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import os
import json
import pandas as pd
import time
from datetime import datetime
from utils import initialize_session_state, save_thinking_logs
# Import refactored LangGraph agents
from agents import (
get_claude_client,
run_chapter_creation,
get_research_agent,
select_personas_for_chapter,
get_persona_contribution_legacy as get_persona_contribution,
synthesize_chapter_legacy as synthesize_chapter,
ChapterWorkflowState
)
# Constants for persistent storage
AUTOSAVE_INTERVAL = 60 # seconds
PERSISTENT_DIR = "persistent_data"
BOOK_DATA_FILE = os.path.join(PERSISTENT_DIR, "book_data.json")
# Create persistent directory if it doesn't exist
os.makedirs(PERSISTENT_DIR, exist_ok=True)
# Set page configuration
st.set_page_config(
page_title="self.api Book Writer",
page_icon="๐",
layout="wide",
initial_sidebar_state="expanded"
)
# Function to save book data to persistent storage
def save_book_data():
try:
with open(BOOK_DATA_FILE, 'w') as f:
json.dump(st.session_state.book_data, f, indent=2)
st.session_state.last_save_time = time.time()
return True
except Exception as e:
print(f"Error saving book data: {str(e)}")
return False
# Function to load book data from persistent storage
def load_book_data():
try:
if os.path.exists(BOOK_DATA_FILE):
with open(BOOK_DATA_FILE, 'r') as f:
return json.load(f)
except Exception as e:
print(f"Error loading book data: {str(e)}")
return None
# Auto-save checker
def check_autosave():
current_time = time.time()
if not hasattr(st.session_state, 'last_save_time') or (current_time - st.session_state.last_save_time) > AUTOSAVE_INTERVAL:
save_book_data()
# Initialize session state
initialize_session_state()
# Load saved book data if available
saved_data = load_book_data()
if saved_data:
st.session_state.book_data = saved_data
# Main UI Layout
st.title("๐ self.api Book Writer")
st.write("A multi-persona writing assistant for your book on spirituality using API metaphors")
# Main tabs for different functionality
main_tabs = st.tabs(["Book Setup", "Chapter Creation", "Review Process", "Thinking Process"])
with main_tabs[0]: # Book Setup tab
st.header("Book Setup")
# Book metadata form
with st.form("book_metadata_form"):
col1, col2 = st.columns(2)
with col1:
book_title = st.text_input("Book Title", value=st.session_state.book_data["title"])
book_subtitle = st.text_input("Book Subtitle", value=st.session_state.book_data["subtitle"])
with col2:
book_author = st.text_input("Author Name", value=st.session_state.book_data["author"])
# Book description
book_description = st.text_area("Book Description",
value=st.session_state.book_data.get("description", ""),
height=150,
help="Provide a general description of the book's purpose and target audience")
submit_metadata = st.form_submit_button("Save Book Metadata")
if submit_metadata:
st.session_state.book_data["title"] = book_title
st.session_state.book_data["subtitle"] = book_subtitle
st.session_state.book_data["author"] = book_author
st.session_state.book_data["description"] = book_description
save_book_data()
st.success("Book metadata saved successfully!")
# Book outline creation
st.subheader("Book Outline Generator")
with st.form("outline_generator_form"):
st.write("Generate a complete book outline based on the self.api concept")
outline_prompt = st.text_area(
"Outline Generation Prompt",
value=f"""Generate a detailed outline for the book '{st.session_state.book_data['title']}' with subtitle '{st.session_state.book_data['subtitle']}'.
The book uses API (Application Programming Interface) as a metaphor for accessing different layers of consciousness, connecting tech concepts with spiritual development in an accessible way.
Include 8-12 chapters with titles and brief descriptions. For each chapter, include 4-6 key sections.
