From 3c27ecc81b4f05be45b6b2b2843ea082cb90f807 Mon Sep 17 00:00:00 2001
From: "google-labs-jules[bot]"
 <161369871+google-labs-jules[bot]@users.noreply.github.com>
Date: Thu, 19 Jun 2025 16:41:10 +0000
Subject: [PATCH] feat: Transform to AI Book Summary Generator

This commit overhauls the application from a general deep research
tool into a specialized AI-powered book summary generator.

Key changes include:
- Updated UI to accept "Book Name" and optional "Author" inputs.
- Modified backend to generate multiple targeted search queries for
  gathering book-related content (summaries, reviews, analyses)
  from at least 20 sources using Firecrawl.
- Engineered a new detailed prompt for the OpenAI LLM (GPT-4o),
  instructing it to synthesize a comprehensive, long-form
  (30-minute read) book summary. The prompt includes the
  "Atomic Habits" summary as a structural and stylistic example.
- Created `lib/prompt-examples.ts` to store the example summary.
- Adjusted `lib/config.ts` to support the new search strategy and
  content requirements (e.g., number of queries, sources per query).
- Enhanced Markdown rendering CSS in `app/globals.css` for better
  readability of long-form content, including improved styles for
  headings, blockquotes, and other elements.
- Adapted `lib/langgraph-search-engine.ts` significantly:
    - Changed input state and search method signatures.
    - Revised the 'plan' node for book-specific query generation.
    - Updated methods for analyzing book requests, scoring content
      relevance, and summarizing individual sources for book context.
    - Implemented `generateStreamingBookSummary` with the new prompt.
    - Replaced "follow-up questions" with "key themes".
- Updated `app/page.tsx` with new heading/description.
---
 app/chat.tsx                   |  434 +++++------
 app/globals.css                |   67 ++
 app/search.tsx                 |   12 +-
 lib/config.ts                  |   45 +-
 lib/langgraph-search-engine.ts | 1338 +++++++++-----------------------
 lib/prompt-examples.ts         |  524 +++++++++++++
 6 files changed, 1193 insertions(+), 1227 deletions(-)
 create mode 100644 lib/prompt-examples.ts

diff --git a/app/chat.tsx b/app/chat.tsx
index 0dbd077..082317f 100644
--- a/app/chat.tsx
+++ b/app/chat.tsx
@@ -20,13 +20,6 @@ import { Button } from "@/components/ui/button";
 import { Input } from "@/components/ui/input";
 import { toast } from "sonner";
 
-const SUGGESTED_QUERIES = [
-  "Who are the founders of Firecrawl?",
-  "When did NVIDIA release the RTX 4080 Super?",
-  "Compare the latest iPhone 16 and Samsung Galaxy S25",
-  "Compare Claude 4 to OpenAI's o3"
-];
-
 // Helper component for sources list
 function SourcesList({ sources }: { sources: Source[] }) {
   const [showSourcesPanel, setShowSourcesPanel] = useState(false);
@@ -187,24 +180,23 @@ export function Chat() {
     id: string;
     role: 'user' | 'assistant';
     content: string | React.ReactNode;
-    isSearch?: boolean;
-    searchResults?: string; // Store search results for context
+    isSearch?: boolean; // Indicates if this message is part of the search process display
+    searchResults?: string; // Store raw search results string for context if needed
+    bookName?: string; // To display what book was searched for
+    author?: string;
   }>>([]);
-  const [input, setInput] = useState('');
+  const [bookNameInput, setBookNameInput] = useState('');
+  const [authorInput, setAuthorInput] = useState('');
   const [isSearching, setIsSearching] = useState(false);
-  const [showSuggestions, setShowSuggestions] = useState(false);
-  const [hasShownSuggestions, setHasShownSuggestions] = useState(false);
+  // const [showSuggestions, setShowSuggestions] = useState(false); // Suggestions not used for book summary
+  // const [hasShownSuggestions, setHasShownSuggestions] = useState(false);
   const [firecrawlApiKey, setFirecrawlApiKey] = useState<string>('');
   const [hasApiKey, setHasApiKey] = useState<boolean>(false);
   const [showApiKeyModal, setShowApiKeyModal] = useState<boolean>(false);
-  const [, setIsCheckingEnv] = useState<boolean>(true);
-  const [pendingQuery, setPendingQuery] = useState<string>('');
+  const [, setIsCheckingEnv] = useState<boolean>(true); // To manage env check state
+  const [pendingSearch, setPendingSearch] = useState<{ bookName: string; author?: string } | null>(null);
   const messagesContainerRef = useRef<HTMLDivElement>(null);
 
-  const handleSelectSuggestion = (suggestion: string) => {
-    setInput(suggestion);
-    setShowSuggestions(false);
-  };
 
   // Check for environment variables on mount
   useEffect(() => {
@@ -215,13 +207,11 @@ export function Chat() {
         const data = await response.json();
         
         if (data.environmentStatus) {
-          // Only check for Firecrawl API key since we can pass it from frontend
-          // OpenAI and Anthropic keys must be in environment
           setHasApiKey(data.environmentStatus.FIRECRAWL_API_KEY);
         }
       } catch (error) {
         console.error('Failed to check environment:', error);
-        setHasApiKey(false);
+        setHasApiKey(false); // Assume no key if check fails
       } finally {
         setIsCheckingEnv(false);
       }
@@ -237,80 +227,69 @@ export function Chat() {
     }
   }, [messages]);
 
-  const saveApiKey = () => {
+  const saveApiKeyAndSearch = () => {
     if (firecrawlApiKey.trim()) {
       setHasApiKey(true);
       setShowApiKeyModal(false);
-      toast.success('API key saved! Starting your search...');
+      toast.success('API key saved! Starting your book summary generation...');
       
-      // Continue with the pending query
-      if (pendingQuery) {
-        performSearch(pendingQuery);
-        setPendingQuery('');
+      if (pendingSearch) {
+        performSearch(pendingSearch.bookName, pendingSearch.author);
+        setPendingSearch(null);
       }
     }
   };
 
-  // Listen for follow-up question events
+  // Listen for follow-up question (key theme) events
   useEffect(() => {
-    const handleFollowUpQuestion = async (event: Event) => {
+    const handleFollowUp = async (event: Event) => {
       const customEvent = event as CustomEvent;
-      const question = customEvent.detail.question;
-      setInput(question);
-      
-      // Trigger the search immediately
-      setTimeout(() => {
-        const form = document.querySelector('form');
-        if (form) {
-          form.dispatchEvent(new Event('submit', { cancelable: true, bubbles: true }));
-        }
-      }, 100);
+      const theme = customEvent.detail.question; // Re-using 'question' for theme
+      // For book summaries, clicking a theme might mean asking a new question about it
+      // For now, let's just set it in the input field for a new search if desired
+      // Or it could trigger a more specific search related to that theme + book.
+      // For simplicity, we'll just log it or potentially set it for a new input.
+      // User can then refine or search.
+      // setBookNameInput(`${messages[messages.length-1]?.bookName} - ${theme}`); // Example: prefill
+      // setAuthorInput(messages[messages.length-1]?.author || '');
+      toast.info(`Exploring theme: ${theme}. You can ask a new question related to this theme and the book.`);
     };
 
-    document.addEventListener('followUpQuestion', handleFollowUpQuestion);
+    document.addEventListener('followUpQuestion', handleFollowUp);
     return () => {
-      document.removeEventListener('followUpQuestion', handleFollowUpQuestion);
+      document.removeEventListener('followUpQuestion', handleFollowUp);
     };
-  }, []);
+  }, [messages]);
 
-  const performSearch = async (query: string) => {
+  const performSearch = async (bookName: string, author?: string) => {
     setIsSearching(true);
 
-    // Create assistant message with search display
     const assistantMsgId = (Date.now() + 1).toString();
     const events: SearchEvent[] = [];
     
     setMessages(prev => [...prev, {
       id: assistantMsgId,
       role: 'assistant',
-      content: <SearchDisplay events={events} />,
-      isSearch: true
+      content: <SearchDisplay events={events} />, // Shows "Understanding request..." etc.
+      isSearch: true,
+      bookName, // Store for context
+      author
     }]);
 
     try {
-      // Build context from previous messages by pairing user queries with assistant responses
       const conversationContext: Array<{ query: string; response: string }> = [];
+      // Context building might be less relevant for first summary of a book.
+      // Could be used if user asks follow-up questions about the summary later.
+      // For now, keeping it simple.
       
-      for (let i = 0; i < messages.length; i++) {
-        const msg = messages[i];
-        // Find user messages followed by assistant messages with search results
-        if (msg.role === 'user' && i + 1 < messages.length) {
-          const nextMsg = messages[i + 1];
-          if (nextMsg.role === 'assistant' && nextMsg.searchResults) {
-            conversationContext.push({
-              query: msg.content as string,
-              response: nextMsg.searchResults
-            });
-          }
-        }
-      }
-      
-      // Get search stream with context
-      // Pass the API key only if user provided one, otherwise let server use env var
-      const { stream } = await search(query, conversationContext, firecrawlApiKey || undefined);
+      const { stream } = await search({
+        bookName,
+        author,
+        context: conversationContext,
+        apiKey: firecrawlApiKey || undefined
+      });
       let finalContent = '';
       
-      // Read stream and update events
       let streamingStarted = false;
       const resultMsgId = (Date.now() + 2).toString();
       
@@ -318,37 +297,33 @@ export function Chat() {
         if (event) {
           events.push(event);
           
-          // Handle content streaming
           if (event.type === 'content-chunk') {
-            const content = events
+            const currentStreamedContent = events
               .filter(e => e.type === 'content-chunk')
               .map(e => e.type === 'content-chunk' ? e.chunk : '')
               .join('');
             
             if (!streamingStarted) {
               streamingStarted = true;
-              // Add new message for streaming content
               setMessages(prev => [...prev, {
                 id: resultMsgId,
                 role: 'assistant',
-                content: <MarkdownRenderer content={content} streaming={true} />,
-                isSearch: false
+                content: <MarkdownRenderer content={currentStreamedContent} streaming={true} />,
+                isSearch: false,
+                bookName,
+                author
               }]);
             } else {
-              // Update streaming message
               setMessages(prev => prev.map(msg => 
                 msg.id === resultMsgId 
-                  ? { ...msg, content: <MarkdownRenderer content={content} streaming={true} /> }
+                  ? { ...msg, content: <MarkdownRenderer content={currentStreamedContent} streaming={true} /> }
                   : msg
               ));
             }
           }
           
-          // Capture final result
           if (event.type === 'final-result') {
             finalContent = event.content;
-            
-            // Update the streaming message with final content and sources
             setMessages(prev => prev.map(msg => 
               msg.id === resultMsgId 
                 ? {
@@ -360,19 +335,18 @@ export function Chat() {
                         </div>
                         <CitationTooltip sources={event.sources || []} />
                         
-                        {/* Follow-up Questions */}
                         {event.followUpQuestions && event.followUpQuestions.length > 0 && (
                           <div className="mt-8 pt-6 border-t border-gray-200 dark:border-gray-700">
                             <h3 className="text-sm font-semibold text-gray-700 dark:text-gray-300 mb-3">
-                              Follow-up questions
+                              Key Themes / Further Exploration
                             </h3>
                             <div className="space-y-2">
-                              {event.followUpQuestions.map((question, index) => (
+                              {event.followUpQuestions.map((theme, index) => (
                                 <button
                                   key={index}
                                   onClick={() => {
                                     const evt = new CustomEvent('followUpQuestion', { 
-                                      detail: { question },
+                                      detail: { question: theme }, // Re-using 'question' for theme
                                       bubbles: true 
                                     });
                                     document.dispatchEvent(evt);
@@ -381,7 +355,7 @@ export function Chat() {
                                 >
                                   <div className="flex items-center justify-between">
                                     <span className="text-sm text-gray-700 dark:text-gray-300 group-hover:text-gray-900 dark:group-hover:text-gray-100">
-                                      {question}
+                                      {theme}
                                     </span>
                                     <svg className="w-4 h-4 text-gray-400 group-hover:text-orange-500 flex-shrink-0 ml-2" fill="none" stroke="currentColor" viewBox="0 0 24 24">
                                       <path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M9 5l7 7-7 7" />
@@ -392,18 +366,15 @@ export function Chat() {
                             </div>
                           </div>
                         )}
-                        
-                        {/* Sources */}
                         <SourcesList sources={event.sources || []} />
                       </div>
                     ),
-                    searchResults: finalContent
+                    searchResults: finalContent // Store the full summary text
                   }
                 : msg
             ));
           }
           
-          // Update research box with new events
           setMessages(prev => prev.map(msg => 
             msg.id === assistantMsgId 
               ? { ...msg, content: <SearchDisplay events={[...events]} />, searchResults: finalContent }
@@ -413,29 +384,25 @@ export function Chat() {
       }
     } catch (error) {
       console.error('Search error:', error);
-      // Remove the search display message
       setMessages(prev => prev.filter(msg => msg.id !== assistantMsgId));
-      
-      // Show error message to user
-      const errorMessage = error instanceof Error ? error.message : 'An error occurred during search';
+      const errorMessage = error instanceof Error ? error.message : 'An error occurred during summary generation.';
       setMessages(prev => [...prev, {
         id: Date.now().toString(),
         role: 'assistant',
         content: (
           <div className="p-4 border border-red-200 dark:border-red-800 bg-red-50 dark:bg-red-900/20 rounded-lg">
-            <p className="text-red-700 dark:text-red-300 font-medium">Search Error</p>
+            <p className="text-red-700 dark:text-red-300 font-medium">Summary Generation Error</p>
             <p className="text-red-600 dark:text-red-400 text-sm mt-1">{errorMessage}</p>
             {(errorMessage.includes('API key') || errorMessage.includes('OPENAI_API_KEY')) && (
               <p className="text-red-600 dark:text-red-400 text-sm mt-2">
-                Please ensure all required API keys are set in your environment variables:
-                <br />• OPENAI_API_KEY (for GPT-4o)
-                <br />• ANTHROPIC_API_KEY (optional, for Claude)
-                <br />• FIRECRAWL_API_KEY (can be provided via UI)
+                Please ensure all required API keys are set:
+                <br />• OPENAI_API_KEY (for GPT models)
+                <br />• FIRECRAWL_API_KEY (can be provided via UI if not in .env)
               </p>
             )}
           </div>
         ),
-        isSearch: false
+        isSearch: false, bookName, author
       }]);
     } finally {
       setIsSearching(false);
@@ -444,113 +411,94 @@ export function Chat() {
 
   const handleSubmit = async (e: React.FormEvent) => {
     e.preventDefault();
-    if (!input.trim() || isSearching) return;
-    setShowSuggestions(false);
+    if (!bookNameInput.trim() || isSearching) return;
 
-    const userMessage = input;
-    setInput('');
+    const currentBookName = bookNameInput;
+    const currentAuthor = authorInput.trim() || undefined;
+
+    setBookNameInput('');
+    setAuthorInput('');
 
-    // Check if we have API key
     if (!hasApiKey) {
-      // Store the query and show modal
-      setPendingQuery(userMessage);
+      setPendingSearch({ bookName: currentBookName, author: currentAuthor });
       setShowApiKeyModal(true);
-      
-      // Still add user message to show what they asked
-      const userMsgId = Date.now().toString();
       setMessages(prev => [...prev, {
-        id: userMsgId,
+        id: Date.now().toString(),
         role: 'user',
-        content: userMessage,
-        isSearch: true
+        content: `Book: ${currentBookName}` + (currentAuthor ? ` by ${currentAuthor}` : ''),
+        isSearch: false,
+        bookName: currentBookName,
+        author: currentAuthor
       }]);
       return;
     }
 
-    // Add user message
-    const userMsgId = Date.now().toString();
     setMessages(prev => [...prev, {
-      id: userMsgId,
+      id: Date.now().toString(),
       role: 'user',
-      content: userMessage,
-      isSearch: true
+      content: `Generate summary for: ${currentBookName}` + (currentAuthor ? ` by ${currentAuthor}` : ''),
+      isSearch: false, // User message itself isn't a search display
+      bookName: currentBookName,
+      author: currentAuthor
     }]);
 
