Project Title

clip-as-service — Scalable Embedding, Reasoning, and Ranking for Images and Sentences with CLIP

Overview

CLIP-as-service is a high-scalability, low-latency service designed for embedding images and text. It is easily integrated as a microservice into neural search solutions, offering fast performance, elasticity, and a modern, easy-to-use interface. This project stands out for its ability to serve CLIP models with high QPS and its support for various protocols, including gRPC, HTTP, and WebSocket.

Key Features

Fast performance with 800QPS using TensorRT, ONNX runtime, and PyTorch without JIT.
Elastic scaling of multiple CLIP models on a single GPU with automatic load balancing.
Easy-to-use minimalist design with intuitive and consistent APIs for image and sentence embedding.
Modern support for async clients and protocols with TLS and compression.
Seamless integration with neural search ecosystem, including Jina and DocArray.

Use Cases

Use case 1: Embedding images and text for neural search solutions, providing fast and scalable service.
Use case 2: Visual reasoning tasks such as object recognition, object counting, color recognition, and spatial relation understanding.
Use case 3: Building cross-modal and multi-modal solutions with integration into the neural search ecosystem.

Advantages

High performance with support for non-blocking duplex streaming on requests and responses.
Horizontal scaling capabilities for handling large data and long-running tasks.
User-friendly APIs that simplify the embedding process for both images and text.
Support for multiple protocols, enhancing flexibility in various applications.

Limitations / Considerations

Limitation 1: The service may require significant computational resources, especially when scaling up multiple CLIP models.
Limitation 2: The project's performance may vary depending on the specific configuration and hardware used.

CLIP: The original CLIP model by OpenAI, which this project builds upon. CLIP-as-service extends CLIP's capabilities with a service-oriented architecture.
Jina: A neural search framework that CLIP-as-service integrates with, providing a more comprehensive solution for neural search.
DocArray: A library for building multimodal and cross-modal solutions, which complements CLIP-as-service in building complex search applications.

Basic Information

GitHub: https://github.com/jina-ai/clip-as-service
Stars: 12,742
License: Unknown
Last Commit: 2025-09-19

📊 Project Information

Project Name: clip-as-service
GitHub URL: https://github.com/jina-ai/clip-as-service
Programming Language: Python
⭐ Stars: 12,742
🍴 Forks: 2,078
📅 Created: 2018-11-12
🔄 Last Updated: 2025-09-19

🏷️ Project Topics

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📚 Documentation

DocArray

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clip-as-service

Project Description