The book should progress logically from basic concepts through increasingly deeper layers of consciousness, with practical exercises throughout.""",
height=200
)
generate_outline = st.form_submit_button("Generate Book Outline")
if generate_outline:
with st.spinner("Generating comprehensive book outline..."):
client = get_claude_client()
if client:
try:
response = client.messages.create(
model="claude-3-7-sonnet-20250219",
messages=[{
"role": "user",
"content": outline_prompt
}],
temperature=0.3,
max_tokens=2500
)
outline = response.content[0].text
# Parse the outline into a structured format for the book data
chapters = {}
current_chapter = None
for line in outline.split('\n'):
line = line.strip()
if line.startswith('##') or line.startswith('Chapter'): # Chapter title
# Extract chapter title
title_parts = line.split(':', 1) if ':' in line else line.split(' ', 1)
if len(title_parts) > 1:
chapter_title = title_parts[1].strip()
else:
chapter_title = line.strip('#').strip()
chapter_id = f"chapter_{len(chapters) + 1}"
current_chapter = {
"title": chapter_title,
"sections": [],
"content": "",
"outline": ""
}
chapters[chapter_id] = current_chapter
elif line and current_chapter and not line.startswith('#'):
if not "outline" in current_chapter or not current_chapter["outline"]:
current_chapter["outline"] = line
else:
current_chapter["outline"] += f"\n{line}"
# Try to identify sections
if line.startswith('*') or line.startswith('-') or (line[0].isdigit() and line[1] == '.'):
section = line.strip('*').strip('-').strip().strip('.').strip()
if section and section not in current_chapter["sections"]:
current_chapter["sections"].append(section)
# Update the book data
st.session_state.book_data["outline"] = outline
st.session_state.book_data["chapters"] = chapters
save_book_data()
st.success("Book outline generated successfully!")
st.write(outline)
except Exception as e:
st.error(f"Error generating outline: {str(e)}")
else:
st.error("Claude client not available. Please check your API key.")
# Display current book outline if it exists
if "outline" in st.session_state.book_data and st.session_state.book_data["outline"]:
with st.expander("Current Book Outline", expanded=False):
st.markdown(st.session_state.book_data["outline"])
# Chapter management
if "chapters" in st.session_state.book_data and st.session_state.book_data["chapters"]:
st.subheader("Chapter Management")
chapters = st.session_state.book_data["chapters"]
chapter_options = {chapter_id: f"{idx+1}. {chapter['title']}"
for idx, (chapter_id, chapter) in enumerate(chapters.items())}
# Display existing chapters as a table
chapter_data = []
for chapter_id, chapter in chapters.items():
chapter_num = list(chapters.keys()).index(chapter_id) + 1
chapter_status = "Complete" if chapter.get("content") else "Not Started"
if chapter_id in st.session_state.chapter_progress:
progress = st.session_state.chapter_progress[chapter_id]
if 0 < progress < 100:
chapter_status = f"In Progress ({progress}%)"
chapter_data.append({
"Chapter": f"{chapter_num}",
"Title": chapter["title"],
"Status": chapter_status,
"ID": chapter_id
})
chapter_df = pd.DataFrame(chapter_data)
if not chapter_df.empty:
st.dataframe(chapter_df[["Chapter", "Title", "Status"]], use_container_width=True)
with main_tabs[1]: # Chapter Creation tab - SIMPLIFIED
st.header("Chapter Creation")
if "chapters" not in st.session_state.book_data or not st.session_state.book_data["chapters"]:
st.warning("Please generate a book outline first in the Book Setup tab.")
else:
chapters = st.session_state.book_data["chapters"]
chapter_options = {chapter_id: f"{idx+1}. {chapter['title']}"
for idx, (chapter_id, chapter) in enumerate(chapters.items())}
# Chapter selection
selected_chapter_id = st.selectbox(
"Select Chapter to Work On",
options=list(chapter_options.keys()),
format_func=lambda x: chapter_options[x],
index=0
)
if selected_chapter_id:
st.session_state.current_chapter = selected_chapter_id
selected_chapter = chapters[selected_chapter_id]
# Display chapter details
st.subheader(f"Working on: {selected_chapter['title']}")
st.write(selected_chapter["outline"])
# Chapter sections
if selected_chapter["sections"]:
with st.expander("Chapter Sections", expanded=True):
for idx, section in enumerate(selected_chapter["sections"]):
st.write(f"{idx+1}. {section}")
# Research section
with st.expander("Research for Chapter", expanded=False):
research_prompt = st.text_input(
"Research Query",
placeholder=f"Enter research query for {selected_chapter['title']}..."
