voice keyword blacklist
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@@ -22,18 +22,22 @@ def _():
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tqdm.pandas()
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TAGUETTE_EXPORT_DIR = Path('./data/processing/02_taguette_export')
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WORKING_DIR = Path('./data/processing/02-b_WordClouds')
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VOICE_EXCLUDE_KEYWORDS_FILE = WORKING_DIR / 'voice_excl_keywords.txt'
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if not WORKING_DIR.exists():
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WORKING_DIR.mkdir(parents=True)
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if not TAGUETTE_EXPORT_DIR.exists():
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TAGUETTE_EXPORT_DIR.mkdir(parents=True)
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if not VOICE_EXCLUDE_KEYWORDS_FILE.exists():
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VOICE_EXCLUDE_KEYWORDS_FILE.touch()
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return (
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OLLAMA_LOCATION,
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TAGUETTE_EXPORT_DIR,
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VOICE_EXCLUDE_KEYWORDS_FILE,
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WORKING_DIR,
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connect_qumo_ollama,
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mo,
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@@ -115,7 +119,7 @@ def _(all_tags_df, mo):
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return (tag_select,)
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@app.cell
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@app.cell(hide_code=True)
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def _(WORKING_DIR, all_tags_df, mo, tag_select):
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mo.stop(not tag_select.value, mo.md("Select tag to continue"))
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@@ -152,7 +156,7 @@ def _(WORKING_DIR, all_tags_df, mo, tag_select):
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@app.cell(hide_code=True)
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def _(KEYWORD_FREQ_FPATH, mo):
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mo.md(rf"""
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# 4) Keyword extraction {'(skippable, see 4b)' if KEYWORD_FREQ_FPATH.exists() else ''}
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# 4) Keyword extraction {'(skippable, see 4b)' if KEYWORD_FREQ_FPATH.exists() else '(Required)'}
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""")
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return
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@@ -267,14 +271,21 @@ def _(KEYWORD_FREQ_FPATH, mo, start_processing_btn):
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load_existing_btn = None
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if KEYWORD_FREQ_FPATH.exists():
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load_existing_btn = mo.ui.run_button(label=f"Load keywords from `{KEYWORD_FREQ_FPATH.name}`", kind='warn')
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load_existing_btn = mo.ui.run_button(label=f"Load `{KEYWORD_FREQ_FPATH.name}`", kind='warn')
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load_existing_btn
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return (load_existing_btn,)
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@app.cell(hide_code=True)
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def _(KEYWORD_FREQ_FPATH, freq_df, load_existing_btn, pd):
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def _(
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KEYWORD_FREQ_FPATH,
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VOICE_EXCLUDE_KEYWORDS_FILE,
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freq_df,
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load_existing_btn,
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pd,
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tag_select,
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):
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if load_existing_btn is not None and load_existing_btn.value:
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_fdf = pd.read_excel(KEYWORD_FREQ_FPATH, engine='openpyxl')
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@@ -284,6 +295,19 @@ def _(KEYWORD_FREQ_FPATH, freq_df, load_existing_btn, pd):
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_fdf.reset_index(drop=True, inplace=True)
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print(f"Loaded `{KEYWORD_FREQ_FPATH}` successfully.")
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if tag_select.value.startswith('V'):
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# Read exclusion list
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excl_kw = []
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with VOICE_EXCLUDE_KEYWORDS_FILE.open('r') as _f:
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for line in _f:
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excl_kw.append(line.strip())
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_drop_idx = _fdf[_fdf['keyword'].isin(excl_kw)].index
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_fdf.drop(index=_drop_idx, inplace=True, axis=0)
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print(f"Dropped {len(_drop_idx)} keywords automatically")
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frequency_df = _fdf
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else:
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@@ -374,7 +398,15 @@ def _(mo, table_selection):
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@app.cell(hide_code=True)
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def _(KEYWORD_FREQ_FPATH, frequency_df, mo, remove_rows_btn, table_selection):
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def _(
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KEYWORD_FREQ_FPATH,
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VOICE_EXCLUDE_KEYWORDS_FILE,
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frequency_df,
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mo,
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remove_rows_btn,
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table_selection,
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tag_select,
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):
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_s = None
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if remove_rows_btn is not None and remove_rows_btn.value:
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# get selected rows
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@@ -382,7 +414,20 @@ def _(KEYWORD_FREQ_FPATH, frequency_df, mo, remove_rows_btn, table_selection):
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if len(selected_rows) >0 :
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rows_to_drop = table_selection.value.index.tolist()
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try:
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if tag_select.value.startswith('V'):
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# append values to an VoiceKeywordsExclusion file (txt file just a list of keywords)
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exclude_keywords = frequency_df.loc[rows_to_drop, 'keyword'].to_list()
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with VOICE_EXCLUDE_KEYWORDS_FILE.open('w') as f:
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for _kw in exclude_keywords:
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f.write(_kw + '\n')
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frequency_df.drop(index=rows_to_drop, inplace=True, axis=0)
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except KeyError:
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_s = mo.callout("GO BACK TO STEP 4b) and reload data to continue refining the dataset.", kind='warn')
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else:
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@@ -395,7 +440,7 @@ def _(KEYWORD_FREQ_FPATH, frequency_df, mo, remove_rows_btn, table_selection):
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print(f"Updated keyword frequencies saved to: `{KEYWORD_FREQ_FPATH}`")
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# mo.callout(f"Updated keyword frequencies saved to: `{KEYWORD_FREQ_FPATH}`", kind="success")
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_s = mo.callout("GO BACK TO STEP 4b) and reload data to continue refining the dataset.", kind='warn')
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_s = mo.callout("GO BACK TO STEP 4b) and reload data before continuing.", kind='warn')
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_s
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return
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@@ -437,7 +482,7 @@ def _(mo):
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logo_switch = mo.ui.switch(label="Include Chase Logo", value=False)
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n_words = mo.ui.slider(start=10, stop=200, step=1, value=40, debounce=True, show_value=True, label="Max number of words in WordCloud")
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n_words = mo.ui.slider(start=10, stop=200, step=1, value=100, debounce=True, show_value=True, label="Max number of words in WordCloud")
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return buffer, canvas_size, logo_switch, n_words
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