborn
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sns.scatterplot(x=embeddings_2d[:, 0], y=embeddings_2d[:, 1], hue=point_colors) # Plot document embeddings
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# Add labels to the scatter plot
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@ -217,10 +218,10 @@ class TextVectorizer:
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# Connect the click event handler to the figure
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plt.gcf().canvas.mpl_connect("button_press_event", on_click)
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if save_fig_path:
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plt.savefig(save_fig_path)
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if show_interactive_form:
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plt.show()
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if save_fig_path:
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plt.savefig(save_fig_path)
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def add_document(self, document_id, text, chunk_size, overlap_size, force_vectorize=False):
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if document_id in self.embeddings and not force_vectorize:
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