-    // Perform the search
-    await performSearch(userMessage);
+    await performSearch(currentBookName, currentAuthor);
   };
 
   return (
     <div className="flex flex-col flex-1">
       {messages.length === 0 ? (
-        // Center input when no messages
         <div className="flex-1 flex items-center justify-center px-4 sm:px-6 lg:px-8">
           <div className="w-full max-w-4xl">
-            <form onSubmit={handleSubmit}>
-              <div className="relative">
-                <input
+            <form onSubmit={handleSubmit} className="space-y-4">
+              <div>
+                <label htmlFor="bookName" className="block text-sm font-medium text-gray-700 dark:text-gray-300 mb-1">
+                  Book Name
+                </label>
+                <Input
+                  id="bookName"
                   type="text"
-                  value={input}
-                  onChange={(e) => setInput(e.target.value)}
-                  onFocus={() => {
-                    if (!hasShownSuggestions && messages.length === 0) {
-                      setShowSuggestions(true);
-                      setHasShownSuggestions(true);
-                    }
-                  }}
-                  onBlur={() => setTimeout(() => setShowSuggestions(false), 200)}
-                  placeholder="Enter query..."
-                  className="w-full h-14 rounded-full border border-zinc-200 bg-white pl-6 pr-16 text-base ring-offset-white file:border-0 file:bg-transparent file:text-sm file:font-medium placeholder:text-zinc-500 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-orange-500 focus-visible:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50 dark:border-zinc-800 dark:bg-zinc-950 dark:ring-offset-zinc-950 dark:placeholder:text-zinc-400 dark:focus-visible:ring-orange-400 shadow-sm"
+                  value={bookNameInput}
+                  onChange={(e) => setBookNameInput(e.target.value)}
+                  placeholder="e.g., Atomic Habits"
+                  className="w-full h-12 rounded-lg border-zinc-200 dark:border-zinc-800"
                   disabled={isSearching}
                 />
-                <button
-                  type="submit"
-                  disabled={isSearching || !input.trim()}
-                  className="absolute right-2 top-2 h-10 w-10 bg-orange-500 hover:bg-orange-600 text-white rounded-full disabled:opacity-50 disabled:cursor-not-allowed transition-colors duration-200 flex items-center justify-center"
-                >
-                  {isSearching ? (
-                    <svg className="w-5 h-5 animate-spin" fill="none" viewBox="0 0 24 24">
-                      <circle className="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" strokeWidth="4"></circle>
-                      <path className="opacity-75" fill="currentColor" d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"></path>
-                    </svg>
-                  ) : (
-                    <svg className="w-5 h-5" fill="none" stroke="currentColor" viewBox="0 0 24 24">
-                      <path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M21 21l-6-6m2-5a7 7 0 11-14 0 7 7 0 0114 0z" />
-                    </svg>
-                  )}
-                </button>
-                
-                {/* Suggestions dropdown - only show on initial load */}
-                {showSuggestions && !input && messages.length === 0 && (
-                  <div className="absolute top-full mt-2 w-full bg-white dark:bg-zinc-900 rounded-2xl shadow-lg border border-zinc-200 dark:border-zinc-800 overflow-hidden">
-                    <div className="p-2">
-                      <p className="text-xs text-gray-500 dark:text-gray-400 px-3 py-2 font-medium">Try searching for:</p>
-                      {SUGGESTED_QUERIES.map((suggestion, index) => (
-                        <button
-                          key={index}
-                          type="button"
-                          onClick={() => handleSelectSuggestion(suggestion)}
-                          className="w-full text-left px-3 py-2.5 hover:bg-gray-50 dark:hover:bg-zinc-800 rounded-lg transition-colors text-sm text-gray-700 dark:text-gray-300"
-                        >
-                          <div className="flex items-center gap-2">
-                            <svg className="w-4 h-4 text-gray-400" fill="none" stroke="currentColor" viewBox="0 0 24 24">
-                              <path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M21 21l-6-6m2-5a7 7 0 11-14 0 7 7 0 0114 0z" />
-                            </svg>
-                            <span className="line-clamp-1">{suggestion}</span>
-                          </div>
-                        </button>
-                      ))}
-                    </div>
-                  </div>
-                )}
               </div>
+              <div>
+                <label htmlFor="authorName" className="block text-sm font-medium text-gray-700 dark:text-gray-300 mb-1">
+                  Author (Optional)
+                </label>
+                <Input
+                  id="authorName"
+                  type="text"
+                  value={authorInput}
+                  onChange={(e) => setAuthorInput(e.target.value)}
+                  placeholder="e.g., James Clear"
+                  className="w-full h-12 rounded-lg border-zinc-200 dark:border-zinc-800"
+                  disabled={isSearching}
+                />
+              </div>
+              <Button
+                type="submit"
+                disabled={isSearching || !bookNameInput.trim()}
+                className="w-full h-12 bg-orange-500 hover:bg-orange-600 text-white rounded-lg disabled:opacity-50"
+              >
+                {isSearching ? (
+                  <svg className="w-5 h-5 animate-spin" fill="none" viewBox="0 0 24 24">
+                    <circle className="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" strokeWidth="4"></circle>
+                    <path className="opacity-75" fill="currentColor" d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"></path>
+                  </svg>
+                ) : (
+                  'Generate Book Summary'
+                )}
+              </Button>
             </form>
           </div>
         </div>
       ) : (
         <>
-          {/* Messages */}
-          <div className="flex-1 overflow-auto scrollbar-hide px-4 sm:px-6 lg:px-8 py-6">
+          <div ref={messagesContainerRef} className="flex-1 overflow-y-auto scrollbar-hide px-4 sm:px-6 lg:px-8 py-6">
             <div className="max-w-4xl mx-auto space-y-6">
               {messages.map(msg => (
                 <div
@@ -558,97 +506,75 @@ export function Chat() {
                   className={`${
                     msg.role === 'user' 
                       ? 'flex justify-end' 
-                      : 'w-full'
+                      : 'w-full' // Assistant messages take full width
                   }`}
                 >
                   {msg.role === 'user' ? (
                     <div className="max-w-2xl">
+                      <div className="text-xs text-gray-500 dark:text-gray-400 mb-1 text-right">You</div>
                       <span className="inline-block px-5 py-3 rounded-2xl bg-[#FBFAF9] dark:bg-zinc-800 text-[#36322F] dark:text-zinc-100">
                         {msg.content}
                       </span>
                     </div>
                   ) : (
-                    <div className="w-full">{msg.content}</div>
+                     <div className="w-full">
+                        <div className="text-xs text-gray-500 dark:text-gray-400 mb-1">
+                          AI Summary Generator {msg.bookName ? `for "${msg.bookName}"` : ''}
+                        </div>
+                        {msg.content}
+                      </div>
                   )}
                 </div>
               ))}
             </div>
           </div>
 
-          {/* Input */}
-          <div className="bg-white dark:bg-zinc-950 px-4 sm:px-6 lg:px-8 py-6">
-            <form onSubmit={handleSubmit} className="max-w-4xl mx-auto">
-          <div className="relative">
-            <input
-              type="text"
-              value={input}
-              onChange={(e) => setInput(e.target.value)}
-              onFocus={() => {
-                if (!hasShownSuggestions) {
-                  setShowSuggestions(true);
-                  setHasShownSuggestions(true);
-                }
-              }}
-              onBlur={() => setTimeout(() => setShowSuggestions(false), 200)}
-              placeholder="Enter query..."
-              className="w-full h-14 rounded-full border border-zinc-200 bg-white pl-6 pr-16 text-base ring-offset-white file:border-0 file:bg-transparent file:text-sm file:font-medium placeholder:text-zinc-500 focus-visible:outline-none focus-visible:ring-2 focus-visible:ring-orange-500 focus-visible:ring-offset-2 disabled:cursor-not-allowed disabled:opacity-50 dark:border-zinc-800 dark:bg-zinc-950 dark:ring-offset-zinc-950 dark:placeholder:text-zinc-400 dark:focus-visible:ring-orange-400 shadow-sm"
-              disabled={isSearching}
-            />
-            
-            <button
-              type="submit"
-              disabled={!input.trim() || isSearching}
-              className="absolute right-2 top-1/2 -translate-y-1/2 w-10 h-10 rounded-full bg-orange-500 hover:bg-orange-600 disabled:bg-gray-300 disabled:cursor-not-allowed text-white flex items-center justify-center transition-colors shadow-sm"
-            >
-              {isSearching ? (
-                <svg className="animate-spin h-5 w-5" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24">
-                  <circle className="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" strokeWidth="4"></circle>
-                  <path className="opacity-75" fill="currentColor" d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"></path>
-                </svg>
-              ) : (
-                <svg
-                  xmlns="http://www.w3.org/2000/svg"
-                  width="20"
-                  height="20"
-                  viewBox="0 0 24 24"
-                  fill="none"
-                  stroke="currentColor"
-                  strokeWidth="2"
-                  strokeLinecap="round"
-                  strokeLinejoin="round"
-                >
-                  <circle cx="11" cy="11" r="8" />
-                  <path d="m21 21-4.35-4.35" />
-                </svg>
-              )}
-            </button>
-            
-            {/* Suggestions dropdown - positioned to show above input */}
-            {showSuggestions && !input && (
-              <div className="absolute bottom-full mb-2 w-full bg-white dark:bg-zinc-900 rounded-2xl shadow-lg border border-zinc-200 dark:border-zinc-800 overflow-hidden">
-                <div className="p-2">
-                  <p className="text-xs text-gray-500 dark:text-gray-400 px-3 py-2 font-medium">Try searching for:</p>
-                  {SUGGESTED_QUERIES.map((suggestion, index) => (
-                    <button
-                      key={index}
-                      type="button"
-                      onClick={() => handleSelectSuggestion(suggestion)}
-                      className="w-full text-left px-3 py-2.5 hover:bg-gray-50 dark:hover:bg-zinc-800 rounded-lg transition-colors text-sm text-gray-700 dark:text-gray-300"
-                    >
-                      <div className="flex items-center gap-2">
-                        <svg className="w-4 h-4 text-gray-400" fill="none" stroke="currentColor" viewBox="0 0 24 24">
-                          <path strokeLinecap="round" strokeLinejoin="round" strokeWidth={2} d="M21 21l-6-6m2-5a7 7 0 11-14 0 7 7 0 0114 0z" />
-                        </svg>
-                        <span className="line-clamp-1">{suggestion}</span>
-                      </div>
-                    </button>
-                  ))}
-                </div>
+          {/* Input form at the bottom */}
+          <div className="bg-white dark:bg-zinc-950 px-4 sm:px-6 lg:px-8 py-4 border-t dark:border-zinc-800">
+            <form onSubmit={handleSubmit} className="max-w-4xl mx-auto space-y-3">
+              <div className="flex flex-col sm:flex-row gap-3">
+                <Input
+                  type="text"
+                  value={bookNameInput}
+                  onChange={(e) => setBookNameInput(e.target.value)}
+                  placeholder="Book Name (e.g., Sapiens)"
+                  className="flex-grow h-12 rounded-lg border-zinc-200 dark:border-zinc-800"
+                  disabled={isSearching}
+                />
+                <Input
+                  type="text"
+                  value={authorInput}
+                  onChange={(e) => setAuthorInput(e.target.value)}
+                  placeholder="Author (Optional, e.g., Yuval Noah Harari)"
+                  className="flex-grow h-12 rounded-lg border-zinc-200 dark:border-zinc-800"
+                  disabled={isSearching}
+                />
               </div>
-            )}
+              <Button
+                type="submit"
+                disabled={isSearching || !bookNameInput.trim()}
+                className="w-full h-12 bg-orange-500 hover:bg-orange-600 text-white rounded-lg disabled:opacity-50 flex items-center justify-center gap-2"
+              >
+                {isSearching ? (
+                  <>
+                    <svg className="w-5 h-5 animate-spin" fill="none" viewBox="0 0 24 24">
+                      <circle className="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" strokeWidth="4"></circle>
+                      <path className="opacity-75" fill="currentColor" d="M4 12a8 8 0 018-8V0C5.373 0 0 5.373 0 12h4zm2 5.291A7.962 7.962 0 014 12H0c0 3.042 1.135 5.824 3 7.938l3-2.647z"></path>
+                    </svg>
+                    Generating Summary...
+                  </>
+                ) : (
+                  <>
+                    <svg xmlns="http://www.w3.org/2000/svg" width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" strokeWidth="2" strokeLinecap="round" strokeLinejoin="round">
+                      <path d="M4 19.5A2.5 2.5 0 0 1 6.5 17H20"/>
+                      <path d="M6.5 2H20v20H6.5A2.5 2.5 0 0 1 4 19.5v-15A2.5 2.5 0 0 1 6.5 2z"/>
+                    </svg>
+                    Generate Book Summary
+                  </>
+                )}
+              </Button>
+            </form>
           </div>
-        </form>
-      </div>
         </>
       )}
 
@@ -658,7 +584,7 @@ export function Chat() {
           <DialogHeader>
             <DialogTitle>Firecrawl API Key Required</DialogTitle>
             <DialogDescription>
-              To use Firesearch, you need a Firecrawl API key. You can get one for free.
+              To generate book summaries, a Firecrawl API key is recommended for web crawling. You can get one for free. If it's set in your server environment (.env), this step might be optional.
             </DialogDescription>
           </DialogHeader>
           <div className="grid gap-4 py-4">
@@ -673,7 +599,7 @@ export function Chat() {
             </div>
             <div className="space-y-2">
               <label htmlFor="apiKey" className="text-sm font-medium">
-                Enter your API key
+                Enter your Firecrawl API key (Optional if set in .env)
               </label>
               <Input
                 id="apiKey"
@@ -688,13 +614,21 @@ export function Chat() {
           <div className="flex gap-2 justify-end">
             <Button
               variant="code"
-              onClick={() => setShowApiKeyModal(false)}
+              onClick={() => {
+                setShowApiKeyModal(false);
+                // If user cancels, and there was a pending search, try it without client-side key
+                if (pendingSearch) {
+                  toast.info("Attempting search without client-side API key...");
+                  performSearch(pendingSearch.bookName, pendingSearch.author);
+                  setPendingSearch(null);
+                }
+              }}
             >
-              Cancel
+              Cancel / Use Env Key
             </Button>
             <Button 
               variant="orange"
-              onClick={saveApiKey}
+              onClick={saveApiKeyAndSearch}
               disabled={!firecrawlApiKey.trim()}
             >
               Save and Continue
diff --git a/app/globals.css b/app/globals.css
index a10b3b2..a5fc97a 100644
--- a/app/globals.css
+++ b/app/globals.css
@@ -216,6 +216,73 @@
   scrollbar-width: none;  /* Firefox */
 }
 
+/* Custom styles for Markdown content generated by markdown-renderer.tsx */
+/* These will work in conjunction with or override Tailwind Prose defaults if necessary */
+.markdown-content {
+  @apply text-sm; /* Base text size from prose-sm */
+}
+
+.markdown-content h1 {
+  @apply text-3xl font-bold mt-8 mb-6 leading-tight;
+  /* prose-sm h1 is text-2xl, making it larger */
+}
+
+.markdown-content h2 {
+  @apply text-2xl font-semibold mt-6 mb-4 leading-snug;
+   /* prose-sm h2 is text-xl */
+}
+
+.markdown-content h3 {
+  @apply text-xl font-semibold mt-5 mb-3 leading-normal;
+   /* prose-sm h3 is text-lg */
+}
+
+.markdown-content h4 {
+  @apply text-lg font-semibold mt-4 mb-2;
+   /* prose-sm h4 is text-base, this is a bit larger */
+}
+
+.markdown-content p {
+  @apply mb-4 leading-relaxed; /* Default prose p has mb-4, leading-relaxed is good */
+}
+
+.markdown-content a {
+  @apply text-orange-600 hover:text-orange-700 dark:text-orange-400 dark:hover:text-orange-500 underline decoration-orange-600/50 hover:decoration-orange-700;
+  /* More specific link styling if needed */
+}
+
+.markdown-content blockquote {
+  @apply border-l-4 border-orange-500 pl-4 py-2 my-6 text-base italic;
+  @apply bg-orange-50 dark:bg-orange-900/20 text-orange-700 dark:text-orange-300;
+  /* Custom blockquote styling */
+}
+
+.markdown-content ul, .markdown-content ol {
+  @apply my-4 pl-5 space-y-1; /* Default prose lists are fine, ensure spacing */
+}
+
+.markdown-content li {
+  @apply mb-1;
+}
+
+.markdown-content code:not(pre code) {
+  @apply bg-gray-100 dark:bg-gray-800 px-1.5 py-0.5 rounded text-xs font-mono text-orange-700 dark:text-orange-300;
+  /* More specific inline code */
+}
+
+.markdown-content pre {
+  @apply bg-gray-800 dark:bg-gray-900 text-gray-100 dark:text-gray-200 p-4 rounded-lg overflow-x-auto my-4 text-xs;
+  /* Darker code blocks for both themes, adjust as needed */
+}
+.markdown-content pre code {
+  @apply bg-transparent p-0 text-xs; /* Reset inner code within pre */
+}
+
+.markdown-content sup.citation {
+  @apply text-orange-500 hover:text-orange-700 dark:text-orange-400 dark:hover:text-orange-300 font-medium no-underline;
+  @apply ml-0.5; /* Minor spacing adjustment */
+}
+
 .scrollbar-hide::-webkit-scrollbar {
   display: none;
 }
diff --git a/app/search.tsx b/app/search.tsx
index 0ef027e..ef78d7d 100644
--- a/app/search.tsx
+++ b/app/search.tsx
@@ -4,7 +4,14 @@ import { createStreamableValue } from 'ai/rsc';
 import { FirecrawlClient } from '@/lib/firecrawl';
 import { LangGraphSearchEngine as SearchEngine, SearchEvent } from '@/lib/langgraph-search-engine';
 
