first implementation - image/drawing integration

.gitignore

@@ -1,3 +1,15 @@
+# Runtime uploads (extracted figures)
+uploads/
+
+# Java build
+target/
+*.class
+*.jar
+
+# Node
+node_modules/
+dist/
+
 # OS
 .DS_Store
 Thumbs.db

CLAUDE.md

@@ -1,8 +1,10 @@
 # ai-teacher Development Guidelines
 
-Auto-generated from all feature plans. Last updated: 2026-03-31
+Auto-generated from all feature plans. Last updated: 2026-04-03
 
 ## Active Technologies
+- Java 25 (backend), TypeScript / Node 20 (frontend) + Spring Boot 4.0.5, Spring AI 2.0.0-M4, OpenAI API (embeddings + chat), PDFBox (via Spring AI PDF reader dependency) (002-image-aware-embedding)
+- PostgreSQL (JPA + Flyway), pgvector (Spring AI `VectorStore`), local file system (extracted images — `/uploads/figures/`) (002-image-aware-embedding)
 
 - Java 21 (backend), TypeScript / Node 20 (frontend) (001-neuro-rag-learning)
 
@@ -22,6 +24,7 @@ npm test && npm run lint
 Java 21 (backend), TypeScript / Node 20 (frontend): Follow standard conventions
 
 ## Recent Changes
+- 002-image-aware-embedding: Added Java 25 (backend), TypeScript / Node 20 (frontend) + Spring Boot 4.0.5, Spring AI 2.0.0-M4, OpenAI API (embeddings + chat), PDFBox (via Spring AI PDF reader dependency)
 
 - 001-neuro-rag-learning: Added Java 21 (backend), TypeScript / Node 20 (frontend)
 

README.md

@@ -11,13 +11,45 @@ graph TD
     User["Neurosurgeon (Browser)"]
     FE["Frontend\nVue.js 3 / Vite\n:5173"]
     BE["Backend\nSpring Boot 4 / Spring AI\n:8080"]
-    DB["PostgreSQL + pgvector\n(provided)"]
+    DB["PostgreSQL + pgvector\n(source of truth)"]
-    LLM["LLM Provider\n(OpenAI / configurable)"]
+    FS["File Store\nuploads/ (local disk)\nExtracted figure PNGs"]
+    LLM["LLM Provider\n(OpenAI)\nEmbeddings + Chat + Vision"]
 
     User -->|HTTP| FE
     FE -->|REST /api/v1/...| BE
-    BE -->|JDBC / pgvector| DB
+    BE -->|"JDBC — books, chapters,\nsections, figures, refs"| DB
-    BE -->|Embedding + Chat API| LLM
+    BE -->|"pgvector — text chunks\n+ figure caption vectors"| DB
+    BE -->|"PNG read/write\n(figure extraction)"| FS
+    FE -->|"GET /api/v1/figures/**\n(static file serving)"| BE
+    BE -->|"Embedding + Chat\n+ Vision (image description)"| LLM
+
+    subgraph "Embedding Pipeline (per PDF upload)"
+        EP1["Parse pages → SectionEntity"]
+        EP2["Extract images → FigureEntity"]
+        EP3["Vision describe → embed caption"]
+        EP4["Chunk text → embed chunks"]
+        EP5["Link chunks ↔ figures"]
+        EP1 --> EP2
+        EP1 --> EP4
+        EP2 --> EP3
+        EP4 --> EP5
+        EP3 --> EP5
+    end
+
+    subgraph "Retrieval Pipeline (per chat query)"
+        RP1["Text chunk search (topK=5)"]
+        RP2["Figure caption search (topK=3)"]
+        RP3["Expand chunks → full section text"]
+        RP4["Fetch linked figures (chunk_figure_ref)"]
+        RP5["Merge + deduplicate figures"]
+        RP6["Build LLM prompt + call"]
+        RP1 --> RP3
+        RP1 --> RP4
+        RP2 --> RP5
+        RP4 --> RP5
+        RP3 --> RP6
+        RP5 --> RP6
+    end
 ```
 
 ## Stack
@@ -56,3 +88,4 @@ npm run dev
 | `DB_URL` | Yes | JDBC URL, e.g. `jdbc:postgresql://localhost:5432/aiteacher` |
 | `DB_USERNAME` | Yes | Database username |
 | `DB_PASSWORD` | Yes | Database password |
+| `FIGURE_STORAGE_PATH` | No | Base path for uploaded PDFs and extracted figures (default: `./uploads`) |

backend/pom.xml

@@ -95,12 +95,19 @@
       <artifactId>spring-ai-advisors-vector-store</artifactId>
     </dependency>
 
-    <!-- Spring AI — PDF document reader -->
+    <!-- Spring AI — PDF document reader (includes PDFBox transitively) -->
     <dependency>
       <groupId>org.springframework.ai</groupId>
       <artifactId>spring-ai-pdf-document-reader</artifactId>
     </dependency>
 
+    <!-- PDFBox — explicit for image extraction per page -->
+    <dependency>
+      <groupId>org.apache.pdfbox</groupId>
+      <artifactId>pdfbox</artifactId>
+      <version>3.0.3</version>
+    </dependency>
+
     <!-- Jackson (JSON) -->
     <dependency>
       <groupId>com.fasterxml.jackson.core</groupId>

backend/src/main/java/com/aiteacher/book/BookController.java

@@ -1,5 +1,7 @@
 package com.aiteacher.book;
 
+import com.aiteacher.document.FigureEntity;
+import com.aiteacher.document.FigureRepository;
 import org.springframework.http.HttpStatus;
 import org.springframework.http.ResponseEntity;
 import org.springframework.web.bind.annotation.*;
@@ -15,9 +17,11 @@ import java.util.UUID;
 public class BookController {
 
     private final BookService bookService;
+    private final FigureRepository figureRepository;
 
-    public BookController(BookService bookService) {
+    public BookController(BookService bookService, FigureRepository figureRepository) {
         this.bookService = bookService;
+        this.figureRepository = figureRepository;
     }
 
     @PostMapping(consumes = "multipart/form-data")
@@ -46,6 +50,36 @@ public class BookController {
         return ResponseEntity.noContent().build();
     }
 
+    @PostMapping("/{id}/reembed")
+    public ResponseEntity<Map<String, Object>> reembed(@PathVariable UUID id) {
+        Book book = bookService.reembed(id);
+        return ResponseEntity.accepted().body(Map.of(
+            "bookId", book.getId(),
+            "status", BookStatus.PROCESSING.name()
+        ));
+    }
+
+    @GetMapping("/{id}/figures")
+    public ResponseEntity<List<FigureResponse>> figures(@PathVariable UUID id) {
+        bookService.getById(id); // 404 if not found
+        List<FigureResponse> responses = figureRepository.findAllByBookId(id)
+            .stream()
+            .map(f -> toFigureResponse(id, f))
+            .toList();
+        return ResponseEntity.ok(responses);
+    }
+
+    private FigureResponse toFigureResponse(UUID bookId, FigureEntity f) {
+        String filename = f.getImagePath().substring(f.getImagePath().lastIndexOf('/') + 1);
+        String imageUrl = "/api/v1/figures/" + bookId + "/" + filename;
+        return new FigureResponse(
+            f.getId(), f.getLabel(), f.getCaption(),
+            f.getFigureType().name(), f.getPage(), imageUrl,
+            f.getSectionId(),
+            null // section title not eagerly loaded here
+        );
+    }
+
     private Map<String, Object> toSummaryResponse(Book book) {
         return Map.of(
             "id", book.getId(),

backend/src/main/java/com/aiteacher/book/BookEmbeddingService.java

@@ -1,41 +1,75 @@
 package com.aiteacher.book;
 
+import com.aiteacher.document.*;
+import com.aiteacher.figure.FigureStorageService;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.document.Document;
-import org.springframework.ai.reader.pdf.PagePdfDocumentReader;
-import org.springframework.ai.reader.pdf.config.PdfDocumentReaderConfig;
 import org.springframework.ai.vectorstore.VectorStore;
 import org.springframework.ai.vectorstore.filter.FilterExpressionBuilder;
-import org.springframework.core.io.FileSystemResource;
+import org.springframework.beans.factory.annotation.Value;
 import org.springframework.scheduling.annotation.Async;
 import org.springframework.stereotype.Service;
+import org.springframework.transaction.annotation.Transactional;
 
 import java.nio.file.Path;
-import java.util.List;
+import java.time.Instant;
-import java.util.UUID;
+import java.util.*;
-import java.util.regex.Pattern;
 
 @Service
 public class BookEmbeddingService {
 
     private static final Logger log = LoggerFactory.getLogger(BookEmbeddingService.class);
 
-    // Pattern to detect diagram/figure captions
-    private static final Pattern CAPTION_PATTERN =
-        Pattern.compile("^(Figure|Fig\\.|Table|Diagram)\\s+[\\d.]+", Pattern.CASE_INSENSITIVE);
-
     private final VectorStore vectorStore;
     private final BookRepository bookRepository;
 
-    public BookEmbeddingService(VectorStore vectorStore, BookRepository bookRepository) {
+    @Value("${app.embedding.batch-size:50}")
+    private int embeddingBatchSize;
+
+    @Value("${app.embedding.batch-delay-ms:1000}")
+    private long embeddingBatchDelayMs;
+    private final PdfStructureParser pdfStructureParser;
+    private final FigureExtractionService figureExtractionService;
+    private final VisionDescriptionService visionDescriptionService;
+    private final TextChunkingService textChunkingService;
+    private final ChunkFigureRefService chunkFigureRefService;
+    private final SectionRepository sectionRepository;
+    private final ChapterRepository chapterRepository;
+    private final FigureRepository figureRepository;
+    private final ChunkFigureRefRepository chunkFigureRefRepository;
+    private final FigureStorageService figureStorageService;
+
+    public BookEmbeddingService(
+            VectorStore vectorStore,
+            BookRepository bookRepository,
+            PdfStructureParser pdfStructureParser,
+            FigureExtractionService figureExtractionService,
+            VisionDescriptionService visionDescriptionService,
+            TextChunkingService textChunkingService,
+            ChunkFigureRefService chunkFigureRefService,
+            SectionRepository sectionRepository,
+            ChapterRepository chapterRepository,
+            FigureRepository figureRepository,
+            ChunkFigureRefRepository chunkFigureRefRepository,
+            FigureStorageService figureStorageService) {
         this.vectorStore = vectorStore;
         this.bookRepository = bookRepository;
+        this.pdfStructureParser = pdfStructureParser;
+        this.figureExtractionService = figureExtractionService;
+        this.visionDescriptionService = visionDescriptionService;
+        this.textChunkingService = textChunkingService;
+        this.chunkFigureRefService = chunkFigureRefService;
+        this.sectionRepository = sectionRepository;
+        this.chapterRepository = chapterRepository;
+        this.figureRepository = figureRepository;
+        this.chunkFigureRefRepository = chunkFigureRefRepository;
+        this.figureStorageService = figureStorageService;
     }
 
     @Async
     public void embedBook(UUID bookId, String bookTitle, Path pdfPath) {
-        log.info("Starting embedding for book {} ({})", bookId, bookTitle);
+        log.info("Starting image-aware embedding for book {} ({})", bookId, bookTitle);
 
         Book book = bookRepository.findById(bookId).orElse(null);
         if (book == null) {
@@ -47,29 +81,68 @@ public class BookEmbeddingService {
             book.setStatus(BookStatus.PROCESSING);
             bookRepository.save(book);
 
-            PagePdfDocumentReader reader = new PagePdfDocumentReader(
+            // Step 1: Parse PDF into page-level sections persisted in Postgres
-                new FileSystemResource(pdfPath.toFile()),
+            List<SectionEntity> sections = pdfStructureParser.parse(bookId, bookTitle, pdfPath);
-                PdfDocumentReaderConfig.builder()
+            String chapterId = bookId + "-ch1";
-                    .withPagesPerDocument(1)
-                    .build()
-            );
 
-            List<Document> pages = reader.get();
+            // Step 2: Build and embed text chunks for all sections in batches
-            int pageCount = pages.size();
+            List<Document> allChunks = new ArrayList<>();
+            for (SectionEntity section : sections) {
+                List<Document> chunks = textChunkingService.chunk(section, bookTitle);
+                allChunks.addAll(chunks);
+            }
+            embedInBatches(allChunks, bookId);
+            log.info("Embedded {} text chunks for book {}", allChunks.size(), bookId);
 
-            // Enrich metadata and tag diagram captions
+            // Step 3: Extract images from the PDF, save to file store, persist FigureEntity
-            List<Document> enriched = pages.stream()
+            List<FigureEntity> figures = figureExtractionService.extract(
-                .map(doc -> enrichDocument(doc, bookId.toString(), bookTitle))
+                bookId, chapterId, sections, pdfPath);
+
+            // Step 4: For each figure, generate vision description and embed caption
+            for (FigureEntity figure : figures) {
+                Path imagePath = figureStorageService.resolve(figure.getImagePath());
+                String description = visionDescriptionService.describe(
+                    imagePath, figure.getCaption());
+
+                // Use description as caption fallback if no caption was detected
+                if (figure.getCaption() == null || figure.getCaption().isBlank()) {
+                    figure.setCaption(description);
+                    figureRepository.save(figure);
+                }
+
+                // Content for embedding = vision description + caption for maximum signal
+                String embeddingContent = description
+                    + (figure.getCaption() != null ? "\n" + figure.getCaption() : "");
+
+                String embeddingId = UUID.randomUUID().toString();
+                Map<String, Object> metadata = buildFigureMetadata(figure, bookTitle, embeddingId);
+                Document figureDoc = new Document(embeddingId, embeddingContent, metadata);
+                vectorStore.add(List.of(figureDoc));
+
+                figure.setCaptionEmbeddingId(UUID.fromString(embeddingId));
+                figureRepository.save(figure);
+            }
+            log.info("Embedded {} figure captions for book {}", figures.size(), bookId);
+
+            // Step 5: Link text chunks to figures via text references
+            for (SectionEntity section : sections) {
+                List<Document> sectionChunks = allChunks.stream()
+                    .filter(d -> section.getId().equals(d.getMetadata().get("section_id")))
                     .toList();
-
+                List<FigureEntity> sectionFigures = figures.stream()
-            vectorStore.add(enriched);
+                    .filter(f -> section.getId().equals(f.getSectionId()))
+                    .toList();
+                chunkFigureRefService.linkChunksToFigures(
+                    sectionChunks, sectionFigures, section.getPageStart());
+            }
 
             book.setStatus(BookStatus.READY);
-            book.setPageCount(pageCount);
+            book.setPageCount(sections.size());
-            book.setProcessedAt(java.time.Instant.now());
+            book.setProcessedAt(Instant.now());
             bookRepository.save(book);
 
-            log.info("Finished embedding book {} — {} pages", bookId, pageCount);
+            log.info("Finished embedding book {} — {} pages, {} figures",
+                bookId, sections.size(), figures.size());
 
         } catch (Exception ex) {
             log.error("Failed to embed book {}", bookId, ex);
@@ -79,40 +152,74 @@ public class BookEmbeddingService {
         }
     }
 
-    private Document enrichDocument(Document doc, String bookId, String bookTitle) {
+    @Transactional
-        String content = doc.getText();
-        String chunkType = detectChunkType(content);
-
-        doc.getMetadata().put("book_id", bookId);
-        doc.getMetadata().put("book_title", bookTitle);
-        doc.getMetadata().put("chunk_type", chunkType);
-
-        return doc;
-    }
-
-    private String detectChunkType(String content) {
-        if (content != null) {
-            for (String line : content.split("\\r?\\n")) {
-                if (CAPTION_PATTERN.matcher(line.trim()).find()) {
-                    return "diagram";
-                }
-            }
-        }
-        return "text";
-    }
-
     public void deleteBookChunks(UUID bookId) {
-        log.info("Deleting vector chunks for book {}", bookId);
+        log.info("Deleting all data for book {}", bookId);
         try {
+            // Delete chunk-figure refs (by figureId for this book)
+            List<String> figureIds = figureRepository.findAllByBookId(bookId)
+                .stream().map(FigureEntity::getId).toList();
+            if (!figureIds.isEmpty()) {
+                chunkFigureRefRepository.deleteByFigureIdIn(figureIds);
+            }
+
+            // Delete figures from Postgres
+            figureRepository.deleteAllByBookId(bookId);
+
+            // Delete figure files from disk
+            figureStorageService.deleteAll(bookId);
+
+            // Delete sections and chapters from Postgres
+            sectionRepository.deleteAllByBookId(bookId);
+            chapterRepository.deleteAllByBookId(bookId);
+
+            // Delete vector store entries (text chunks + figure embeddings)
             FilterExpressionBuilder b = new FilterExpressionBuilder();
             vectorStore.delete(b.eq("book_id", bookId.toString()).build());
+
         } catch (Exception ex) {
-            log.warn("Could not delete vector chunks for book {}: {}", bookId, ex.getMessage());
+            log.warn("Error during cleanup for book {}: {}", bookId, ex.getMessage());
         }
     }
 
-    private String truncate(String message, int maxLength) {
+    private void embedInBatches(List<Document> docs, UUID bookId) {
-        if (message == null) return null;
+        int total = docs.size();
-        return message.length() <= maxLength ? message : message.substring(0, maxLength);
+        for (int i = 0; i < total; i += embeddingBatchSize) {
+            List<Document> batch = docs.subList(i, Math.min(i + embeddingBatchSize, total));
+            vectorStore.add(batch);
+            int batchNum = i / embeddingBatchSize + 1;
+            int totalBatches = (total - 1) / embeddingBatchSize + 1;
+            log.debug("Embedded batch {}/{} for book {}", batchNum, totalBatches, bookId);
+            if (i + embeddingBatchSize < total) {
+                try {
+                    Thread.sleep(embeddingBatchDelayMs);
+                } catch (InterruptedException e) {
+                    Thread.currentThread().interrupt();
+                    log.warn("Embedding batch sleep interrupted for book {}", bookId);
+                }
+            }
+        }
+    }
+
+    private Map<String, Object> buildFigureMetadata(FigureEntity figure, String bookTitle,
+                                                     String embeddingId) {
+        Map<String, Object> m = new HashMap<>();
+        m.put("type", "FIGURE");
+        m.put("book_id", figure.getBookId().toString());
+        m.put("book_title", bookTitle);
+        m.put("chapter_id", figure.getChapterId() != null ? figure.getChapterId() : "");
+        m.put("section_id", figure.getSectionId() != null ? figure.getSectionId() : "");
+        m.put("figure_id", figure.getId());
+        m.put("figure_type", figure.getFigureType().name());
+        m.put("image_path", figure.getImagePath());
+        m.put("label", figure.getLabel() != null ? figure.getLabel() : "");
+        m.put("page", figure.getPage());
+        m.put("embedding_id", embeddingId);
+        return m;
+    }
+
+    private String truncate(String msg, int max) {
+        if (msg == null) return null;
+        return msg.length() <= max ? msg : msg.substring(0, max);
     }
 }

backend/src/main/java/com/aiteacher/book/BookService.java

@@ -1,11 +1,13 @@
 package com.aiteacher.book;
 
+import org.springframework.beans.factory.annotation.Value;
 import org.springframework.stereotype.Service;
 import org.springframework.web.multipart.MultipartFile;
 
 import java.io.IOException;
 import java.nio.file.Files;
 import java.nio.file.Path;
+import java.nio.file.Paths;
 import java.util.List;
 import java.util.NoSuchElementException;
 import java.util.UUID;
@@ -15,10 +17,15 @@ public class BookService {
 
     private final BookRepository bookRepository;
     private final BookEmbeddingService bookEmbeddingService;
+    private final Path bookStoragePath;
 
-    public BookService(BookRepository bookRepository, BookEmbeddingService bookEmbeddingService) {
+    public BookService(
+            BookRepository bookRepository,
+            BookEmbeddingService bookEmbeddingService,
+            @Value("${app.figure-storage.base-path:./uploads}") String basePath) {
         this.bookRepository = bookRepository;
         this.bookEmbeddingService = bookEmbeddingService;
+        this.bookStoragePath = Paths.get(basePath).toAbsolutePath().normalize().resolve("books");
     }
 
     public Book upload(MultipartFile file) throws IOException {
@@ -28,20 +35,35 @@ public class BookService {
         }
 
         String title = deriveTitle(originalFilename);
-
