cleanup notebook and make usable

utils/__init__.py

@@ -2,4 +2,4 @@ from .ollama_utils import connect_qumo_ollama
 from .data_utils import create_sentiment_matrix, extract_theme
 from .transcript_utils import load_srt, csv_to_markdown, cpc_smb_to_markdown
 from .sentiment_analysis import dummy_sentiment_analysis, ollama_sentiment_analysis
-from .keyword_analysis import ollama_keyword_extraction, worker_extraction
+from .keyword_analysis import ollama_keyword_extraction, worker_extraction, blue_color_func

utils/keyword_analysis.py

@@ -2,6 +2,23 @@ import pandas as pd
 
 from ollama import Client
 import json
+import matplotlib.pyplot as plt
+
+import random
+import matplotlib.colors as mcolors
+
+def blue_color_func( word, font_size, position, orientation, random_state=None, **kwargs):
+    # Use the provided random_state for reproducibility if available, else use random module
+    r = random_state if random_state else random
+
+    # Sample from the darker end of the 'Blues' colormap (e.g., 0.4 to 1.0)
+    # 0.0 is white/light, 1.0 is dark blue
+    min_val, max_val = 0.4, 1.0
+    color_val = r.uniform(min_val, max_val)
+
+    # Get color from matplotlib colormap
+    rgba = plt.cm.Blues(color_val)
+    return mcolors.to_hex(rgba)
 
 
 def worker_extraction(row, host, model):