-export async function search(query: string, context?: { query: string; response: string }[], apiKey?: string) {
+interface BookSearchParams {
+  bookName: string;
+  author?: string;
+  context?: { query: string; response: string }[];
+  apiKey?: string;
+}
+
+export async function search({ bookName, author, context, apiKey }: BookSearchParams) {
   const stream = createStreamableValue<SearchEvent>();
   
   // Create FirecrawlClient with API key if provided
@@ -15,7 +22,8 @@ export async function search(query: string, context?: { query: string; response:
   (async () => {
     try {
       // Stream events as they happen
-      await searchEngine.search(query, (event) => {
+      // The searchEngine will internally use bookName and author to generate queries
+      await searchEngine.search(bookName, author, (event) => {
         stream.update(event);
       }, context);
       
diff --git a/lib/config.ts b/lib/config.ts
index 293d6d2..d7407d5 100644
--- a/lib/config.ts
+++ b/lib/config.ts
@@ -1,29 +1,32 @@
 // Search Engine Configuration
 export const SEARCH_CONFIG = {
-  // Search Settings
-  MAX_SEARCH_QUERIES: 4,        // Maximum number of search queries to generate
-  MAX_SOURCES_PER_SEARCH: 6,     // Maximum sources to return per search query
-  MAX_SOURCES_TO_SCRAPE: 6,      // Maximum sources to scrape for additional content
-  
+  // Search Settings for Book Summaries
+  MAX_BOOK_SUMMARY_QUERIES: 8,       // Max number of different search query variations for a book
+  MAX_SOURCES_PER_BOOK_QUERY: 5,   // Max sources Firecrawl returns for each of those ~8 queries
+                                     // Aiming for 8 queries * 3-5 sources/query = 24-40 potential sources initially
+  MIN_SOURCES_FOR_BOOK_SUMMARY: 10, // Minimum unique sources required before attempting synthesis
+  MAX_SOURCES_FOR_SYNTHESIS: 25,   // Max sources to pass to the LLM for final summary generation (to manage context window)
+
   // Content Processing
-  MIN_CONTENT_LENGTH: 100,       // Minimum content length to consider valid
-  SUMMARY_CHAR_LIMIT: 100,       // Character limit for source summaries
-  CONTEXT_PREVIEW_LENGTH: 500,   // Preview length for previous context
-  ANSWER_CHECK_PREVIEW: 2500,    // Content preview length for answer checking
-  MAX_SOURCES_TO_CHECK: 10,      // Maximum sources to check for answers
+  MIN_CONTENT_LENGTH_FOR_SOURCE: 250, // Minimum markdown characters for a source to be considered useful
+  MIN_CONTENT_LENGTH_FOR_SUMMARY: 100, // Minimum content length for a source to attempt to make a mini-summary for it
+  SUMMARY_CHAR_LIMIT: 150,       // Character limit for individual source summaries (used in `summarizeSourceForBook`)
+  CONTEXT_PREVIEW_LENGTH: 500,   // Preview length for previous conversation context
+  // ANSWER_CHECK_PREVIEW: 2500, // Less relevant for book summary
+  // MAX_SOURCES_TO_CHECK: 10,   // Less relevant for book summary
   
-  // Retry Logic
-  MAX_RETRIES: 2,                // Maximum retry attempts for failed operations
-  MAX_SEARCH_ATTEMPTS: 3,        // Maximum attempts to find answers via search
-  MIN_ANSWER_CONFIDENCE: 0.3,    // Minimum confidence (0-1) that a question was answered
-  EARLY_TERMINATION_CONFIDENCE: 0.8, // Confidence level to skip additional searches
+  // Retry Logic (may need adjustment for book summary context)
+  MAX_RETRIES: 1,                // Maximum retry attempts for a single failed operation (e.g. a single Firecrawl search)
+  // MAX_SEARCH_ATTEMPTS: 3,     // Less relevant as we generate a batch of queries upfront
+  // MIN_ANSWER_CONFIDENCE: 0.3, // Less relevant
+  // EARLY_TERMINATION_CONFIDENCE: 0.8, // Less relevant
   
   // Timeouts
-  SCRAPE_TIMEOUT: 15000,         // Timeout for scraping operations (ms)
+  SCRAPE_TIMEOUT: 15000,         // Timeout for scraping operations (ms) - Firecrawl search includes scrape
   
   // Performance
-  SOURCE_ANIMATION_DELAY: 50,    // Delay between source animations (ms) - reduced from 150
-  PARALLEL_SUMMARY_GENERATION: true, // Generate summaries in parallel
+  SOURCE_ANIMATION_DELAY: 50,    // Delay between source animations (ms)
+  PARALLEL_SUMMARY_GENERATION: true, // Generate individual source summaries in parallel
 } as const;
 
 // You can also export individual configs for different components
@@ -35,7 +38,7 @@ export const UI_CONFIG = {
 
 // Model Configuration
 export const MODEL_CONFIG = {
-  FAST_MODEL: "gpt-4o-mini",     // Fast model for quick operations
-  QUALITY_MODEL: "gpt-4o",       // High-quality model for final synthesis
-  TEMPERATURE: 0,                // Model temperature (0 = deterministic)
+  FAST_MODEL: "gpt-4o-mini",     // Fast model for quick operations (like source pre-summarization)
+  QUALITY_MODEL: "gpt-4o",       // High-quality model for final book summary synthesis
+  TEMPERATURE: 0.1,              // Model temperature (0 = deterministic, slight increase for more varied summaries if needed)
 } as const;
\ No newline at end of file
diff --git a/lib/langgraph-search-engine.ts b/lib/langgraph-search-engine.ts
index ced093e..5fffcf1 100644
--- a/lib/langgraph-search-engine.ts
+++ b/lib/langgraph-search-engine.ts
@@ -20,7 +20,7 @@ export type SearchEvent =
   | { type: 'thinking'; message: string }
   | { type: 'searching'; query: string; index: number; total: number }
   | { type: 'found'; sources: Source[]; query: string }
-  | { type: 'scraping'; url: string; index: number; total: number; query: string }
+  | { type: 'scraping'; url: string; index: number; total: number; query: string } // query here is the user's original query for context
   | { type: 'content-chunk'; chunk: string }
   | { type: 'final-result'; content: string; sources: Source[]; followUpQuestions?: string[] }
   | { type: 'error'; error: string; errorType?: ErrorType }
@@ -33,15 +33,15 @@ export interface Source {
   url: string;
   title: string;
   content?: string;
-  quality?: number;
-  summary?: string;
+  quality?: number; // Optional: could be relevance score to a specific query
+  summary?: string; // Optional: short summary of the source content
 }
 
 export interface SearchResult {
   url: string;
   title: string;
-  content?: string;
-  markdown?: string;
+  content?: string; // Markdown content from Firecrawl search
+  markdown?: string; // Ensure markdown is prioritized
 }
 
 export interface SearchStep {
@@ -54,7 +54,15 @@ export interface SearchStep {
 // Proper LangGraph state using Annotation with reducers
 const SearchStateAnnotation = Annotation.Root({
   // Input fields
-  query: Annotation<string>({
+  bookName: Annotation<string>({ // New: Book Name
+    reducer: (_, y) => y ?? "",
+    default: () => ""
+  }),
+  author: Annotation<string | undefined>({ // New: Author (optional)
+    reducer: (_, y) => y,
+    default: () => undefined
+  }),
+  query: Annotation<string>({ // Retained for internal use, like the main topic for LLMs
     reducer: (_, y) => y ?? "",
     default: () => ""
   }),
@@ -64,65 +72,76 @@ const SearchStateAnnotation = Annotation.Root({
   }),
   
   // Process fields
-  understanding: Annotation<string | undefined>({
+  understanding: Annotation<string | undefined>({ // What the agent understands it needs to do
     reducer: (x, y) => y ?? x,
     default: () => undefined
   }),
-  searchQueries: Annotation<string[] | undefined>({
+  searchQueries: Annotation<string[] | undefined>({ // The list of queries to execute
     reducer: (x, y) => y ?? x,
     default: () => undefined
   }),
-  currentSearchIndex: Annotation<number>({
+  currentSearchIndex: Annotation<number>({ // Index for iterating through searchQueries
     reducer: (x, y) => y ?? x,
     default: () => 0
   }),
   
   // Results fields - with proper array reducers
-  sources: Annotation<Source[]>({
+  sources: Annotation<Source[]>({ // Aggregated sources from all search queries
     reducer: (existing: Source[], update: Source[] | undefined) => {
       if (!update) return existing;
-      // Deduplicate sources by URL
       const sourceMap = new Map<string, Source>();
       [...existing, ...update].forEach(source => {
-        sourceMap.set(source.url, source);
+        // If new source has content and existing one doesn't, or new one is simply preferred
+        const existingSource = sourceMap.get(source.url);
+        if (!existingSource || (source.content && !existingSource.content) || source.content) {
+          sourceMap.set(source.url, source);
+        }
       });
       return Array.from(sourceMap.values());
     },
     default: () => []
   }),
-  scrapedSources: Annotation<Source[]>({
+  scrapedSources: Annotation<Source[]>({ // Sources that needed explicit scraping (not used much if search scrapes)
     reducer: (existing: Source[], update: Source[] | undefined) => {
       if (!update) return existing;
-      return [...existing, ...update];
+      // Similar deduplication/update logic as sources
+      const sourceMap = new Map<string, Source>();
+      [...existing, ...update].forEach(source => {
+         const existingSource = sourceMap.get(source.url);
+        if (!existingSource || (source.content && !existingSource.content) || source.content) {
+          sourceMap.set(source.url, source);
+        }
+      });
+      return Array.from(sourceMap.values());
     },
     default: () => []
   }),
-  processedSources: Annotation<Source[] | undefined>({
+  processedSources: Annotation<Source[] | undefined>({ // Sources after filtering/ranking for synthesis
     reducer: (x, y) => y ?? x,
     default: () => undefined
   }),
-  finalAnswer: Annotation<string | undefined>({
+  finalAnswer: Annotation<string | undefined>({ // The final generated book summary
     reducer: (x, y) => y ?? x,
     default: () => undefined
   }),
-  followUpQuestions: Annotation<string[] | undefined>({
+  followUpQuestions: Annotation<string[] | undefined>({ // Potentially "Key Themes" or similar for books
     reducer: (x, y) => y ?? x,
     default: () => undefined
   }),
   
-  // Answer tracking
-  subQueries: Annotation<Array<{
-    question: string;
-    searchQuery: string;
-    answered: boolean;
-    answer?: string;
-    confidence: number;
-    sources: string[];
-  }> | undefined>({
-    reducer: (x, y) => y ?? x,
-    default: () => undefined
-  }),
-  searchAttempt: Annotation<number>({
+  // Answer tracking - This might be less relevant for book summaries
+  // subQueries: Annotation<Array<{
+  //   question: string; // e.g., "What is the plot?"
+  //   searchQuery: string; // The actual query used for this sub-question
+  //   answered: boolean;
+  //   answer?: string;
+  //   confidence: number;
+  //   sources: string[]; // URLs
+  // }> | undefined>({
+  //   reducer: (x, y) => y ?? x,
+  //   default: () => undefined
+  // }),
+  searchAttempt: Annotation<number>({ // Could be used if initial searches don't yield enough
     reducer: (x, y) => y ?? x,
     default: () => 0
   }),
@@ -156,7 +175,7 @@ type SearchState = typeof SearchStateAnnotation.State;
 interface GraphConfig {
   configurable?: {
     eventCallback?: (event: SearchEvent) => void;
-    checkpointId?: string;
+    checkpointId?: string; // For potential future use with LangGraph persistence
   };
 }
 
@@ -164,8 +183,8 @@ export class LangGraphSearchEngine {
   private firecrawl: FirecrawlClient;
   private contextProcessor: ContextProcessor;
   private graph: ReturnType<typeof this.buildGraph>;
-  private llm: ChatOpenAI;
-  private streamingLlm: ChatOpenAI;
+  private llm: ChatOpenAI; // For non-streaming tasks
+  private streamingLlm: ChatOpenAI; // For streaming the final answer
   private checkpointer?: MemorySaver;
 
   constructor(firecrawl: FirecrawlClient, options?: { enableCheckpointing?: boolean }) {
@@ -177,7 +196,6 @@ export class LangGraphSearchEngine {
       throw new Error('OPENAI_API_KEY environment variable is not set');
     }
     
-    // Initialize LangChain models
     this.llm = new ChatOpenAI({
       modelName: MODEL_CONFIG.FAST_MODEL,
       temperature: MODEL_CONFIG.TEMPERATURE,
@@ -185,13 +203,12 @@ export class LangGraphSearchEngine {
     });
     
     this.streamingLlm = new ChatOpenAI({
-      modelName: MODEL_CONFIG.QUALITY_MODEL,
+      modelName: MODEL_CONFIG.QUALITY_MODEL, // Use quality model for the summary
       temperature: MODEL_CONFIG.TEMPERATURE,
       streaming: true,
       openAIApiKey: apiKey,
     });
 
-    // Enable checkpointing if requested
     if (options?.enableCheckpointing) {
       this.checkpointer = new MemorySaver();
     }
@@ -200,1159 +217,572 @@ export class LangGraphSearchEngine {
   }
 
   getInitialSteps(): SearchStep[] {
+    // These steps can be generic and still apply
     return [
       { id: 'understanding', label: 'Understanding request', status: 'pending' },
-      { id: 'planning', label: 'Planning search', status: 'pending' },
-      { id: 'searching', label: 'Searching sources', status: 'pending' },
-      { id: 'analyzing', label: 'Analyzing content', status: 'pending' },
-      { id: 'synthesizing', label: 'Synthesizing answer', status: 'pending' },
+      { id: 'planning', label: 'Planning search strategy', status: 'pending' },
+      { id: 'searching', label: 'Gathering information', status: 'pending' },
+      { id: 'analyzing', label: 'Analyzing sources', status: 'pending' },
+      { id: 'synthesizing', label: 'Generating summary', status: 'pending' },
       { id: 'complete', label: 'Complete', status: 'pending' }
     ];
   }
 
   private buildGraph() {
-    // Create closures for helper methods
-    const analyzeQuery = this.analyzeQuery.bind(this);
-    const scoreContent = this.scoreContent.bind(this);
-    const summarizeContent = this.summarizeContent.bind(this);
-    const generateStreamingAnswer = this.generateStreamingAnswer.bind(this);
-    const generateFollowUpQuestions = this.generateFollowUpQuestions.bind(this);
+    const analyzeBookRequest = this.analyzeBookRequest.bind(this);
+    const scoreContentRelevance = this.scoreContentRelevance.bind(this);
+    const summarizeSourceForBook = this.summarizeSourceForBook.bind(this);
+    const generateStreamingBookSummary = this.generateStreamingBookSummary.bind(this);
+    const generateKeyThemes = this.generateKeyThemes.bind(this); // New method for "follow-up"
     const firecrawl = this.firecrawl;
-    const contextProcessor = this.contextProcessor;
+    const contextProcessor = this.contextProcessor; // May need adjustment or less emphasis
     
     const workflow = new StateGraph(SearchStateAnnotation)
-      // Understanding node
       .addNode("understand", async (state: SearchState, config?: GraphConfig): Promise<Partial<SearchState>> => {
         const eventCallback = config?.configurable?.eventCallback;
-        
         if (eventCallback) {
-          eventCallback({
-            type: 'phase-update',
-            phase: 'understanding',
-            message: 'Analyzing your request...'
-          });
+          eventCallback({ type: 'phase-update', phase: 'understanding', message: 'Understanding book request...' });
         }
         
         try {
-          const understanding = await analyzeQuery(state.query, state.context);
-          
+          // The "query" for analysis will be the book title and author
+          const understanding = await analyzeBookRequest(state.bookName, state.author, state.context);
           if (eventCallback) {
-            eventCallback({
-              type: 'thinking',
-              message: understanding
-            });
+            eventCallback({ type: 'thinking', message: understanding });
           }
-          
-          return {
-            understanding,
-            phase: 'planning' as SearchPhase
-          };
+          return { understanding, query: `Summary of "${state.bookName}"${state.author ? ` by ${state.author}` : ''}`, phase: 'planning' as SearchPhase };
         } catch (error) {
-          return {
-            error: error instanceof Error ? error.message : 'Failed to understand query',
-            errorType: 'llm' as ErrorType,
-            phase: 'error' as SearchPhase
-          };
+          return { error: error instanceof Error ? error.message : 'Failed to understand request', errorType: 'llm' as ErrorType, phase: 'error' as SearchPhase };
         }
       })
       