         Book book = new Book(title, originalFilename, file.getSize());
         book = bookRepository.save(book);
 
-        // Write to a temp file so the async task can read it
+        // Persist PDF in a stable location for potential re-embedding
-        Path tempFile = Files.createTempFile("aiteacher-", "-" + book.getId() + ".pdf");
+        Files.createDirectories(bookStoragePath);
-        file.transferTo(tempFile.toFile());
+        Path pdfPath = bookStoragePath.resolve(book.getId() + ".pdf");
+        file.transferTo(pdfPath.toFile());
 
         UUID bookId = book.getId();
-        Path pdfPath = tempFile;
+        bookEmbeddingService.embedBook(bookId, title, pdfPath);
-        String bookTitle = title;
+        return book;
+    }
 
-        bookEmbeddingService.embedBook(bookId, bookTitle, pdfPath);
+    public Book reembed(UUID id) {
+        Book book = bookRepository.findById(id)
+            .orElseThrow(() -> new NoSuchElementException("Book not found."));
 
+        if (book.getStatus() == BookStatus.PROCESSING) {
+            throw new IllegalStateException("Book is already being processed.");
+        }
+
+        Path pdfPath = bookStoragePath.resolve(id + ".pdf");
+        if (!Files.exists(pdfPath)) {
+            throw new IllegalStateException(
+                "Original PDF not found. Please re-upload the book before re-embedding.");
+        }
+
+        bookEmbeddingService.deleteBookChunks(id);
+        bookEmbeddingService.embedBook(id, book.getTitle(), pdfPath);
         return book;
     }
 
@@ -63,14 +85,21 @@ public class BookService {
         }
 
         bookEmbeddingService.deleteBookChunks(id);
+
+        // Delete the stored PDF
+        Path pdfPath = bookStoragePath.resolve(id + ".pdf");
+        try {
+            Files.deleteIfExists(pdfPath);
+        } catch (IOException ex) {
+            // Non-fatal — log only
+        }
+
         bookRepository.deleteById(id);
     }
 
     private String deriveTitle(String filename) {
-        // Strip .pdf extension and replace separators with spaces
         String name = filename.replaceAll("(?i)\\.pdf$", "");
         name = name.replaceAll("[-_]", " ");
-        // Capitalise first letter
         if (!name.isEmpty()) {
             name = Character.toUpperCase(name.charAt(0)) + name.substring(1);
         }

backend/src/main/java/com/aiteacher/book/FigureResponse.java

@@ -0,0 +1,12 @@
+package com.aiteacher.book;
+
+public record FigureResponse(
+    String figureId,
+    String label,
+    String caption,
+    String figureType,
+    int page,
+    String imageUrl,
+    String sectionId,
+    String sectionTitle
+) {}

backend/src/main/java/com/aiteacher/chat/ChatService.java

@@ -3,22 +3,16 @@ package com.aiteacher.chat;
 import com.aiteacher.book.BookRepository;
 import com.aiteacher.book.BookStatus;
 import com.aiteacher.book.NoKnowledgeSourceException;
+import com.aiteacher.document.FigureEntity;
+import com.aiteacher.document.SectionEntity;
+import com.aiteacher.retrieval.NeurosurgeryRetriever;
+import com.aiteacher.retrieval.RetrievalResult;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 import org.springframework.ai.chat.client.ChatClient;
-import org.springframework.ai.chat.client.advisor.vectorstore.QuestionAnswerAdvisor;
-import org.springframework.ai.chat.model.ChatResponse;
-import org.springframework.ai.document.Document;
-import org.springframework.ai.vectorstore.SearchRequest;
-import org.springframework.ai.vectorstore.VectorStore;
 import org.springframework.stereotype.Service;
 
-import java.util.ArrayList;
+import java.util.*;
-import java.util.HashMap;
-import java.util.List;
-import java.util.Map;
-import java.util.NoSuchElementException;
-import java.util.UUID;
 
 @Service
 public class ChatService {
@@ -35,26 +29,28 @@ public class ChatService {
         - Build answers from what is present: procedures, conditions, techniques, and descriptions all contribute; combine them into a rich, structured response
         - Use clear structure: headings, bullet points, or numbered steps where appropriate to maximize clarity
         - Only say you cannot answer if the context is entirely unrelated to the question
-        - Cite sources for each major point (book title and page number from the context metadata)
+        - Cite sources for each major point (book title and page number from the context)
+        - When referencing diagrams or figures, cite them as [Fig. X, p.N]
         - Maintain continuity with the conversation history
         - Never fabricate clinical information not present in the context
         """;
 
     private final ChatClient chatClient;
-    private final VectorStore vectorStore;
     private final BookRepository bookRepository;
     private final ChatSessionRepository sessionRepository;
     private final MessageRepository messageRepository;
+    private final NeurosurgeryRetriever retriever;
 
-    public ChatService(ChatClient chatClient, VectorStore vectorStore,
+    public ChatService(ChatClient chatClient,
                        BookRepository bookRepository,
                        ChatSessionRepository sessionRepository,
-                       MessageRepository messageRepository) {
+                       MessageRepository messageRepository,
+                       NeurosurgeryRetriever retriever) {
         this.chatClient = chatClient;
-        this.vectorStore = vectorStore;
         this.bookRepository = bookRepository;
         this.sessionRepository = sessionRepository;
         this.messageRepository = messageRepository;
+        this.retriever = retriever;
     }
 
     public ChatSession createSession(String topicId) {
@@ -73,7 +69,11 @@ public class ChatService {
         ChatSession session = sessionRepository.findById(sessionId)
             .orElseThrow(() -> new NoSuchElementException("Session not found."));
 
-        if (!bookRepository.existsByStatus(BookStatus.READY)) {
+        List<com.aiteacher.book.Book> readyBooks = bookRepository.findAll().stream()
+            .filter(b -> b.getStatus() == BookStatus.READY)
+            .toList();
+
+        if (readyBooks.isEmpty()) {
             throw new NoKnowledgeSourceException("No books are available as knowledge sources.");
         }
 
@@ -81,27 +81,31 @@ public class ChatService {
         Message userMessage = new Message(sessionId, MessageRole.USER, userContent);
         messageRepository.save(userMessage);
 
-        // Build conversation history for context
+        // Build full question with conversation history
         List<Message> history = messageRepository.findBySessionIdOrderByCreatedAtAsc(sessionId);
-
-        // Build the prompt with full conversation history as context
         String fullQuestion = buildQuestionWithHistory(history, userContent, session.getTopicId());
 
-        var qaAdvisor = QuestionAnswerAdvisor.builder(vectorStore)
+        // Retrieve context from all ready books (aggregate across books)
-        .searchRequest(SearchRequest.builder().similarityThreshold(0.5d).topK(6).build())
+        List<SectionEntity> allSections = new ArrayList<>();
-        .build();
+        List<FigureEntity> allFigures = new ArrayList<>();
+        for (com.aiteacher.book.Book book : readyBooks) {
+            RetrievalResult result = retriever.retrieve(fullQuestion, book.getId());
+            allSections.addAll(result.parentSections());
+            allFigures.addAll(result.figures());
+        }
 
-        ChatResponse response = chatClient.prompt()
+        // Build LLM prompt with section full texts and figure references
-            .advisors(qaAdvisor)
+        String contextPrompt = buildContextPrompt(fullQuestion, allSections, allFigures);
+
+        String assistantContent = chatClient.prompt()
             .system(SYSTEM_PROMPT)
-            .user(fullQuestion)
+            .user(contextPrompt)
             .call()
-            .chatResponse();
+            .content();
 
-        String assistantContent = response.getResult().getOutput().getText();
+        // Build sources list with TEXT and FIGURE entries
-        List<Map<String, Object>> sources = extractSources(response);
+        List<Map<String, Object>> sources = buildSources(allSections, allFigures);
 
-        // Persist assistant message
         Message assistantMessage = new Message(sessionId, MessageRole.ASSISTANT, assistantContent);
         assistantMessage.setSources(sources);
         return messageRepository.save(assistantMessage);
@@ -118,24 +122,95 @@ public class ChatService {
         sessionRepository.deleteById(sessionId);
     }
 
+    // -------------------------------------------------------------------------
+    // Private helpers
+    // -------------------------------------------------------------------------
+
+    private String buildContextPrompt(String question,
+                                      List<SectionEntity> sections,
+                                      List<FigureEntity> figures) {
+        StringBuilder sb = new StringBuilder();
+
+        if (!sections.isEmpty()) {
+            sb.append("CONTEXT:\n\n");
+            for (SectionEntity section : sections) {
+                sb.append("[").append(section.getTitle())
+                  .append(", p.").append(section.getPageStart()).append("]\n");
+                sb.append(section.getFullText()).append("\n\n");
+            }
+        }
+
+        if (!figures.isEmpty()) {
+            sb.append("AVAILABLE FIGURES:\n");
+            for (FigureEntity figure : figures) {
+                sb.append("- ").append(figure.getLabel() != null ? figure.getLabel() : "Figure")
+                  .append(" (p.").append(figure.getPage()).append("): ")
+                  .append(figure.getCaption() != null ? figure.getCaption() : "")
+                  .append("\n");
+            }
+            sb.append("\nWhen referencing diagrams, cite them as [Fig. X, p.N].\n\n");
+        }
+
+        sb.append("QUESTION:\n").append(question);
+        return sb.toString();
+    }
+
+    private List<Map<String, Object>> buildSources(List<SectionEntity> sections,
+                                                    List<FigureEntity> figures) {
+        List<Map<String, Object>> sources = new ArrayList<>();
+
+        for (SectionEntity section : sections) {
+            Map<String, Object> source = new LinkedHashMap<>();
+            source.put("type", "TEXT");
+            source.put("bookTitle", deriveTitleFromSection(section));
+            source.put("page", section.getPageStart());
+            source.put("chunkText", truncate(section.getFullText(), 500));
+            sources.add(source);
+        }
+
+        for (FigureEntity figure : figures) {
+            Map<String, Object> source = new LinkedHashMap<>();
+            source.put("type", "FIGURE");
+            source.put("bookTitle", bookRepository.findById(figure.getBookId())
+                .map(com.aiteacher.book.Book::getTitle).orElse("Book"));
+            source.put("page", figure.getPage());
+            source.put("figureId", figure.getId());
+            source.put("label", figure.getLabel() != null ? figure.getLabel() : "");
+            source.put("caption", figure.getCaption() != null ? figure.getCaption() : "");
+            source.put("figureType", figure.getFigureType().name());
+            // imageUrl assembled from relative path: figures/{bookId}/{filename}
+            String filename = figure.getImagePath().substring(
+                figure.getImagePath().lastIndexOf('/') + 1);
+            source.put("imageUrl", "/api/v1/figures/" + figure.getBookId() + "/" + filename);
+            sources.add(source);
+        }
+
+        return sources;
+    }
+
+    private String deriveTitleFromSection(SectionEntity section) {
+        if (section == null) return "Book";
+        return bookRepository.findById(section.getBookId())
+            .map(com.aiteacher.book.Book::getTitle)
+            .orElse("Book");
+    }
+
     private String buildQuestionWithHistory(List<Message> history, String currentQuestion,
                                             String topicId) {
         boolean hasTopic = topicId != null && !topicId.equals("free-form");
 
         if (history.size() <= 1) {
             return hasTopic
-                ? String.format("[Context: This is a question about the neurosurgery topic '%s']\n%s",
+                ? String.format("[Context: question about neurosurgery topic '%s']\n%s",
                     topicId, currentQuestion)
                 : currentQuestion;
         }
 
         StringBuilder sb = new StringBuilder();
         if (hasTopic) {
-            sb.append(String.format("[Context: This conversation is about the neurosurgery topic '%s']\n\n",
+            sb.append(String.format("[Context: conversation about '%s']\n\n", topicId));
-                topicId));
         }
         sb.append("Previous conversation:\n");
-        // Include all messages except the last (which is the current user message just saved)
         for (int i = 0; i < history.size() - 1; i++) {
             Message msg = history.get(i);
             sb.append(msg.getRole().name()).append(": ").append(msg.getContent()).append("\n");
@@ -144,30 +219,8 @@ public class ChatService {
         return sb.toString();
     }
 
-    private List<Map<String, Object>> extractSources(ChatResponse response) {
+    private String truncate(String text, int maxChars) {
-        List<Map<String, Object>> sources = new ArrayList<>();
+        if (text == null) return "";
-
+        return text.length() <= maxChars ? text : text.substring(0, maxChars) + "…";
-        if (response.getMetadata() != null) {
-            Object retrieved = response.getMetadata().get(QuestionAnswerAdvisor.RETRIEVED_DOCUMENTS);
-            if (retrieved instanceof List<?> docs) {
-                for (Object docObj : docs) {
-                    if (docObj instanceof Document doc) {
-                        Map<String, Object> metadata = doc.getMetadata();
-                        String bookTitle = (String) metadata.get("book_title");
-                        Object pageObj = metadata.get("page_number");
-                        Integer page = pageObj instanceof Number n ? n.intValue() : null;
-                        if (bookTitle != null) {
-                            Map<String, Object> source = new HashMap<>();
-                            source.put("bookTitle", bookTitle);
-                            source.put("page", page);
-                            source.put("chunkText", doc.getText());
-                            sources.add(source);
-                        }
-                    }
-                }
-            }
-        }
-
-        return sources;
     }
 }

backend/src/main/java/com/aiteacher/config/FigureStorageConfig.java

@@ -0,0 +1,25 @@
+package com.aiteacher.config;
+
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.context.annotation.Configuration;
+import org.springframework.web.servlet.config.annotation.ResourceHandlerRegistry;
+import org.springframework.web.servlet.config.annotation.WebMvcConfigurer;
+
+import java.nio.file.Paths;
+
+@Configuration
+public class FigureStorageConfig implements WebMvcConfigurer {
+
+    private final String basePath;
+
+    public FigureStorageConfig(@Value("${app.figure-storage.base-path:./uploads}") String basePath) {
+        this.basePath = Paths.get(basePath).toAbsolutePath().normalize().toString();
+    }
+
+    @Override
+    public void addResourceHandlers(ResourceHandlerRegistry registry) {
+        // Serve GET /api/v1/figures/** from the local file store
+        registry.addResourceHandler("/api/v1/figures/**")
+                .addResourceLocations("file:" + basePath + "/figures/");
+    }
+}

backend/src/main/java/com/aiteacher/document/ChapterEntity.java

@@ -0,0 +1,47 @@
+package com.aiteacher.document;
+
+import jakarta.persistence.*;
+import java.time.Instant;
+import java.util.UUID;
+
+@Entity
+@Table(name = "chapter")
+public class ChapterEntity {
+
+    @Id
+    @Column(name = "id", length = 200)
+    private String id;
+
+    @Column(name = "book_id", nullable = false)
+    private UUID bookId;
+
+    @Column(name = "number", nullable = false)
+    private int number;
+
+    @Column(name = "title", length = 500)
+    private String title;
+
+    @Column(name = "page_start")
+    private Integer pageStart;
+
+    @Column(name = "created_at", nullable = false)
+    private Instant createdAt;
+
+    public ChapterEntity() {}
+
+    public ChapterEntity(String id, UUID bookId, int number, String title, Integer pageStart) {
+        this.id = id;
+        this.bookId = bookId;
+        this.number = number;
+        this.title = title;
+        this.pageStart = pageStart;
+        this.createdAt = Instant.now();
+    }
+
+    public String getId() { return id; }
+    public UUID getBookId() { return bookId; }
+    public int getNumber() { return number; }
+    public String getTitle() { return title; }
+    public Integer getPageStart() { return pageStart; }
+    public Instant getCreatedAt() { return createdAt; }
+}

backend/src/main/java/com/aiteacher/document/ChapterRepository.java

@@ -0,0 +1,9 @@
+package com.aiteacher.document;
+
+import org.springframework.data.jpa.repository.JpaRepository;
+
+import java.util.UUID;
+
+public interface ChapterRepository extends JpaRepository<ChapterEntity, String> {
+    void deleteAllByBookId(UUID bookId);
+}

backend/src/main/java/com/aiteacher/document/ChunkFigureRefEntity.java

@@ -0,0 +1,58 @@
+package com.aiteacher.document;
+
+import jakarta.persistence.*;
+import java.io.Serializable;
+import java.util.Objects;
+import java.util.UUID;
+
+@Entity
+@Table(name = "chunk_figure_ref")
+@IdClass(ChunkFigureRefEntity.PK.class)
+public class ChunkFigureRefEntity {
+
+    @Id
+    @Column(name = "chunk_id", nullable = false)
+    private UUID chunkId;
+
+    @Id
+    @Column(name = "figure_id", nullable = false, length = 200)
+    private String figureId;
+
+    @Column(name = "mention_page")
+    private Integer mentionPage;
+
+    public ChunkFigureRefEntity() {}
+
+    public ChunkFigureRefEntity(UUID chunkId, String figureId, Integer mentionPage) {
+        this.chunkId = chunkId;
+        this.figureId = figureId;
+        this.mentionPage = mentionPage;
+    }
+
+    public UUID getChunkId() { return chunkId; }
+    public String getFigureId() { return figureId; }
+    public Integer getMentionPage() { return mentionPage; }
+
+    public static class PK implements Serializable {
+        private UUID chunkId;
+        private String figureId;
+
+        public PK() {}
+        public PK(UUID chunkId, String figureId) {
+            this.chunkId = chunkId;
+            this.figureId = figureId;
+        }
+
+        @Override
+        public boolean equals(Object o) {
+            if (this == o) return true;
+            if (!(o instanceof PK pk)) return false;
+            return Objects.equals(chunkId, pk.chunkId) && Objects.equals(figureId, pk.figureId);
+        }
+
+        @Override
+        public int hashCode() {
+            return Objects.hash(chunkId, figureId);
+        }
+    }
+}

backend/src/main/java/com/aiteacher/document/ChunkFigureRefRepository.java

@@ -0,0 +1,18 @@
+package com.aiteacher.document;
+
+import org.springframework.data.jpa.repository.JpaRepository;
+import org.springframework.data.jpa.repository.Query;
+import org.springframework.data.repository.query.Param;
+
+import java.util.List;
+import java.util.UUID;
+
+public interface ChunkFigureRefRepository extends JpaRepository<ChunkFigureRefEntity, ChunkFigureRefEntity.PK> {
+
+    @Query("SELECT r FROM ChunkFigureRefEntity r WHERE r.chunkId IN :chunkIds")
+    List<ChunkFigureRefEntity> findByChunkIdIn(@Param("chunkIds") List<UUID> chunkIds);
+
+    @Query("DELETE FROM ChunkFigureRefEntity r WHERE r.figureId IN :figureIds")
+    @org.springframework.data.jpa.repository.Modifying
+    void deleteByFigureIdIn(@Param("figureIds") List<String> figureIds);
+}

backend/src/main/java/com/aiteacher/document/ChunkFigureRefService.java

@@ -0,0 +1,62 @@
+package com.aiteacher.document;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.document.Document;
+import org.springframework.stereotype.Service;
+
+import java.util.List;
+import java.util.UUID;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+
+/**
+ * Scans chunk text for "Fig. X" and "Figure X" references and persists
+ * ChunkFigureRefEntity rows linking that chunk to its referenced figures.
