Update utils.py

utils.py

@@ -1,18 +1,51 @@
 import streamlit as st
+import os
+import json
+
+# Constants for persistent storage
+PERSISTENT_DIR = "persistent_data"
+BOOK_DATA_FILE = os.path.join(PERSISTENT_DIR, "book_data.json")
+LOGS_FILE = os.path.join(PERSISTENT_DIR, "thinking_logs.json")
 
 def initialize_session_state():
     """Initialize all the session state variables needed for the application"""
     
+    # Create persistent directory if it doesn't exist
+    os.makedirs(PERSISTENT_DIR, exist_ok=True)
+    
+    # Load book data if available
+    saved_book_data = None
+    try:
+        if os.path.exists(BOOK_DATA_FILE):
+            with open(BOOK_DATA_FILE, 'r') as f:
+                saved_book_data = json.load(f)
+                print("Loaded book data from persistent storage")
+    except Exception as e:
+        print(f"Error loading book data: {str(e)}")
+    
+    # Load thinking logs if available
+    saved_thinking_logs = None
+    try:
+        if os.path.exists(LOGS_FILE):
+            with open(LOGS_FILE, 'r') as f:
+                saved_thinking_logs = json.load(f)
+                print("Loaded thinking logs from persistent storage")
+    except Exception as e:
+        print(f"Error loading thinking logs: {str(e)}")
+    
     # Main book data
     if "book_data" not in st.session_state:
-        st.session_state.book_data = {
-            "title": "self.api",
-            "subtitle": "Accessing the Interface to Your Consciousness",
-            "author": "",
-            "chapters": {},
-            "outline": {},
-            "current_chapter": None,
-        }
+        if saved_book_data:
+            st.session_state.book_data = saved_book_data
+        else:
+            st.session_state.book_data = {
+                "title": "self.api",
+                "subtitle": "Accessing the Interface to Your Consciousness",
+                "author": "",
+                "chapters": {},
+                "outline": "",
+                "current_chapter": None,
+            }
 
     # Persona library with system prompts
     if "persona_library" not in st.session_state:
@@ -371,76 +404,4 @@ Provide your contribution with these elements:
 3. Main content contribution (500-800 words)
 4. Suggested system visualizations or models (described in detail)
 5. Integration points with other perspectives"""
-            }
-        }
-
-    # Organize personas by category
-    if "persona_categories" not in st.session_state:
-        st.session_state.persona_categories = {
-            "Meta": ["meta_agent", "selector_agent"],
-            "Technical Personas": ["tech_architect", "systems_thinker"],
-            "Philosophical Personas": ["eastern_philosopher", "western_philosopher"],
-            "Scientific Personas": ["neuroscientist"],
-            "Practical Personas": ["meditation_teacher", "pragmatic_implementer"],
-            "Creative Personas": ["creative_writer"]
-        }
-
-    # Chapter progress tracking
-    if "chapter_progress" not in st.session_state:
-        st.session_state.chapter_progress = {}
-
-    # Agent thinking logs
-    if "thinking_logs" not in st.session_state:
-        st.session_state.thinking_logs = []
-
-def convert_markdown_to_html(markdown_text):
-    """Convert markdown text to simple HTML for export"""
-    html_text = markdown_text
-    
-    # Headers
-    html_text = html_text.replace('# ', '<h1>').replace('\n# ', '</h1>\n')
-    html_text = html_text.replace('## ', '<h2>').replace('\n## ', '</h2>\n')
-    html_text = html_text.replace('### ', '<h3>').replace('\n### ', '</h3>\n')
-    
-    # Emphasis
-    html_text = html_text.replace('**', '<strong>').replace('**', '</strong>')
-    html_text = html_text.replace('*', '<em>').replace('*', '</em>')
-    
-    # Line breaks
-    html_text = html_text.replace('\n\n', '<br><br>')
-    
-    return html_text
-
-def get_word_count(text):
-    """Calculate word count in a text"""
-    if not text:
-        return 0
-    return len(text.split())
-
-def estimate_reading_time(word_count, wpm=250):
-    """Estimate reading time in minutes based on word count"""
-    return max(1, word_count // wpm)
-
-def calculate_section_word_counts(content):
-    """Calculate word counts for each section in the content"""
-    section_counts = {}
-    current_section = "Introduction"
-    section_text = ""
-    
-    for line in content.split("\n"):
-        if line.startswith("# ") or line.startswith("## "):
-            # Save the previous section count
-            if section_text:
-                section_counts[current_section] = len(section_text.split())
-            
-            # Start a new section
-            current_section = line.strip("# ")
-            section_text = ""
-        else:
-            section_text += line + " "
-    
-    # Add the last section
-    if section_text:
-        section_counts[current_section] = len(section_text.split())
-    
-    return section_counts
+            }