-      // Planning node
       .addNode("plan", async (state: SearchState, config?: GraphConfig): Promise<Partial<SearchState>> => {
         const eventCallback = config?.configurable?.eventCallback;
-        
         if (eventCallback) {
-          eventCallback({
-            type: 'phase-update',
-            phase: 'planning',
-            message: 'Planning search strategy...'
-          });
+          eventCallback({ type: 'phase-update', phase: 'planning', message: 'Devising search plan for the book...' });
         }
         
         try {
-          // Extract sub-queries if not already done
-          let subQueries = state.subQueries;
-          if (!subQueries) {
-            const extractSubQueries = this.extractSubQueries.bind(this);
-            const extracted = await extractSubQueries(state.query);
-            subQueries = extracted.map(sq => ({
-              question: sq.question,
-              searchQuery: sq.searchQuery,
-              answered: false,
-              confidence: 0,
-              sources: []
-            }));
-          }
+          const bookName = state.bookName;
+          const author = state.author;
           
-          // Generate search queries for unanswered questions
-          const unansweredQueries = subQueries.filter(sq => !sq.answered || sq.confidence < SEARCH_CONFIG.MIN_ANSWER_CONFIDENCE);
-          
-          if (unansweredQueries.length === 0) {
-            // All questions answered, skip to analysis
-            return {
-              subQueries,
-              phase: 'analyzing' as SearchPhase
-            };
-          }
-          
-          // Use alternative search queries if this is a retry
-          let searchQueries: string[];
-          if (state.searchAttempt > 0) {
-            const generateAlternativeSearchQueries = this.generateAlternativeSearchQueries.bind(this);
-            searchQueries = await generateAlternativeSearchQueries(subQueries, state.searchAttempt);
-            
-            // Update sub-queries with new search queries
-            let alternativeIndex = 0;
-            subQueries.forEach(sq => {
-              if (!sq.answered || sq.confidence < SEARCH_CONFIG.MIN_ANSWER_CONFIDENCE) {
-                if (alternativeIndex < searchQueries.length) {
-                  sq.searchQuery = searchQueries[alternativeIndex];
-                  alternativeIndex++;
-                }
-              }
-            });
-          } else {
-            // First attempt - use the search queries from sub-queries
-            searchQueries = unansweredQueries.map(sq => sq.searchQuery);
+          let searchQueries: string[] = [
+            `"${bookName}" summary`,
+            `"${bookName}" book review`,
+            `"${bookName}" detailed summary`,
+            `"${bookName}" analysis`,
+            `"${bookName}" key takeaways`,
+            `best summaries of "${bookName}"`,
+          ];
+          if (author) {
+            searchQueries.push(`"${bookName}" by ${author} summary`);
+            searchQueries.push(`"${bookName}" by ${author} review`);
+            searchQueries.push(`"${bookName}" by ${author} detailed analysis`);
           }
-          
+          // Ensure we don't exceed MAX_SEARCH_QUERIES from config, though we might want more for books
+          searchQueries = searchQueries.slice(0, SEARCH_CONFIG.MAX_BOOK_SUMMARY_QUERIES);
+
+
           if (eventCallback) {
-            if (state.searchAttempt === 0) {
-              eventCallback({
-                type: 'thinking',
-                message: searchQueries.length > 3 
-                  ? `I detected ${subQueries.length} different questions. I'll search for each one separately.`
-                  : `I'll search for information to answer your question.`
-              });
-            } else {
-              eventCallback({
-                type: 'thinking',
-                message: `Trying alternative search strategies for: ${unansweredQueries.map(sq => sq.question).join(', ')}`
-              });
-            }
+            eventCallback({ type: 'thinking', message: `Planning to search with ${searchQueries.length} different queries to gather comprehensive information about "${bookName}".` });
           }
           
           return {
             searchQueries,
-            subQueries,
             currentSearchIndex: 0,
             phase: 'searching' as SearchPhase
           };
         } catch (error) {
-          return {
-            error: error instanceof Error ? error.message : 'Failed to plan search',
-            errorType: 'llm' as ErrorType,
-            phase: 'error' as SearchPhase
-          };
+          return { error: error instanceof Error ? error.message : 'Failed to plan search strategy', errorType: 'llm'as ErrorType, phase: 'error'as SearchPhase };
         }
       })
-      
-      // Search node (handles one search at a time)
+
       .addNode("search", async (state: SearchState, config?: GraphConfig): Promise<Partial<SearchState>> => {
         const eventCallback = config?.configurable?.eventCallback;
         const searchQueries = state.searchQueries || [];
         const currentIndex = state.currentSearchIndex || 0;
         
         if (currentIndex === 0 && eventCallback) {
-          eventCallback({
-            type: 'phase-update',
-            phase: 'searching',
-            message: 'Searching the web...'
-          });
+          eventCallback({ type: 'phase-update', phase: 'searching', message: 'Gathering information from various sources...' });
         }
         
         if (currentIndex >= searchQueries.length) {
-          return {
-            phase: 'scrape' as SearchPhase
-          };
+          // All planned searches are done, move to scraping/analyzing
+          // If Firecrawl's search includes scraping, 'scrape' node might be light
+          return { phase: 'scrape' as SearchPhase };
         }
         
-        const searchQuery = searchQueries[currentIndex];
-        
+        const currentQuery = searchQueries[currentIndex];
         if (eventCallback) {
-          eventCallback({
-            type: 'searching',
-            query: searchQuery,
-            index: currentIndex + 1,
-            total: searchQueries.length
-          });
+          eventCallback({ type: 'searching', query: currentQuery, index: currentIndex + 1, total: searchQueries.length });
         }
         
         try {
-          const results = await firecrawl.search(searchQuery, {
-            limit: SEARCH_CONFIG.MAX_SOURCES_PER_SEARCH,
-            scrapeOptions: {
-              formats: ['markdown']
-            }
+          const results = await firecrawl.search(currentQuery, {
+            limit: SEARCH_CONFIG.MAX_SOURCES_PER_BOOK_QUERY, // Configurable: sources per specific query
+            scrapeOptions: { formats: ['markdown'] } // Crucial: get content directly
           });
           
-          const newSources: Source[] = results.data.map((r: SearchResult) => ({
-            url: r.url,
-            title: r.title,
-            content: r.markdown || r.content || '',
-            quality: 0
+          const newSources: Source[] = results.data
+            .filter((r: SearchResult) => r.markdown && r.markdown.length > SEARCH_CONFIG.MIN_CONTENT_LENGTH_FOR_SOURCE) // Filter out very short/empty pages
+            .map((r: SearchResult) => ({
+              url: r.url,
+              title: r.title,
+              content: r.markdown || r.content || '', // Prefer markdown
+              quality: 0 // Will be scored later
           }));
           
           if (eventCallback) {
-            eventCallback({
-              type: 'found',
-              sources: newSources,
-              query: searchQuery
-            });
+            eventCallback({ type: 'found', sources: newSources, query: currentQuery });
           }
-          
-          // Process sources in parallel for better performance
-          if (SEARCH_CONFIG.PARALLEL_SUMMARY_GENERATION) {
-            await Promise.all(newSources.map(async (source) => {
-              if (eventCallback) {
-                eventCallback({
-                  type: 'source-processing',
-                  url: source.url,
-                  title: source.title,
-                  stage: 'browsing'
-                });
-              }
-              
-              // Score the content
-              source.quality = scoreContent(source.content || '', state.query);
-              
-              // Generate summary if content is available
-              if (source.content && source.content.length > SEARCH_CONFIG.MIN_CONTENT_LENGTH) {
-                const summary = await summarizeContent(source.content, searchQuery);
-                
-                // Store the summary in the source object
-                if (summary && !summary.toLowerCase().includes('no specific')) {
-                  source.summary = summary;
-                  
-                  if (eventCallback) {
-                    eventCallback({
-                      type: 'source-complete',
-                      url: source.url,
-                      summary: summary
-                    });
-                  }
-                }
-              }
-            }));
-          } else {
-            // Original sequential processing
-            for (const source of newSources) {
-              if (eventCallback) {
-                eventCallback({
-                  type: 'source-processing',
-                  url: source.url,
-                  title: source.title,
-                  stage: 'browsing'
-                });
-              }
-              
-              // Small delay for animation
-              await new Promise(resolve => setTimeout(resolve, SEARCH_CONFIG.SOURCE_ANIMATION_DELAY));
-              
-              // Score the content
-              source.quality = scoreContent(source.content || '', state.query);
-              
-              // Generate summary if content is available
-              if (source.content && source.content.length > SEARCH_CONFIG.MIN_CONTENT_LENGTH) {
-                const summary = await summarizeContent(source.content, searchQuery);
-                
-                // Store the summary in the source object
-                if (summary && !summary.toLowerCase().includes('no specific')) {
-                  source.summary = summary;
-                  
-                  if (eventCallback) {
-                    eventCallback({
-                      type: 'source-complete',
-                      url: source.url,
-                      summary: summary
-                    });
-                  }
+
+          // Parallel processing of sources (scoring and initial summary)
+          await Promise.all(newSources.map(async (source) => {
+            if (eventCallback) {
+              eventCallback({ type: 'source-processing', url: source.url, title: source.title, stage: 'browsing' });
+            }
+            source.quality = scoreContentRelevance(source.content || '', state.bookName, state.author);
+            if (source.content && source.content.length > SEARCH_CONFIG.MIN_CONTENT_LENGTH_FOR_SUMMARY) {
+              const summary = await summarizeSourceForBook(source.content, state.bookName, currentQuery);
+              if (summary && !summary.toLowerCase().includes('no specific information')) {
+                source.summary = summary;
+                if (eventCallback) {
+                  eventCallback({ type: 'source-complete', url: source.url, summary: summary });
                 }
               }
             }
-          }
+          }));
           
           return {
-            sources: newSources,
+            sources: newSources, // newSources will be merged with existing by the reducer
             currentSearchIndex: currentIndex + 1
           };
-        } catch {
+        } catch (error) {
+          console.warn(`Search for query "${currentQuery}" failed:`, error);
+          // Still increment index to try next query, report error if needed via event
+          if (eventCallback) {
+            eventCallback({ type: 'error', error: `Search for "${currentQuery}" failed.`, errorType: 'search' });
+          }
           return {
             currentSearchIndex: currentIndex + 1,
-            errorType: 'search' as ErrorType
+            // error: `Search for query "${currentQuery}" failed.`, // Avoid setting global error yet
+            // errorType: 'search' as ErrorType
           };
         }
       })
       
-      // Scraping node
       .addNode("scrape", async (state: SearchState, config?: GraphConfig): Promise<Partial<SearchState>> => {
         const eventCallback = config?.configurable?.eventCallback;
-        const sourcesToScrape = state.sources?.filter(s => 
-          !s.content || s.content.length < SEARCH_CONFIG.MIN_CONTENT_LENGTH
-        ) || [];
-        const newScrapedSources: Source[] = [];
-        
-        // Sources with content were already processed in search node, just pass them through
-        const sourcesWithContent = state.sources?.filter(s => 
-          s.content && s.content.length >= SEARCH_CONFIG.MIN_CONTENT_LENGTH
-        ) || [];
-        newScrapedSources.push(...sourcesWithContent);
-        
-        // Then scrape sources without content
-        for (let i = 0; i < Math.min(sourcesToScrape.length, SEARCH_CONFIG.MAX_SOURCES_TO_SCRAPE); i++) {
-          const source = sourcesToScrape[i];
-          
-          if (eventCallback) {
-            eventCallback({
-              type: 'scraping',
-              url: source.url,
-              index: newScrapedSources.length + 1,
-              total: sourcesWithContent.length + Math.min(sourcesToScrape.length, SEARCH_CONFIG.MAX_SOURCES_TO_SCRAPE),
-              query: state.query
-            });
-          }
-          
-          try {
-            const scraped = await firecrawl.scrapeUrl(source.url, SEARCH_CONFIG.SCRAPE_TIMEOUT);
-            if (scraped.success && scraped.markdown) {
-              const enrichedSource = {
-                ...source,
-                content: scraped.markdown,
-                quality: scoreContent(scraped.markdown, state.query)
-              };
-              newScrapedSources.push(enrichedSource);
-              
-              // Show processing animation
-              if (eventCallback) {
-                eventCallback({
-                  type: 'source-processing',
-                  url: source.url,
-                  title: source.title,
-                  stage: 'browsing'
-                });
-              }
-              
-              await new Promise(resolve => setTimeout(resolve, 150));
-              
-              const summary = await summarizeContent(scraped.markdown, state.query);
-              if (summary) {
-                enrichedSource.summary = summary;
-                
-                if (eventCallback) {
-                  eventCallback({
-                    type: 'source-complete',
-                    url: source.url,
-                    summary: summary
-                  });
-                }
-              }
-            } else if (scraped.error === 'timeout') {
-              if (eventCallback) {
-                eventCallback({
-                  type: 'thinking',
-                  message: `${new URL(source.url).hostname} is taking too long to respond, moving on...`
-                });
-              }
-            }
-          } catch {
-            if (eventCallback) {
-              eventCallback({
-                type: 'thinking',
-                message: `Couldn't access ${new URL(source.url).hostname}, trying other sources...`
-              });
-            }
-          }
+        // This node might be less critical if Firecrawl search already scrapes.
+        // It could be used for sources found via other means or if initial scrape was shallow.
+        // For now, we assume search node gets enough content.
+        if (eventCallback) {
+          eventCallback({ type: 'phase-update', phase: 'analyzing', message: 'Consolidating information...' });
         }
-        
+        // Directly pass to analyzing, assuming search node did its job
         return {
-          scrapedSources: newScrapedSources,
+          scrapedSources: state.sources, // Pass all good sources from search
           phase: 'analyzing' as SearchPhase
         };
       })
       
-      // Analyzing node
       .addNode("analyze", async (state: SearchState, config?: GraphConfig): Promise<Partial<SearchState>> => {
         const eventCallback = config?.configurable?.eventCallback;
-        
         if (eventCallback) {
-          eventCallback({
-            type: 'phase-update',
-            phase: 'analyzing',
-            message: 'Analyzing gathered information...'
-          });
+          eventCallback({ type: 'phase-update', phase: 'analyzing', message: 'Selecting best information for summary...' });
         }
         
-        // Combine sources and remove duplicates by URL
-        const sourceMap = new Map<string, Source>();
-        
-        // Add all sources (not just those with long content, since summaries contain key info)
-        (state.sources || []).forEach(s => sourceMap.set(s.url, s));
-        
-        // Add scraped sources (may override with better content)
-        (state.scrapedSources || []).forEach(s => sourceMap.set(s.url, s));
-        
-        const allSources = Array.from(sourceMap.values());
+        const allSources = state.sources || []; // Reducer already deduped and merged sources
         