)
if st.button("Conduct Research"):
if research_prompt:
with st.spinner("Researching..."):
# Use the new LangGraph-based research
research_agent = get_research_agent()
if research_agent:
try:
research_results = research_agent.invoke({
"input": f"Research for book chapter '{selected_chapter['title']}': {research_prompt}",
"chat_history": []
})
# Store research results
if "research" not in selected_chapter:
selected_chapter["research"] = []
selected_chapter["research"].append({
"query": research_prompt,
"results": research_results["output"],
"timestamp": datetime.now().strftime("%Y-%m-%d %H:%M:%S")
})
# Update the book data
st.session_state.book_data["chapters"][selected_chapter_id] = selected_chapter
save_book_data()
save_thinking_logs()
st.success("Research completed!")
st.write(research_results["output"])
except Exception as e:
st.error(f"Error conducting research: {str(e)}")
else:
st.error("Research agent not available. Please check your Tavily API key.")
# Display previous research results
if "research" in selected_chapter and selected_chapter["research"]:
st.subheader("Previous Research Results")
for idx, research in enumerate(selected_chapter["research"]):
with st.expander(f"Research: {research['query']}", expanded=False):
st.write(f"**Query:** {research['query']}")
st.write(f"**Timestamp:** {research['timestamp']}")
st.write("**Results:**")
st.write(research['results'])
# Chapter creation options - NEW INTEGRATED WORKFLOW
st.subheader("Chapter Creation")
creation_options = st.radio(
"Creation Method",
["Step-by-Step", "Automatic (LangGraph Workflow)"],
horizontal=True
)
if creation_options == "Automatic (LangGraph Workflow)":
# Integrated LangGraph workflow
num_personas = st.number_input(
"Number of personas to include",
min_value=3,
max_value=7,
value=5
)
# Get research query if any
research_query = None
if st.checkbox("Include research in chapter creation"):
research_query = st.text_input(
"Research Query for Chapter Creation",
placeholder="Enter a research topic related to this chapter..."
)
if st.button("๐ Generate Complete Chapter with LangGraph"):
with st.spinner("Creating chapter with LangGraph workflow (this may take several minutes)..."):
progress_bar = st.progress(0)
status_placeholder = st.empty()
try:
# Setup progress tracking
progress_stages = ["Initializing", "Research", "Persona Selection",
"Generating Contributions", "Synthesis"]
# Update initial progress
progress_bar.progress(0.05)
status_placeholder.text(f"Stage 1/5: {progress_stages[0]}")
# Run the LangGraph workflow
final_state = run_chapter_creation(
chapter_info=selected_chapter,
research_query=research_query,
num_personas=num_personas
)
# Update the book data with the results
st.session_state.book_data["chapters"][selected_chapter_id] = selected_chapter
save_book_data()
save_thinking_logs()
# Final update
progress_bar.progress(1.0)
if "error" in final_state and final_state["error"]:
status_placeholder.text(f"Error: {final_state['error']}")
st.error(f"Error during chapter creation: {final_state['error']}")
else:
status_placeholder.text("Chapter created successfully!")
st.success("Chapter created successfully with LangGraph!")
