https://github.com/johnexzy/smart-recommender
Guide to Building an Intelligent Recommendation System Using Node.js, PGVector, and Google Gemini for Personalized Content Discovery
https://github.com/johnexzy/smart-recommender
Last synced: 2 months ago
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Guide to Building an Intelligent Recommendation System Using Node.js, PGVector, and Google Gemini for Personalized Content Discovery
- Host: GitHub
- URL: https://github.com/johnexzy/smart-recommender
- Owner: johnexzy
- Created: 2024-09-14T23:20:29.000Z (about 1 year ago)
- Default Branch: dev
- Last Pushed: 2024-10-20T20:38:08.000Z (12 months ago)
- Last Synced: 2025-01-23T04:17:02.563Z (9 months ago)
- Language: TypeScript
- Homepage:
- Size: 45.9 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Building an Intelligent Recommendation System: Leveraging Node.js, PGVector, and Google Gemini for Personalized Content Discovery
This project provides a service to embed text using Google's Generative AI and store the embeddings in a PostgreSQL database. It also includes functionality to find similar embeddings and recommend content based on user preferences.
## Prerequisites
- Node.js
- PostgreSQL
- Google Generative AI API Key
## Setup
1. **Clone the repository:**
```sh
git clone
cd
```
2. **Install dependencies:**
```sh
npm install
```
3. **Environment Variables:**
Create a `.env` file in the root directory and add the following:
```env
API_KEY=your_google_generative_ai_api_key
DATABASE_URL=your_postgresql_database_url
ACCESS_TOKEN_SECRET=your_jwt_secret
```
4. **Setup the database:**
```sh
npx ts-node src/setupDatabase.ts
```
## Running the Service
1. **Start the server:**
```sh
npx ts-node src/index.ts
```
2. The server will run on `http://localhost:9000`.
## API Endpoints
### User Management
#### Create User
- **URL:** `/user`
- **Method:** `POST`
- **Body:**
```json
{
"name": "username",
"password": "userpassword",
"preferences": { /* user preferences */ }
}
```
- **Response:**
```json
{
"userId": "generated_user_id",
"name": "username",
"preferences": { /* user preferences */ }
}
```
#### User Login
- **URL:** `/login`
- **Method:** `POST`
- **Body:**
```json
{
"username": "username",
"password": "userpassword"
}
```
- **Response:**
```json
{
"accessToken": "jwt_access_token"
}
```
### Embedding and Similarity
#### Embed Text
- **URL:** `/embed`
- **Method:** `POST`
- **Headers:**
```json
{
"Authorization": "Bearer jwt_access_token"
}
```
- **Body:**
```json
{
"text": "Your text to embed"
}
```
- **Response:**
```json
{
"userId": "user_id",
"text": "Your text to embed",
"embedding": [/* embedding vector */]
}
```
#### Find Similar Embeddings
- **URL:** `/similarity`
- **Method:** `POST`
- **Headers:**
```json
{
"Authorization": "Bearer jwt_access_token"
}
```
- **Body:**
```json
{
"text": "Your text to find similarity"
}
```
- **Response:**
```json
[
{
"text": "Similar text",
"vector": [/* embedding vector */],
"distance": 0.123
},
// more results
]
```
### Recommendations
#### Recommend Similar Texts
- **URL:** `/recommend`
- **Method:** `POST`
- **Headers:**
```json
{
"Authorization": "Bearer jwt_access_token"
}
```
- **Body:**
```json
{
"text": "Your text to get recommendations"
}
```
- **Response:**
```json
[
{
"text": "Recommended text",
"similarity": 0.877
},
// more recommendations
]
```
### Postman Documentation [Here](https://documenter.getpostman.com/view/9785245/2sAXqs72PA)
## License
This project is licensed under the MIT License.