-        // Check which questions have been answered
-        if (state.subQueries) {
-          const checkAnswersInSources = this.checkAnswersInSources.bind(this);
-          const updatedSubQueries = await checkAnswersInSources(state.subQueries, allSources);
-          
-          const answeredCount = updatedSubQueries.filter(sq => sq.answered).length;
-          const totalQuestions = updatedSubQueries.length;
-          const searchAttempt = (state.searchAttempt || 0) + 1;
-          
-          // Check if we have partial answers with decent confidence
-          const partialAnswers = updatedSubQueries.filter(sq => sq.confidence >= 0.3);
-          const hasPartialInfo = partialAnswers.length > answeredCount;
-          
+        if (allSources.length < SEARCH_CONFIG.MIN_SOURCES_FOR_BOOK_SUMMARY) {
+          // Not enough sources, could try to broaden search if implemented, or error out
           if (eventCallback) {
-            if (answeredCount === totalQuestions) {
-              eventCallback({
-                type: 'thinking',
-                message: `Found answers to all ${totalQuestions} questions across ${allSources.length} sources`
-              });
-            } else if (answeredCount > 0) {
-              eventCallback({
-                type: 'thinking',
-                message: `Found answers to ${answeredCount} of ${totalQuestions} questions. Still missing: ${updatedSubQueries.filter(sq => !sq.answered).map(sq => sq.question).join(', ')}`
-              });
-            } else if (searchAttempt >= SEARCH_CONFIG.MAX_SEARCH_ATTEMPTS) {
-              // Only show "could not find" message when we've exhausted all attempts
-              eventCallback({
-                type: 'thinking',
-                message: `Could not find specific answers in ${allSources.length} sources. The information may not be publicly available.`
-              });
-            } else if (hasPartialInfo && searchAttempt >= 3) {
-              // If we have partial info and tried 3+ times, stop searching
-              eventCallback({
-                type: 'thinking',
-                message: `Found partial information. Moving forward with what's available.`
-              });
-            } else {
-              // For intermediate attempts, show a different message
-              eventCallback({
-                type: 'thinking',
-                message: `Searching for more specific information...`
-              });
-            }
-          }
-          
-          // If we haven't found all answers and haven't exceeded attempts, try again
-          // BUT stop if we have partial info and already tried 2+ times
-          if (answeredCount < totalQuestions && 
-              searchAttempt < SEARCH_CONFIG.MAX_SEARCH_ATTEMPTS &&
-              !(hasPartialInfo && searchAttempt >= 2)) {
-            return {
-              sources: allSources,
-              subQueries: updatedSubQueries,
-              searchAttempt,
-              phase: 'planning' as SearchPhase  // Go back to planning for retry
-            };
-          }
-          
-          // Otherwise proceed with what we have
-          try {
-            const processedSources = await contextProcessor.processSources(
-              state.query,
-              allSources,
-              state.searchQueries || []
-            );
-            
-            return {
-              sources: allSources,
-              processedSources,
-              subQueries: updatedSubQueries,
-              searchAttempt,
-              phase: 'synthesizing' as SearchPhase
-            };
-          } catch {
-            return {
-              sources: allSources,
-              processedSources: allSources,
-              subQueries: updatedSubQueries,
-              searchAttempt,
-              phase: 'synthesizing' as SearchPhase
-            };
+            eventCallback({ type: 'thinking', message: `Found ${allSources.length} sources. Ideally, we need at least ${SEARCH_CONFIG.MIN_SOURCES_FOR_BOOK_SUMMARY} for a good summary.` });
           }
-        } else {
-          // Fallback for queries without sub-queries
-          if (eventCallback && allSources.length > 0) {
-            eventCallback({
-              type: 'thinking',
-              message: `Found ${allSources.length} sources with quality information`
-            });
+          // For now, proceed if some sources exist, otherwise error.
+          if (allSources.length === 0) {
+            return { error: `Could not find enough information about "${state.bookName}" to generate a summary.`, errorType: 'search' as ErrorType, phase: 'error' as SearchPhase };
           }
+        } else if (eventCallback) {
+            eventCallback({ type: 'thinking', message: `Gathered information from ${allSources.length} sources for "${state.bookName}".`});
+        }
+
+        try {
+          // The contextProcessor might need to be adapted for book summaries.
+          // For now, we can assume it filters/ranks sources based on relevance and content quality.
+          // The "query" for processSources should be the general book topic.
+          const processedSources = await contextProcessor.processSources(
+            state.query, // state.query is `Summary of "Book Name" by Author`
+            allSources,
+            state.searchQueries || [] // Pass original search queries for context
+          );
           
-          try {
-            const processedSources = await contextProcessor.processSources(
-              state.query,
-              allSources,
-              state.searchQueries || []
-            );
-            
-            return {
-              sources: allSources,
-              processedSources,
-              phase: 'synthesizing' as SearchPhase
-            };
-          } catch {
-            return {
-              sources: allSources,
-              processedSources: allSources,
-              phase: 'synthesizing' as SearchPhase
-            };
-          }
+          return {
+            processedSources: processedSources.length > 0 ? processedSources : allSources, // Fallback to allSources if processing returns empty
+            phase: 'synthesizing' as SearchPhase
+          };
+        } catch (error) {
+          console.error("Error processing sources:", error);
+          // Fallback to using all gathered sources if processing fails
+          return {
+            processedSources: allSources,
+            phase: 'synthesizing' as SearchPhase
+          };
         }
       })
       
-      // Synthesizing node with streaming
       .addNode("synthesize", async (state: SearchState, config?: GraphConfig): Promise<Partial<SearchState>> => {
         const eventCallback = config?.configurable?.eventCallback;
-        
         if (eventCallback) {
-          eventCallback({
-            type: 'phase-update',
-            phase: 'synthesizing',
-            message: 'Creating comprehensive answer...'
-          });
+          eventCallback({ type: 'phase-update', phase: 'synthesizing', message: `Crafting detailed summary for "${state.bookName}"...` });
         }
         
         try {
           const sourcesToUse = state.processedSources || state.sources || [];
+          if (sourcesToUse.length === 0) {
+            return { error: "No information available to synthesize the summary.", errorType: 'llm' as ErrorType, phase: 'error' as SearchPhase };
+          }
           
-          const answer = await generateStreamingAnswer(
-            state.query,
+          const summary = await generateStreamingBookSummary(
+            state.bookName,
+            state.author,
             sourcesToUse,
             (chunk) => {
               if (eventCallback) {
                 eventCallback({ type: 'content-chunk', chunk });
               }
             },
-            state.context
+            state.context // Pass conversation context if any
           );
           
-          // Generate follow-up questions
-          const followUpQuestions = await generateFollowUpQuestions(
-            state.query,
-            answer,
-            sourcesToUse,
-            state.context
-          );
+          // Generate key themes (replaces follow-up questions for books)
+          const keyThemes = await generateKeyThemes(state.bookName, summary, sourcesToUse);
           
           return {
-            finalAnswer: answer,
-            followUpQuestions,
+            finalAnswer: summary,
+            followUpQuestions: keyThemes, // Re-using this field for key themes
             phase: 'complete' as SearchPhase
           };
         } catch (error) {
-          return {
-            error: error instanceof Error ? error.message : 'Failed to generate answer',
-            errorType: 'llm' as ErrorType,
-            phase: 'error' as SearchPhase
-          };
+          return { error: error instanceof Error ? error.message : 'Failed to generate book summary', errorType: 'llm' as ErrorType, phase: 'error' as SearchPhase };
         }
       })
       
-      // Error handling node
       .addNode("handleError", async (state: SearchState, config?: GraphConfig): Promise<Partial<SearchState>> => {
         const eventCallback = config?.configurable?.eventCallback;
-        
         if (eventCallback) {
-          eventCallback({
-            type: 'error',
-            error: state.error || 'An unknown error occurred',
-            errorType: state.errorType
-          });
-        }
-        
-        // Retry logic based on error type
-        if ((state.retryCount || 0) < (state.maxRetries || SEARCH_CONFIG.MAX_RETRIES)) {
-              
-          // Different retry strategies based on error type
-          const retryPhase = state.errorType === 'search' ? 'searching' : 'understanding';
-          
-          return {
-            retryCount: (state.retryCount || 0) + 1,
-            phase: retryPhase as SearchPhase,
-            error: undefined,
-            errorType: undefined
-          };
+          eventCallback({ type: 'error', error: state.error || 'An unknown error occurred', errorType: state.errorType });
         }
-        
-        return {
-          phase: 'error' as SearchPhase
-        };
+        // For book summaries, retrying might involve different strategies not yet implemented.
+        // For now, we'll end on error.
+        return { phase: 'error' as SearchPhase }; // Ends the process
       })
       
-      // Complete node
       .addNode("complete", async (state: SearchState, config?: GraphConfig): Promise<Partial<SearchState>> => {
         const eventCallback = config?.configurable?.eventCallback;
-        
         if (eventCallback) {
-          eventCallback({
-            type: 'phase-update',
-            phase: 'complete',
-            message: 'Search complete!'
-          });
-          
+          eventCallback({ type: 'phase-update', phase: 'complete', message: 'Book summary generation complete!' });
           eventCallback({
             type: 'final-result',
             content: state.finalAnswer || '',
-            sources: state.sources || [],
-            followUpQuestions: state.followUpQuestions
+            sources: state.sources || [], // All unique sources found
+            followUpQuestions: state.followUpQuestions // Key themes
           });
         }
-        
-        return {
-          phase: 'complete' as SearchPhase
-        };
+        return { phase: 'complete' as SearchPhase };
       });
 
-    // Add edges with proper conditional routing
     workflow
       .addEdge(START, "understand")
-      .addConditionalEdges(
-        "understand",
-        (state: SearchState) => state.phase === 'error' ? "handleError" : "plan",
-        {
-          handleError: "handleError",
-          plan: "plan"
-        }
-      )
-      .addConditionalEdges(
-        "plan",
-        (state: SearchState) => state.phase === 'error' ? "handleError" : "search",
-        {
-          handleError: "handleError",
-          search: "search"
-        }
-      )
-      .addConditionalEdges(
-        "search",
-        (state: SearchState) => {
-          if (state.phase === 'error') return "handleError";
-          if ((state.currentSearchIndex || 0) < (state.searchQueries?.length || 0)) {
-            return "search"; // Continue searching
-          }
-          return "scrape"; // Move to scraping
-        },
-        {
-          handleError: "handleError",
-          search: "search",
-          scrape: "scrape"
-        }
-      )
-      .addConditionalEdges(
-        "scrape",
-        (state: SearchState) => state.phase === 'error' ? "handleError" : "analyze",
-        {
-          handleError: "handleError",
-          analyze: "analyze"
-        }
-      )
-      .addConditionalEdges(
-        "analyze",
-        (state: SearchState) => {
-          if (state.phase === 'error') return "handleError";
-          if (state.phase === 'planning') return "plan";  // Retry with new searches
-          return "synthesize";
-        },
-        {
-          handleError: "handleError",
-          plan: "plan",
-          synthesize: "synthesize"
-        }
-      )
-      .addConditionalEdges(
-        "synthesize",
-        (state: SearchState) => state.phase === 'error' ? "handleError" : "complete",
-        {
-          handleError: "handleError",
-          complete: "complete"
+      .addConditionalEdges("understand", (state: SearchState) => state.phase === 'error' ? "handleError" : "plan")
+      .addConditionalEdges("plan", (state: SearchState) => state.phase === 'error' ? "handleError" : "search")
+      .addConditionalEdges("search", (state: SearchState) => {
+        if (state.phase === 'error') return "handleError"; // Should be rare here, individual query errors handled inside
+        if ((state.currentSearchIndex || 0) < (state.searchQueries?.length || 0)) {
+          return "search"; // Continue with next search query
         }
-      )
-      .addConditionalEdges(
-        "handleError",
-        (state: SearchState) => state.phase === 'error' ? END : "understand",
-        {
-          [END]: END,
-          understand: "understand"
-        }
-      )
+        return "scrape"; // All searches done, move to scrape/analyze
+      })
+      .addConditionalEdges("scrape", (state: SearchState) => state.phase === 'error' ? "handleError" : "analyze") // scrape is now a pass-through
+      .addConditionalEdges("analyze", (state: SearchState) => state.phase === 'error' ? "handleError" : "synthesize")
+      .addConditionalEdges("synthesize", (state: SearchState) => state.phase === 'error' ? "handleError" : "complete")
+      .addEdge("handleError", END) // Error leads to end
       .addEdge("complete", END);
 
-    // Compile with optional checkpointing
     return workflow.compile(this.checkpointer ? { checkpointer: this.checkpointer } : undefined);
   }
 
   async search(
-    query: string,
+    bookName: string, // Changed from query
+    author: string | undefined, // New parameter
     onEvent: (event: SearchEvent) => void,
-    context?: { query: string; response: string }[],
+    context?: { query: string; response: string }[], // Context from previous interactions (if any)
     checkpointId?: string
   ): Promise<void> {
     try {
       const initialState: SearchState = {
-        query,
+        bookName,
+        author,
+        query: `Summary of "${bookName}"${author ? ` by ${author}` : ''}`, // Internal query representation
         context,
         sources: [],
         scrapedSources: [],
         processedSources: undefined,
         phase: 'understanding',
         currentSearchIndex: 0,
-        maxRetries: SEARCH_CONFIG.MAX_RETRIES,
+        maxRetries: SEARCH_CONFIG.MAX_RETRIES, // This might be less relevant now
         retryCount: 0,
         understanding: undefined,
         searchQueries: undefined,
         finalAnswer: undefined,
-        followUpQuestions: undefined,
+        followUpQuestions: undefined, // Will hold key themes
         error: undefined,
         errorType: undefined,
-        subQueries: undefined,
+        // subQueries: undefined, // Not using subQueries in the same way
         searchAttempt: 0
       };
 
-      // Configure with event callback
       const config: GraphConfig = {
         configurable: {
           eventCallback: onEvent,
           ...(checkpointId && this.checkpointer ? { thread_id: checkpointId } : {})
         }
       };
-
-      // Invoke the graph with increased recursion limit
-      await this.graph.invoke(initialState, {
-        ...config,
-        recursionLimit: 35  // Increased from default 25 to handle MAX_SEARCH_ATTEMPTS=5
-      });
+      // Increased recursion limit might still be useful if graph is deep
+      await this.graph.invoke(initialState, { ...config, recursionLimit: 35 });
     } catch (error) {
       onEvent({
         type: 'error',
-        error: error instanceof Error ? error.message : 'Search failed',
+        error: error instanceof Error ? error.message : 'Book summary generation failed',
         errorType: 'unknown'
       });
     }
   }
 
-
-  // Get current date for context
   private getCurrentDateContext(): string {
     const now = new Date();
-    const dateStr = now.toLocaleDateString('en-US', { 
-      weekday: 'long', 
-      year: 'numeric', 
-      month: 'long', 
-      day: 'numeric' 
-    });
-    const year = now.getFullYear();
-    const month = now.getMonth() + 1;
-    
-    return `Today's date is ${dateStr}. The current year is ${year} and it's currently ${month}/${year}.`;
+    return `Today's date is ${now.toLocaleDateString('en-US', { weekday: 'long', year: 'numeric', month: 'long', day: 'numeric' })}.`;
   }
 
-  // Pure helper methods (no side effects)
-  private async analyzeQuery(query: string, context?: { query: string; response: string }[]): Promise<string> {
+  private async analyzeBookRequest(bookName: string, author?: string, context?: { query: string; response: string }[]): Promise<string> {
     let contextPrompt = '';
     if (context && context.length > 0) {
-      contextPrompt = '\n\nPrevious conversation:\n';
+      contextPrompt = '\n\nPrevious conversation for context:\n';
       context.forEach(c => {
         contextPrompt += `User: ${c.query}\nAssistant: ${c.response.substring(0, SEARCH_CONFIG.CONTEXT_PREVIEW_LENGTH)}...\n\n`;
       });
     }
+    const queryDescription = `User wants a detailed summary for the book titled "${bookName}"` + (author ? ` by ${author}` : '') + ".";
     
     const messages = [
       new SystemMessage(`${this.getCurrentDateContext()}
-
-Analyze this search query and explain what you understand the user is looking for.
-
-Instructions:
-- Start with a clear, concise title (e.g., "Researching egg shortage" or "Understanding climate change impacts")
-- Then explain in 1-2 sentences what aspects of the topic the user wants to know about
-- If this relates to previous questions, acknowledge that connection
-- Finally, mention that you'll search for information to help answer their question
-- Only mention searching for "latest" information if the query is explicitly about recent events or current trends
-
-Keep it natural and conversational, showing you truly understand their request.`),
-      new HumanMessage(`Query: "${query}"${contextPrompt}`)
+You are an AI assistant tasked with generating a book summary.
+Confirm your understanding of the request. State that you will gather information from multiple online sources to create a comprehensive summary.
+Keep it concise and professional.`),
+      new HumanMessage(`${queryDescription}${contextPrompt}`)
     ];
     
     const response = await this.llm.invoke(messages);
     return response.content.toString();
   }
 