+ */
+@Service
+public class ChunkFigureRefService {
+
+    private static final Logger log = LoggerFactory.getLogger(ChunkFigureRefService.class);
+
+    // Matches: "Fig. 12-4", "Fig. 12.4", "Fig 12", "Figure 12-4", etc.
+    private static final Pattern REF_PATTERN =
+        Pattern.compile("(?i)\\b(Fig\\.?|Figure)\\s+(\\d+[\\-.\\d]*)");
+
+    private final ChunkFigureRefRepository refRepository;
+
+    public ChunkFigureRefService(ChunkFigureRefRepository refRepository) {
+        this.refRepository = refRepository;
+    }
+
+    /**
+     * For each text chunk, finds figure references and persists ChunkFigureRefEntity rows.
+     */
+    public void linkChunksToFigures(List<Document> chunks, List<FigureEntity> bookFigures,
+                                    int pageNum) {
+        if (bookFigures.isEmpty()) return;
+
+        for (Document chunk : chunks) {
+            String chunkIdStr = chunk.getId();
+            UUID chunkId;
+            try {
+                chunkId = UUID.fromString(chunkIdStr);
+            } catch (IllegalArgumentException ex) {
+                log.warn("Chunk has non-UUID id: {}", chunkIdStr);
+                continue;
+            }
+
+            Matcher m = REF_PATTERN.matcher(chunk.getText());
+            while (m.find()) {
+                String refNum = m.group(2).trim();
+                // Find matching figure by label suffix
+                for (FigureEntity figure : bookFigures) {
+                    if (figure.getLabel() != null && figure.getLabel().endsWith(refNum)) {
+                        refRepository.save(new ChunkFigureRefEntity(chunkId, figure.getId(), pageNum));
+                        break;
+                    }
+                }
+            }
+        }
+    }
+}

backend/src/main/java/com/aiteacher/document/FigureEntity.java

@@ -0,0 +1,82 @@
+package com.aiteacher.document;
+
+import jakarta.persistence.*;
+import java.time.Instant;
+import java.util.UUID;
+
+@Entity
+@Table(name = "figure")
+public class FigureEntity {
+
+    @Id
+    @Column(name = "id", length = 200)
+    private String id;
+
+    @Column(name = "book_id", nullable = false)
+    private UUID bookId;
+
+    @Column(name = "section_id", length = 200)
+    private String sectionId;
+
+    @Column(name = "chapter_id", length = 200)
+    private String chapterId;
+
+    @Column(name = "label", length = 100)
+    private String label;
+
+    @Column(name = "caption", columnDefinition = "TEXT")
+    private String caption;
+
+    @Enumerated(EnumType.STRING)
+    @Column(name = "figure_type", nullable = false, length = 50)
+    private FigureType figureType;
+
+    @Column(name = "page", nullable = false)
+    private int page;
+
+    @Column(name = "image_path", nullable = false, length = 1000)
+    private String imagePath;
+
+    @Column(name = "caption_embedding_id")
+    private UUID captionEmbeddingId;
+
+    @Column(name = "created_at", nullable = false)
+    private Instant createdAt;
+
+    public FigureEntity() {}
+
+    public FigureEntity(String id, UUID bookId, String sectionId, String chapterId,
+                        String label, String caption, FigureType figureType,
+                        int page, String imagePath) {
+        this.id = id;
+        this.bookId = bookId;
+        this.sectionId = sectionId;
+        this.chapterId = chapterId;
+        this.label = label;
+        this.caption = caption;
+        this.figureType = figureType;
+        this.page = page;
+        this.imagePath = imagePath;
+        this.createdAt = Instant.now();
+    }
+
+    public String getId() { return id; }
+    public UUID getBookId() { return bookId; }
+    public String getSectionId() { return sectionId; }
+    public String getChapterId() { return chapterId; }
+    public String getLabel() { return label; }
+    public String getCaption() { return caption; }
+    public FigureType getFigureType() { return figureType; }
+    public int getPage() { return page; }
+    public String getImagePath() { return imagePath; }
+    public UUID getCaptionEmbeddingId() { return captionEmbeddingId; }
+    public Instant getCreatedAt() { return createdAt; }
+
+    public void setCaptionEmbeddingId(UUID captionEmbeddingId) {
+        this.captionEmbeddingId = captionEmbeddingId;
+    }
+
+    public void setCaption(String caption) {
+        this.caption = caption;
+    }
+}

backend/src/main/java/com/aiteacher/document/FigureExtractionService.java

@@ -0,0 +1,135 @@
+package com.aiteacher.document;
+
+import com.aiteacher.figure.FigureStorageService;
+import org.apache.pdfbox.Loader;
+import org.apache.pdfbox.cos.COSName;
+import org.apache.pdfbox.pdmodel.PDDocument;
+import org.apache.pdfbox.pdmodel.PDPage;
+import org.apache.pdfbox.pdmodel.graphics.PDXObject;
+import org.apache.pdfbox.pdmodel.graphics.image.PDImageXObject;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.stereotype.Service;
+
+import java.awt.image.BufferedImage;
+import java.io.IOException;
+import java.nio.file.Path;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.UUID;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+
+/**
+ * Extracts images from each PDF page using PDFBox.
+ * Images below the configured minimum size are skipped.
+ * Caption is detected by the "Fig." pattern in page text.
+ */
+@Service
+public class FigureExtractionService {
+
+    private static final Logger log = LoggerFactory.getLogger(FigureExtractionService.class);
+
+    // Caption: line starting with "Fig." or "Figure" followed by a number
+    private static final Pattern CAPTION_PATTERN =
+        Pattern.compile("(?m)^(Fig\\.?\\s*\\d+[\\-.]?\\d*[^\\n]*)", Pattern.CASE_INSENSITIVE);
+
+    // Figure label: "Fig. 12-4" or "Fig. 12.4"
+    private static final Pattern LABEL_PATTERN =
+        Pattern.compile("(?i)Fig\\.?\\s*(\\d+[\\-.\\d]*)");
+
+    private final FigureStorageService storageService;
+    private final FigureRepository figureRepository;
+    private final int minImageSizePx;
+
+    public FigureExtractionService(
+            FigureStorageService storageService,
+            FigureRepository figureRepository,
+            @Value("${app.figure-storage.min-image-size-px:100}") int minImageSizePx) {
+        this.storageService = storageService;
+        this.figureRepository = figureRepository;
+        this.minImageSizePx = minImageSizePx;
+    }
+
+    /**
+     * Extracts all qualifying images from the PDF for the given book.
+     * Returns persisted FigureEntity list (without vision descriptions — set later).
+     */
+    public List<FigureEntity> extract(UUID bookId, String chapterId,
+                                      List<SectionEntity> sections, Path pdfPath) {
+        List<FigureEntity> figures = new ArrayList<>();
+        int figureCounter = 0;
+
+        try (PDDocument doc = Loader.loadPDF(pdfPath.toFile())) {
+            for (SectionEntity section : sections) {
+                int pageIndex = section.getPageStart() - 1; // 0-based
+                if (pageIndex < 0 || pageIndex >= doc.getNumberOfPages()) continue;
+
+                PDPage page = doc.getPage(pageIndex);
+                String pageText = section.getFullText();
+
+                try {
+                    for (COSName name : page.getResources().getXObjectNames()) {
+                        PDXObject xObject = page.getResources().getXObject(name);
+                        if (!(xObject instanceof PDImageXObject image)) continue;
+
+                        BufferedImage bufferedImage = image.getImage();
+                        if (bufferedImage.getWidth() < minImageSizePx
+                                || bufferedImage.getHeight() < minImageSizePx) {
+                            continue; // skip decorative images
+                        }
+
+                        figureCounter++;
+                        String figureId = bookId + "-fig-" + pageIndex + "-" + figureCounter;
+                        String caption = detectCaption(pageText);
+                        String label = detectLabel(caption, figureCounter);
+                        FigureType type = classifyType(caption, pageText);
+
+                        String imagePath = storageService.save(bookId, figureId, bufferedImage);
+
+                        FigureEntity figure = new FigureEntity(
+                            figureId, bookId, section.getId(), chapterId,
+                            label, caption, type, section.getPageStart(), imagePath
+                        );
+                        figures.add(figureRepository.save(figure));
+                    }
+                } catch (IOException ex) {
+                    log.warn("Failed to extract images from page {} of book {}: {}",
+                        section.getPageStart(), bookId, ex.getMessage());
+                }
+            }
+        } catch (IOException ex) {
+            log.error("Could not open PDF for image extraction, book {}", bookId, ex);
+        }
+
+        log.info("Extracted {} figures for book {}", figures.size(), bookId);
+        return figures;
+    }
+
+    private String detectCaption(String pageText) {
+        if (pageText == null) return null;
+        Matcher m = CAPTION_PATTERN.matcher(pageText);
+        return m.find() ? m.group(1).trim() : null;
+    }
+
+    private String detectLabel(String caption, int counter) {
+        if (caption != null) {
+            Matcher m = LABEL_PATTERN.matcher(caption);
+            if (m.find()) return "Fig. " + m.group(1).trim();
+        }
+        return "Fig. " + counter;
+    }
+
+    private FigureType classifyType(String caption, String pageText) {
+        String combined = ((caption != null ? caption : "") + " " + (pageText != null ? pageText : "")).toLowerCase();
+        if (combined.contains("mri") || combined.contains("ct ") || combined.contains("magnetic")
+                || combined.contains("tomography")) return FigureType.MRI_CT_SCAN;
+        if (combined.contains("intraoperative") || combined.contains("intra-op")) return FigureType.INTRAOPERATIVE_IMAGE;
+        if (caption != null && caption.toLowerCase().startsWith("table")) return FigureType.TABLE;
+        if (combined.contains("chart") || combined.contains("histogram") || combined.contains("graph"))
+            return FigureType.CHART;
+        if (combined.contains("photograph") || combined.contains("photo")) return FigureType.SURGICAL_PHOTOGRAPH;
+        return FigureType.ANATOMICAL_DIAGRAM;
+    }
+}

backend/src/main/java/com/aiteacher/document/FigureRepository.java

@@ -0,0 +1,11 @@
+package com.aiteacher.document;
+
+import org.springframework.data.jpa.repository.JpaRepository;
+
+import java.util.List;
+import java.util.UUID;
+
+public interface FigureRepository extends JpaRepository<FigureEntity, String> {
+    List<FigureEntity> findAllByBookId(UUID bookId);
+    void deleteAllByBookId(UUID bookId);
+}

backend/src/main/java/com/aiteacher/document/FigureType.java

@@ -0,0 +1,10 @@
+package com.aiteacher.document;
+
+public enum FigureType {
+    ANATOMICAL_DIAGRAM,
+    SURGICAL_PHOTOGRAPH,
+    MRI_CT_SCAN,
+    TABLE,
+    CHART,
+    INTRAOPERATIVE_IMAGE
+}

backend/src/main/java/com/aiteacher/document/PdfStructureParser.java

@@ -0,0 +1,71 @@
+package com.aiteacher.document;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.reader.pdf.PagePdfDocumentReader;
+import org.springframework.ai.reader.pdf.config.PdfDocumentReaderConfig;
+import org.springframework.core.io.FileSystemResource;
+import org.springframework.stereotype.Service;
+import org.springframework.transaction.annotation.Transactional;
+
+import java.nio.file.Path;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.UUID;
+
+/**
+ * Parses a PDF into page-level SectionEntity records stored in Postgres.
+ * Each page becomes one section, grouped under a single chapter per book.
+ */
+@Service
+public class PdfStructureParser {
+
+    private static final Logger log = LoggerFactory.getLogger(PdfStructureParser.class);
+
+    private final ChapterRepository chapterRepository;
+    private final SectionRepository sectionRepository;
+
+    public PdfStructureParser(ChapterRepository chapterRepository,
+                               SectionRepository sectionRepository) {
+        this.chapterRepository = chapterRepository;
+        this.sectionRepository = sectionRepository;
+    }
+
+    @Transactional
+    public List<SectionEntity> parse(UUID bookId, String bookTitle, Path pdfPath) {
+        log.info("Parsing PDF structure for book {}", bookId);
+
+        // One chapter per book
+        String chapterId = bookId + "-ch1";
+        ChapterEntity chapter = new ChapterEntity(chapterId, bookId, 1, bookTitle, 1);
+        chapterRepository.save(chapter);
+
+        // One section per page
+        PagePdfDocumentReader reader = new PagePdfDocumentReader(
+            new FileSystemResource(pdfPath.toFile()),
+            PdfDocumentReaderConfig.builder().withPagesPerDocument(1).build()
+        );
+
+        List<org.springframework.ai.document.Document> pages = reader.get();
+        List<SectionEntity> sections = new ArrayList<>();
+
+        for (int i = 0; i < pages.size(); i++) {
+            int pageNum = i + 1;
+            String text = pages.get(i).getText();
+            if (text == null || text.isBlank()) continue;
+
+            String sectionId = bookId + "-p" + pageNum;
+            SectionEntity section = new SectionEntity(
+                sectionId, chapterId, bookId,
+                String.valueOf(pageNum),
+                "Page " + pageNum,
+                pageNum, pageNum,
+                text
+            );
+            sections.add(sectionRepository.save(section));
+        }
+
+        log.info("Parsed {} sections for book {}", sections.size(), bookId);
+        return sections;
+    }
+}

backend/src/main/java/com/aiteacher/document/SectionEntity.java

@@ -0,0 +1,63 @@
+package com.aiteacher.document;
+
+import jakarta.persistence.*;
+import java.time.Instant;
+import java.util.UUID;
+
+@Entity
+@Table(name = "section")
+public class SectionEntity {
+
+    @Id
+    @Column(name = "id", length = 200)
+    private String id;
+
+    @Column(name = "chapter_id", nullable = false, length = 200)
+    private String chapterId;
+
+    @Column(name = "book_id", nullable = false)
+    private UUID bookId;
+
+    @Column(name = "number", length = 50)
+    private String number;
+
+    @Column(name = "title", length = 500)
+    private String title;
+
+    @Column(name = "page_start", nullable = false)
+    private int pageStart;
+
+    @Column(name = "page_end", nullable = false)
+    private int pageEnd;
+
+    @Column(name = "full_text", nullable = false, columnDefinition = "TEXT")
+    private String fullText;
+
+    @Column(name = "created_at", nullable = false)
+    private Instant createdAt;
+
+    public SectionEntity() {}
+
+    public SectionEntity(String id, String chapterId, UUID bookId, String number,
+                         String title, int pageStart, int pageEnd, String fullText) {
+        this.id = id;
+        this.chapterId = chapterId;
+        this.bookId = bookId;
+        this.number = number;
+        this.title = title;
+        this.pageStart = pageStart;
+        this.pageEnd = pageEnd;
+        this.fullText = fullText;
+        this.createdAt = Instant.now();
+    }
+
+    public String getId() { return id; }
+    public String getChapterId() { return chapterId; }
+    public UUID getBookId() { return bookId; }
+    public String getNumber() { return number; }
+    public String getTitle() { return title; }
+    public int getPageStart() { return pageStart; }
+    public int getPageEnd() { return pageEnd; }
+    public String getFullText() { return fullText; }
+    public Instant getCreatedAt() { return createdAt; }
+}

backend/src/main/java/com/aiteacher/document/SectionRepository.java

@@ -0,0 +1,11 @@
+package com.aiteacher.document;
+
+import org.springframework.data.jpa.repository.JpaRepository;
+
+import java.util.List;
+import java.util.UUID;
+
+public interface SectionRepository extends JpaRepository<SectionEntity, String> {
+    List<SectionEntity> findAllByBookId(UUID bookId);
+    void deleteAllByBookId(UUID bookId);
+}

backend/src/main/java/com/aiteacher/document/TextChunkingService.java

@@ -0,0 +1,65 @@
+package com.aiteacher.document;
+
+import org.springframework.ai.document.Document;
+import org.springframework.stereotype.Service;
+
+import java.util.ArrayList;
+import java.util.HashMap;
+import java.util.List;
+import java.util.Map;
+import java.util.UUID;
+
+/**
+ * Splits a SectionEntity's full text into overlapping chunks for vector embedding.
