ai-teacher/README.md

# AI Teacher — Neurosurgeon RAG Learning Platform

A web application for neurosurgeons to upload medical textbooks (PDF), have them
embedded into a pgvector store, then select from a predefined topic list to receive
AI-generated cross-book summaries, and engage in grounded RAG chat.

## Architecture

```mermaid
graph TD
    User["Neurosurgeon (Browser)"]
    Login["Login Page\n(username + password form)"]
    FE["Frontend\nVue.js 3 / Vite\n:5173"]
    BE["Backend\nSpring Boot 4 / Spring AI\n:8080"]
    Auth["Spring Security\nHTTP Basic Auth"]
    DB["PostgreSQL + pgvector\n(source of truth)"]
    FS["File Store\nuploads/ (local disk)\nExtracted figure PNGs"]
    LLM["LLM Provider\n(OpenAI)\nEmbeddings + Chat + Vision"]

    User -->|"First visit / unauthenticated"| Login
    Login -->|"POST credentials\n(GET /api/v1/auth/check)"| Auth
    Auth -->|"401 → back to login\n200 → app access"| Login
    Login -->|"Authenticated"| FE
    FE -->|"REST /api/v1/...\n(HTTP Basic on every request)"| Auth
    Auth --> BE
    BE -->|"JDBC — books, chapters,\nsections, figures, refs"| DB
    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)"
        RP0["Query expansion\n(QueryExpansionService)\nlay → clinical terms"]
        RP1["Text chunk search (topK=5)"]
        RP2["Figure caption search (topK=3)"]
        RP3["Expand chunks → ±1-page section text"]
        RP4["Fetch linked figures (chunk_figure_ref)"]
        RP5["Merge + deduplicate figures"]
        RP6["Build labelled prompt\n[S1],[F1]… tags"]
        RP7["LLM chat call"]
        RP8["Citation validation\n(CitationValidatorService)\nstrip hallucinated refs"]
        RP0 --> RP1
        RP0 --> RP2
        RP1 --> RP3
        RP1 --> RP4
        RP2 --> RP5
        RP4 --> RP5
        RP3 --> RP6
        RP5 --> RP6
        RP6 --> RP7
        RP7 --> RP8
    end
```

## Marker API Response Structure

The PDF parsing pipeline calls a local [Marker](https://github.com/VikParuchuri/marker) server (`POST /marker/upload`).

### Top-level envelope

```json
{
  "format": "json",
  "output": "<JSON-encoded string>"
}
```

`output` is a **JSON-encoded string** (not a nested object) and must be parsed a second time to get the document tree.

### Parsed `output` shape

```
{
  "children": [ <Page block>, ... ]
}
```

### Block types

Every block shares these fields:

| Field            | Type              | Notes                                      |
|------------------|-------------------|--------------------------------------------|
| `id`             | string            | e.g. `/page/0/Picture/2`                   |
| `block_type`     | string            | see table below                            |
| `html`           | string            | rendered HTML; may contain `<content-ref>` |
| `bbox`           | `[x0,y0,x1,y1]`  | bounding box in page coordinates           |
| `children`       | array or null     | nested blocks                              |
| `images`         | object or null    | base64 PNG map (leaf image blocks only)    |
| `section_hierarchy` | object         | heading ancestry                           |

#### Known `block_type` values

| block_type       | Category | Notes                                                 |
|------------------|----------|-------------------------------------------------------|
| `Page`           | structure | Top-level; direct children are the page content       |
| `SectionHeader`  | text      | Section / chapter heading                             |
| `Text`           | text      |                                                       |
| `TextInlineMath` | text      |                                                       |
| `ListItem`       | text      |                                                       |
| `Table`          | text      |                                                       |
| `Code`           | text      |                                                       |
| `Equation`       | text      |                                                       |
| `Footnote`       | text      |                                                       |
| `Caption`        | text      | Usually a child of a `*Group` block                   |
| `PageHeader`     | text      |                                                       |
| `PageFooter`     | text      |                                                       |
| `Handwriting`    | text      |                                                       |
| `Picture`        | image     | Leaf block; `images` map holds base64 PNG keyed by ID |
| `Figure`         | image     | Leaf block; same as `Picture`                         |
| `PictureGroup`   | container | Wraps one `Picture` + one `Caption` child             |
| `FigureGroup`    | container | Wraps one `Figure` + one `Caption` child              |