-  private async checkAnswersInSources(
-    subQueries: Array<{ question: string; searchQuery: string; answered: boolean; answer?: string; confidence: number; sources: string[] }>,
-    sources: Source[]
-  ): Promise<typeof subQueries> {
-    if (sources.length === 0) return subQueries;
-    
-    const messages = [
-      new SystemMessage(`Check which questions have been answered by the provided sources.
-
-For each question, determine:
-1. If the sources contain a direct answer
-2. The confidence level (0.0-1.0) that the question was fully answered
-3. A brief answer summary if found
-
-Guidelines:
-- For "who" questions about people/founders: Mark as answered (0.8+ confidence) if you find names of specific people
-- For "what" questions: Mark as answered (0.8+ confidence) if you find the specific information requested
-- For "when" questions: Mark as answered (0.8+ confidence) if you find dates or time periods
-- For "how many" questions: Require specific numbers (0.8+ confidence)
-- For comparison questions: Require information about all items being compared
-- If sources clearly answer the question but lack some minor details, use medium confidence (0.6-0.7)
-- If sources mention the topic but don't answer the specific question, use low confidence (< 0.3)
-
-Version number matching:
-- "0528" in the question matches "0528", "-0528", "May 28", or "May 28, 2025" in sources
-- Example: Question about "DeepSeek R1 0528" is ANSWERED if sources mention:
-  - "DeepSeek R1-0528" (exact match)
-  - "DeepSeek R1 was updated on May 28" (date match)
-  - "DeepSeek's R1 model was updated on May 28, 2025" (date match)
-- Hyphens and spaces in version numbers should be ignored when matching
-- If the summary mentions the product and a matching date/version, that's a full answer
-
-Special cases:
-- If asking about a product/model with a version number (e.g., "ModelX v2.5.1" or "Product 0528"), check BOTH:
-  1. If sources mention the EXACT version → mark as answered with high confidence (0.8+)
-  2. If sources only mention the base product → mark as answered with medium confidence (0.6+)
-- Example: Question "What is ProductX 1234?" 
-  - If sources mention "ProductX 1234" specifically → confidence: 0.9
-  - If sources only mention "ProductX" → confidence: 0.6
-- IMPORTANT: For questions like "What is DeepSeek R1 0528?", if sources contain "DeepSeek R1-0528" or "DeepSeek R1 0528", that's a DIRECT match (confidence 0.9+)
-- If multiple sources contradict whether something exists, use low confidence (0.3) but still provide what information was found
-
-Important: Be generous in recognizing answers. If the source clearly provides the information asked for (e.g., "The founders are X, Y, and Z"), mark it as answered with high confidence.
-
-Return ONLY a JSON array, no markdown formatting or code blocks:
-[
-  {
-    "question": "the original question",
-    "answered": true/false,
-    "confidence": 0.0-1.0,
-    "answer": "brief answer if found",
-    "sources": ["urls that contain the answer"]
-  }
-]`),
-      new HumanMessage(`Questions to check:
-${subQueries.map(sq => sq.question).join('\n')}
-
-Sources:
-${sources.slice(0, SEARCH_CONFIG.MAX_SOURCES_TO_CHECK).map(s => {
-  let sourceInfo = `URL: ${s.url}\nTitle: ${s.title}\n`;
-  
-  // Include summary if available (this is the key insight from the search)
-  if (s.summary) {
-    sourceInfo += `Summary: ${s.summary}\n`;
-  }
-  
-  // Include content preview
-  if (s.content) {
-    sourceInfo += `Content: ${s.content.slice(0, SEARCH_CONFIG.ANSWER_CHECK_PREVIEW)}\n`;
-  }
-  
-  return sourceInfo;
-}).join('\n---\n')}`)
-    ];
-
-    try {
-      const response = await this.llm.invoke(messages);
-      let content = response.content.toString();
-      
-      // Strip markdown code blocks if present
-      content = content.replace(/```json\s*/g, '').replace(/```\s*$/g, '').trim();
-      
-      const results = JSON.parse(content);
-      
-      // Update sub-queries with results
-      return subQueries.map(sq => {
-        const result = results.find((r: { question: string }) => r.question === sq.question);
-        if (result && result.confidence > sq.confidence) {
-          return {
-            ...sq,
-            answered: result.confidence >= SEARCH_CONFIG.MIN_ANSWER_CONFIDENCE,
-            answer: result.answer,
-            confidence: result.confidence,
-            sources: [...new Set([...sq.sources, ...(result.sources || [])])]
-          };
-        }
-        return sq;
-      });
-    } catch (error) {
-      console.error('Error checking answers:', error);
-      return subQueries;
-    }
-  }
-
-  private async extractSubQueries(query: string): Promise<Array<{ question: string; searchQuery: string }>> {
-    const messages = [
-      new SystemMessage(`Extract the individual factual questions from this query. Each question should be something that can be definitively answered.
-
-IMPORTANT: 
-- When the user mentions something with a version/number (like "deepseek r1 0528"), include the FULL version in the question
-- For the search query, you can simplify slightly but keep key identifiers
-- Example: "deepseek r1 0528" → question: "What is DeepSeek R1 0528?", searchQuery: "DeepSeek R1 0528"
-
-Examples:
-"Who founded Anthropic and when" → 
-[
-  {"question": "Who founded Anthropic?", "searchQuery": "Anthropic founders"},
-  {"question": "When was Anthropic founded?", "searchQuery": "Anthropic founded date year"}
-]
-
-"What is OpenAI's Q3 2024 revenue and who is their VP of Infrastructure" →
-[
-  {"question": "What was OpenAI's Q3 2024 revenue?", "searchQuery": "OpenAI Q3 2024 revenue earnings"},
-  {"question": "Who is OpenAI's VP of Infrastructure?", "searchQuery": "OpenAI VP Infrastructure executive team"}
-]
-
-"Tell me about Product A + Model B version 123" →
-[
-  {"question": "What is Product A?", "searchQuery": "Product A features"},
-  {"question": "What is Model B version 123?", "searchQuery": "Model B"}
-]
-
-"Who founded Company X, compare Product A and Product B, and tell me about Technology Y + Model Z 1234" →
-[
-  {"question": "Who founded Company X?", "searchQuery": "Company X founders"},
-  {"question": "How do Product A and Product B compare?", "searchQuery": "Product A vs Product B comparison"},
-  {"question": "What is Technology Y?", "searchQuery": "Technology Y features"},
-  {"question": "What is Model Z 1234?", "searchQuery": "Model Z"}
-]
-
-Important: 
-- For comparison requests, create a single question/search that covers both items
-- If a term looks like it might be a model name with a version/date (like "R1 0528"), treat it as a single entity first, but create a search query that focuses on the main product name
-- Keep the number of sub-queries reasonable (aim for 3-5 max)
-
-Return ONLY a JSON array of {question, searchQuery} objects.`),
-      new HumanMessage(`Query: "${query}"`)
-    ];
+  // Simplified scoring: relevance to book title and author
+  private scoreContentRelevance(content: string, bookName: string, author?: string): number {
+    const contentLower = content.toLowerCase();
+    const bookNameLower = bookName.toLowerCase();
+    let score = 0;
 
-    try {
-      const response = await this.llm.invoke(messages);
-      return JSON.parse(response.content.toString());
-    } catch {
-      // Fallback: treat as single query
-      return [{ question: query, searchQuery: query }];
+    if (contentLower.includes(bookNameLower)) {
+      score += 0.5;
     }
-  }
+    // More sophisticated scoring could count occurrences, proximity etc.
+    // For now, simple presence is a basic check.
 
-  // This method was removed as it's not used in the current implementation
-  // Search queries are now generated from sub-queries in the plan node
-
-  private async generateAlternativeSearchQueries(
-    subQueries: Array<{ question: string; searchQuery: string; answered: boolean; answer?: string; confidence: number; sources: string[] }>,
-    previousAttempts: number
-  ): Promise<string[]> {
-    const unansweredQueries = subQueries.filter(sq => !sq.answered || sq.confidence < SEARCH_CONFIG.MIN_ANSWER_CONFIDENCE);
-    
-    // If we're on attempt 3 and still searching for the same thing, just give up on that specific query
-    if (previousAttempts >= 2) {
-      const problematicQueries = unansweredQueries.filter(sq => {
-        // Check if the question contains a version number or specific identifier that might not exist
-        const hasVersionPattern = /\b\d{3,4}\b|\bv\d+\.\d+|\bversion\s+\d+/i.test(sq.question);
-        const hasFailedMultipleTimes = previousAttempts >= 2;
-        return hasVersionPattern && hasFailedMultipleTimes;
-      });
-      
-      if (problematicQueries.length > 0) {
-        // Return generic searches that might find partial info
-        return problematicQueries.map(sq => {
-          const baseTerm = sq.question.replace(/0528|specific version/gi, '').trim();
-          return baseTerm.substring(0, 50); // Keep it short
-        });
+    if (author) {
+      const authorLower = author.toLowerCase();
+      if (contentLower.includes(authorLower)) {
+        score += 0.3;
       }
     }
-    
-    const messages = [
-      new SystemMessage(`${this.getCurrentDateContext()}
-
-Generate ALTERNATIVE search queries for questions that weren't answered in previous attempts.
-
-Previous search attempts: ${previousAttempts}
-Previous queries that didn't find answers:
-${unansweredQueries.map(sq => `- Question: "${sq.question}"\n  Previous search: "${sq.searchQuery}"`).join('\n')}
-
-IMPORTANT: If searching for something with a specific version/date that keeps failing (like "R1 0528"), try searching for just the base product without the version.
-
-Generate NEW search queries using these strategies:
-1. Try broader or more general terms
-2. Try different phrasings or synonyms
-3. Remove specific qualifiers (like years or versions) if they're too restrictive
-4. Try searching for related concepts that might contain the answer
-5. For products that might not exist, search for the company or base product name
-
-Examples of alternative searches:
-- Original: "ModelX 2024.05" → Alternative: "ModelX latest version"
-- Original: "OpenAI Q3 2024 revenue" → Alternative: "OpenAI financial results 2024"
-- Original: "iPhone 15 Pro features" → Alternative: "latest iPhone specifications"
-
-Return one alternative search query per unanswered question, one per line.`),
-      new HumanMessage(`Generate alternative searches for these ${unansweredQueries.length} unanswered questions.`)
-    ];
-
-    try {
-      const response = await this.llm.invoke(messages);
-      const result = response.content.toString();
-      
-      const queries = result
-        .split('\n')
-        .map(q => q.trim())
-        .map(q => q.replace(/^["']|["']$/g, ''))
-        .map(q => q.replace(/^\d+\.\s*/, ''))
-        .map(q => q.replace(/^[-*#]\s*/, ''))
-        .filter(q => q.length > 0)
-        .filter(q => !q.match(/^```/))
-        .filter(q => q.length > 3);
-      
-      return queries.slice(0, SEARCH_CONFIG.MAX_SEARCH_QUERIES);
-    } catch {
-      // Fallback: return original queries with slight modifications
-      return unansweredQueries.map(sq => sq.searchQuery + " news reports").slice(0, SEARCH_CONFIG.MAX_SEARCH_QUERIES);
-    }
-  }
-
-  private scoreContent(content: string, query: string): number {
-    const queryWords = query.toLowerCase().split(' ');
-    const contentLower = content.toLowerCase();
-    
-    let score = 0;
-    for (const word of queryWords) {
-      if (contentLower.includes(word)) score += 0.2;
+    // Add points if terms like "summary", "review", "chapter", "plot" appear
+    const summaryKeywords = ["summary", "review", "plot", "chapter", "analysis", "takeaway"];
+    if (summaryKeywords.some(keyword => contentLower.includes(keyword))) {
+        score += 0.2;
     }
-    
     return Math.min(score, 1);
   }
 
-  private async summarizeContent(content: string, query: string): Promise<string> {
+  // Adapted summarization for book context
+  private async summarizeSourceForBook(content: string, bookName: string, originalSearchQuery: string): Promise<string> {
     try {
       const messages = [
         new SystemMessage(`${this.getCurrentDateContext()}
-
-Extract ONE key finding from this content that's SPECIFICALLY relevant to the search query.
-
-CRITICAL: Only summarize information that directly relates to the search query.
-- If searching for "Samsung phones", only mention Samsung phone information
-- If searching for "Firecrawl founders", only mention founder information
-- If no relevant information is found, just return the most relevant fact from the page
+You are tasked with extracting a key piece of information relevant to the book "${bookName}" from the provided text.
+The text was found using the search query: "${originalSearchQuery}".
+Focus on information that would be useful for a book summary (e.g., plot points, character descriptions, main themes, author's arguments, key facts or examples if non-fiction).
 
 Instructions:
-- Return just ONE sentence with a specific finding
-- Include numbers, dates, or specific details when available
-- Keep it under ${SEARCH_CONFIG.SUMMARY_CHAR_LIMIT} characters
-- Don't say "No relevant information was found" - find something relevant to the current search`),
-        new HumanMessage(`Query: "${query}"\n\nContent: ${content.slice(0, 2000)}`)
+- Return ONE concise sentence (max ${SEARCH_CONFIG.SUMMARY_CHAR_LIMIT} characters).
+- If the text provides a direct quote related to the book's themes or critical reception, that's valuable.
+- If it mentions specific chapter content or plot details, extract that.
+- If no highly relevant information for a summary of "${bookName}" is found, state "No specific summary points found in this excerpt."
+- Do not invent information. Stick to the provided text.`),
+        new HumanMessage(`Book: "${bookName}"\nOriginal Search Query: "${originalSearchQuery}"\n\nContent to summarize: ${content.slice(0, 3000)}`) // Increased slice for better context
       ];
       
       const response = await this.llm.invoke(messages);
       return response.content.toString().trim();
-    } catch {
-      return '';
+    } catch (error) {
+      console.warn("Source summarization for book failed:", error);
+      return ''; // Return empty on error
     }
   }
 
-  private async generateStreamingAnswer(
-    query: string,
-    sources: Source[],
-    onChunk: (chunk: string) => void,
-    context?: { query: string; response: string }[]
-  ): Promise<string> {
-    const sourcesText = sources
-      .map((s, i) => {
-        if (!s.content) return `[${i + 1}] ${s.title}\n[No content available]`;
-        return `[${i + 1}] ${s.title}\n${s.content}`;
-      })
-      .join('\n\n');
-    
-    let contextPrompt = '';
-    if (context && context.length > 0) {
-      contextPrompt = '\n\nPrevious conversation for context:\n';
-      context.forEach(c => {
-        contextPrompt += `User: ${c.query}\nAssistant: ${c.response.substring(0, 300)}...\n\n`;
-      });
-    }
-    
-    const messages = [
-      new SystemMessage(`${this.getCurrentDateContext()}
+import { ATOMIC_HABITS_EXAMPLE_SUMMARY } from './prompt-examples'; // Import the example
+
+// This is the new core function for generating the book summary.
+// It will incorporate the "Atomic Habits" example in its prompt.
+private async generateStreamingBookSummary(
+  bookName: string,
+  author: string | undefined,
+  sources: Source[],
+  onChunk: (chunk: string) => void,
+  context?: { query: string; response: string }[]
+): Promise<string> {
+  const sourcesText = sources
+    .slice(0, SEARCH_CONFIG.MAX_SOURCES_FOR_SYNTHESIS) // Limit sources for the prompt
+    .map((s, i) => {
+      let sourceEntry = `[Source ${i + 1}: ${s.title} (${s.url})]\n`;
+      if (s.summary) { // Prefer using the pre-generated summary of the source
+          sourceEntry += `Key information from this source: ${s.summary}\n`;
+      }
+      if (s.content) {
+           // Add a snippet of the content for more direct info, especially if summary is missing/short
+          sourceEntry += `Content excerpt: ${s.content.substring(0, 1500)}...\n`; // Slightly longer excerpt
+      } else {
+          sourceEntry += "[No content excerpt available]\n";
+      }
+      return sourceEntry;
+    })
+    .join('\n---\n');
 
