https://github.com/redisai/redisai-py
Python client for RedisAI
https://github.com/redisai/redisai-py
onnx python-client redisai tensor torch
Last synced: about 1 month ago
JSON representation
Python client for RedisAI
- Host: GitHub
- URL: https://github.com/redisai/redisai-py
- Owner: RedisAI
- License: bsd-3-clause
- Created: 2019-01-21T16:00:08.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-07-13T03:52:50.000Z (almost 2 years ago)
- Last Synced: 2025-04-10T01:08:13.419Z (about 1 month ago)
- Topics: onnx, python-client, redisai, tensor, torch
- Language: Python
- Homepage: https://redisai.io
- Size: 91.9 MB
- Stars: 89
- Watchers: 5
- Forks: 13
- Open Issues: 13
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
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README
==========
redisai-py
==========
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redisai-py is the Python client for RedisAI. Checkout the
`documentation `_ for API details and examples
Installation
------------
1. Install Redis 5.0 or above
2. Install `RedisAI `_
3. Install the Python client
.. code-block:: bash
$ pip install redisai
4. Install serialization-deserialization utility (optional)
.. code-block:: bash
$ pip install ml2rt
Development
-----------
1. Assuming you have virtualenv installed, create a virtualenv to manage your python dependencies, and activate it.
```virtualenv -v venv; source venv/bin/activate```
2. Install [pypoetry](https://python-poetry.org/) to manage your dependencies.
```pip install poetry```
3. Install dependencies.
```poetry install --no-root```
[tox](https://tox.readthedocs.io/en/latest/) runs all tests as its default target. Running *tox* by itself will run unit tests. Ensure you have a running redis, with the module loaded.
**Contributing**
Prior to submitting a pull request, please ensure you've built and installed poetry as above. Then:
1. Run the linter.
```tox -e linters.```
2. Run the unit tests. This assumes you have a redis server running, with the [RedisAI module](https://redisai.io) already loaded. If you don't, you may want to install a [docker build](https://hub.docker.com/r/redislabs/redisai/tags).
```tox -e tests```
`RedisAI example repo `_ shows few examples
made using redisai-py under `python_client` folder. Also, checkout
`ml2rt `_ for convenient functions those might help in
converting models (sparkml, sklearn, xgboost to ONNX), serializing models to disk, loading
it back to redisai-py etc.