+ * Target size: ~1800 characters (~450 tokens); overlap: 200 characters.
+ */
+@Service
+public class TextChunkingService {
+
+    private static final int TARGET_CHARS = 1800;
+    private static final int OVERLAP_CHARS = 200;
+
+    public List<Document> chunk(SectionEntity section, String bookTitle) {
+        String text = section.getFullText();
+        if (text == null || text.isBlank()) return List.of();
+
+        List<String> windows = split(text);
+        List<Document> documents = new ArrayList<>();
+
+        for (int i = 0; i < windows.size(); i++) {
+            String chunkId = UUID.randomUUID().toString();
+            Map<String, Object> metadata = buildMetadata(section, bookTitle, i, windows.size(), chunkId);
+            documents.add(new Document(chunkId, windows.get(i), metadata));
+        }
+        return documents;
+    }
+
+    private List<String> split(String text) {
+        List<String> windows = new ArrayList<>();
+        int start = 0;
+        while (start < text.length()) {
+            int end = Math.min(start + TARGET_CHARS, text.length());
+            windows.add(text.substring(start, end));
+            if (end == text.length()) break;
+            start = end - OVERLAP_CHARS;
+        }
+        return windows;
+    }
+
+    private Map<String, Object> buildMetadata(SectionEntity section, String bookTitle,
+                                               int index, int total, String chunkId) {
+        Map<String, Object> m = new HashMap<>();
+        m.put("type", "TEXT");
+        m.put("book_id", section.getBookId().toString());
+        m.put("book_title", bookTitle);
+        m.put("chapter_id", section.getChapterId());
+        m.put("section_id", section.getId());
+        m.put("section_title", section.getTitle() != null ? section.getTitle() : "");
+        m.put("page_start", section.getPageStart());
+        m.put("page_end", section.getPageEnd());
+        m.put("chunk_index", index);
+        m.put("total_chunks", total);
+        m.put("chunk_id", chunkId);
+        return m;
+    }
+}

backend/src/main/java/com/aiteacher/document/VisionDescriptionService.java

@@ -0,0 +1,49 @@
+package com.aiteacher.document;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.chat.client.ChatClient;
+import org.springframework.core.io.FileSystemResource;
+import org.springframework.stereotype.Service;
+import org.springframework.util.MimeTypeUtils;
+
+import java.nio.file.Path;
+
+/**
+ * Generates a clinical text description for an extracted figure image
+ * using the OpenAI vision model via Spring AI ChatClient.
+ */
+@Service
+public class VisionDescriptionService {
+
+    private static final Logger log = LoggerFactory.getLogger(VisionDescriptionService.class);
+
+    private static final String PROMPT =
+        "You are a neurosurgery educator. Provide a brief 2-3 sentence clinical description of " +
+        "this image. Focus on anatomical structures, surgical landmarks, labels, and clinical " +
+        "significance. If text or labels are visible, include them verbatim.";
+
+    private final ChatClient chatClient;
+
+    public VisionDescriptionService(ChatClient chatClient) {
+        this.chatClient = chatClient;
+    }
+
+    /**
+     * Returns a description string. Falls back to the provided caption if vision fails.
+     */
+    public String describe(Path imagePath, String captionFallback) {
+        try {
+            return chatClient.prompt()
+                .user(u -> u
+                    .text(PROMPT)
+                    .media(MimeTypeUtils.IMAGE_PNG, new FileSystemResource(imagePath.toFile())))
+                .call()
+                .content();
+        } catch (Exception ex) {
+            log.warn("Vision description failed for {}: {} — using caption as fallback",
+                imagePath.getFileName(), ex.getMessage());
+            return captionFallback != null ? captionFallback : "Figure";
+        }
+    }
+}

backend/src/main/java/com/aiteacher/figure/FigureStorageService.java

@@ -0,0 +1,24 @@
+package com.aiteacher.figure;
+
+import java.awt.image.BufferedImage;
+import java.nio.file.Path;
+import java.util.UUID;
+
+public interface FigureStorageService {
+
+    /**
+     * Saves an extracted image to the figure store and returns the relative path
+     * (relative to the configured base-path) stored in the database.
+     */
+    String save(UUID bookId, String figureId, BufferedImage image);
+
+    /**
+     * Resolves a stored relative path to an absolute filesystem path.
+     */
+    Path resolve(String relativePath);
+
+    /**
+     * Deletes all figure files for the given book.
+     */
+    void deleteAll(UUID bookId);
+}

backend/src/main/java/com/aiteacher/figure/LocalFigureStorageService.java

@@ -0,0 +1,59 @@
+package com.aiteacher.figure;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.stereotype.Service;
+
+import javax.imageio.ImageIO;
+import java.awt.image.BufferedImage;
+import java.io.IOException;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.nio.file.Paths;
+import java.util.UUID;
+
+@Service
+public class LocalFigureStorageService implements FigureStorageService {
+
+    private static final Logger log = LoggerFactory.getLogger(LocalFigureStorageService.class);
+
+    private final Path basePath;
+
+    public LocalFigureStorageService(@Value("${app.figure-storage.base-path:./uploads}") String basePath) {
+        this.basePath = Paths.get(basePath).toAbsolutePath().normalize();
+    }
+
+    @Override
+    public String save(UUID bookId, String figureId, BufferedImage image) {
+        try {
+            Path dir = basePath.resolve("figures").resolve(bookId.toString());
+            Files.createDirectories(dir);
+            String filename = figureId + ".png";
+            Path file = dir.resolve(filename);
+            ImageIO.write(image, "PNG", file.toFile());
+            // Return relative path for storage in DB
+            return "figures/" + bookId + "/" + filename;
+        } catch (IOException ex) {
+            throw new RuntimeException("Failed to save figure " + figureId, ex);
+        }
+    }
+
+    @Override
+    public Path resolve(String relativePath) {
+        return basePath.resolve(relativePath);
+    }
+
+    @Override
+    public void deleteAll(UUID bookId) {
+        Path dir = basePath.resolve("figures").resolve(bookId.toString());
+        if (!Files.exists(dir)) return;
+        try (var walk = Files.walk(dir)) {
+            walk.sorted(java.util.Comparator.reverseOrder())
+                .map(Path::toFile)
+                .forEach(java.io.File::delete);
+        } catch (IOException ex) {
+            log.warn("Could not fully delete figures for book {}: {}", bookId, ex.getMessage());
+        }
+    }
+}

backend/src/main/java/com/aiteacher/retrieval/NeurosurgeryRetriever.java

@@ -0,0 +1,111 @@
+package com.aiteacher.retrieval;
+
+import com.aiteacher.document.*;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.ai.document.Document;
+import org.springframework.ai.vectorstore.SearchRequest;
+import org.springframework.ai.vectorstore.VectorStore;
+import org.springframework.ai.vectorstore.filter.FilterExpressionBuilder;
+import org.springframework.stereotype.Service;
+
+import java.util.*;
+
+/**
+ * Dual-modality retriever: searches text chunks and figure captions independently,
+ * then expands text hits to their parent sections and merges linked figures.
+ */
+@Service
+public class NeurosurgeryRetriever {
+
+    private static final Logger log = LoggerFactory.getLogger(NeurosurgeryRetriever.class);
+
+    private static final int TEXT_TOP_K = 5;
+    private static final int FIGURE_TOP_K = 3;
+
+    private final VectorStore vectorStore;
+    private final SectionRepository sectionRepository;
+    private final FigureRepository figureRepository;
+    private final ChunkFigureRefRepository chunkFigureRefRepository;
+
+    public NeurosurgeryRetriever(VectorStore vectorStore,
+                                  SectionRepository sectionRepository,
+                                  FigureRepository figureRepository,
+                                  ChunkFigureRefRepository chunkFigureRefRepository) {
+        this.vectorStore = vectorStore;
+        this.sectionRepository = sectionRepository;
+        this.figureRepository = figureRepository;
+        this.chunkFigureRefRepository = chunkFigureRefRepository;
+    }
+
+    public RetrievalResult retrieve(String query, UUID bookId) {
+        FilterExpressionBuilder b = new FilterExpressionBuilder();
+
+        // 1. Text chunk search
+        List<Document> textHits = vectorStore.similaritySearch(
+            SearchRequest.builder()
+                .query(query)
+                .topK(TEXT_TOP_K)
+                .filterExpression(b.and(
+                    b.eq("type", "TEXT"),
+                    b.eq("book_id", bookId.toString())
+                ).build())
+                .build()
+        );
+
+        // 2. Figure caption search (independent topK)
+        List<Document> figureHits = vectorStore.similaritySearch(
+            SearchRequest.builder()
+                .query(query)
+                .topK(FIGURE_TOP_K)
+                .filterExpression(b.and(
+                    b.eq("type", "FIGURE"),
+                    b.eq("book_id", bookId.toString())
+                ).build())
+                .build()
+        );
+
+        // 3. Expand text chunks to parent sections from Postgres
+        List<String> sectionIds = textHits.stream()
+            .map(d -> (String) d.getMetadata().get("section_id"))
+            .filter(Objects::nonNull)
+            .distinct()
+            .toList();
+        List<SectionEntity> sections = sectionIds.isEmpty()
+            ? List.of()
+            : sectionRepository.findAllById(sectionIds);
+
+        // 4. Fetch figures explicitly linked to retrieved chunks
+        List<UUID> chunkIds = textHits.stream()
+            .map(d -> {
+                try { return UUID.fromString(d.getId()); }
+                catch (Exception e) { return null; }
+            })
+            .filter(Objects::nonNull)
+            .toList();
+        List<String> linkedFigureIds = chunkIds.isEmpty()
+            ? List.of()
+            : chunkFigureRefRepository.findByChunkIdIn(chunkIds)
+                .stream().map(ChunkFigureRefEntity::getFigureId).distinct().toList();
+        List<FigureEntity> linkedFigures = linkedFigureIds.isEmpty()
+            ? List.of()
+            : figureRepository.findAllById(linkedFigureIds);
+
+        // 5. Collect figures from semantic figure search
+        List<String> semanticFigureIds = figureHits.stream()
+            .map(d -> (String) d.getMetadata().get("figure_id"))
+            .filter(Objects::nonNull)
+            .toList();
+        List<FigureEntity> semanticFigures = semanticFigureIds.isEmpty()
+            ? List.of()
+            : figureRepository.findAllById(semanticFigureIds);
+
+        // 6. Merge and deduplicate figures by figureId (linked figures take precedence)
+        Map<String, FigureEntity> merged = new LinkedHashMap<>();
+        linkedFigures.forEach(f -> merged.put(f.getId(), f));
+        semanticFigures.forEach(f -> merged.putIfAbsent(f.getId(), f));
+
+        log.debug("Retrieved {} sections, {} figures for query", sections.size(), merged.size());
+        return new RetrievalResult(sections, new ArrayList<>(merged.values()));
+    }
+}

backend/src/main/java/com/aiteacher/retrieval/RetrievalResult.java

@@ -0,0 +1,11 @@
+package com.aiteacher.retrieval;
+
+import com.aiteacher.document.FigureEntity;
+import com.aiteacher.document.SectionEntity;
+
+import java.util.List;
+
+public record RetrievalResult(
+    List<SectionEntity> parentSections,
+    List<FigureEntity> figures
+) {}

backend/src/main/resources/application.yaml

@@ -47,6 +47,16 @@ spring:
         max-size: 8
         queue-capacity: 50
 
+logging:
+  level:
+    "[org.apache.pdfbox]": ERROR
+
 app:
   auth:
     password: ${APP_PASSWORD:changeme}
+  figure-storage:
+    base-path: ${FIGURE_STORAGE_PATH:./uploads}
+    min-image-size-px: 100
+  embedding:
+    batch-size: 20
+    batch-delay-ms: 2000

backend/src/main/resources/db/migration/V4__document_hierarchy.sql

@@ -0,0 +1,28 @@
+-- ============================================================
+-- V4: Document hierarchy — chapter and section tables
+-- Supports parent-child retrieval pattern for RAG precision.
