Install Jina via pip

If you prefer to run Jina natively on your host, please make sure you have Python >= 3.7 installed.

Install from PyPi

On Linux/Mac, simply run:

pip install jina

Install from the Master Branch

If you want to keep track of the master branch of our development repository:

pip install git+https://github.com/jina-ai/jina.git

Be aware that the master branch may not be stable. We only recommend this branch for testing new features.

Install from Your Local Fork/Clone

If you are a developer and want to test your changes on-the-fly:

git clone https://github.com/jina-ai/jina
cd jina && pip install -e .

In the dev mode, if you later switch to a different method of Jina installation, remember to first uninstall the version you edited:

pip uninstall $(basename $(find . -name '*.egg-info') .egg-info)

Cherry-Pick Extra Dependencies

Jina requires only five dependencies numpy, pyzmq, protobuf, grpcio and pyyaml. No third-party pre-trained models, deep learning/NLP/CV packages will be installed.

However, some Executors may require extra dependencies. The full table of these extra dependencies can be found in extra-requirements.txt. You can cherry-pick what you want to install, e.g.

pip install "jina[nlp+cv]"

This will install all dependencies tagged with nlp or cv.

Though not recommended, you can install Jina with full dependencies via:

pip install "jina[all]"

To Install Cherry-Picked Dependencies From the Master Branch

pip install "git+https://github.com/jina-ai/jina.git#egg=jina[http]"

Extra Dependencies Explained

These are the extra dependencies used by Jina:

PyPi Name Required by Description Compatibility
scipy>=0.4.1 numeric, index Scientific Library for Python. Required for similarity measure computation and required for many other extra packages (tensorflow, paddlehub ...) tensorflow>=2.0.0 requires scipy>=1.4.1, while paddlepaddle<1.8.1 require scipy<=1.3.1.
flask, flask-cors http, sse A simple framework for building complex web applications, used for logging server and exposing REST API.
fluent-logger logging fluent-logger-python is a Python library, to record the events from Python application.
nmslib index Non-Metric Space Library (NMSLIB) is an efficient cross-platform similarity search library
docker network A Python library for the Docker Engine API See https://docs.docker.com/engine/api/ for compatibility with docker engine versions.
torch>=1.0.0 framework Tensors and Dynamic neural networks in Python with strong GPU acceleration. Enables several image encoders, object detection crafters and transformers models It imposes compatibility restrictions with torchvision (https://pypi.org/project/torchvision/).
transformers>=2.6.0 nlp Repository of pre-trained NLP Transformer models Some flair versions impose some requirements on the transformer version required. For proper padding to work, version 2.6.0 is required as minimmum version.
flair nlp A very simple framework for state-of-the-art NLP It imposes restrictions on torch and transformers version compatibility.
paddlepaddle framework Parallel Distributed Deep Learning It imposes restrictions on scipy version and is required for paddlehub models.
paddlehub framework A toolkit for managing pretrained models of PaddlePaddle Requires paddlepaddle.
tensorflow>=2.0 framework TensorFlow is an open source machine learning framework for everyone.
tensorflow-hub framework TensorFlow Hub is a library to foster the publication, discovery, and consumption of reusable parts of machine learning models.
torchvision>=0.3.0 framework, cv image and video datasets and models for torch deep learning Make sure that the models you want to use ara available at your installed torchvision version.
Pillow cv Python Imaging Library
onnx framework Open Neural Network Exchange.
onnxruntime framework ONNX Runtime Python bindings.
annoy index Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk.
sklearn numeric A set of python modules for machine learning and data mining. Used for a variety of numeric encoders.
plyvel index fast and feature-rich Python interface to LevelDB. Enables the use of LevelDB as a Key-Value indexer.
jieba nlp Chinese Words Segmentation Utilities
lz4 optimization, network LZ4 Bindings for Python. Enables compression to send large messages.
gevent http Coroutine-based network library
python-magic http File type identification using libmagic. Used to identify document request type.
pymilvus index Python Sdk for Milvus. Enables the usage of Milvus DB as vector indexer as a client.
librosa audio Python module for audio and music processing.
deepsegment nlp Sentence Segmentation with sequence tagging.
ngt index Neighborhood Graph and Tree for Indexing High-dimensional Data.
uvloop òptimization Fast implementation of asyncio event loop on top of libuv.

On Windows

Currently we do not support native python on Windows.

If you are a Windows user, one workaround is to run Jina on Windows Subsystem for Linux or run Jina in a Docker container. If you manage to run Jina on Windows after some tweaks, please submit your changes here.

Other OSes

Please refer to run Jina in a Docker container. If you manage to run Jina on other OSes after some tweaks, please submit your changes here.

Upgrade Jina

If you have a previously installed version of Jina, you can upgrade it by running:

pip install -U jina

For Docker users:

docker pull jinaai/jina