Adrien
92 lines
2.8 KiB
Markdown
92 lines
2.8 KiB
Markdown
# AI Teacher — Neurosurgeon RAG Learning Platform
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A web application for neurosurgeons to upload medical textbooks (PDF), have them
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embedded into a pgvector store, then select from a predefined topic list to receive
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AI-generated cross-book summaries, and engage in grounded RAG chat.
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## Architecture
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```mermaid
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graph TD
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User["Neurosurgeon (Browser)"]
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FE["Frontend\nVue.js 3 / Vite\n:5173"]
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BE["Backend\nSpring Boot 4 / Spring AI\n:8080"]
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DB["PostgreSQL + pgvector\n(source of truth)"]
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FS["File Store\nuploads/ (local disk)\nExtracted figure PNGs"]
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LLM["LLM Provider\n(OpenAI)\nEmbeddings + Chat + Vision"]
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User -->|HTTP| FE
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FE -->|REST /api/v1/...| BE
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BE -->|"JDBC — books, chapters,\nsections, figures, refs"| DB
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BE -->|"pgvector — text chunks\n+ figure caption vectors"| DB
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BE -->|"PNG read/write\n(figure extraction)"| FS
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FE -->|"GET /api/v1/figures/**\n(static file serving)"| BE
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BE -->|"Embedding + Chat\n+ Vision (image description)"| LLM
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subgraph "Embedding Pipeline (per PDF upload)"
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EP1["Parse pages → SectionEntity"]
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EP2["Extract images → FigureEntity"]
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EP3["Vision describe → embed caption"]
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EP4["Chunk text → embed chunks"]
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EP5["Link chunks ↔ figures"]
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EP1 --> EP2
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EP1 --> EP4
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EP2 --> EP3
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EP4 --> EP5
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EP3 --> EP5
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end
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subgraph "Retrieval Pipeline (per chat query)"
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RP1["Text chunk search (topK=5)"]
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RP2["Figure caption search (topK=3)"]
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RP3["Expand chunks → full section text"]
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RP4["Fetch linked figures (chunk_figure_ref)"]
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RP5["Merge + deduplicate figures"]
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RP6["Build LLM prompt + call"]
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RP1 --> RP3
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RP1 --> RP4
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RP2 --> RP5
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RP4 --> RP5
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RP3 --> RP6
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RP5 --> RP6
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end
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```
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## Stack
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- **Backend**: Spring Boot 4.0.5 + Spring AI 2.0.0-M4, Java 21, Maven
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- **Frontend**: Vue.js 3 + Vite + TypeScript + Pinia + Axios
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- **Database**: PostgreSQL 16 + pgvector extension
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- **Auth**: HTTP Basic (single shared in-memory user)
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## Quick Start
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See [specs/001-neuro-rag-learning/quickstart.md](specs/001-neuro-rag-learning/quickstart.md) for full instructions.
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### Local Dev
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```bash
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# Start the database
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docker compose up -d
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# Backend
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cd backend
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mvn spring-boot:run
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# Frontend
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cd frontend
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npm install
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npm run dev
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```
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### Environment Variables
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| Variable | Required | Description |
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|----------|----------|-------------|
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| `OPENAI_API_KEY` | Yes | OpenAI API key for embeddings and chat |
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| `APP_PASSWORD` | Yes | Shared password for HTTP Basic auth |
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| `DB_URL` | Yes | JDBC URL, e.g. `jdbc:postgresql://localhost:5432/aiteacher` |
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| `DB_USERNAME` | Yes | Database username |
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| `DB_PASSWORD` | Yes | Database password |
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| `FIGURE_STORAGE_PATH` | No | Base path for uploaded PDFs and extracted figures (default: `./uploads`) |
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