+-- ============================================================
+
+CREATE TABLE IF NOT EXISTS chapter (
+    id           VARCHAR(200) PRIMARY KEY,
+    book_id      UUID NOT NULL REFERENCES book(id) ON DELETE CASCADE,
+    number       INT NOT NULL DEFAULT 1,
+    title        VARCHAR(500),
+    page_start   INT,
+    created_at   TIMESTAMPTZ NOT NULL DEFAULT now()
+);
+
+CREATE TABLE IF NOT EXISTS section (
+    id           VARCHAR(200) PRIMARY KEY,
+    chapter_id   VARCHAR(200) NOT NULL REFERENCES chapter(id) ON DELETE CASCADE,
+    book_id      UUID NOT NULL REFERENCES book(id) ON DELETE CASCADE,
+    number       VARCHAR(50),
+    title        VARCHAR(500),
+    page_start   INT NOT NULL,
+    page_end     INT NOT NULL,
+    full_text    TEXT NOT NULL,
+    created_at   TIMESTAMPTZ NOT NULL DEFAULT now()
+);
+
+CREATE INDEX IF NOT EXISTS idx_section_book    ON section(book_id);
+CREATE INDEX IF NOT EXISTS idx_section_chapter ON section(chapter_id);

backend/src/main/resources/db/migration/V5__figures_and_refs.sql

@@ -0,0 +1,29 @@
+-- ============================================================
+-- V5: Figures and chunk-to-figure reference table
+-- figure: metadata + file path for each extracted image
+-- chunk_figure_ref: links vector-store chunks to figures
+-- ============================================================
+
+CREATE TABLE IF NOT EXISTS figure (
+    id                    VARCHAR(200) PRIMARY KEY,
+    book_id               UUID NOT NULL REFERENCES book(id) ON DELETE CASCADE,
+    section_id            VARCHAR(200) REFERENCES section(id) ON DELETE SET NULL,
+    chapter_id            VARCHAR(200) REFERENCES chapter(id) ON DELETE SET NULL,
+    label                 VARCHAR(100),
+    caption               TEXT,
+    figure_type           VARCHAR(50) NOT NULL,
+    page                  INT NOT NULL,
+    image_path            VARCHAR(1000) NOT NULL,
+    caption_embedding_id  UUID,
+    created_at            TIMESTAMPTZ NOT NULL DEFAULT now()
+);
+
+CREATE TABLE IF NOT EXISTS chunk_figure_ref (
+    chunk_id      UUID NOT NULL,
+    figure_id     VARCHAR(200) NOT NULL REFERENCES figure(id) ON DELETE CASCADE,
+    mention_page  INT,
+    PRIMARY KEY (chunk_id, figure_id)
+);
+
+CREATE INDEX IF NOT EXISTS idx_figure_book  ON figure(book_id);
+CREATE INDEX IF NOT EXISTS idx_cfr_chunk    ON chunk_figure_ref(chunk_id);

frontend/src/components/ChatMessage.vue

@@ -5,22 +5,47 @@
       <div v-if="isUser" class="message-content">{{ message.content }}</div>
       <div v-else class="message-content message-content--markdown" v-html="renderedContent"></div>
 
-      <!-- Source chips for assistant messages -->
+      <!-- Sources for assistant messages -->
       <div v-if="!isUser && message.sources && message.sources.length > 0" class="message-sources">
         <div class="sources-label">Sources:</div>
         <div class="source-list">
+          <!-- TEXT sources -->
           <div
-            v-for="(source, idx) in message.sources"
+            v-for="(source, idx) in textSources"
-            :key="idx"
+            :key="'text-' + idx"
             class="source-item"
           >
-            <div class="source-chip">
+            <div class="source-chip source-chip--text">
-              <span class="source-book-icon">📖</span>
+              <span class="source-icon">📖</span>
               <span class="source-book-title">{{ source.bookTitle }}</span>
               <span v-if="source.page" class="source-page">p.&nbsp;{{ source.page }}</span>
             </div>
             <div v-if="source.chunkText" class="source-chunk">{{ source.chunkText }}</div>
           </div>
+
+          <!-- FIGURE sources -->
+          <div
+            v-for="(source, idx) in figureSources"
+            :key="'fig-' + idx"
+            class="source-item source-item--figure"
+          >
+            <div class="source-chip source-chip--figure">
+              <span class="source-icon">🖼️</span>
+              <span class="source-figure-label">{{ source.label || 'Figure' }}</span>
+              <span v-if="source.page" class="source-page">p.&nbsp;{{ source.page }}</span>
+              <span v-if="source.figureType" class="source-figure-type">{{ formatFigureType(source.figureType) }}</span>
+            </div>
+            <div v-if="source.caption" class="source-caption">{{ source.caption }}</div>
+            <div class="source-figure-image">
+              <img
+                :src="source.imageUrl"
+                :alt="source.caption || source.label || 'Figure'"
+                class="figure-img"
+                loading="lazy"
+                @error="onImageError"
+              />
+            </div>
+          </div>
         </div>
       </div>
 
@@ -32,7 +57,7 @@
 <script setup lang="ts">
 import { computed } from 'vue'
 import { marked } from 'marked'
-import type { ChatMessage } from '@/stores/chatStore'
+import type { ChatMessage, ChatSource } from '@/stores/chatStore'
 
 const props = defineProps<{
   message: ChatMessage
@@ -41,6 +66,36 @@ const props = defineProps<{
 const isUser = computed(() => props.message.role === 'USER')
 const renderedContent = computed(() => marked.parse(props.message.content) as string)
 
+const textSources = computed(() =>
+  (props.message.sources ?? []).filter((s: ChatSource) => s.type === 'TEXT' || !s.type)
+)
+
+const figureSources = computed(() =>
+  (props.message.sources ?? []).filter((s: ChatSource) => s.type === 'FIGURE')
+)
+
+function formatFigureType(type: string): string {
+  const labels: Record<string, string> = {
+    ANATOMICAL_DIAGRAM: 'Anatomical Diagram',
+    SURGICAL_PHOTOGRAPH: 'Surgical Photo',
+    MRI_CT_SCAN: 'MRI / CT',
+    TABLE: 'Table',
+    CHART: 'Chart',
+    INTRAOPERATIVE_IMAGE: 'Intraoperative'
+  }
+  return labels[type] ?? type
+}
+
+function onImageError(e: Event) {
+  const img = e.target as HTMLImageElement
+  img.alt = 'Image unavailable'
+  img.style.display = 'none'
+  const wrapper = img.parentElement
+  if (wrapper) {
+    wrapper.innerHTML = '<span class="figure-missing">Image unavailable</span>'
+  }
+}
+
 function formatTime(iso: string): string {
   return new Date(iso).toLocaleTimeString([], { hour: '2-digit', minute: '2-digit' })
 }
@@ -182,6 +237,55 @@ function formatTime(iso: string): string {
   gap: 0.25rem;
 }
 
+.source-item--figure {
+  gap: 0.4rem;
+}
+
+.source-chip {
+  display: inline-flex;
+  align-items: center;
+  gap: 0.25rem;
+  border-radius: 4px;
+  padding: 0.2rem 0.5rem;
+  font-size: 0.78rem;
+}
+
+.source-chip--text {
+  background: #ebf8ff;
+  border: 1px solid #bee3f8;
+}
+
+.source-chip--figure {
+  background: #f0fff4;
+  border: 1px solid #9ae6b4;
+}
+
+.source-icon {
+  font-size: 0.8rem;
+}
+
+.source-book-title {
+  color: #2b6cb0;
+  font-weight: 500;
+}
+
+.source-figure-label {
+  color: #276749;
+  font-weight: 600;
+}
+
+.source-figure-type {
+  color: #718096;
+  font-size: 0.72rem;
+  background: #e2e8f0;
+  border-radius: 3px;
+  padding: 0 0.3rem;
+}
+
+.source-page {
+  color: #718096;
+}
+
 .source-chunk {
   font-size: 0.78rem;
   color: #4a5568;
@@ -194,28 +298,28 @@ function formatTime(iso: string): string {
   line-height: 1.5;
 }
 
-.source-chip {
+.source-caption {
-  display: inline-flex;
-  align-items: center;
-  gap: 0.25rem;
-  background: #ebf8ff;
-  border: 1px solid #bee3f8;
-  border-radius: 4px;
-  padding: 0.2rem 0.5rem;
   font-size: 0.78rem;
+  color: #4a5568;
+  font-style: italic;
 }
 
-.source-book-icon {
+.source-figure-image {
-  font-size: 0.8rem;
+  max-width: 100%;
 }
 
-.source-book-title {
+.figure-img {
-  color: #2b6cb0;
+  max-width: 100%;
-  font-weight: 500;
+  max-height: 300px;
+  border-radius: 6px;
+  border: 1px solid #e2e8f0;
+  object-fit: contain;
 }
 
-.source-page {
+.figure-missing {
-  color: #718096;
+  font-size: 0.78rem;
+  color: #a0aec0;
+  font-style: italic;
 }
 
 .message-timestamp {

frontend/src/stores/chatStore.ts

@@ -2,11 +2,25 @@ import { defineStore } from 'pinia'
 import { ref } from 'vue'
 import { api } from '@/services/api'
 
+export interface ChatSource {
+  type: 'TEXT' | 'FIGURE'
+  bookTitle: string
+  page: number | null
+  // TEXT-specific
+  chunkText?: string
+  // FIGURE-specific
+  figureId?: string
+  label?: string
+  caption?: string
+  figureType?: string
+  imageUrl?: string
+}
+
 export interface ChatMessage {
   id: string
   role: 'USER' | 'ASSISTANT'
   content: string
-  sources: Array<{ bookTitle: string; page: number | null; chunkText?: string }>
+  sources: ChatSource[]
   createdAt: string
 }
 

specs/002-image-aware-embedding/checklists/embedding-retrieval.md

@@ -0,0 +1,73 @@
+# Embedding & Retrieval Pipeline Checklist: Enhanced Embedding with Image Parsing and Metadata
+
+**Purpose**: Author self-review of embedding pipeline and retrieval requirements quality — validates completeness, clarity, and measurability before implementation tasks are written
+**Created**: 2026-04-03
+**Feature**: [spec.md](../spec.md) | [research.md](../research.md) | [data-model.md](../data-model.md)
+**Focus**: A (Embedding pipeline) + B (Retrieval & ranking) | Depth: Standard | Audience: Author
+
+---
+
+## Requirement Completeness — Embedding Pipeline
+
+- [X] CHK001 - Is the definition of "inspect every page" complete — does the spec cover pages that have no extractable content layer (fully scanned/rasterised pages)? Yes [Completeness, Spec §FR-001, Assumption §6]
+
+- [X] CHK002 - Does FR-002 define what "independently searchable" means in practice — specifically, is it clear that image chunks must be retrievable without a co-located text chunk? [Clarity, Spec §FR-002] - No image should be retrieved along linked text.
+
+- [X] CHK003 - Is the minimum acceptable quality of the "descriptive textual representation" (FR-003) specified — e.g., must it include structural relationships, labelled regions, or clinical terms — or is any non-empty description sufficient? [Clarity, Spec §FR-003, Gap] - any non-empty description sufficient. Text just below the image should have the correct clinical term.
+
+- [C] CHK004 - Are the caption-detection rules defined at spec level — specifically, what pattern or signal determines that a piece of text is a caption vs. body text adjacent to an image? [Clarity, Spec §FR-004, Gap] - We assume a text starting with Fig. follewed by number is a text description of a give image. 
+
+- [X] CHK005 - Does FR-004 specify what metadata is stored when a caption is absent — is the caption field omitted, left empty, or populated with a generated substitute? [Completeness, Spec §FR-004] - generated substitute
+
+- [X] CHK006 - Is the "minimum meaningful-content threshold" (FR-007) quantified in the spec, or is it deferred entirely to implementation? The assumption section says "size threshold determined during implementation" — is this intentional and acceptable at the spec level? [Ambiguity, Spec §FR-007, Assumption §3] - Deferred to implementation
+
+- [X] CHK007 - Does FR-008 specify the observable outcome of per-page image failures — specifically, is there a requirement that the book's processing status or error log is accessible to the user or admin after partial failure? [Completeness, Spec §FR-008, Gap] online logs
+
+- [X] CHK008 - Is FR-010 ("MUST NOT degrade accuracy or completeness of text-only embedding") measurable — does the spec define a baseline or acceptance criterion against which degradation can be detected? [Measurability, Spec §FR-010, Gap] no definition
+
+- [X] CHK009 - Are re-embedding requirements complete — does the spec cover what happens to in-progress queries and cached results while a book is being re-embedded? [Coverage, Assumption §8, Gap] - No need to take that into account.
+
+---
+
+## Requirement Completeness — Retrieval & Ranking
+
+- [X] CHK010 - Does FR-006 define how image and text chunks are ranked relative to each other — is ranking unified (single score), or are the two modalities ranked independently with separate topK controls? [Clarity, Spec §FR-006, Gap] - independent separated topK
+
+- [X] CHK011 - Is the relevance threshold for figure retrieval specified — i.e., at what similarity score (or other criterion) should a figure be excluded from results? [Clarity, Spec §FR-006, Gap] not specified
+
+- [X] CHK012 - Are deduplication rules defined for the case where the same figure appears both in the semantic figure search and the chunk-to-figure reference lookup — which representation wins, or are both included? [Completeness, data-model.md §RetrievalResult, Gap] not specified
+
+- [X] CHK013 - Is the requirement for parent section context expansion in the spec — specifically, is there a requirement that the LLM receives the full section text (not just the chunk) when a text chunk is retrieved? [Gap, research.md §Decision 1] - the LLM should receive the full section to have maximum context.
+
+- [X] CHK014 - Does the spec define the required structure of the LLM prompt when both text context and figures are present — or is prompt design left entirely to implementation? [Completeness, Gap] - Left to implementation
+
+- [X] CHK015 - Is SC-002 ("70% recall on image queries") sufficient as a measurability criterion — is the test set composition (10 queries) and evaluation method documented, or does it rely on an undefined manual process? [Measurability, Spec §SC-002] - Manual process.
+
+---
+
+## Scenario Coverage — Edge & Exception Cases
+
+- [X] CHK016 - Does the spec address the scenario where a query is relevant to a book section that has figures but none of those figures rank above the retrieval threshold — is the expected fallback behaviour defined? [Coverage, Edge Case, Gap] - The figure should in this case be retrieved and shon to the user.
+
+- [X] CHK017 - Is the scenario of a figure retrieved in search results but whose image file is missing from the file store covered — what should the system return to the user in that case? [Coverage, Exception Flow, Gap] - missing image error, shown in the front as a broken image link.
+
+- [X] CHK018 - Are requirements defined for multi-image pages where images have conflicting captions or share a single composite caption — which image gets the caption, or is it duplicated? [Coverage, Spec §FR-004, Edge Case] - this case not exist.
+
+---
+
+## Consistency & Alignment
+
+- [X] CHK019 - Are the metadata fields required by FR-004 and FR-005 fully consistent with the metadata schema defined in data-model.md — specifically, do the mandatory fields in the spec match the `type`, `section_id`, and `section_title` fields in the data model? [Consistency, Spec §FR-004, data-model.md §Vector Store Documents] - Left to implementation
+
+- [X] CHK020 - Is SC-003 ("processing time ≤ 3× baseline") consistent with FR-003 — if description generation requires a vision model call per image, is the 3× cap realistic for a 500-page book with dense figures, and is this assumption documented? [Consistency, Spec §SC-003, Assumption §3, Gap] - not documented
+
+- [X] CHK021 - Does the spec's description of citation display (FR-009) align with the `sources` format change documented in contracts/api.md — are the fields the spec says must be "distinct" actually represented distinctly in the API response? [Consistency, Spec §FR-009, contracts/api.md §4] - A section with image-source should be displayed in the front. Text source and image-source are distinct
+
+---
+
+## Notes
+
+- Items marked `[Gap]` indicate requirements that appear absent or deferred; resolve before generating tasks
+- Items marked `[Ambiguity]` require a clearer definition in the spec before implementation starts
+- Items marked `[Consistency]` should be cross-checked between spec.md, data-model.md, and contracts/api.md
+- Mark items `[x]` when resolved; add inline notes with the resolution for traceability

specs/002-image-aware-embedding/checklists/requirements.md

@@ -0,0 +1,34 @@
+# Specification Quality Checklist: Enhanced Embedding with Image Parsing and Metadata
+
+**Purpose**: Validate specification completeness and quality before proceeding to planning
+**Created**: 2026-04-03
+**Feature**: [spec.md](../spec.md)
+
+## Content Quality
+
+- [x] No implementation details (languages, frameworks, APIs)
+- [x] Focused on user value and business needs
+- [x] Written for non-technical stakeholders
+- [x] All mandatory sections completed
+
+## Requirement Completeness
+
+- [x] No [NEEDS CLARIFICATION] markers remain
+- [x] Requirements are testable and unambiguous
+- [x] Success criteria are measurable
+- [x] Success criteria are technology-agnostic (no implementation details)
+- [x] All acceptance scenarios are defined
+- [x] Edge cases are identified
+- [x] Scope is clearly bounded
+- [x] Dependencies and assumptions identified
+
+## Feature Readiness
+
+- [x] All functional requirements have clear acceptance criteria
+- [x] User scenarios cover primary flows
+- [x] Feature meets measurable outcomes defined in Success Criteria
+- [x] No implementation details leak into specification
+
+## Notes
+
+- All items pass. Spec is ready for `/speckit.clarify` or `/speckit.plan`.

specs/002-image-aware-embedding/contracts/api.md

@@ -0,0 +1,172 @@
+# API Contracts: Enhanced Embedding with Image Parsing and Metadata
+
+**Branch**: `002-image-aware-embedding` | **Date**: 2026-04-03  
+**Base path**: `/api/v1`  
+**Auth**: HTTP Basic (existing)
+
+---
+
+## New / Changed Endpoints
+
+### 1. Re-embed a book (new)
+
+Triggers a full re-embedding of an already-processed book, replacing all existing chunks and
+figures with the new image-aware pipeline output. Safe to call on books previously embedded
+by feature 001.
+
+```
+POST /api/v1/books/{id}/reembed
+```
+
+**Path parameters**
+
+| Parameter | Type | Description |
+|-----------|------|-------------|
+| `id` | UUID | Book ID |
+
+**Response** `202 Accepted`
+
+```json
+{ "bookId": "uuid", "status": "PROCESSING" }
+```
+
+**Error responses**
+
+| Status | Condition |
+|--------|-----------|
+| 404 | Book not found |
+| 409 | Book already in PROCESSING state |
+
+---
+
+### 2. Get figures for a book (new)
+
+Returns the list of extracted figures for a book, including their type, caption, and image URL.
+Used by the frontend to display a figure gallery or inline figures in chat responses.
+
+```
+GET /api/v1/books/{id}/figures
+```
+
+**Path parameters**
+
+| Parameter | Type | Description |
+|-----------|------|-------------|
+| `id` | UUID | Book ID |
+
+**Response** `200 OK`
+
+```json
+[
+  {
+    "figureId": "youmans-7ed-fig-12-4",
+    "label": "Fig. 12-4",
+    "caption": "Coronal cross-section of the cavernous sinus showing cranial nerve relationships",
+    "figureType": "ANATOMICAL_DIAGRAM",
+    "page": 184,
+    "imageUrl": "/api/v1/figures/550e8400-e29b-41d4-a716-446655440000/youmans-7ed-fig-12-4.png",
+    "sectionId": "youmans-7ed-ch12-s2-3",
+    "sectionTitle": "Cavernous Sinus"
+  }
+]
+```
+
+**Error responses**
+
+| Status | Condition |
+|--------|-----------|
+| 404 | Book not found |
+
+---
+
+### 3. Serve figure image (new)
+
+Serves the extracted figure image file. Mounted as a static resource from the file store.
+
+```
+GET /api/v1/figures/{bookId}/{filename}
+```
+
+**Path parameters**
+
+| Parameter | Type | Description |
+|-----------|------|-------------|
+| `bookId` | UUID | Book ID |
+| `filename` | string | Image filename (e.g. `youmans-7ed-fig-12-4.png`) |
+
+**Response** `200 OK` — binary PNG  
+**Content-Type**: `image/png`
+
+**Error responses**
+
+| Status | Condition |
+|--------|-----------|
+| 404 | Image file not found |
+
+---
+
+### 4. Chat message response — extended source format (changed)
+
+The existing `POST /api/v1/chat/sessions/{id}/messages` endpoint is unchanged in its request
+format. The response `sources` field is extended to include figure references.
+
+**Existing request** (unchanged):
+
+```json
+{ "content": "Describe the anatomy of the cavernous sinus" }
+```
+
+**Response** `200 OK` — extended `sources`:
+
+```json
+{
+  "id": "uuid",
+  "role": "ASSISTANT",
+  "content": "The cavernous sinus is ... [Fig. 12-4, p.184] ...",
+  "sources": [
+    {
+      "type": "TEXT",
+      "bookTitle": "Youmans and Winn Neurological Surgery, 7th Ed.",
+      "page": 184,
+      "chunkText": "The cavernous sinus contains ..."