st.experimental_rerun()
except Exception as e:
progress_bar.progress(1.0)
status_placeholder.text(f"Error: {str(e)}")
st.error(f"Error during chapter creation: {str(e)}")
else:
# Step-by-Step Creation (original method with refactored components)
col1, col2 = st.columns(2)
with col1:
# One-click persona selection
if st.button("๐ Select Optimal Personas"):
with st.spinner("Selecting ideal personas for this chapter..."):
# Automatic selection using the refactored function
selected_personas, rationale = select_personas_for_chapter(selected_chapter, 5)
# Store selected personas
selected_chapter["selected_personas"] = selected_personas
selected_chapter["selection_rationale"] = rationale
# Update the book data
st.session_state.book_data["chapters"][selected_chapter_id] = selected_chapter
save_book_data()
save_thinking_logs()
st.success(f"Selected {len(selected_personas)} personas for this chapter!")
st.experimental_rerun()
with col2:
# One-click chapter generation
if "selected_personas" not in selected_chapter or not selected_chapter["selected_personas"]:
st.button("๐ Generate Chapter Draft", disabled=True, help="Select personas first")
else:
if st.button("๐ Generate Chapter Draft"):
with st.spinner("Creating chapter draft (this may take a few minutes)..."):
progress_bar = st.progress(0)
status_text = st.empty()
# 1. Generate all persona contributions
missing_personas = []
for persona_id in selected_chapter["selected_personas"]:
if persona_id == "meta_agent":
continue # Skip meta agent
missing_personas.append(persona_id)
if "contributions" not in selected_chapter:
selected_chapter["contributions"] = {}
for i, persona_id in enumerate(missing_personas):
if persona_id in st.session_state.persona_library:
persona = st.session_state.persona_library[persona_id]
status_text.text(f"Generating {persona['name']} contribution...")
# Get relevant research if available
research_text = ""
if "research" in selected_chapter and selected_chapter["research"]:
for research in selected_chapter["research"]:
research_text += f"Research Query: {research['query']}\nResults: {research['results']}\n\n"
# Use the refactored function
contribution = get_persona_contribution(persona_id, selected_chapter, research_text)
if contribution:
selected_chapter["contributions"][persona_id] = contribution
# Update the book data and save
st.session_state.book_data["chapters"][selected_chapter_id] = selected_chapter
save_book_data()
save_thinking_logs()
# Update progress (70% of total for contributions)
progress = (i + 1) / len(missing_personas) * 0.7
progress_bar.progress(progress)
# 2. Synthesize final chapter
status_text.text("Synthesizing complete chapter from all contributions...")
progress_bar.progress(0.8)
# Use the refactored function
final_chapter = synthesize_chapter(selected_chapter, selected_chapter["contributions"])
if final_chapter:
selected_chapter["content"] = final_chapter
# Update the book data
st.session_state.book_data["chapters"][selected_chapter_id] = selected_chapter
save_book_data()
save_thinking_logs()
progress_bar.progress(1.0)
status_text.text("Chapter completed successfully!")
st.success("Chapter draft created! Review it below.")
st.experimental_rerun()
# Display selected personas
if "selected_personas" in selected_chapter and selected_chapter["selected_personas"]:
st.subheader("Selected Personas")
personas = []
for persona_id in selected_chapter["selected_personas"]:
if persona_id in st.session_state.persona_library:
personas.append(st.session_state.persona_library[persona_id]["name"])
st.write(", ".join(personas))
with st.expander("Selection Rationale", expanded=False):
st.write(selected_chapter.get("selection_rationale", "No rationale available."))