### Image extraction

Images are only present on **leaf** image blocks (`Picture`, `Figure`).
Group blocks (`PictureGroup`, `FigureGroup`) have `images: null` — the base64 PNG lives on the child leaf block.

```
PictureGroup
├── Picture   ← images: { "/page/0/Picture/2": "<base64 PNG>" }
└── Caption   ← html: "<p>Figure 1 — ...</p>"
```

## Stack

- **Backend**: Spring Boot 4.0.5 + Spring AI 2.0.0-M4, Java 25, Maven
- **Frontend**: Vue.js 3 + Vite + TypeScript + Pinia + Axios
- **Database**: PostgreSQL 16 + pgvector extension
- **Auth**: HTTP Basic (single shared in-memory user)

## Quick Start

See [specs/001-neuro-rag-learning/quickstart.md](specs/001-neuro-rag-learning/quickstart.md) for full instructions.

### Local Dev (JVM)

```bash
# Start the database
docker compose up -d

# Backend
cd backend
mvn spring-boot:run

# Frontend
cd frontend
npm install
npm run dev
```

### Native Image Build

Produces a GraalVM native binary packaged into a minimal Docker image via Jib.

**Prerequisite**: GraalVM 25 must be installed and set as `JAVA_HOME`.

```bash
# Install GraalVM 25 CE via sdkman (one-time)
sdk install java 25-graalce
sdk use java 25-graalce

# Build native executable + Docker image (requires Docker daemon)
cd backend
mvn -Pnative package jib:dockerBuild -DskipTests
```

The image `ai-teacher-backend:latest` will appear in your local Docker. It starts in under 1 second and uses significantly less memory than the JVM image.

### Run Native Stack (Docker Compose)

```bash
# Copy and fill in secrets
cp .env.example .env
# edit .env — add OPENAI_API_KEY at minimum

# Start PostgreSQL + native backend
docker compose -f docker-compose.native.yml up
```

App available at `http://localhost:8080`.

### Build Pipeline (Native)

```mermaid
graph LR
    SRC["Source Code\n(Java 25)"]
    AOT["Spring Boot AOT\n(process-aot)"]
    NI["GraalVM native-image\n(native-maven-plugin)"]
    EXE["Native Executable\ntarget/ai-teacher-backend"]
    JIB["Jib\n(jib-native-image-extension)"]
    IMG["Docker Image\nai-teacher-backend:latest\n(distroless base)"]

    SRC --> AOT
    AOT --> NI
    NI --> EXE
    EXE --> JIB
    JIB --> IMG
```

### Environment Variables

#### Backend

| Variable | Required | Description |
|----------|----------|-------------|
| `OPENAI_API_KEY` | Yes | OpenAI API key for embeddings and chat |
| `APP_PASSWORD` | Yes | Shared password for HTTP Basic auth |
| `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`) |
| `UPLOAD_ENABLED` | No | Set to `false` to disable the book upload endpoint (default: `true`) |
| `DELETE_ENABLED` | No | Set to `false` to disable the book delete endpoint (default: `true`) |

#### Frontend

| Variable | Required | Description |
|----------|----------|-------------|
| `VITE_API_URL` | No | Backend API base URL (default: `/api/v1`) |
| `VITE_APP_PASSWORD` | Yes | Shared password for HTTP Basic auth (must match `APP_PASSWORD`) |
| `VITE_UPLOAD_ENABLED` | No | Set to `false` to hide the upload UI (default: `true`) |
| `VITE_DELETE_ENABLED` | No | Set to `false` to hide the delete button (default: `true`) |