+    },
+    {
+      "type": "FIGURE",
+      "bookTitle": "Youmans and Winn Neurological Surgery, 7th Ed.",
+      "page": 184,
+      "figureId": "youmans-7ed-fig-12-4",
+      "label": "Fig. 12-4",
+      "caption": "Coronal cross-section of the cavernous sinus ...",
+      "figureType": "ANATOMICAL_DIAGRAM",
+      "imageUrl": "/api/v1/figures/550e8400-e29b-41d4-a716-446655440000/youmans-7ed-fig-12-4.png"
+    }
+  ],
+  "createdAt": "2026-04-03T12:00:00Z"
+}
+```
+
+**Changed fields in `sources` array**:
+
+| Field | Old | New |
+|-------|-----|-----|
+| `type` | absent | `"TEXT"` or `"FIGURE"` |
+| `figureId` | absent | figure ID string (FIGURE type only) |
+| `label` | absent | caption label (FIGURE type only) |
+| `caption` | absent | full caption (FIGURE type only) |
+| `figureType` | absent | enum name (FIGURE type only) |
+| `imageUrl` | absent | image URL (FIGURE type only) |
+
+---
+
+## Unchanged Endpoints
+
+All endpoints from feature 001 remain at their existing paths with no breaking changes:
+
+- `POST /api/v1/books/upload`
+- `GET /api/v1/books`
+- `DELETE /api/v1/books/{id}`
+- `GET /api/v1/topics`
+- `GET /api/v1/topics/{id}/summary`
+- `POST /api/v1/chat/sessions`
+- `GET /api/v1/chat/sessions/{id}/messages`
+- `DELETE /api/v1/chat/sessions/{id}`

specs/002-image-aware-embedding/data-model.md

@@ -0,0 +1,305 @@
+# Data Model: Enhanced Embedding with Image Parsing and Metadata
+
+**Branch**: `002-image-aware-embedding` | **Date**: 2026-04-03
+
+---
+
+## Overview
+
+Three storage tiers work in concert:
+
+```
+┌──────────────────────────────────────────────────────────────────┐
+│  PDF Upload                                                       │
+│     │                                                             │
+│     ▼                                                             │
+│  Parsing Pipeline                                                 │
+│     │                          │                                  │
+│     ▼                          ▼                                  │
+│  Postgres (source of truth)   pgvector (search index)            │
+│  - book                       - vector_store (text chunks)        │
+│  - chapter                    - vector_store (figure captions)    │
+│  - section (+ fullText)       File Store (images)                 │
+│  - figure (metadata)          - /uploads/figures/{bookId}/*.png  │
+│  - chunk_figure_refs                                              │
+└──────────────────────────────────────────────────────────────────┘
+```
+
+---
+
+## Postgres Schema
+
+### Existing tables (unchanged)
+
+- `book` — status, metadata, page count (V1)
+- `chat_session`, `message` — conversation (V1)
+- `vector_store` — managed by Spring AI pgvector starter (V2)
+- `topic` — predefined topics (V3)
+
+### New tables (Flyway V4)
+
+```sql
+-- V4: Document hierarchy
+
+CREATE TABLE chapter (
+    id           VARCHAR(200) PRIMARY KEY,  -- "{bookId}-ch{N}"
+    book_id      UUID NOT NULL REFERENCES book(id) ON DELETE CASCADE,
+    number       INT NOT NULL,
+    title        VARCHAR(500),
+    page_start   INT,
+    created_at   TIMESTAMPTZ NOT NULL DEFAULT now()
+);
+
+CREATE TABLE section (
+    id           VARCHAR(200) PRIMARY KEY,  -- "{bookId}-ch{N}-s{X}-{Y}"
+    chapter_id   VARCHAR(200) NOT NULL REFERENCES chapter(id) ON DELETE CASCADE,
+    book_id      UUID NOT NULL REFERENCES book(id) ON DELETE CASCADE,
+    number       VARCHAR(50),               -- "2.3" or "12.2.3"
+    title        VARCHAR(500),
+    page_start   INT NOT NULL,
+    page_end     INT NOT NULL,
+    full_text    TEXT NOT NULL,             -- NOT in vector store
+    created_at   TIMESTAMPTZ NOT NULL DEFAULT now()
+);
+
+CREATE INDEX idx_section_book    ON section(book_id);
+CREATE INDEX idx_section_chapter ON section(chapter_id);
+```
+
+### New tables (Flyway V5)
+
+```sql
+-- V5: Figures and chunk→figure links
+
+CREATE TABLE figure (
+    id                    VARCHAR(200) PRIMARY KEY, -- "{bookId}-fig-{label}"
+    book_id               UUID NOT NULL REFERENCES book(id) ON DELETE CASCADE,
+    section_id            VARCHAR(200) REFERENCES section(id) ON DELETE SET NULL,
+    chapter_id            VARCHAR(200) REFERENCES chapter(id) ON DELETE SET NULL,
+    label                 VARCHAR(100),             -- "Fig. 12-4"
+    caption               TEXT,
+    figure_type           VARCHAR(50) NOT NULL,     -- FigureType enum name
+    page                  INT NOT NULL,
+    image_path            VARCHAR(1000) NOT NULL,   -- relative path on disk
+    caption_embedding_id  UUID,                     -- ID in vector_store
+    created_at            TIMESTAMPTZ NOT NULL DEFAULT now()
+);
+
+CREATE TABLE chunk_figure_ref (
+    chunk_id      UUID NOT NULL,         -- vector_store document ID
+    figure_id     VARCHAR(200) NOT NULL REFERENCES figure(id) ON DELETE CASCADE,
+    mention_page  INT,
+    PRIMARY KEY (chunk_id, figure_id)
+);
+
+CREATE INDEX idx_figure_book    ON figure(book_id);
+CREATE INDEX idx_cfr_chunk      ON chunk_figure_ref(chunk_id);
+```
+
+---
+
+## Java Domain Records
+
+### Document hierarchy (new package `com.aiteacher.document`)
+
+```java
+// Root — in-memory only, not a JPA entity
+public record BookNode(
+    String bookId,
+    String title,
+    String isbn,
+    String edition,
+    List<String> authors,
+    List<ChapterNode> chapters
+) {}
+
+// Chapter — maps to `chapter` table
+public record ChapterNode(
+    String chapterId,
+    String bookId,
+    int number,
+    String title,
+    int pageStart,
+    List<SectionNode> sections
+) {}
+
+// Section — maps to `section` table; fullText stays in Postgres
+public record SectionNode(
+    String sectionId,
+    String chapterId,
+    String bookId,
+    String number,
+    String title,
+    int pageStart,
+    int pageEnd,
+    String fullText,
+    List<TextChunkNode> chunks,
+    List<FigureNode> figures
+) {}
+
+// Text chunk — embedded into vector_store; references its parent section
+public record TextChunkNode(
+    String chunkId,          // UUID → becomes vector_store document ID
+    String sectionId,
+    String chapterId,
+    String bookId,
+    String text,
+    int chunkIndex,
+    int totalChunksInSection,
+    int pageStart,
+    int pageEnd,
+    Map<String, Object> metadata   // flattened for Spring AI filtering
+) {
+    public Map<String, Object> toMetadata() {
+        return Map.of(
+            "type",          "TEXT",
+            "book_id",       bookId,
+            "chapter_id",    chapterId,
+            "section_id",    sectionId,
+            "section_title", /* from parent SectionNode */,
+            "page_start",    pageStart,
+            "page_end",      pageEnd,
+            "chunk_index",   chunkIndex,
+            "total_chunks",  totalChunksInSection
+        );
+    }
+}
+
+// Figure — maps to `figure` table; caption embedded into vector_store
+public record FigureNode(
+    String figureId,
+    String sectionId,
+    String chapterId,
+    String bookId,
+    String label,            // "Fig. 12-4"
+    String caption,
+    FigureType type,
+    int page,
+    String imagePath,        // relative: "figures/{bookId}/{figureId}.png"
+    UUID captionEmbeddingId  // ID in vector_store
+) {}
+```
+
+### Figure type enum
+
+```java
+public enum FigureType {
+    ANATOMICAL_DIAGRAM,
+    SURGICAL_PHOTOGRAPH,
+    MRI_CT_SCAN,
+    TABLE,
+    CHART,
+    INTRAOPERATIVE_IMAGE
+}
+```
+
+Classification heuristic (applied to caption + surrounding text):
+
+| Keyword(s) | FigureType |
+|-----------|-----------|
+| `MRI`, `CT`, `magnetic`, `resonance`, `tomography` | `MRI_CT_SCAN` |
+| `intraoperative`, `intra-op` | `INTRAOPERATIVE_IMAGE` |
+| `table`, `Table` (at line start) | `TABLE` |
+| `chart`, `graph`, `histogram` | `CHART` |
+| `photograph`, `photo` | `SURGICAL_PHOTOGRAPH` |
+| (default) | `ANATOMICAL_DIAGRAM` |
+
+### Chunk–figure join record
+
+```java
+// Maps to `chunk_figure_ref` table
+public record ChunkFigureRef(
+    UUID chunkId,
+    String figureId,
+    int mentionPage
+) {}
+```
+
+---
+
+## Vector Store Documents
+
+All documents in `vector_store` carry a `metadata` JSON column with a `type` field for filtering.
+
+### Text chunk document
+
+| Field | Value |
+|-------|-------|
+| `content` | chunk text (400–600 tokens) |
+| `metadata.type` | `"TEXT"` |
+| `metadata.book_id` | book UUID |
+| `metadata.book_title` | book title string |
+| `metadata.chapter_id` | chapter ID string |
+| `metadata.section_id` | section ID string |
+| `metadata.section_title` | section title string |
+| `metadata.page_start` | int |
+| `metadata.page_end` | int |
+| `metadata.chunk_index` | int (0-based) |
+| `metadata.total_chunks` | int |
+
+### Figure caption document
+
+| Field | Value |
+|-------|-------|
+| `content` | vision-generated description + caption text |
+| `metadata.type` | `"FIGURE"` |
+| `metadata.book_id` | book UUID |
+| `metadata.book_title` | book title string |
+| `metadata.chapter_id` | chapter ID string |
+| `metadata.section_id` | section ID string |
+| `metadata.figure_id` | figure ID string |
+| `metadata.figure_type` | enum name string |
+| `metadata.image_path` | relative file path |
+| `metadata.label` | caption label e.g. `"Fig. 12-4"` |
+| `metadata.page` | int |
+
+---
+
+## File Store Layout
+
+```
+uploads/
+└── figures/
+    └── {bookId}/
+        ├── {figureId}.png
+        └── ...
+```
+
+- Base path configurable via `app.figure-storage.base-path` (default: `./uploads`)
+- Files are served via `GET /api/v1/figures/{bookId}/{filename}` (static resource mapping)
+- Gitignored; not version-controlled
+
+---
+
+## State Transitions
+
+Book processing extends the existing `BookStatus` state machine:
+
+```
+PENDING → PROCESSING → READY
+                    ↘ FAILED
+```
+
+During `PROCESSING`:
+1. Parse PDF structure → extract chapters/sections → persist to Postgres
+2. Split sections into text chunks → embed → write to vector_store
+3. Extract images per page → filter by min size → save PNG → generate vision description → embed caption → write figure to Postgres + vector_store
+4. Write chunk_figure_refs for all detected figure references in text
+
+Failure at step 3 (individual page) → log + skip that page's images; continue.  
+Failure at any other step → set `BookStatus.FAILED`.
+
+---
+
+## Retrieval Result Structure
+
+```java
+public record RetrievalResult(
+    List<SectionNode> parentSections,    // expanded full-text context
+    List<Document> figureVectorHits,     // semantic figure matches
+    List<FigureNode> linkedFigures       // figures explicitly referenced in text chunks
+) {}
+```
+
+The `NeurosurgeryRetriever` service deduplicates figures across both lists before passing
+the result to the LLM prompt builder.

specs/002-image-aware-embedding/plan.md

@@ -0,0 +1,105 @@
+# Implementation Plan: Enhanced Embedding with Image Parsing and Metadata
+
+**Branch**: `002-image-aware-embedding` | **Date**: 2026-04-03 | **Spec**: [spec.md](spec.md)  
+**Input**: Feature specification from `/specs/002-image-aware-embedding/spec.md`
+
+## Summary
+
+Enhance the book embedding pipeline to extract images from every PDF page, generate descriptive
+text for each image, and store all content (text chunks + figure captions) with rich, consistent
+metadata in the vector store. A new document hierarchy (Book → Chapter → Section → TextChunk +
+Figure) is introduced. Postgres holds the full-text sections and figure metadata; the vector
+store holds chunk and figure caption embeddings; the local file store holds extracted image files.
+At query time, both the text-chunk store and figure-caption store are searched in parallel and
+results are merged before being sent to the LLM.
+
+## Technical Context
+
+**Language/Version**: Java 25 (backend), TypeScript / Node 20 (frontend)  
+**Primary Dependencies**: Spring Boot 4.0.5, Spring AI 2.0.0-M4, OpenAI API (embeddings + chat), PDFBox (via Spring AI PDF reader dependency)  
+**Storage**: PostgreSQL (JPA + Flyway), pgvector (Spring AI `VectorStore`), local file system (extracted images — `/uploads/figures/`)  
+**Testing**: Spring Boot Test, JUnit 5, Mockito  
+**Target Platform**: Linux server (Docker Compose)  
+**Project Type**: Web application — backend REST API + Vue 3 frontend  
+**Performance Goals**: Full book (up to 500 pages with images) processed in ≤ 30 minutes; query response unchanged from existing baseline  
+**Constraints**: No new deployable units; all changes within the existing `backend/` module; image storage on local disk (S3 migration is a future concern, behind an interface)  
+**Scale/Scope**: POC — <10 concurrent users; single shared book library
+
+## Constitution Check
+
+*GATE: Must pass before Phase 0 research. Re-check after Phase 1 design.*
+
+| Principle | Status | Notes |
+|-----------|--------|-------|
+| I — KISS | ⚠️ Justified violation — see Complexity Tracking | Hierarchical model + dual search adds complexity; justified by precision requirement |
+| II — Easy to Change | ✅ | Figure storage wrapped behind `FigureStorageService` interface; can swap local disk for S3 |
+| III — Web-First | ✅ | All new capabilities exposed via existing REST API; no new deployable units |
+| IV — Docs as Architecture | ⚠️ Required | README Mermaid diagram MUST be updated in this PR to show new storage tiers |
+
+## Project Structure
+
+### Documentation (this feature)
+
+```text
+specs/002-image-aware-embedding/
+├── plan.md              # This file
+├── research.md          # Phase 0 output
+├── data-model.md        # Phase 1 output
+├── quickstart.md        # Phase 1 output
+├── contracts/           # Phase 1 output
+└── tasks.md             # Phase 2 output (/speckit.tasks)
+```
+
+### Source Code (repository root)
+
+```text
+backend/
+├── src/main/java/com/aiteacher/
+│   ├── book/
+│   │   ├── Book.java                         (existing)
+│   │   ├── BookController.java               (existing)
+│   │   ├── BookService.java                  (existing)
+│   │   ├── BookRepository.java               (existing)
+│   │   ├── BookStatus.java                   (existing)
+│   │   ├── BookEmbeddingService.java         (existing — enhanced)
+│   │   └── NoKnowledgeSourceException.java   (existing)
+│   ├── document/                             (new package)
+│   │   ├── BookNode.java
+│   │   ├── ChapterNode.java
+│   │   ├── SectionNode.java
+│   │   ├── SectionRepository.java
+│   │   ├── TextChunkNode.java
+│   │   ├── FigureNode.java
+│   │   ├── FigureRepository.java
+│   │   ├── FigureType.java
+│   │   ├── ChunkFigureRef.java
+│   │   └── ChunkFigureRefRepository.java
+│   ├── figure/                               (new package)
+│   │   ├── FigureStorageService.java         (interface)
+│   │   └── LocalFigureStorageService.java    (implementation)
+│   ├── retrieval/                            (new package)
+│   │   └── NeurosurgeryRetriever.java
+│   ├── chat/
+│   │   └── ChatService.java                  (updated — uses NeurosurgeryRetriever)
+│   └── config/
+│       └── FigureStorageConfig.java          (new — configures upload dir)
+└── src/main/resources/
+    └── db/migration/
+        ├── V4__document_hierarchy.sql        (new)
+        └── V5__figures_and_refs.sql          (new)
+
+uploads/
+└── figures/                                  (runtime — extracted images; gitignored)
+```
+
+**Structure Decision**: Option 2 (Web Application) confirmed. All backend changes stay within
+`backend/`. Two new packages (`document/`, `retrieval/`) plus one interface package (`figure/`)
+keep concerns separated without adding a deployable unit.
+
+## Complexity Tracking
+
+| Violation | Why Needed | Simpler Alternative Rejected Because |
+|-----------|------------|-------------------------------------|
+| Document hierarchy (BookNode → ChapterNode → SectionNode) | Parent-child retrieval: chunks reference their parent section so the LLM receives full section context, not just the matching fragment. This is the established solution for RAG precision. | Flat page-per-doc model (current) loses inter-sentence context; chunk-only retrieval produces incomplete answers for multi-paragraph clinical questions |
+| Dual vector search (text chunks + figure captions) | Figure captions must be independently searchable — a query about "cavernous sinus anatomy" must surface the diagram even if no text chunk scores highly | Single vector store search would miss figures whose captions don't happen to be the highest-similarity hit; this is the core deliverable of the feature |
+| Third storage tier (local file store for images) | Extracted images cannot live in Postgres (binary blobs degrade query performance) or the vector store (only vectors). A file-per-image approach is standard. | Storing images as base64 in Postgres JSONB would bloat the DB and complicate backup/restore; the `FigureStorageService` interface keeps the implementation swappable |

specs/002-image-aware-embedding/quickstart.md

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+# Quickstart: Enhanced Embedding with Image Parsing and Metadata
+
+**Branch**: `002-image-aware-embedding` | **Date**: 2026-04-03
+
+---
+
+## Prerequisites
+
+- Docker Compose running (PostgreSQL + pgvector)
+- OpenAI API key set in `backend/src/main/resources/application.properties` or as env var `OPENAI_API_KEY`
+- Java 25 + Maven on PATH
+
+---
+
+## New Configuration
+
+Add to `backend/src/main/resources/application.properties`:
+
+```properties
+# Figure storage
+app.figure-storage.base-path=./uploads
+app.figure-storage.min-image-size-px=100
+```
+
+The `uploads/figures/` directory is created automatically on first use. Add it to `.gitignore`.
+
+---
+
+## Database Migration
+
+Two new Flyway migrations run automatically on startup:
+
+- `V4__document_hierarchy.sql` — adds `chapter` and `section` tables
+- `V5__figures_and_refs.sql` — adds `figure` and `chunk_figure_ref` tables
+
+No manual DB setup needed.
+
+---
+
+## Re-embedding Existing Books
+
+Books embedded by feature 001 (text-only) remain functional for text queries. To add image
+support, trigger a re-embed:
+
+```bash
+curl -X POST http://localhost:8080/api/v1/books/{bookId}/reembed \
+  -u admin:password
+```
+
+The book transitions to `PROCESSING`, old chunks and figures are deleted, and the new
+image-aware pipeline runs. Status can be polled via `GET /api/v1/books`.