# Display final chapter content if available
if "content" in selected_chapter and selected_chapter["content"]:
st.subheader("Chapter Draft")
final_content = selected_chapter["content"]
word_count = len(final_content.split())
target_count = "7,500-9,000"
# Display word count with visual indicator
col1, col2 = st.columns([3, 1])
with col1:
st.write(f"**Word count**: {word_count:,} words (target: {target_count})")
# Calculate progress as percentage of minimum target (7500)
progress_pct = min(word_count / 7500, 1.0)
st.progress(progress_pct)
with col2:
if word_count < 7500:
st.warning(f"โ ๏ธ {7500 - word_count:,} words short")
elif word_count > 9000:
st.info(f"โน๏ธ {word_count - 9000:,} words over")
else:
st.success("โ
Target reached")
# Display options
display_option = st.radio(
"Display Options",
["Preview", "Edit", "Export"],
horizontal=True
)
if display_option == "Preview":
# Add estimated reading time
reading_time = max(1, word_count // 250) # Assuming 250 words per minute reading speed
st.write(f"**Estimated reading time**: {reading_time} minutes")
# Display the content
st.markdown(final_content)
elif display_option == "Edit":
edited_content = st.text_area(
"Edit Chapter Content",
value=final_content,
height=600
)
# Show word count as user edits
edit_word_count = len(edited_content.split())
col1, col2 = st.columns([3, 1])
with col1:
st.write(f"**Current word count**: {edit_word_count:,} words (target: 7,500-9,000)")
progress_pct = min(edit_word_count / 7500, 1.0)
st.progress(progress_pct)
with col2:
if edit_word_count < 7500:
st.warning(f"โ ๏ธ {7500 - edit_word_count:,} words short")
elif edit_word_count > 9000:
st.info(f"โน๏ธ {edit_word_count - 9000:,} words over")
else:
st.success("โ
Target reached")
if st.button("Save Edits"):
selected_chapter["content"] = edited_content
# Update the book data
st.session_state.book_data["chapters"][selected_chapter_id] = selected_chapter
save_book_data()
st.success("Chapter edits saved successfully!")
st.experimental_rerun()
elif display_option == "Export":
st.download_button(
"Download Chapter as Markdown",
final_content,
file_name=f"{selected_chapter['title']}.md",
mime="text/markdown"
)
# Also provide HTML export option
html_content = f"""<!DOCTYPE html>
<html>
<head>
<title>{selected_chapter['title']} - {st.session_state.book_data['title']}</title>
<meta charset="utf-8">
<style>
body {{ font-family: Arial, sans-serif; line-height: 1.6; max-width: 800px; margin: 0 auto; padding: 20px; }}
h1, h2, h3 {{ color: #333; }}
code {{ background-color: #f4f4f4; padding: 2px 5px; border-radius: 3px; }}
pre {{ background-color: #f4f4f4; padding: 15px; border-radius: 5px; overflow-x: auto; }}
blockquote {{ border-left: 4px solid #ddd; padding-left: 15px; color: #666; }}
</style>
</head>
<body>
<h1>{selected_chapter['title']}</h1>
"""
# Process markdown to HTML in a safer way
content_html = final_content
content_html = content_html.replace('# ', '<h1>').replace('\n# ', '</h1>\n<h1>')
content_html = content_html.replace('## ', '<h2>').replace('\n## ', '</h2>\n<h2>')
content_html = content_html.replace('### ', '<h3>').replace('\n### ', '</h3>\n<h3>')
# Fix unbalanced tags by ensuring closing tags exist
if '<h1>' in content_html and not '</h1>' in content_html:
content_html += '</h1>'
if '<h2>' in content_html and not '</h2>' in content_html:
content_html += '</h2>'
if '<h3>' in content_html and not '</h3>' in content_html:
content_html += '</h3>'
# Handle emphasis and strong formatting with proper nesting
# Replace pairs of ** with <strong> and </strong>
i = 0
strong_parts = []
while i < len(content_html):
if content_html[i:i+2] == '**':
if len(strong_parts) % 2 == 0:
strong_parts.append('<strong>')
else:
strong_parts.append('</strong>')
i += 2
else:
strong_parts.append(content_html[i])
i += 1
content_html = ''.join(strong_parts)
# Replace pairs of * with <em> and </em>
i = 0
em_parts = []
while i < len(content_html):
if content_html[i:i+1] == '*':
if len(em_parts) % 2 == 0:
em_parts.append('<em>')
else:
em_parts.append('</em>')
i += 1
else:
em_parts.append(content_html[i])
i += 1
content_html = ''.join(em_parts)
content_html = content_html.replace('\n\n', '<br><br>')
html_content += content_html
html_content += """
</body>
</html>"""
st.download_button(
"Download Chapter as HTML",
html_content,
file_name=f"{selected_chapter['title']}.html",
mime="text/html"
)
with main_tabs[2]: # Review Process tab
st.header("Book Review and Export")
if "chapters" not in st.session_state.book_data or not st.session_state.book_data["chapters"]:
st.warning("Please generate a book outline first in the Book Setup tab.")
