import streamlit as st 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="📚", 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("📚 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("🚀 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("📋 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("🚀 Generate Chapter Draft", disabled=True, help="Select personas first") else: if st.button("🚀 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"⚠ī¸ {7500 - word_count:,} words short") elif word_count > 9000: st.info(f"ℹī¸ {word_count - 9000:,} words over") else: st.success("✅ 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"⚠ī¸ {7500 - edit_word_count:,} words short") elif edit_word_count > 9000: st.info(f"ℹī¸ {edit_word_count - 9000:,} words over") else: st.success("✅ 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""" {selected_chapter['title']} - {st.session_state.book_data['title']}

{selected_chapter['title']}

""" # Process markdown to HTML in a safer way content_html = final_content content_html = content_html.replace('# ', '

').replace('\n# ', '

\n

') content_html = content_html.replace('## ', '

').replace('\n## ', '

\n

') content_html = content_html.replace('### ', '

').replace('\n### ', '

\n

') # Fix unbalanced tags by ensuring closing tags exist if '

' in content_html and not '

' in content_html: content_html += '' if '

' in content_html and not '

' in content_html: content_html += '' if '

' in content_html and not '

' in content_html: content_html += '' # Handle emphasis and strong formatting with proper nesting # Replace pairs of ** with and i = 0 strong_parts = [] while i < len(content_html): if content_html[i:i+2] == '**': if len(strong_parts) % 2 == 0: strong_parts.append('') else: strong_parts.append('') i += 2 else: strong_parts.append(content_html[i]) i += 1 content_html = ''.join(strong_parts) # Replace pairs of * with and i = 0 em_parts = [] while i < len(content_html): if content_html[i:i+1] == '*': if len(em_parts) % 2 == 0: em_parts.append('') else: em_parts.append('') i += 1 else: em_parts.append(content_html[i]) i += 1 content_html = ''.join(em_parts) content_html = content_html.replace('\n\n', '

') html_content += content_html html_content += """ """ 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""" {st.session_state.book_data['title']} - {st.session_state.book_data['subtitle']}

{st.session_state.book_data['title']}

{st.session_state.book_data['subtitle']}

By {st.session_state.book_data['author']}

Table of Contents

    """ # Add table of contents toc_content = "" for chapter_idx, (chapter_id, chapter) in enumerate(chapters.items()): toc_content += f'
  1. {chapter["title"]}
    2. \n' toc_content += """
""" # 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
\n' chapters_content += f'

Chapter {chapter_idx + 1}: {chapter["title"]}

\n' # Process the chapter content - improved handling for HTML tags chapter_content = chapter["content"] # Replace headings chapter_content = chapter_content.replace('# ', '

').replace('\n# ', '

\n

') chapter_content = chapter_content.replace('## ', '

').replace('\n## ', '

\n

') chapter_content = chapter_content.replace('### ', '

').replace('\n### ', '

\n

') # Ensure all heading tags are properly closed if chapter_content.count('

') > chapter_content.count('

'): chapter_content += '' if chapter_content.count('

') > chapter_content.count('

'): chapter_content += '' if chapter_content.count('

') > chapter_content.count('

'): chapter_content += '' # 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_open = True else: strong_parts.append('') 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('') 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_open = True else: em_parts.append('') 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('') chapter_content = ''.join(em_parts) # Handle paragraph breaks chapter_content = chapter_content.replace('\n\n', '

') chapters_content += f' {chapter_content}\n' chapters_content += '
\n' html_foot = """ """ 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" )