-Answer the user's question based on the provided sources. Provide a clear, comprehensive answer with citations [1], [2], etc. Use markdown formatting for better readability. If this question relates to previous topics discussed, make connections where relevant.`),
-      new HumanMessage(`Question: "${query}"${contextPrompt}\n\nBased on these sources:\n${sourcesText}`)
-    ];
-    
-    let fullText = '';
-    
-    try {
-      const stream = await this.streamingLlm.stream(messages);
-      
-      for await (const chunk of stream) {
-        const content = chunk.content;
-        if (typeof content === 'string') {
-          fullText += content;
-          onChunk(content);
-        }
+  const bookTopic = `the book "${bookName}"` + (author ? ` by ${author}` : '');
+
+  let contextPrompt = '';
+  if (context && context.length > 0) {
+    contextPrompt = '\n\nPrevious conversation for context (if relevant):\n';
+    context.forEach(c => {
+      contextPrompt += `User: ${c.query}\nAssistant: ${c.response.substring(0, 300)}...\n\n`;
+    });
+  }
+
+  const systemPrompt = `${this.getCurrentDateContext()}
+You are an expert book summarizer. Your task is to generate a comprehensive, detailed, long-form summary for ${bookTopic}, similar in style, length, and structure to the provided example.
+The summary should be substantial, aiming for a 30-minute read time, which means several thousand words.
+
+INSTRUCTIONS:
+1.  **Understand the Sources:** Carefully review the provided source materials. These contain summaries, reviews, analyses, and potentially excerpts from various websites.
+2.  **Synthesize, Don't Copy:** Create an ORIGINAL and COHERENT summary by synthesizing the information. Do NOT directly copy-paste sentences or paragraphs from the sources. Rephrase and integrate ideas smoothly.
+3.  **Structure:** Organize the summary logically. Use Markdown for clear formatting:
+    *   Use H1 (#) for the main book title (if you reiterate it) and major sections like "Introduction", "Conclusion".
+    *   Use H2 (##) for main parts or chapters of the book's ideas.
+    *   Use H3 (###) and H4 (####) for sub-sections and finer details.
+    *   Use blockquotes (>) for any direct quotes FROM THE BOOK ITSELF (if such quotes are clearly identifiable in the provided source materials and attributed to the book's author). If quoting a reviewer or a summary website, make that clear or avoid it.
+    *   Use bold text (**) for emphasis on key terms, concepts, or chapter titles within your summary.
+    *   Use bulleted lists (-) or numbered lists (1.) for key points, steps, rules, or examples discussed in the book.
+4.  **Content and Tone:**
+    *   Start with an engaging introduction: Hook the reader, introduce the book, its author, and its central premise or importance.
+    *   Systematically cover the main ideas, arguments, concepts, plot points (for fiction), characters (for fiction), and themes of the book.
+    *   For non-fiction: Explain core principles, methodologies, and provide illustrative examples if these are detailed in the sources.
+    *   For fiction: Outline the main plot arcs, describe key characters and their development, and discuss major literary themes and symbolism.
+    *   Maintain a knowledgeable, engaging, yet objective and analytical tone. Your voice should be that of an expert guide to the book.
+    *   Conclude with a section that summarizes the book's main message, its overall impact or significance, and perhaps who would benefit most from reading the original book. A "personal application" or "how I'm using this book" section, like in the example, can be very effective if the source material provides enough information to inspire it.
+5.  **Length and Detail:** Aim for a very substantial summary. The example provided for "Atomic Habits" is a benchmark for the expected depth, detail, and length. This means multiple layered sections, detailed explanations of concepts, and thorough coverage of the book's content as reflected in the sources. A "30-minute read" implies a word count likely in the 4000-7000 range. Be comprehensive.
+6.  **Originality:** Your primary goal is to create a NEW summary based on the *information* from the sources, not to combine existing summaries. The example shows how to structure an original, long-form piece.
+7.  **Use the Example as a Guide:** The provided "Atomic Habits" summary is your GOLD STANDARD for style, structure, sectioning, use of formatting, depth of explanation, and overall flow. Emulate its comprehensiveness.
+
+EXAMPLE SUMMARY (This is your guide for style, structure, and length):
+--- START OF EXAMPLE ---
+${ATOMIC_HABITS_EXAMPLE_SUMMARY}
+--- END OF EXAMPLE ---
+
+Now, generate the detailed, long-form book summary for ${bookTopic} based on the following sources. Ensure the output is well-structured Markdown.
+${contextPrompt}
+Sources:
+${sourcesText}
+`;
+
+  const messages = [
+    new SystemMessage(systemPrompt),
+    new HumanMessage(`Please generate the detailed book summary for "${bookName}"` + (author ? ` by ${author}` : '') + ".")
+  ];
+
+  let fullText = '';
+  try {
+    const stream = await this.streamingLlm.stream(messages);
+    for await (const chunk of stream) {
+      const content = chunk.content;
+      if (typeof content === 'string') {
+        fullText += content;
+        onChunk(content);
       }
-    } catch {
-      // Fallback to non-streaming if streaming fails
-      const response = await this.llm.invoke(messages);
-      fullText = response.content.toString();
-      onChunk(fullText);
     }
-    
-    return fullText;
+  } catch (error) {
+    console.error("Streaming LLM call failed for book summary:", error);
+    const errorMsg = `\n\n[Error generating the book summary: ${error instanceof Error ? error.message : "An unknown error occurred during LLM streaming."}]`;
+    onChunk(errorMsg);
+    // Do not throw here if you want the graph to potentially handle it or finish "gracefully" with an error message.
+    // However, for critical failure in synthesis, throwing might be appropriate if handled by an error node.
+    // For now, let's append error and return, allowing flow to 'complete'.
+    fullText += errorMsg;
   }
 
-  private async generateFollowUpQuestions(
-    originalQuery: string,
-    answer: string,
-    _sources: Source[],
-    context?: { query: string; response: string }[]
+  return fullText;
+}
+
+// Replaces generateFollowUpQuestions for book summaries
+  private async generateKeyThemes(
+    bookName: string,
+    summary: string, // The generated summary
+    _sources: Source[] // Sources might be used for more context if needed
   ): Promise<string[]> {
     try {
-      let contextPrompt = '';
-      if (context && context.length > 0) {
-        contextPrompt = '\n\nPrevious conversation topics:\n';
-        context.forEach(c => {
-          contextPrompt += `- ${c.query}\n`;
-        });
-        contextPrompt += '\nConsider the full conversation flow when generating follow-ups.\n';
-      }
-      
       const messages = [
         new SystemMessage(`${this.getCurrentDateContext()}
-
-Based on this search query and answer, generate 3 relevant follow-up questions that the user might want to explore next.
+Based on the book "${bookName}" and its provided summary, identify 3-5 key themes or major takeaways from the book.
+These should be distinct and significant aspects that a reader would find important.
 
 Instructions:
-- Generate exactly 3 follow-up questions
-- Each question should explore a different aspect or dig deeper into the topic
-- Questions should be natural and conversational
-- They should build upon the information provided in the answer
-- Make them specific and actionable
-- Keep each question under 80 characters
-- Return only the questions, one per line, no numbering or bullets
-- Consider the entire conversation context when generating questions
-- Only include time-relevant questions if the original query was about current events or trends
-
-Examples of good follow-up questions:
-- "How does this compare to [alternative]?"
-- "Can you explain [technical term] in more detail?"
-- "What are the practical applications of this?"
-- "What are the main benefits and drawbacks?"
-- "How is this typically implemented?"`),
-        new HumanMessage(`Original query: "${originalQuery}"\n\nAnswer summary: ${answer.length > 1000 ? answer.slice(0, 1000) + '...' : answer}${contextPrompt}`)
+- Generate 3 to 5 key themes.
+- Each theme should be a concise phrase or short sentence.
+- Return only the themes, one per line, no numbering or bullets.
+- Keep each theme under 100 characters.
+
+Example (for a hypothetical book on leadership):
+The importance of empathetic communication
+Building trust through transparency
+Fostering a growth mindset in teams
+Leading by example`),
+        new HumanMessage(`Book: "${bookName}"\n\nGenerated Summary (excerpt): ${summary.length > 1500 ? summary.slice(0, 1500) + '...' : summary}`)
       ];
       
       const response = await this.llm.invoke(messages);
-      const questions = response.content.toString()
+      const themes = response.content.toString()
         .split('\n')
-        .map(q => q.trim())
-        .filter(q => q.length > 0 && q.length < 80)
-        .slice(0, 3);
+        .map(q => q.trim().replace(/^[-*]\s*/, '')) // Remove bullets/dashes
+        .filter(q => q.length > 0 && q.length < 100)
+        .slice(0, 5); // Max 5 themes
       