else:
# Book progress overview
st.subheader("Book Progress")
chapters = st.session_state.book_data["chapters"]
total_chapters = len(chapters)
completed_chapters = sum(1 for chapter in chapters.values() if "content" in chapter and chapter["content"])
progress_percentage = int((completed_chapters / total_chapters) * 100) if total_chapters > 0 else 0
st.progress(progress_percentage / 100)
st.write(f"**{completed_chapters}** out of **{total_chapters}** chapters completed ({progress_percentage}%)")
# Chapter overview table
chapter_data = []
for chapter_id, chapter in chapters.items():
chapter_num = list(chapters.keys()).index(chapter_id) + 1
# Determine chapter status
if "content" in chapter and chapter["content"]:
status = "Complete"
word_count = len(chapter.get('content', '').split())
elif "contributions" in chapter and chapter["contributions"]:
status = "Draft (Needs Synthesis)"
word_count = sum(len(contrib.split()) for contrib in chapter["contributions"].values())
elif "selected_personas" in chapter:
status = "Planned"
word_count = 0
else:
status = "Not Started"
word_count = 0
chapter_data.append({
"Chapter": f"{chapter_num}",
"Title": chapter["title"],
"Status": status,
"Word Count": f"{word_count:,}" if word_count > 0 else "0",
"Target %": f"{min(word_count / 7500 * 100, 100):.0f}%" if word_count > 0 else "0%",
"ID": chapter_id
})
chapter_df = pd.DataFrame(chapter_data)
if not chapter_df.empty:
st.dataframe(chapter_df[["Chapter", "Title", "Status", "Word Count", "Target %"]], use_container_width=True)
# Book export options
st.subheader("Export Book")
export_format = st.radio(
"Export Format",
["Markdown", "HTML", "JSON"],
horizontal=True
)
if st.button("Generate Complete Book"):
with st.spinner("Generating complete book..."):
# Collect all completed chapters
book_content = f"# {st.session_state.book_data['title']}\n\n"
book_content += f"## {st.session_state.book_data['subtitle']}\n\n"
book_content += f"By {st.session_state.book_data['author']}\n\n"
# Add table of contents
book_content += "## Table of Contents\n\n"
for chapter_idx, (chapter_id, chapter) in enumerate(chapters.items()):
book_content += f"{chapter_idx + 1}. {chapter['title']}\n"
book_content += "\n\n"
# Add each chapter
for chapter_idx, (chapter_id, chapter) in enumerate(chapters.items()):
if "content" in chapter and chapter["content"]:
book_content += f"# Chapter {chapter_idx + 1}: {chapter['title']}\n\n"
book_content += chapter["content"]
book_content += "\n\n---\n\n"
if export_format == "Markdown":
st.download_button(
"Download Complete Book (Markdown)",
book_content,
file_name=f"{st.session_state.book_data['title']}.md",
mime="text/markdown"
)
elif export_format == "HTML":
# Convert markdown to simple HTML
html_head = f"""<!DOCTYPE html>
<html>
<head>
<title>{st.session_state.book_data['title']} - {st.session_state.book_data['subtitle']}</title>
<meta charset="utf-8">
<style>
body {{ font-family: Arial, sans-serif; line-height: 1.6; max-width: 800px; margin: 0 auto; padding: 20px; }}
h1, h2, h3 {{ color: #333; }}
code {{ background-color: #f4f4f4; padding: 2px 5px; border-radius: 3px; }}
pre {{ background-color: #f4f4f4; padding: 15px; border-radius: 5px; overflow-x: auto; }}
blockquote {{ border-left: 4px solid #ddd; padding-left: 15px; color: #666; }}
