---
title: CLIP Service
emoji: 🔍
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
---

# CLIP Service 🔍

A FastAPI service that provides CLIP (Contrastive Language-Image Pre-training) embeddings for images and text using the `openai/clip-vit-large-patch14` model.

## 🚀 Features

- **Image Encoding**: Generate 768-dimensional embeddings from image URLs
- **Text Encoding**: Generate embeddings from text descriptions
- **High Performance**: Optimized for batch processing
- **REST API**: Simple HTTP endpoints for easy integration

## 📋 API Endpoints

### `POST /encode/image`
Generate embeddings for an image from URL.

**Request:**
```json
{
  "image_url": "https://example.com/image.jpg"
}
```

**Response:**
```json
{
  "embedding": [0.1, -0.2, 0.3, ...], // 768 dimensions
  "dimensions": 768
}
```

### `POST /encode/text`
Generate embeddings for text.

**Request:**
```json
{
  "text": "a beautiful sunset over mountains"
}
```

**Response:**
```json
{
  "embedding": [0.1, -0.2, 0.3, ...], // 768 dimensions
  "dimensions": 768
}
```

### `GET /health`
Check service health and status.

## 🔧 Usage Examples

```bash
# Encode an image
curl -X POST "https://your-username-clip-service.hf.space/encode/image" \
  -H "Content-Type: application/json" \
  -d '{"image_url": "https://example.com/image.jpg"}'

# Encode text
curl -X POST "https://your-username-clip-service.hf.space/encode/text" \
  -H "Content-Type: application/json" \
  -d '{"text": "a beautiful landscape"}'
```

## 🏗️ Integration

This service is designed to work with Pinterest-like applications for:
- Visual similarity search
- Content-based recommendations
- Cross-modal search (text to image, image to text)

## 📝 Model Information

- **Model**: `openai/clip-vit-large-patch14`
- **Embedding Dimensions**: 768
- **Supported Images**: JPG, PNG, GIF, WebP
- **Max Image Size**: Recommended < 10MB

## ⚡ Performance

- **CPU**: ~2-5 seconds per image
- **GPU**: ~0.5-1 second per image (when available)
- **Batch Processing**: Supported for multiple requests

---

Built with ❤️ using [Transformers](https://huggingface.co/transformers) and [FastAPI](https://fastapi.tiangolo.com/)