# Simple Knowledge Base - Backend Service (Server)

A RAG (Retrieval-Augmented Generation) knowledge base backend system built with the [NestJS](https://nestjs.com/) framework. Provides file parsing, vector indexing, hybrid search, and multi-model management features.

## 🌟 Key Features

- **Intelligent Document Processing**: Integrated with [Apache Tika](https://tika.apache.org/) to support text extraction from various formats including PDF, Word, Markdown, and TXT.
- **Efficient Vector Search**: Uses [Elasticsearch](https://www.elastic.co/) as the vector database. Supports hybrid search combining KNN vector search and full-text search.
- **Flexible RAG Engine**: Built on LangChain. Supports customization of chunking rules and reranking.
- **Multi-Model Provider**: Supports dynamic connection to OpenAI, Google Gemini, and locally deployed LLM models.
- **Secure Management**: Built-in JWT authentication and user permission management.

## 🛠️ Tech Stack

- **Framework**: NestJS (TypeScript)
- **Database**: SQLite (TypeORM)
- **Search Engine**: Elasticsearch 8.x/9.x
- **AI Framework**: LangChain
- **Libraries**: RxJS, Class-Validator

## 📋 Prerequisites

Before running the project, ensure you have the following environment set up:

- [Node.js](https://nodejs.org/) (v18 or higher recommended)
- [Yarn](https://yarnpkg.com/)
- [Docker](https://www.docker.com/) & Docker Compose (for infrastructure)

## 🚀 Quick Start

### 1. Start Infrastructure

Use the `docker-compose.yml` file in the project root (`simple-kb/`) to quickly start Elasticsearch and Tika.

```bash
# Run from project root directory
docker-compose up -d
```

After successful startup:

- **Elasticsearch**: Listens on port `19200` (maps container's 9200 port)
- **Tika**: Listens on port `9998`

### 2. Install Dependencies

Navigate to the `server` directory and install packages:

```bash
cd server
yarn install
```

### 3. Environment Configuration

The project uses environment variables for configuration. Make sure the settings are correct (especially Elasticsearch address):

```env
# Database path
DATABASE_PATH=server/data/metadata.db

# JWT secret
JWT_SECRET=your_secure_secret

# Elasticsearch settings (match docker-compose ports)
ELASTICSEARCH_HOST=http://localhost:19200
ELASTICSEARCH_INDEX=knowledge_base

# Tika settings
TIKA_HOST=http://localhost:9998

# File upload storage path
UPLOAD_FILE_PATH=./uploads
```

### 4. Start Services

```bash
# Development mode (recommended, with hot reload)
yarn run start:dev

# Build and run in production mode
yarn build
yarn run start:prod
```

The backend service runs on **http://localhost:13000** by default, with API prefix `/api`.

## 🧪 Testing

```bash
# Unit tests
yarn run test

# E2E tests
yarn run test:e2e
```

## ⚠️ Notes and Tips

1. **Database Initialization**:
   - On first run, TypeORM automatically creates `metadata.db` (or configured DB) under the `server/data/` directory.
   - In development mode, with `synchronize: true`, table structures are auto-synced.

2. **Elasticsearch Connection**:
   - If you encounter a `Connection refused` error, check if Docker containers are running properly (`docker ps`).
   - On service startup, an index named `knowledge_base` is automatically detected and created.

3. **Default Account**:
   - If you reset the database, either register a new user or refer to existing admin data. It's recommended to use the frontend registration feature to create the first user.

4. **File Parsing**:
   - When uploading large files, parsing by Tika may take a few seconds. Please wait while checking the frontend processing status.