Update app.py

app.py

@@ -1,154 +1,4 @@
-with main_tabs[3]:  # Thinking Process tab
-    st.header("Multi-Persona Thinking Processes")
-    
-    if not st.session_state.thinking_logs:
-        st.info("No thinking process to display yet. Start writing a chapter to see the personas at work.")
-    else:
-        # Display the thinking logs
-        for i, log in enumerate(st.session_state.thinking_logs):
-            step_num = i + 1
-            timestamp = log.get("timestamp", "")
-            timestamp_str = datetime.fromtimestamp(timestamp).strftime('%Y-%m-%d %H:%M:%S') if timestamp else ""
-            
-            with st.expander(f"Step {step_num}: {log.get('agent', 'Unknown Agent')} {timestamp_str}", expanded=i==0):
-                st.markdown(log.get("thought", "No thought recorded"))
-                
-        # Clear logs button
-        if st.button("Clear Thinking Logs"):
-            st.session_state.thinking_logs = []
-            save_thinking_logs()
-            st.success("Thinking logs cleared.")
-            st.experimental_rerun()
-
-# Sidebar
-with st.sidebar:
-    # About the app
-    with st.expander("📖 About self.api Book Writer", expanded=False):
-        st.markdown("""
-        # About self.api Book Writer
-        
-        This application helps you write a book that uses API metaphors to explain spiritual concepts. It employs a multi-persona reasoning approach, where different specialist personas collaborate on each chapter.
-        
-        ## Key Features
-        
-        - **Multi-Persona Writing**: Each chapter benefits from diverse specialist perspectives
-        - **Research Integration**: Web research can be incorporated into chapter development
-        - **LangGraph Workflow**: Orchestrated agent collaboration for chapter creation
-        - **Complete Book Management**: From outline to final export
-        - **Transparency**: See the thinking process behind each contribution
-        
-        ## Workflow
-        
-        1. Setup your book outline
-        2. Select the appropriate personas for each chapter
-        3. Generate persona contributions 
-        4. Synthesize the final chapter
-        5. Export your completed book
-        
-        Built with Streamlit, LangGraph, and Claude 3.7.
-        """)
-    
-    # Persona Library
-    with st.expander("👤 Persona Library", expanded=False):
-        st.subheader("Available Personas")
-        
-        # Display personas by category
-        for category, persona_ids in st.session_state.persona_categories.items():
-            show_category = st.checkbox(f"{category} ({len(persona_ids)} personas)", key=f"cat_{category}")
-            if show_category:
-                for persona_id in persona_ids:
-                    if persona_id in st.session_state.persona_library:
-                        persona = st.session_state.persona_library[persona_id]
-                        with st.expander(f"{persona['name']}", expanded=False):
-                            st.write(f"**Description:** {persona['description']}")
-                            
-                            # Show system prompt if desired
-                            if st.checkbox("Show System Prompt", key=f"show_prompt_{persona_id}"):
-                                st.text_area(
-                                    "System Prompt",
-                                    value=persona['system_prompt'],
-                                    height=200,
-                                    key=f"prompt_{persona_id}",
-                                    disabled=True
-                                )
-    
-    # Save/Load Book Data
-    with st.expander("💾 Save/Load Book Data", expanded=False):
-        st.subheader("Save Book Data")
-        
-        # Export book data
-        book_json = json.dumps(st.session_state.book_data, indent=2)
-        st.download_button(
-            "Download Book Project Data",
-            book_json,
-            file_name=f"{st.session_state.book_data['title']}_project.json",
-            mime="application/json"
-        )
-        
-        st.subheader("Load Book Data")
-        
-        uploaded_book = st.file_uploader("Upload Book Project Data", type=["json"])
-        if uploaded_book:
-            try:
-                book_data = json.loads(uploaded_book.read().decode())
-                if st.button("Load Book Project"):
-                    st.session_state.book_data = book_data
-                    save_book_data()
-                    st.success("Book project loaded successfully!")
-                    st.experimental_rerun()
-            except Exception as e:
-                st.error(f"Error loading book data: {str(e)}")
-    
-    # Settings
-    st.header("Settings")
-    
-    # API Keys
-    with st.expander("API Keys", expanded=False):
-        anthropic_api_key = st.text_input(
-            "Anthropic API Key", 
-            type="password",
-            value=st.session_state.get("anthropic_api_key", ""),
-            help="Required for Claude 3.7 access"
-        )
-        if anthropic_api_key:
-            st.session_state.anthropic_api_key = anthropic_api_key
-            os.environ["ANTHROPIC_API_KEY"] = anthropic_api_key
-            
-        tavily_api_key = st.text_input(
-            "Tavily API Key", 
-            type="password",
-            value=st.session_state.get("tavily_api_key", ""),
-            help="Required for web research capabilities"
-        )
-        if tavily_api_key:
-            st.session_state.tavily_api_key = tavily_api_key
-            os.environ["TAVILY_API_KEY"] = tavily_api_key
-            
-    # Test connection
-    if st.button("Test Connection"):
-        client = get_claude_client()
-        if client:
-            try:
-                response = client.messages.create(
-                    model="claude-3-7-sonnet-20250219",
-                    messages=[{"role": "user", "content": "Hello"}],
-                    max_tokens=10
-                )
-                st.success("Claude connection successful!")
-            except Exception as e:
-                st.error(f"Claude connection failed: {str(e)}")
-                
-        # Test Tavily if API key is provided
-        if st.session_state.get("tavily_api_key"):
-            try:
-                research_agent = get_research_agent()
-                if research_agent:
-                    st.success("Tavily research connection successful!")
-            except Exception as e:
-                st.error(f"Tavily research connection failed: {str(e)}")
-
-# Check for autosave
-check_autosave()import streamlit as st
+import streamlit as st
 import os
 import json
 import pandas as pd