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Update app.py
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app.py
CHANGED
@@ -4,55 +4,43 @@ import json
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from normalizer import process_df
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from process_tags import list_ents, no_of_tags, color_creator, scatter_document
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tags_data = {
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"_dtags_": [],
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"DEP": [],
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"dep_explain": {},
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"_ptags_": [],
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"POS": [],
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"pos_explain": {},
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"_ntags_": ["concept", "tool", "framework", "crew", "position", "measurement", "artifact", "datasheet", "briefing", "standard", "insight", "client", "output", "output_component", "system", "challenge", "environment", "process", "process_component", "activity", "business_need", "third_party", "agreement", "raw_data", "authority", "resource_pool", "field_of_study", "geo_loc", "TBD"],
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"NER": ["concept", "#e3648a", "tool", "#d56b2e", "framework", "#ff0000", "crew", "#ffafcc", "position", "#a2cd5a", "measurement", "#779be7", "artifact", "#bee1e6", "datasheet", "#7e7d61", "briefing", "#4b8d76", "standard", "#9381ff", "insight", "#ffc125", "client", "#ffc6ff", "output", "#ffcfd2", "output_component", "#fde4cf", "system", "#656e1b", "challenge", "#ff5400", "environment", "#affc41", "process", "#adc178", "process_component", "#dde5b6", "activity", "#cfbaf0", "business_need", "#ced4da", "third_party", "#ee00ee", "agreement", "#484676", "raw_data", "#cdad00", "authority", "#d689c4", "resource_pool", "#8ea44c", "field_of_study", "#c39fe9", "geo_loc", "#c0ff3e", "TBD", "#ccdbfd"],
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"ner_explain": {},
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"_ctags_": [],
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"CAT": [],
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"cat_explain": {}
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}
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with st.sidebar:
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uploaded_file = st.file_uploader("Upload the sentence Json", type="json")
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# uploaded_color = st.file_uploader("Upload the tag Json", type="json")
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if uploaded_file is not None:
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raw_data = json.load(uploaded_file)
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# tags_data = json.load(uploaded_color)
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df_list = []
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key = 0
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for data in raw_data:
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df_list.append(process_df(data))
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st.plotly_chart(scatter_document(df_list, tags_data), use_container_width=True)
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tags = []
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ent = []
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for df in df_list:
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ent = list_ents(df)
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tags = list(no_of_tags(df).keys())
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doc = [{
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"text": ' '.join(df['words']),
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"ents": ent,
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"title": None
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}]
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spacy_streamlit.visualize_ner(
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doc,
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labels=tags,
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show_table=False,
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title=None,
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manual=True,
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displacy_options={
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"colors": color_creator(tags_data["NER"])
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},
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key=f"{key}"
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)
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key += 1
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from normalizer import process_df
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from process_tags import list_ents, no_of_tags, color_creator, scatter_document
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def main():
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st.set_page_config(layout='wide')
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st.write(
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"Tags Json is the file we get from exporting tags from d555 tag editor. You may need to format it to be in proper json format. For the demo, use this Tag json file https://github.com/kandysh/odin_json_sheets/blob/main/tag_color.json")
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with st.sidebar:
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uploaded_file = st.file_uploader("Upload the SENTENCE Json", type="json")
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uploaded_color = st.file_uploader("Upload the TAG Json", type="json")
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if uploaded_file and uploaded_color is not None:
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raw_data = json.load(uploaded_file)
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tags_data = json.load(uploaded_color)
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st.title(f'{uploaded_file.name.split(".")[0].upper()}')
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df_list = [process_df(data) for data in raw_data]
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st.plotly_chart(scatter_document(df_list, tags_data), use_container_width=True)
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key = 0
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for df in df_list:
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ents = list_ents(df)
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tags = list(no_of_tags(df).keys())
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doc = [{
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"text": ' '.join(df['words']),
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"ents": ents,
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"title": None
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}]
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st.text(f"Sentence {key}")
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spacy_streamlit.visualize_ner(
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doc,
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labels=tags,
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show_table=False,
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title=None,
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manual=True,
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displacy_options={
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"colors": color_creator(tags_data["NER"])
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},
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key=f"{key}"
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)
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key += 1
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if __name__ == "__main__":
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main()
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