.chapter {{ margin-top: 50px; border-top: 1px solid #ddd; padding-top: 20px; }}
.toc {{ margin: 30px 0; }}
.toc a {{ text-decoration: none; color: #0066cc; }}
</style>
</head>
<body>
<h1>{st.session_state.book_data['title']}</h1>
<h2>{st.session_state.book_data['subtitle']}</h2>
<p>By {st.session_state.book_data['author']}</p>
<div class="toc">
<h2>Table of Contents</h2>
<ol>
"""
# Add table of contents
toc_content = ""
for chapter_idx, (chapter_id, chapter) in enumerate(chapters.items()):
toc_content += f' <li><a href="#chapter-{chapter_idx + 1}">{chapter["title"]}</a></li>\n'
toc_content += """ </ol>
</div>
"""
# Add each chapter
chapters_content = ""
for chapter_idx, (chapter_id, chapter) in enumerate(chapters.items()):
if "content" in chapter and chapter["content"]:
chapters_content += f'\n <div id="chapter-{chapter_idx + 1}" class="chapter">\n'
chapters_content += f' <h1>Chapter {chapter_idx + 1}: {chapter["title"]}</h1>\n'
# Process the chapter content - improved handling for HTML tags
chapter_content = chapter["content"]
# Replace headings
chapter_content = chapter_content.replace('# ', '<h1>').replace('\n# ', '</h1>\n<h1>')
chapter_content = chapter_content.replace('## ', '<h2>').replace('\n## ', '</h2>\n<h2>')
chapter_content = chapter_content.replace('### ', '<h3>').replace('\n### ', '</h3>\n<h3>')
# Ensure all heading tags are properly closed
if chapter_content.count('<h1>') > chapter_content.count('</h1>'):
chapter_content += '</h1>'
if chapter_content.count('<h2>') > chapter_content.count('</h2>'):
chapter_content += '</h2>'
if chapter_content.count('<h3>') > chapter_content.count('</h3>'):
chapter_content += '</h3>'
# Handle bold text - balanced pairs of **
i = 0
strong_parts = []
strong_open = False
while i < len(chapter_content):
if i+1 < len(chapter_content) and chapter_content[i:i+2] == '**':
if not strong_open:
strong_parts.append('<strong>')
strong_open = True
else:
strong_parts.append('</strong>')
strong_open = False
i += 2
else:
strong_parts.append(chapter_content[i])
i += 1
# Ensure all strong tags are closed
if strong_open:
strong_parts.append('</strong>')
chapter_content = ''.join(strong_parts)
# Handle italic text - balanced pairs of *
i = 0
em_parts = []
em_open = False
while i < len(chapter_content):
if chapter_content[i:i+1] == '*':
if not em_open:
em_parts.append('<em>')
em_open = True
else:
em_parts.append('</em>')
em_open = False
i += 1
else:
em_parts.append(chapter_content[i])
i += 1
# Ensure all em tags are closed
if em_open:
em_parts.append('</em>')
chapter_content = ''.join(em_parts)
# Handle paragraph breaks
chapter_content = chapter_content.replace('\n\n', '<br><br>')
chapters_content += f' {chapter_content}\n'
chapters_content += ' </div>\n'
html_foot = """
</body>
</html>"""
html_content = html_head + toc_content + chapters_content + html_foot
st.download_button(
"Download Complete Book (HTML)",
html_content,
file_name=f"{st.session_state.book_data['title']}.html",
mime="text/html"
)
elif export_format == "JSON":
# Export the entire book data structure
book_json = json.dumps(st.session_state.book_data, indent=2)
st.download_button(
"Download Book Data (JSON)",
book_json,
file_name=f"{st.session_state.book_data['title']}.json",
mime="application/json"
) |