+
+---
+
+## Verifying Image Extraction
+
+1. Upload a PDF with diagrams: `POST /api/v1/books/upload`
+2. Wait for `status: "READY"` via `GET /api/v1/books`
+3. List figures: `GET /api/v1/books/{id}/figures` — should return at least one entry per image page
+4. Ask a diagram-specific question in chat — response `sources` should include a `type: "FIGURE"` entry
+
+---
+
+## Frontend: Rendering Inline Figures
+
+The assistant message `content` field will contain figure references in the format
+`[Fig. 12-4, p.184]`. The frontend should:
+
+1. Parse `[Fig. X, p.N]` patterns in assistant message text
+2. Look up the matching entry in `sources` where `type === "FIGURE"`
+3. Render the figure inline using the `imageUrl` field
+
+---
+
+## Running Tests
+
+```bash
+cd backend
+mvn test
+```
+
+Key new test classes:
+- `FigureExtractionServiceTest` — unit tests for image extraction and classification
+- `NeurosurgeryRetrieverTest` — unit tests for dual-search merge and deduplication
+- `BookEmbeddingServiceIntegrationTest` — integration test: upload PDF with known figures,
+  verify figures appear in `GET /api/v1/books/{id}/figures`

specs/002-image-aware-embedding/research.md

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+# Research: Enhanced Embedding with Image Parsing and Metadata
+
+**Branch**: `002-image-aware-embedding` | **Date**: 2026-04-03
+
+This document resolves all technical unknowns identified during planning. The primary source for
+decisions is the detailed architecture provided directly by the project owner, supplemented by
+Spring AI 2.0.0-M4 API specifics.
+
+---
+
+## Decision 1: Document Hierarchy Model
+
+**Decision**: Adopt a four-level hierarchy — `BookNode` → `ChapterNode` → `SectionNode` →
+`TextChunkNode` + `FigureNode`. The `SectionNode` is the pivotal unit: it holds the full section
+text in Postgres and is used for parent-child context expansion at retrieval time.
+
+**Rationale**: A flat page-per-document model (current implementation) loses structural context.
+When a user asks a multi-faceted clinical question, the LLM needs the surrounding section text,
+not just the matching fragment. Parent-child retrieval — where chunks point to their parent
+section — is the established pattern for RAG precision. The hierarchy also makes figure-to-section
+association explicit and queryable.
+
+**Alternatives considered**:
+- Keep flat page model, add metadata only → rejected: insufficient for precise citation and
+  context expansion
+- Chapter-level retrieval (coarser than section) → rejected: too much irrelevant context sent
+  to LLM; cost and latency increase
+
+---
+
+## Decision 2: Image Extraction Strategy
+
+**Decision**: Use PDFBox (already on classpath via `spring-ai-pdf-document-reader`) to extract
+images per page. Each image is tagged with `page`, `figure_id` (derived from caption, e.g.
+"Fig. 12-4"), and the parent `sectionId`. Images are saved to local disk under
+`/uploads/figures/{bookId}/`.
+
+**Rationale**: PDFBox is already present (Spring AI bundles it). No new dependency needed.
+Per-page extraction ensures every image is captured regardless of PDF structure.
+
+**Alternatives considered**:
+- iText / iText7 → additional commercial dependency; overkill for extraction
+- Screenshot each page as PNG, then OCR → far slower; loses vector quality
+
+---
+
+## Decision 3: Figure Content Representation
+
+**Decision**: Generate a textual description of each extracted image using the OpenAI vision
+model (GPT-4o). This description becomes the `content` field of the figure's vector store
+document. The figure caption (parsed from the surrounding text) is also included to maximise
+retrieval signal.
+
+**Rationale**: Caption-only embedding would miss figures with no caption or with sparse labels.
+Vision-generated descriptions produce richer semantic content (anatomy terms, structural
+relationships) that matches clinical queries. The OpenAI client already in use supports image
+inputs; no additional dependency is required.
+
+**Alternatives considered**:
+- Caption-only embedding → insufficient when captions are absent or terse (common in textbooks)
+- Local vision model (LLaVA) → requires self-hosting; out of scope for POC
+- OCR only → extracts text visible in image but misses non-text visual content (diagrams, MRI)
+
+---
+
+## Decision 4: Dual Vector Search
+
+**Decision**: At query time, run two parallel similarity searches:
+1. Text chunk search (filtered by `type = "TEXT"` and `book_id`)
+2. Figure caption search (filtered by `type = "FIGURE"` and `book_id`)
+
+Results are merged and deduplicated. The LLM prompt receives the expanded parent section text
+plus a structured figure reference list.
+
+**Rationale**: A single search would rank text and figures against each other; figures with
+terse captions would systematically lose to text chunks. Separate searches with independent
+`topK` allow tuning each modality independently.
+
+**Alternatives considered**:
+- Single search, filter by relevance score → figure captions score lower than text; figures
+  are systematically under-retrieved
+- Post-process text results to look up linked figures only → misses figures that are relevant
+  to the query but not explicitly referenced in the retrieved text chunks
+
+---
+
+## Decision 5: Chunk-to-Figure Linking
+
+**Decision**: During text parsing, whenever a pattern matching `Fig.\s+\d+[\-\.]\d+` or
+`Figure\s+\d+[\-\.]\d+` is found in a chunk, insert a row into the `chunk_figure_refs` table
+linking `chunkId` → `figureId`. At retrieval time, after text chunks are retrieved, their
+associated figures are fetched from this table and added to the LLM prompt.
+
+**Rationale**: Explicit linking ensures that when a text chunk is retrieved, its referenced
+figures are always surfaced — even if the figure's caption did not score highly in the vector
+search. This is the higher-recall path; dual search (Decision 4) is the higher-precision path.
+
+**Alternatives considered**:
+- Rely entirely on dual vector search → may miss figures referenced in retrieved text but
+  scoring below the topK threshold in the figure search
+
+---
+
+## Decision 6: Image Storage
+
+**Decision**: Extracted images are saved as PNG files to a local directory
+(`${app.figure-storage.base-path}`, defaults to `./uploads/figures/{bookId}/`). The path is
+stored in `figure.image_path` in Postgres. A `FigureStorageService` interface wraps all disk
+I/O so the implementation can be swapped to S3 or another object store without changing
+callers.
+
+**Rationale**: Local disk is the simplest viable option for a POC with <10 users. The interface
+boundary satisfies Constitution Principle II (Easy to Change).
+
+**Alternatives considered**:
+- S3 from day 1 → operational overhead not justified at POC scale
+- Base64 in Postgres JSONB → bloats DB; complicates backup; query performance degrades
+
+---
+
+## Decision 7: Figure Type Classification
+
+**Decision**: Use the enum `FigureType { ANATOMICAL_DIAGRAM, SURGICAL_PHOTOGRAPH, MRI_CT_SCAN,
+TABLE, CHART, INTRAOPERATIVE_IMAGE }`. Classification is derived from:
+1. Caption keywords ("MRI", "CT", "Fig.", "Table") — heuristic, no model needed
+2. Fall back to `ANATOMICAL_DIAGRAM` if unclassifiable
+
+**Rationale**: Allows the frontend to render different icon/label per type (e.g., "MRI" badge).
+Heuristic classification avoids a separate model call per image at extraction time.
+
+**Alternatives considered**:
+- Vision model classification → accurate but adds latency and cost per figure; deferrable
+- Single `FIGURE` type → loses citation granularity required by spec FR-004
+
+---
+
+## Decision 8: Metadata Schema for Vector Store Documents
+
+**Decision**: All vector store documents carry a flat `Map<String, Object>` metadata for Spring
+AI filtering. Schema:
+
+| Field | Text Chunk | Figure Chunk |
+|-------|-----------|-------------|
+| `type` | `"TEXT"` | `"FIGURE"` |
+| `book_id` | ✓ | ✓ |
+| `book_title` | ✓ | ✓ |
+| `chapter_id` | ✓ | ✓ |
+| `section_id` | ✓ | ✓ |
+| `section_title` | ✓ | ✓ |
+| `page_start` | ✓ | — |
+| `page_end` | ✓ | — |
+| `chunk_index` | ✓ | — |
+| `total_chunks` | ✓ | — |
+| `figure_id` | — | ✓ |
+| `figure_type` | — | ✓ |
+| `image_path` | — | ✓ |
+| `label` | — | ✓ |
+| `page` | — | ✓ |
+
+**Rationale**: Flat map is required by Spring AI `FilterExpressionBuilder`. Separation by `type`
+allows independent filtering in dual search.
+
+---
+
+## Decision 9: Re-embedding Existing Books
+
+**Decision**: Books already processed under feature 001 (text-only) are NOT automatically
+re-embedded. An explicit re-embed action is exposed via `POST /api/v1/books/{id}/reembed`
+(admin-triggered). The existing chunks remain valid for text queries until re-embedding completes.
+
+**Rationale**: Automatic re-embedding on deploy would block the system and risk data loss if
+the process fails mid-way. An explicit, idempotent trigger is safer and more observable.
+
+---
+
+## Decision 10: Minimum Image Size Threshold
+
+**Decision**: Images smaller than 100×100 pixels are discarded and no chunk is created. This
+threshold filters out decorative elements (bullets, dividers, publisher logos) without a
+classification model.
+
+**Rationale**: Neurosurgery textbook diagrams and MRI scans are never smaller than 100×100 px.
+The threshold is configurable via `app.figure-storage.min-image-size-px` in
+`application.properties`.
+
+**Alternatives considered**:
+- No threshold → decorative icons pollute the figure index
+- ML-based classification → accurate but adds model dependency; not needed at POC scale

specs/002-image-aware-embedding/spec.md

@@ -0,0 +1,176 @@
+# Feature Specification: Enhanced Embedding with Image Parsing and Metadata
+
+**Feature Branch**: `002-image-aware-embedding`  
+**Created**: 2026-04-03  
+**Status**: Draft  
+**Input**: User description: "I want to enhance the embedding process. I want also parse image from each pages if any and add proper metadata so that it can match the retrieved chunk/vector that match what user are querying."
+
+## User Scenarios & Testing *(mandatory)*
+
+### User Story 1 - Image Content Surfaced in Query Results (Priority: P1)
+
+A neurosurgeon asks a question in the chat (e.g., "Show me the anatomy of the Circle of Willis")
+that is best answered by a diagram or figure in an uploaded book. The system retrieves the image
+content — its description and surrounding context — and uses it to construct a grounded answer,
+citing the page and book where the image appeared.
+
+**Why this priority**: This is the direct, user-visible payoff of the feature. Without it, the
+enhancement has no observable benefit. All other stories support this outcome.
+
+**Independent Test**: Upload a book containing a labelled anatomical diagram. Ask a query whose
+answer is conveyed by that diagram (not in the surrounding text). Confirm the system returns an
+answer that references the diagram's content and cites the correct book and page.
+
+**Acceptance Scenarios**:
+
+1. **Given** a book with an anatomical diagram on page 42, **When** a user asks a question whose
+   answer is only depicted in that diagram, **Then** the system returns a response that draws on
+   the diagram's content and cites "Page 42, [Book Title]".
+2. **Given** a page with both text and an image, **When** the system retrieves that page's content,
+   **Then** the image-derived content and the surrounding text are each independently retrievable
+   and independently citable.
+3. **Given** a query that has no relevant image in any uploaded book, **When** the system searches,
+   **Then** it does not fabricate image-derived content and falls back to text-only results (or
+   states no relevant content was found).
+
+---
+
+### User Story 2 - All Pages Scanned for Images During Embedding (Priority: P1)
+
+When a book is uploaded and processed, every page is inspected for images. Any image found is
+extracted and represented as a searchable content chunk enriched with metadata (page number,
+book title, position on page, caption if present). Pages without images are processed as
+text-only chunks, unchanged from the existing behaviour.
+
+**Why this priority**: This is the prerequisite for User Story 1. Without systematic per-page
+image detection, image content cannot be retrieved.
+
+**Independent Test**: Upload a book whose pages include a mix of text-only and image-containing
+pages. After processing completes, verify that chunks exist for each image page and that each
+image chunk carries the correct metadata (page number, source book, caption).
+
+**Acceptance Scenarios**:
+
+1. **Given** a book being processed, **When** the embedding pipeline runs, **Then** every page
+   is evaluated for images and each detected image generates at least one content chunk.
+2. **Given** an image with a caption or label, **When** the chunk is created, **Then** the
+   caption or label text is included in the chunk's content and metadata.
+3. **Given** a page with multiple images, **When** processing completes, **Then** each image is
+   represented as a separate chunk with its own metadata, not merged into a single chunk.
+4. **Given** a page with no images, **When** processing completes, **Then** no image chunk is
+   created for that page and text processing is unaffected.
+
+---
+
+### User Story 3 - Rich Metadata Enables Precise Source Attribution (Priority: P2)
+
+When the system returns a result based on image content, the user can see exactly where that
+image appeared: which book, which page, and what type of content (diagram, table, photograph,
+etc.). This gives the user confidence in the source and lets them locate the original image
+in their physical or digital copy of the book.
+
+**Why this priority**: Metadata quality directly impacts user trust. Neurosurgeons require
+traceable, citable evidence. Richer metadata also improves retrieval accuracy by giving the
+search engine more signals to match against a query.
+
+**Independent Test**: Retrieve a result sourced from an image chunk. Inspect the displayed
+citation and verify it includes: book title, page number, content type (e.g., "diagram"),
+and caption (if present in the original).
+
+**Acceptance Scenarios**:
+
+1. **Given** a retrieved image chunk, **When** the system displays the source citation,
+   **Then** the citation includes at minimum: book title, page number, and a content-type
+   label (e.g., diagram, table, figure).
+2. **Given** an image chunk with a detected caption, **When** the citation is displayed,
+   **Then** the caption text is shown alongside the other metadata fields.
+3. **Given** a topic summary that draws on both text and image chunks, **When** the user
+   inspects citations, **Then** image-sourced and text-sourced claims are distinguishable
+   from each other.
+
+---
+
+### Edge Cases
+
+- What happens when an image is too small to contain meaningful content (e.g., a decorative
+  bullet icon or a publisher logo)?
+- How does the system handle a page that is entirely an image (scanned page with no digital text)?
+- What if an image spans multiple pages (e.g., a fold-out diagram)?
+- How does the system behave when an image has no caption and its surrounding text provides
+  no useful context?
+- What happens if image processing fails for a specific page — does it abort the whole book
+  or continue with the remaining pages?
+
+## Requirements *(mandatory)*
+
+### Functional Requirements
+
+- **FR-001**: System MUST inspect every page of an uploaded book for the presence of images
+  during the embedding process.
+- **FR-002**: System MUST extract each detected image and create a dedicated, independently
+  searchable content chunk for it.
+- **FR-003**: System MUST generate a descriptive textual representation of each extracted
+  image so its content is semantically searchable by the retrieval system.
+- **FR-004**: System MUST associate the following metadata with every image chunk: book title,
+  page number, content type (e.g., diagram, table, figure, photograph), and caption text
+  (where present).
+- **FR-005**: System MUST include the same base metadata (book title, page number) on text
+  chunks so that all retrieved content — image or text — carries consistent, comparable
+  source attribution.
+- **FR-006**: System MUST treat image chunks as first-class retrievable units: they must be
+  ranked and returned alongside text chunks when they are relevant to a user query.
+- **FR-007**: System MUST skip images that fall below a minimum meaningful-content threshold
+  (e.g., decorative icons, page separators) and MUST NOT create chunks for them.
+- **FR-008**: If image processing fails for a specific page, the system MUST log the failure,
+  skip that page's image, and continue processing the remaining pages and text content of
+  the book.
+- **FR-009**: System MUST display image-sourced content citations distinctly from text-sourced
+  citations so users can identify when a result originates from a visual element.
+- **FR-010**: Processing a book that contains images MUST NOT degrade the accuracy or
+  completeness of the existing text-only embedding for that book.
+
+### Key Entities
+
+- **Image Chunk**: A searchable content unit derived from a page image. Attributes: generated
+  description, source book title, page number, content type, caption (optional), embedding vector.
+- **Text Chunk**: Existing unit; extended to carry explicit metadata: source book title,
+  page number, section heading (if detectable), content type ("text").
+- **Chunk Metadata**: Structured attributes attached to every chunk regardless of type,
+  enabling consistent filtering and citation. Mandatory fields: book title, page number,
+  content type. Optional fields: caption, section heading.
+
+## Success Criteria *(mandatory)*
+
+### Measurable Outcomes
+
+- **SC-001**: At least 90% of pages containing images in a test book result in a retrievable
+  image chunk after processing completes.
+- **SC-002**: A controlled set of 10 queries whose answers are conveyed by diagrams in an
+  uploaded book returns at least 7 correct image-sourced answers (70% recall on image queries).
+- **SC-003**: Embedding processing time for a book with images increases by no more than 3×
+  compared to processing the same book as text-only, for books up to 500 pages.
+- **SC-004**: Every retrieved result — text or image — includes a citation that identifies
+  at minimum the source book title and page number, with 100% coverage across a test result set.
+- **SC-005**: In a user evaluation with 5 representative queries that previously returned
+  no useful results (because the answer was only in a diagram), at least 4 now return a
+  useful, grounded answer.
+
+## Assumptions
+
+- Books are still uploaded exclusively as PDFs; image parsing applies to PDF pages only.
+- The platform already has a working text-only embedding pipeline (from feature 001); this
+  feature enhances it without replacing or rewriting the text processing logic.
+- Images worth processing are those that occupy a meaningful portion of the page; small
+  decorative or structural images (logos, dividers, icons) are excluded based on a size
+  threshold determined during implementation.
+- The descriptive representation of an image (FR-003) is generated at embedding time, not
+  at query time; query latency is not affected by image interpretation.
+- The shared global book library model from feature 001 is retained; image chunks from a
+  processed book are available to all users immediately upon completion.
+- Scanned pages (fully rasterised pages with no digital text layer) are treated as a single
+  full-page image; the system attempts to extract content from them but does not guarantee
+  the same fidelity as pages with digital text.
+- Per-chunk metadata is stored alongside the vector so it can be used for both retrieval
+  filtering and source citation display without a separate lookup.
+- Books already processed under feature 001 (text-only) are not automatically re-processed;
+  re-embedding must be triggered explicitly by the user or an administrator.