-      return questions.length > 0 ? questions : [];
-    } catch {
-      return [];
+      return themes.length > 0 ? themes : [];
+    } catch (error) {
+      console.warn("Failed to generate key themes:", error);
+      return []; // Return empty array on error
     }
   }
+
+  // Methods like extractSubQueries, checkAnswersInSources, generateAlternativeSearchQueries
+  // are less relevant in their current form for the book summary task.
+  // They would need significant adaptation if we wanted to, for example,
+  // ensure specific aspects of a book (plot, characters, themes) are covered.
+  // For now, the multiple broad search queries and a powerful synthesis prompt are the primary strategy.
 }
\ No newline at end of file
diff --git a/lib/prompt-examples.ts b/lib/prompt-examples.ts
new file mode 100644
index 0000000..8ddeace
--- /dev/null
+++ b/lib/prompt-examples.ts
@@ -0,0 +1,524 @@
+export const ATOMIC_HABITS_EXAMPLE_SUMMARY = `
+# Introduction
+
+Do you ever feel like you're just floating through life, but not actually getting closer to the person that you want to be?
+
+It usually happens around New Year's… You imagine all the bad habits you're going to break free from, and all the good habits you will begin.
+
+This time we'll be different, you say to yourself.
+
+This time I am going to do the things that I say I will.
+
+Only to end up back where you began shortly after, and no closer to what you had envisaged.
+
+So the question is, how do you break free from bad habits and make the habits you desire easier and automatic?
+
+Atomic habits by James Clear answers all these questions.
+
+We're going to be doing a fast-paced, detailed summary of the book, and dive deep into topics like habit loops, dopamine spikes, priming your environment, plus heaps more. And make sure you stick around until the end of the video where I go through step-by-step how I'm personally using this book to improve my own habits.
+
+I hope this summary inspires you to go out and grab a copy of the book for yourself because this book deserves a space on everyone's bookshelf.
+
+Let's jump into it.
+
+Imagine a plane taking off and traveling from New York to Los Angeles.
+
+Just before take-off, you would just plane just slightly by 3 degrees, or around 80 inches. If you were to keep flying in a straight line, you would end up closer to Tijuana in Mexico than to your intended destination of Los Angeles.
+
+And the same goes for our habits.
+
+Tiny changes in our habits can change the trajectory of our lives in ways that we can't even notice until many years into the future looking back. In both good ways and bad, you are your habits.
+
+
+
+# The Power Of Atomic Habits
+
+> “A slight change in your daily habits can guide your life to a very different destination.” **James Clear**
+>
+
+## Massive Action vs 1% Improvements
+
+Far too often we convince ourselves that massive success is only possible through massive action in any goal we are pursuing.
+
+We expect ourselves to make some quantum leap or momentous improvement that will gain others' attention. However, it is the tiny improvements that aren't even noticeable at first that create incredible change.
+
+Let's look deeper into the math. 1% better every day for a year will compound to 37 times better, but 1% worse every day over a year will bring you close to zero.
+
+Your habits can compound against you in the form of things like stress or negative self-talk, or they can compound for you in the form of things like knowledge, productivity, skills, and relationships.
+
+> “Success is the product of daily habits, not once in a lifetime transformations.” **James Clear**
+>
+
+## The Truth About Progress
+
+When you start any endeavor in your life, here is what you think should happen… **linear progress**
+
+…but here is what actually happens.
+
+Notice this section here in the beginning. Small changes in our progress are not even noticeable. James Clear refers to this part of the graph as the Valley of Disappointment.
+
+You've done so much, you've put in so much effort, and you can barely see any results. This is where most people fail and slip back into their old routines. The most powerful outcomes of any compounding process are delayed, so patience is required.
+
+## Goals vs Systems
+
+> “Forget about goals focus on systems instead.” **James Clear**
+>
+
+A goal is the result you want to accomplish… systems deal with processes that lead to the results.
+
+The conventional wisdom suggests that the best way to achieve anything we want in life be it getting into better shape, putting a successful business, or spending more time with family is to set specific, realistic goals.
+
+But if you completely ignored your goals and focused only on your systems, would you still succeed? The author of this book argues that you would.
+
+Here are some problems with only having goals.
+
+1. **Win or Lose = Same Goals:** Successful and unsuccessful people share the same goals, so therefore the goal cannot be what differentiates winners from losers.
+2. O**nly Momentary Change:** Achieving a goal only changes your life for that moment in time.
+3. **Either /Or Conflict:** Goals can create an either or conflict, either you achieve the goal and succeed, or you don't, and you're a failure, even if you are making progress in the right direction.
+4. **Goal vs Long-Term Progress:** When you achieve a goal, what do you do after? If your goal was running the local marathon, chances are after completing it, your motivation will quickly fade and you will just slip back into your old routines.
+
+> “Goals are good for setting a direction, but systems are best for making progress.” **James Clear**
+>
+
+## A System Of Atomic Habits
+
+The problem with changing your habits is not you… The reason why you repeat the same bad habits for so long isn't because you don't want to change, but because you have the wrong system for change.
+
+Atomic habits are small routines of behaviors that accumulate to produce incremental positive outcomes over time. Big breakthroughs tend to get more attention than small improvements, but what really matters are the little daily decisions and actions we take.
+
+Just as atoms are the building blocks of molecules, atomic habits are the building blocks of remarkable results.
+
+### Three Layers To Behavior Change
+
+There are three layers to behavior change.
+
+1. **OUTCOMES:** The first layer is changing outcomes, the result, losing that weight, writing that book, or winning the season, the outcomes are what you get.
+2. **PROCESSES:** The second layer is changing your process, and what you do. The new workout routine, or developing a daily reading habit.
+3. **IDENTITY:** The third layer is changing your identity, what you believe, your world views, and how you think about yourself and others.
+
+Most people focus on the outcomes, but the best way to change your habits is by focusing on the person you want to become instead of the results that you want.
+
+The goal isn't to learn an instrument, it's to become a musician. The goal isn't to run a marathon, it's to become a runner.
+
+When something you want in your life becomes part of your identity, that is when your behaviors will start to naturally change. When you tell yourself and others, I'm a runner, you want to live up to that identity.
+
+Remind yourself, every time you do a workout, you are an athlete. Every time you write a line of code, you are a programmer. And each time you instruct your team, you are a leader.
+
+### The Habit Loop
+
+A habit is when something becomes repeated enough times that it becomes automatic.
+
+Ultimately, we want our habits to solve problems in our lives with the least amount of effort. a Habit is form and reinforced by means of a continuous feedback loop?
+
+1. Cue
+2. Craving
+3. Response
+4. Reward.
+
+The key to creating habits that stick is to create feedback loops that are continuously being improved.
+
+**Habit Loop Example #1:**
+
+1. **Cue:** Phone Buzz
+2. **Craving:** Want to know who messaged?
+3. **Response:** Pick up the phone?
+4. **Reward:** Solve the problem of who messaged.
+
+**Habit Loop Example #2:**
+
+1. **Cue:** Mine goes blank at work?
+2. **Craving:** Want to alleviate the frustration?
+3. **Response:** Check social media
+4. **Reward:** Satisfied the need to feel less frustrated.
+
+Over time, rewards become associated with cues.
+
+So in this example, checking social media becomes tied to your mind going blank at work. And then checking Facebook may be the cue to check Instagram, which becomes the cue to watch YouTube. And before you know it, your mind going blank cue has led to 20 minutes of wasted time.
+
+And the more you repeat these habit loops, the stronger and more automatic they become.
+
+Cues can really be anything…
+
+A smell, a sound, a sight, a person, a location. Try to think of any cues in your daily life that are initiating your good or bad habit loops.
+
+So how can we influence the habit loop to work for us?
+
+This book shows us the four laws that will guide us to do just that.
+
+
+
+# Law 1: Make It Obvious
+
+Most of your current habits are so automatic that you don't even realize them. You must first become aware of your habits before you can change them.
+
+## Habit scorecard
+
+You can achieve that with your habit scorecard.
+
+Write down all your daily behaviors on a habit scorecard. From the moment you wake up until the moment you go to bed, your scorecard may look something like this.
+
+Based on whether it helps you become the person you aspire to be, categorize each habit as positive, negative, or neutral.
+
+At this stage, we aren't trying to change anything, but just observe what is actually going on in our daily lives.
+
+> “Until you make the unconscious conscious, it will direct your life and you will call it fate.” **Carl Yung**
+>
+
+Vagueness is a real problem when it comes to habit formation, and studies have shown that quite often the reason people fail to stick to a habit is not because of a lack of motivation, but because of a lack of clarity.
+
+One day I will get into shape is easy to say to yourself, but too vague to get any momentum.
+
+What you need is a time and a place.
+
+### Set A Time And Place
+
+The most common cues time and location will help you achieve your goals.
+
+Usually, state your intention to act using the following formula.
+
+“I will **[behavior]** at the **[time]** in this **[location]**”
+
+Here is a bad example…
+
+I will read more this month.
+
+Here is a good example…
+
+will read a book for 15 minutes daily at 6 am in the spare bedroom.
+
+Another good way to get a habit started is by habit stacking.
+
+## Habit Stacking.
+
+To stack habits, tired desired habit to an existing habit according to the following formula.
+
+After a **[current habit]**, I will **[New Habits]**
+
+For example, after I brush my teeth, I will stretch for 5 minutes.
+
+You can stack habits together. For example, after you finish brushing your teeth, you will meditate for 10 minutes and then plan the rest of your day before checking social media.
+
+A chain of habits is more likely to be sustained if you practice this consistently.
+
+Choosing the correct trigger is essential… You need a trigger cue.
+
+Your trigger should be something that you do automatically without fail during your day, such as waking up, toning off your alarm, or brushing your teeth.
+
+## Environment VS Motivation
+
+James Clear tells us in the book that motivation is highly overrated. You can better shape your behavior by designing your environment. We are more influenced by our environment than our willpower or motivation.
+
+It's hard to stick with positive habits in a negative environment.
+
+> “The environment is the invisible hand that shapes human behavior”. James Clear
+>
+
+Creating a habit requires you to redesign the space around you To:
+
+1. Make it easier to see the cues for the desired habits, and
+2. Avert bad habits by making them invisible.
+
+If you want to drink more water, make the cues visible and obvious.
+
+Place water bottles around the house and in places you are likely to see them. Want to read more? Place the book somewhere where you'll see it. If you want to get better at guitar, don't leave it out of sight in the closet.
+
+Context is the cue.
+
+Objects in the environment do not determine our behavior. Rather, it is our relationship with them that does. Stop seeing your environment as a place simply filled with objects. Imagine it as a place filled with relationships.
+
+The couch in the living room is the place where one person reads for an hour or night. For another, the couch is where they watch Netflix and eat pizza and relax after work.
+
+If you're in a relationship with the couch as a place to relax, then trying to get a work-related task done in that environment may be difficult.
+
+Try to make separate zones in your house for different activities. Be author likes to use the mantra, **[one space, one use]**
+
+## Breaking a Bad Habit: Make it Invisible
+
+If you're trying to eliminate a bad habit, you can only rely on self-control in the short term.
+
+Cutting off bad habits of the source is a more reliable solution, and one of the most practical ways to eliminate a bad habit is to make it invisible.
+
+Eliminate it from your environment…
+
+For example, put your phone in another room for a few hours if you have trouble getting work done. Or, put junk food out of sight or remove it from your house if you're trying to lose weight.
+
+
+# Law 2: Make It Attractive
+
+When we expect to be rewarded, we take action. The more rewarding an action is, the more likely we are to repeat it until it becomes a habit.
+
+Hence the first step to forming good habits is to make them more attractive.
+
+## Dopamine
+
+Understanding how dopamine affects your body will help you.
+
+Our motivation levels are affected by dopamine… A hormone and neurotransmitter
+
+We are more motivated to act when our dopamine levels rise. By measuring dopamine Scientists can pinpoint the exact moment of craving occurs.
+
+It was once assumed that dopamine was just about pleasure, but now we know it is vital to many neurological functions, including motivation, memory, learning, punishment, and voluntary movement.
+
+The hormone dopamine is released not only when we experience pleasure, but also when we anticipate it.
+
+> “Gambling addicts have a dopamine spike right before they place a bet, not after they win” **James Clear**
+>
+
+let’s dive deeper into dopamine spikes,
+
+### Dopamine Spikes
+
+Using social media, eating junk food, and taking drugs are all associated with high levels of dopamine and can be highly habit-forming.
+
+Think about before going on a vacation. Sometimes thinking and anticipation of the vacation is better than the actual vacation.
+
+Seeing the junk food you desire surges dopamine, not after eating it. Drug addicts increase dopamine when they see the drugs, not after taking them.
+
+The craving is what causes us to take action in the first place.
+
+Making our habits attractive is vital because it is expectation of a rewarding experience that drives us to act.
+
+Here you can use a strategy known as Temptation Bundling…
+
+## How to use temptation Bundling
+
+Temptation bundling Process makes a habit more attractive by combining it with an action we need to do with the one that we want to do.
+
+For example, you could bundle watching Netflix (something you want to do) with working out (something you need to do).
+
+Temptation bundling applies a psychology principle known as **Premack’s Principle…** Develop by professor David Premack..
+
+The Premack principle states,  “More probable behaviors will reinforce less probable behaviors”
+
+In other words even if you are not looking forward to doing some exercise, you’ll become conditioned to do it because you will get something else you really enjoy.
+
+## Group influence
+
+> “We are continually wondering what will others think of me? And altering our behavior based on the answer” **James Clear**
+>
+
+We are influenced by the people closest to us, and the group we belong to.
+
+If you are trying to build a new habit, one of the best ways to reinforce the habit is to find and become part of culture where that habit is the norm.
+
+If you want to Get into better shape… Surround yourself wit fit people. If you want to read more, join a book club.
+
+## Where Craving Comes From
+
+Primal motivators, the source of cravings
+
+In your normal everyday life you wouldn't say something to yourself like, I want to eat pizza because I need to consume this food to survive.
+
+Surface level cravings are merely manifestations of our deeper underlying motives. And these underlying motives guide our behavior.
+
+Here are some examples from the book of underlying motives, conserving energy, obtaining food and water, finding love and reproducing, connecting and bonding with others, winning social acceptance and approval, reducing uncertainty, achieving status and prestige.
+
+Your brain did not evolve with a desire to smoke cigarettes. Check Instagram every five minutes or to play video games. Online platforms and products do not invent new motivations, but rather appeal to the underlying motives of human nature that we already have to gain our attention.
+
+> “Your habits are modern day solutions to ancient desires, new versions of old vices. The underlying motives behind human behavior remain the same” **James Clear**
+>
+
+People who have the underlying motive of connecting with others may jump onto Facebook. Others seeking the underlying motive of finding love and reproducing may sign up for Tinder.
+
+If you want to reduce uncertainty, there's Google for that and seeking social acceptance. There's Instagram.
+
+## How To Reprogram Your Brain To Enjoy Hard Habits
+
+> “You can make hard habits more attractive if you can learn to associate them with a positive experience.” **James Clear**
+>
+
+By highlighting the benefits of a habit rather than its downsides, you can quickly reprogram your mind and make it seem more appealing.
+
+For example, Fitness = health and wellbeing and not fatigue.
+
+Cleaning the house = an environment conducive to peace of mind and not wasted time
+
+Saving money = future financial freedom and not sacrifice.
+
+## Breaking A Bad Habit: Make it unattractive
+
+To break a bad habit, do the same, but highlight the benefits of not doing that habit to make it as unattractive to keep doing as possible.
+
+
+# Law 3: Make It Easy
+
+## How Long Does It Actually Take To Form A New Habit?
+
+During habit formation, a behavior becomes increasingly automatic as it is repeated. As you repeat an activity, your brain changes in order to become more efficient at doing it.
+
+Long before neuroscientist dug into the process of forming habits, repetition was known as a powerful tool for establishing habits. You activate, particularly in neural circuits associated with habits every time you repeat them.
+
+So framing habit formation in terms of time is flaw. It should be framed in terms of number of repetitions.
+
+## Reducing Friction, The Law Of Least Effort
+
+The more energy required, the less likely it is to happen. It takes almost no energy to get into the habit of reading one page of a book each day.
+
+Habits are more likely to occur when they require less energy.
+
+The bigger the obstacle, the more friction there is between you and the desired outcome. If you need to travel 20 minutes out of your way to go to your gym, chances are you will not. But if your gym is located on your commute to. You will greatly decrease the friction.
+
+By making your good habits more convenient, you're more likely to stick to them.
+
+Your life will be easier if you find ways to reduce friction rather than trying to solve it. In order to build better habits, we have to find ways to reduce friction associated with our good habits and increase friction associated with our bad habits.
+
+## Priming The Environment For Use
+
+By automating or setting up your environment, you can reduce the friction for future action.
+
+For example, I will lay out my workout clothes the night before, so when I get up, I can get moving in the morning. Or to prepare a healthier breakfast, place the pan on the stove, cooking, spray on the counter, and gather the ingredients the night before.
+
+Again, to reduce any friction.
+
+## The Two Minute Rule
+
+Using the two minute rule to stop procrastinating.
+
+Using the two minute rule can help you establish small habits that will lead to success in bigger ones. Find a simple two minute version of your desired habit. You want to scale down your desired outcome. Running a marathon becomes putting on your shoes and stretching for two minutes.
+
+Reading an hour per day becomes reading one page. You need to get the routine anchored in place and then slowly build up the difficulty.
+
+After you've mastered the two minute habit, you can progress to the next phase.
+
+## Breaking A Bad Habit: Make it difficult
+
+To make something more difficult, think about ways you can create barriers of friction between yourself and the bad habit.
+
+Make it as impractical as possible. If you want to watch less tv, unplug the TV after each use and put the remote in an inconvenient location. When you go shopping, leave your credit cards under the seat of the car. If you have a bad habit of spontaneous spending.
+
+Do anything you can to make your bad habits less likely to occur.
+
+
+# Law 4: Make It Satisfying
+
+## The Most Important Rule of Behavior Change
+
+A feeling of pleasure is a message to the brain. “This feels good. Let's repeat this next time”. When you experience pleasure, your brain learns the behavior is worth remembering and repeating.
+
+> “What is immediately rewarded is repeated. What is immediately punished is avoided.“ **James Clear**
+>
+
+The first three laws increase your chances of doing the habit this time, and the last law increases your chances of repeating the habit next time.
+
+## The Mismatch Between Immediate And Delayed Returns
+
+It is common for us to feel good about our immediate results, but bad about our long-term outcomes.
+
+When we practice bad habits. It is the opposite With good habits, the immediate result is unpleasant, but the ultimate outcome is satisfying. A certain amount of success in just about every field involves ignoring an immediate reward for the long-term one
+
+It is best to add a little immediate pleasure to the habits that will pay off in the long run and a little pain to those that don.
+
+## Rewarding Yourself And Feeling Successful
+
+The vital thing in getting a habit to stick is to feel successful, even if it's in a small way. The feeling of success is a signal that your habit paid off and the work was worth the effort. It is satisfying to make progress, and you can monitor your progress using visual measures such as moving paper clips, hair pins, or marbles.
+
+These little wins can go a long way.
+
+For example, for each sales call you make today, move a marble from one jar to the complete jar. For each 25 minutes of writing, move a paper. Visual measurements can take many forms, diet journals, workout logs, download progress bars, or even page numbers in a book.
+
+## Habit Tracker
+
+Keeping a habit tracker may be the best method to monitor your progress. Using a habit tracker is a simple way to determine whether you did a particular habit.
+
+Tracking becomes a reward in and of itself. Crossing a task off your to-do list, completing an entry in your exercise log or writing an X on the calendar is satisfying.
+
+## When Life Gets In The Way
+
+In spite of your best efforts, it is inevitable that life will interrupt you at some point.
+
+A bad day at work, a bad performance or a bad workout can happen to anyone. When you're having a bad day, you don't realize how valuable it is to just show up.
+
+“Lost days hurt you. More than successful days help you” **James Clear**
+
+Don't break the chain.
+
+### The Chain Of Continuity
+
+Don't break the chain of Continuity.
+
+Every time you cross a day off your calendar for a given habit, you are creating a chain. Showing up is so important. Missing two days or links in a row is the start of a bad.
+
+Even if you usually do 50 pushups, just do 10 on that given day. If that means not breaking the chain,
+
+### Breaking A Bad Habit: Make it unsatisfying.
+
+1. **Accountability Partners:** A behavior is less likely to occur when pain is immediate. Being held accountable by a partner is a good way to keep your desired habits in check. We all wanna be liked and respected, so we would rather just avoid the punishment that we will be held accountable to. For example, I owe you $10 every time I miss a. Plus the respect I lose for failing to do what I said I would. Your behavior is more likely to be influenced by concrete and immediate consequences.
+2. **The Habit Contract:** you can create a habit contract to hold yourself accountable just as governments use laws to hold citizens accountable. You can create a habit contract, either verbally or in writing, which makes it clear that you will honor a particular habit and there will be punishments. If you do not, you can then use your accountability partners to enforce this contract.
+
+
+# Conclusion
+
+Okay? So it's one thing to read a book, but another to actually apply it to your life. So I'm gonna try and visually represent how I've personally been using this book to build systems around my habits, the past few.
+
+After you guys read the book, maybe your approach will be different than mine or much better, or maybe there are some parts that I completely missed or could improve upon. So do let me know in the comments below.
+
+The good habits I wanted to develop were more consistent workout and reading routines. The bad habit I wanted to eliminate was becoming distracted and over consuming social media.
+
+First, I completed the habit scorecard.
+
+This gave me a good idea of habits. I could try to. But more importantly, it gave me an idea of daily habits I was already doing that I could stack my new habits with.
+
+Ultimately, when you find the habits you want to work on, you want to be pushing the desired good habits towards this side of the spectrum and the bad habits towards the other side.
+
+For the working out habit, the first step was to make the cues more obvious, and I had a few tools that I could use from the book. In this case, I used what James Clear calls the implementation strategy, so I will work out at 6:00 AM in the living room.
+
+Next, I tried as best I could to design my environment conducive to this new habit.
+
+I took my dumbbell set out of the closet and I put them in the living. I also found a few pictures of healthy physiques on the internet and put them in places around the house as cues that would remind me of the habit.
+
+Next, I moved onto the craving phase, so to increase dopamine and motivation. I bundled the workout with listening to some of my favorite podcasts, and I also implement reprogramming of the brain.
+
+So I tell myself repeatedly, I don't have to do a workout. But I get to build strength and a healthier body, and that subtle shift in mindset has gone a long way.
+
+Ideally joining a gym or finding a group of people to work out with would be even better to strengthen this. But unfortunately all the gyms are closed where I live, so I'm kind of on my own and these two tools will have to suffice for the moment.
+
+Next, making it easy using the two minute rule to make sure that I don't end up like most people, starting a new habit that try to do too much too soon. I want my habit to not feel like a challenge at all. So my two minute rule was putting on my workout clothes and stretching. And if that was the only thing that I accomplished, then that was fine because I showed up.
+
+But you will quickly find that once you are there, you are now motivated to get the workout done. So it is weird, but the, the motivation seems to come after you get the habit started.
+
+My mindset is focused on small 1% changes, compounding into meaningful results and that my systems will get me the results and not vague goals.
+
+Remembering that my main focus at this point is just making sure that I show up and start anchoring this habit in place.
+
+Once you are consistently showing up, you can increase the progression to decrease friction Imade the rule that I'm not allowed to check my phone until the workout was complete. If I get distracted by emails or social media, it is one excuse and one step of friction between myself and the workout getting completed.
+
+Lastly, this was a game changer for me priming the environment. When I place my shoes yoga mat and dumbbells out the night before, I skyrocket my show up and workout percent. As soon as I place these items out the night before, I feel like the ritual has begun and the workout is already complete because I have zero excuses.
+
+So with those three phases of the loop systemized to get me to show up, I only had the last phase of the loop left, which was to make sure I keep repeating the habit.
+
+I use both of these tools somewhat together to close out the loop. I use a habit tracker, crossing the day off the calendar becomes the.
+
+And it also forces me to not want to break the chain.
+
+I also take a picture of my calories that I burnt and I send that picture to my partner, and that also increases the satisfaction.
+
+Mindset wise, I begin with identity and I remind myself after each workout that I want to become the kind of person that enjoys fitness and doesn't miss workouts.
+
+I don't put all my focus on outcomes such as I want to be 10 kilograms lighter by such and such date. And I also remind myself that I need to be patient for the results and that I'm probably still somewhere in this valley of disappointment before I will see those results.
+
+I went through the same process with the reading habit with a few minor changes.
+
+So I used the habit stack after making a coffee. I will read for 90 minutes, so making a coffee was my trigger cue for reading my one space. One use rule was reading on the balcony of my apartment.
+
+One of the best parts of my day is a nice cup of coffee in the morning... So this was the perfect thing for me to bundle my reading habit with remembering how dopamine raises in anticipation of a reward and not the reward itself. I wanted this dopamine spike for wanting coffee to start becoming associated with reading.
+
+My two minute rule was to read one page of the Daily Stoic by Ryan Holiday. Super simple.
+
+Again, in the beginning, all I was concerned with was showing up and getting this habit anchored. Then I slowly built up the habit to 90 minutes for the bad habit I was trying to eliminate to make the habit invisible.
+
+I started by making my phone as boring as I possibly could, which required deleting a lot of apps.
+
+I use the reprogramming tool to highlight the unattractive side of over consuming social media. Telling myself things like consuming is the easy and lazy option of the masses, and do I want to be a consumer or a producer?
+
+Random scrolling through feeds is for losers, so you wanna try and paint your bad habit in a light that makes it super unattractive to keep doing.
+
+To increase friction I left my phone in a drawer in another room. So completely out of sight. And to make it unsatisfying, I have an accountability partner. I get my partner to enforce this habit. The punishment is if she sees me using social media during work time, I owe her $10.
+
+So that is how I've been using this fantastic book Guys, to get great results so far
+
+Go out and grab a copy of this book for yourself. If you haven't already, you're going to take in the knowledge at a much deeper level from all the stories and examples that James Clear gives you in.
+
+As well as some advanced techniques, which we didn't cover in the summary that will help you strengthen your habits.
+
+Good luck in your journey. Thank you for watching and see you in the next video.
+`;