Welcome to Jina!

Jina is a neural search framework that empowers anyone to build SOTA and scalable deep learning search applications in minutes.

⏱️ Save time - The design pattern of neural search systems. Native support for PyTorch/Keras/ONNX/Paddle. Build solutions in just minutes.

🌌 All data types - Process, index, query, and understand videos, images, long/short text, audio, source code, PDFs, etc.

🌩️ Local & cloud friendly - Distributed architecture, scalable & cloud-native from day one. Same developer experience on both local and cloud.

🍱 Own your stack - Keep end-to-end stack ownership of your solution. Avoid integration pitfalls you get with fragmented, multi-vendor, generic legacy tools.


  1. Make sure that you have Python 3.7+ installed on Linux/MacOS/Windows.

    pip install -U jina
    conda install jina -c conda-forge
    docker pull jinaai/jina:latest
  2. That’s it! Try a hello-world demo

    jina hello fashion
    docker run -v "$(pwd)/j:/j" jinaai/jina:latest hello fashion --workdir /j && open j/demo.html

Now that you’re set up, let’s dive into more of how Jina works and how to build great apps.

Next steps

Play 3 Hello World

Try Jina on fashion image search, QA chatbot and multimodal search.

Understand Basics

Document, Executor, and Flow are the three fundamental concepts in Jina.

Tasks on Multi Data Types

Learn to use Jina to build neural search solution for different types of data.

Share Executors

Learn to share and reuse Executors from the Jina community.

Manage Remote Jina

Learn to deploy and manage Jina on remote via a RESTful interface.

Try Experimental Features

Preview the next big things we are building. Careful not to get zapped!


Join Us

Jina is backed by Jina AI and licensed under Apache-2.0. We are actively hiring AI engineers, solution engineers to build the next neural search ecosystem in open source.

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