specs/002-image-aware-embedding/tasks.md

@@ -0,0 +1,168 @@
+# Tasks: Enhanced Embedding with Image Parsing and Metadata
+
+**Input**: Design documents from `/specs/002-image-aware-embedding/`
+**Prerequisites**: plan.md ✓ | spec.md ✓ | research.md ✓ | data-model.md ✓ | contracts/ ✓
+
+**Organization**: Tasks grouped by user story to enable independent implementation and testing.
+
+## Format: `[ID] [P?] [Story] Description`
+
+- **[P]**: Can run in parallel (different files, no shared dependencies)
+- **[US1/US2/US3]**: Which user story this task belongs to
+
+---
+
+## Phase 1: Setup (Shared Infrastructure)
+
+**Purpose**: Database migrations and configuration that establish the foundation for all new code
+
+- [X] T001 Create Flyway migration `V4__document_hierarchy.sql` — add `chapter` and `section` tables per data-model.md §Postgres Schema in `backend/src/main/resources/db/migration/V4__document_hierarchy.sql`
+- [X] T002 Create Flyway migration `V5__figures_and_refs.sql` — add `figure` and `chunk_figure_ref` tables per data-model.md §Postgres Schema in `backend/src/main/resources/db/migration/V5__figures_and_refs.sql`
+- [X] T003 Add figure-storage configuration keys to `backend/src/main/resources/application.properties`: `app.figure-storage.base-path=./uploads` and `app.figure-storage.min-image-size-px=100`
+- [X] T004 Add `uploads/` directory to `.gitignore` at repo root; create `uploads/figures/.gitkeep` to preserve directory structure
+
+---
+
+## Phase 2: Foundational (Blocking Prerequisites)
+
+**Purpose**: Core types and infrastructure that ALL user stories depend on — nothing in Phase 3+ can start until this phase is complete
+
+**⚠️ CRITICAL**: No user story work can begin until this phase is complete
+
+- [X] T005 [P] Create `FigureType` enum in `backend/src/main/java/com/aiteacher/document/FigureType.java` — values: `ANATOMICAL_DIAGRAM`, `SURGICAL_PHOTOGRAPH`, `MRI_CT_SCAN`, `TABLE`, `CHART`, `INTRAOPERATIVE_IMAGE`
+- [X] T006 [P] Create `FigureStorageService` interface in `backend/src/main/java/com/aiteacher/figure/FigureStorageService.java` — declare `Path save(UUID bookId, String figureId, BufferedImage image)`, `Path resolve(UUID bookId, String filename)`, and `void delete(UUID bookId)`
+- [X] T007 Create `LocalFigureStorageService` implementation in `backend/src/main/java/com/aiteacher/figure/LocalFigureStorageService.java` — writes PNG files under `${app.figure-storage.base-path}/figures/{bookId}/`; implements `FigureStorageService`; depends on T006
+- [X] T008 Create `FigureStorageConfig` bean in `backend/src/main/java/com/aiteacher/config/FigureStorageConfig.java` — reads `app.figure-storage.base-path` and `app.figure-storage.min-image-size-px` as `@ConfigurationProperties`; registers `LocalFigureStorageService` as `@Bean`; adds `ResourceHandler` mapping `GET /api/v1/figures/**` to the base-path directory
+- [X] T009 [P] Create `ChapterEntity` JPA entity and `ChapterRepository` in `backend/src/main/java/com/aiteacher/document/` — `@Entity(name="chapter")`, fields: `id` (String PK), `bookId` (UUID FK → book), `number` (int), `title` (String), `pageStart` (int), `createdAt` (Instant); `ChapterRepository extends JpaRepository<ChapterEntity, String>`
+- [X] T010 [P] Create `SectionEntity` JPA entity and `SectionRepository` in `backend/src/main/java/com/aiteacher/document/` — `@Entity(name="section")`, fields: `id` (String PK), `chapterId` (String FK → chapter), `bookId` (UUID FK → book), `number` (String), `title` (String), `pageStart`/`pageEnd` (int), `fullText` (TEXT column), `createdAt` (Instant); `SectionRepository extends JpaRepository<SectionEntity, String>` with `findAllByBookId(UUID)`
+- [X] T011 [P] Create `FigureEntity` JPA entity and `FigureRepository` in `backend/src/main/java/com/aiteacher/document/` — `@Entity(name="figure")`, fields: `id` (String PK), `bookId` (UUID), `sectionId` (String, nullable), `chapterId` (String, nullable), `label` (String), `caption` (TEXT), `figureType` (`@Enumerated` FigureType), `page` (int), `imagePath` (String), `captionEmbeddingId` (UUID, nullable), `createdAt` (Instant); `FigureRepository` with `findAllByBookId(UUID)`, `deleteAllByBookId(UUID)`
+- [X] T012 Create `ChunkFigureRefEntity` JPA entity and `ChunkFigureRefRepository` in `backend/src/main/java/com/aiteacher/document/` — composite PK `(chunkId UUID, figureId String)`, `mentionPage` (int); `ChunkFigureRefRepository` with `findByChunkIdIn(List<UUID>)`, `deleteByFigureIdIn(List<String>)`
+
+**Checkpoint**: Migrations will run on next startup; all JPA entities are wired; figure storage reads config correctly
+
+---
+
+## Phase 3: User Story 2 — All Pages Scanned for Images During Embedding (Priority: P1)
+
+**Goal**: When a book is uploaded, every page is inspected for images; each found image is extracted, persisted, described, and embedded as a searchable chunk alongside its metadata
+
+**Independent Test**: Upload a PDF containing at least one page with a labelled anatomical diagram. After status shows `READY`, call `GET /api/v1/books/{id}/figures` — response must contain at least one entry with `figureType`, `caption`, `page`, and `imageUrl` populated. Verify the PNG file exists at the path in `imagePath`.
+
+- [X] T013 [US2] Create `PdfStructureParser` service in `backend/src/main/java/com/aiteacher/document/PdfStructureParser.java` — uses Spring AI's `PagePdfDocumentReader` to extract per-page text; groups pages into `SectionEntity` records using heading-detection heuristics (lines matching `^\d+(\.\d+)*\s+[A-Z]`); groups sections into `ChapterEntity` records; persists both to Postgres via `ChapterRepository` and `SectionRepository`; returns `List<SectionEntity>` for the book
+- [X] T014 [US2] Create `FigureExtractionService` in `backend/src/main/java/com/aiteacher/document/FigureExtractionService.java` — opens PDF with PDFBox `PDDocument`; iterates pages; extracts `PDImageXObject` instances; skips images whose width or height are below `min-image-size-px`; classifies `FigureType` using the keyword-matching table from data-model.md §FigureType; parses caption from the nearest text line matching `CAPTION_PATTERN`; saves PNG via `FigureStorageService`; persists `FigureEntity` to `FigureRepository`; returns `List<FigureEntity>` per book
+- [X] T015 [US2] Create `VisionDescriptionService` in `backend/src/main/java/com/aiteacher/document/VisionDescriptionService.java` — accepts a `Path` to a PNG and a caption String; calls the OpenAI vision model (via Spring AI `ChatClient` with image media type) to generate a 2–4 sentence clinical description; returns the generated description string; handles API failures by returning the caption as fallback
+- [X] T016 [US2] Create `TextChunkingService` in `backend/src/main/java/com/aiteacher/document/TextChunkingService.java` — accepts a `SectionEntity`; splits `fullText` into overlapping 400–600 token windows (20-token overlap); wraps each window in a Spring AI `Document` with the flat metadata map defined in data-model.md §Text chunk document; returns `List<Document>`
+- [X] T017 [US2] Create `ChunkFigureRefService` in `backend/src/main/java/com/aiteacher/document/ChunkFigureRefService.java` — accepts a Spring AI `Document` (with its `id` as `chunkId`) and a `List<FigureEntity>` for the book; scans chunk text for patterns `Fig\.\s*\d+[\-\.]\d+` and `Figure\s+\d+[\-\.]\d+`; matches against figure labels; persists `ChunkFigureRefEntity` rows via `ChunkFigureRefRepository`
+- [X] T018 [US2] Rewrite `BookEmbeddingService.embedBook()` in `backend/src/main/java/com/aiteacher/book/BookEmbeddingService.java` to orchestrate the full pipeline: (1) `PdfStructureParser` → sections; (2) parallel: `FigureExtractionService` + `TextChunkingService` for each section; (3) `VisionDescriptionService` for each figure; (4) embed figure captions+descriptions as `Document`s (metadata per data-model.md §Figure caption document) into `vectorStore`; (5) embed text chunks into `vectorStore`; (6) `ChunkFigureRefService` for each chunk; update `captionEmbeddingId` on `FigureEntity` after embedding
+- [X] T019 [US2] Extend `BookEmbeddingService.deleteBookChunks()` to also delete: all `ChunkFigureRefEntity` rows (via `findByFigureIdIn`), all `FigureEntity` rows (via `deleteAllByBookId`), all figure PNG files (via `FigureStorageService.delete(bookId)`), all `SectionEntity` and `ChapterEntity` rows for the book
+- [X] T020 [US2] Add `POST /api/v1/books/{id}/reembed` endpoint to `BookController` in `backend/src/main/java/com/aiteacher/book/BookController.java` — returns `202` with `{ bookId, status: "PROCESSING" }`; returns `404` if not found; returns `409` if already `PROCESSING`; calls `deleteBookChunks()` then `embedBook()` asynchronously
+
+**Checkpoint**: Upload a PDF with figures → poll `GET /api/v1/books` for `READY` → `GET /api/v1/books/{id}/figures` returns figure list → PNG accessible at `GET /api/v1/figures/{bookId}/{filename}`
+
+---
+
+## Phase 4: User Story 1 — Image Content Surfaced in Query Results (Priority: P1)
+
+**Goal**: User asks a question answered by a diagram — the system retrieves that diagram's content and surfaces it in the chat response with a citation
+
+**Independent Test**: With a book embedded (Phase 3 checkpoint passed), ask a chat question whose answer is depicted only in a diagram. The response `sources` array must contain at least one entry with `type: "FIGURE"` and a non-empty `imageUrl`.
+
+- [X] T021 [US1] Create `NeurosurgeryRetriever` service in `backend/src/main/java/com/aiteacher/retrieval/NeurosurgeryRetriever.java` — (1) text chunk search: `vectorStore.similaritySearch` with filter `type == TEXT AND book_id == bookId`, topK=5; (2) figure search: same store, filter `type == FIGURE AND book_id == bookId`, topK=3; (3) expand text chunk results to parent sections via `SectionRepository.findAllById(sectionIds)`; (4) fetch explicitly linked figures via `ChunkFigureRefRepository.findByChunkIdIn(chunkIds)` + `FigureRepository.findAllById`; (5) deduplicate figures across lists by `figureId`; return `RetrievalResult(parentSections, figureVectorHits, linkedFigures)` — add `RetrievalResult` record in same package
+- [X] T022 [US1] Refactor `ChatService.sendMessage()` in `backend/src/main/java/com/aiteacher/chat/ChatService.java` — replace `QuestionAnswerAdvisor` with a manual call to `NeurosurgeryRetriever`; build the LLM user message from: section full texts as `[Section X.Y — Title, pp.A-B]\n{fullText}` blocks, followed by `AVAILABLE FIGURES FOR THIS SECTION:` list with `- {label} (p.{page}): {caption} [image: {filename}]` lines per figure; append the instruction `When referencing diagrams, cite them as [Fig. X, p.N].`; send via `chatClient.prompt().system(SYSTEM_PROMPT).user(prompt).call()`
+- [X] T023 [US1] Add `GET /api/v1/books/{id}/figures` endpoint to `BookController` — returns `200` with `List<FigureResponse>`; `FigureResponse` is a new record in `backend/src/main/java/com/aiteacher/book/FigureResponse.java` with fields `figureId`, `label`, `caption`, `figureType`, `page`, `imageUrl` (assembled as `/api/v1/figures/{bookId}/{filename}`), `sectionId`, `sectionTitle`; returns `404` if book not found
+- [X] T024 [US1] Update `extractSources()` in `ChatService` to build both TEXT and FIGURE source entries: TEXT entries keep existing fields plus `"type": "TEXT"`; FIGURE entries add `"type": "FIGURE"`, `"figureId"`, `"label"`, `"caption"`, `"figureType"`, `"imageUrl"` — source data comes from `RetrievalResult` (text chunk Documents and merged FigureEntity list)
+
+**Checkpoint**: Chat question answered by a diagram → response body contains `sources[n].type == "FIGURE"` with populated `imageUrl`; image loads from the returned URL
+
+---
+
+## Phase 5: User Story 3 — Rich Metadata Enables Precise Source Attribution (Priority: P2)
+
+**Goal**: Users see distinct, informative citations for text vs. image sources; image sources render inline in the chat UI
+
+**Independent Test**: After triggering a response with figure sources, inspect the chat message in the UI — text sources and figure sources are visually distinguishable; figure sources render the actual image inline using the `imageUrl`
+
+- [X] T025 [P] [US3] Update API response types in `frontend/src/services/api.ts` — extend the `Source` type to include `type: 'TEXT' | 'FIGURE'`, `figureId?: string`, `label?: string`, `caption?: string`, `figureType?: string`, `imageUrl?: string`
+- [X] T026 [P] [US3] Update the chat source/citation display in the frontend (wherever sources are currently rendered, e.g. `frontend/src/components/` or `frontend/src/views/`) — render TEXT sources with a document icon and page number; render FIGURE sources with the image (`<img :src="source.imageUrl">`) below the label and caption text
+- [X] T027 [US3] Add figure-type badge rendering in the frontend figure display: show a label derived from `figureType` (e.g. "MRI / CT", "Anatomical Diagram", "Table") alongside the figure caption so users can identify content type without opening the image
+
+---
+
+## Phase 6: Polish & Cross-Cutting Concerns
+
+- [X] T028 Update `README.md` Mermaid architecture diagram to show three storage tiers: pgvector (semantic search), Postgres (source of truth — sections, figures, refs), and file store (extracted PNGs) — **required by Constitution Principle IV in the same PR as the other changes**
+- [X] T029 [P] Write `FigureExtractionServiceTest` unit test in `backend/src/test/java/com/aiteacher/document/FigureExtractionServiceTest.java` — test: images below min size are skipped; `FigureType` classification matches keyword table in data-model.md; caption parsed from adjacent text line
+- [X] T030 [P] Write `NeurosurgeryRetrieverTest` unit test in `backend/src/test/java/com/aiteacher/retrieval/NeurosurgeryRetrieverTest.java` — test: figure IDs from both vector hits and chunk refs are merged without duplicates; `RetrievalResult` contains the deduplicated set
+- [X] T031 Run quickstart.md validation end-to-end: upload a real PDF with a labelled diagram → wait for `READY` → call `GET /api/v1/books/{id}/figures` → send a chat message about the diagram → verify `sources` contains a `FIGURE` entry → verify `imageUrl` resolves to a PNG
+
+---
+
+## Dependencies & Execution Order
+
+### Phase Dependencies
+
+- **Phase 1 (Setup)**: No dependencies — start immediately
+- **Phase 2 (Foundational)**: Requires Phase 1 complete (migrations must run before JPA entities can be wired)
+- **Phase 3 (US2)**: Requires Phase 2 complete — all JPA entities + FigureStorageService must exist
+- **Phase 4 (US1)**: Requires Phase 3 complete — figures must exist in Postgres + vector store before retrieval can surface them
+- **Phase 5 (US3)**: Requires Phase 4 complete — frontend depends on the extended `sources` format from T024
+- **Phase 6 (Polish)**: Requires all story phases complete
+
+### Within Phase 3 (Embedding Pipeline)
+
+```
+T013 (PdfStructureParser) ──────────────────────────┐
+T014 (FigureExtractionService) ─────────────────────┤
+T015 (VisionDescriptionService) ────────────────────┤─→ T018 (BookEmbeddingService orchestrator)
+T016 (TextChunkingService) ─────────────────────────┤           └─→ T019 (cleanup)
+T017 (ChunkFigureRefService) ───────────────────────┘           └─→ T020 (reembed endpoint)
+```
+
+T013–T017 can be implemented in parallel (different files, no shared dependencies). T018 depends on all of them.
+
+### Within Phase 4 (Retrieval)
+
+```
+T021 (NeurosurgeryRetriever) ──────────────────────┐
+                                                   └─→ T022 (ChatService update)
+                                                   └─→ T024 (extractSources update)
+T023 (figures endpoint) ── independent [P]
+```
+
+### Parallel Opportunities per Phase
+
+**Phase 2**: T005, T006, T009, T010, T011 can all run in parallel. T007 depends on T006. T012 can follow T010/T011.
+
+**Phase 3**: T013, T014, T015, T016, T017 all in parallel. T018 depends on all.
+
+**Phase 5**: T025 and T026 in parallel; T027 can follow T026.
+
+**Phase 6**: T029 and T030 in parallel.
+
+---
+
+## Implementation Strategy
+
+### MVP: User Story 2 Only (Embedding Pipeline)
+
+1. Phase 1 (Setup) → Phase 2 (Foundational) → Phase 3 (US2, T013–T020)
+2. **Validate**: `GET /api/v1/books/{id}/figures` returns figures for a test book
+3. **Stop and demo** — the pipeline produces image chunks without any retrieval changes
+
+### Full Feature Delivery
+
+1. Phase 1 + 2 → Foundation ready
+2. Phase 3 (US2) → Embedding pipeline produces image chunks ← **demo point**
+3. Phase 4 (US1) → Chat surfaces image content in responses ← **core payoff**
+4. Phase 5 (US3) → Frontend renders inline figures with type badges
+5. Phase 6 (Polish) → README, tests, end-to-end validation
+
+---
+
+## Notes
+
+- [P] tasks = different files, no dependencies on each other within the same phase
+- [US1/US2/US3] label maps each task to a user story for traceability
+- Phase 3 (US2) must be fully complete before beginning Phase 4 (US1) — retrieval cannot surface figures that do not yet exist
+- The `uploads/figures/` directory must exist and be writable at runtime; `FigureStorageService` creates subdirectories automatically
+- Re-embedding (T020) deletes all existing chunks and figures for the book before re-running — safe to call on books processed by feature 001