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Jinad is the daemon tool for running Jina on remote machines. Jina is the cloud-native neural search solution powered by the state-of-the-art AI and deep learning

Project description

Jina banner

An easier way to build neural search in the cloud

Jina Python 3.7 3.8 PyPI Docker Image Version (latest semver) CI CD codecov

jinad - The Daemon to manage Jina remotely

jinad is a REST + Websockets based server to allow remote workflows in Jina. It is built using FastAPI and deployed using Uvicorn.


Jina Docs: https://docs.jina.ai/

JinaD API Docs: https://api.jina.ai/jinad


Set up:

Pypi:

On Linux/macOS with Python 3.7/3.8:

pip install -U jinad && jinad
Docker Container:
docker run -p 8000:8000 jinaai/jinad
Systemd:

Debian / Ubuntu:

curl -L https://raw.githubusercontent.com/jina-ai/jinad/main/scripts/deb-systemd.sh | bash

RPM:

to be added

Use Cases:

Start jinad on a remote machine - 1.2.3.4:8000

1: Create Remote Pod in a Flow

f = (Flow()
     .add(name='p1', uses='_logforward')
     .add(name='p2', host='1.2.3.4', port_expose='8000', uses='_logforward')
with f:
     f.search_lines(lines=['jina', 'is', 'cute'], output_fn=print)

2: Create Remote Pod using Jina CLI

jina pod --host 1.2.3.4 --port-expose 8000 --uses _logforward

3: Create a Remote Flow

curl -s --request PUT "http://1.2.3.4:8000/v1/flow/yaml" -H  "accept: application/json" -H  "Content-Type: multipart/form-data" -F "uses_files=@helloworld.encoder.yml" -F "uses_files=@helloworld.indexer.yml" -F "pymodules_files=@components.py" -F "yamlspec=@helloworld.flow.index.yml"

Project details


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