Metadata-Version: 2.1
Name: cortex-deploy
Version: 0.20.0.dev0
Summary: Model serving at scale
Home-page: https://www.cortex.dev
Author: cortex.dev
Author-email: dev@cortex.dev
License: Apache License 2.0
Project-URL: Bug Reports, https://github.com/cortexlabs/cortex/issues
Project-URL: Chat with us, https://gitter.im/cortexlabs/cortex
Project-URL: Documentation, https://docs.cortex.dev
Project-URL: Source Code, https://github.com/cortexlabs/cortex
Description: Cortex makes it simple to deploy machine learning models in production.
        
        ### Deploy
        
        * Deploy TensorFlow, PyTorch, ONNX, scikit-learn, and other models.
        * Define preprocessing and postprocessing steps in Python.
        * Configure APIs as realtime or batch.
        * Deploy multiple models per API.
        
        ### Manage
        
        * Monitor API performance and track predictions.
        * Update APIs with no downtime.
        * Stream logs from APIs.
        * Perform A/B tests.
        
        ### Scale
        
        * Test locally, scale on your AWS account.
        * Autoscale to handle production traffic.
        * Reduce cost with spot instances.
        
        <!-- CORTEX_VERSION_MINOR -->
        [documentation](https://docs.cortex.dev) • [tutorial](https://docs.cortex.dev/deployments/realtime-api/text-generator) • [examples](https://github.com/cortexlabs/cortex/tree/0.20/examples) • [chat with us](https://gitter.im/cortexlabs/cortex)
        
        ## Install the CLI
        
        <!-- CORTEX_VERSION_MINOR -->
        ```bash
        pip install cortex
        ```
        
        You must have [Docker](https://docs.docker.com/install) installed to run Cortex locally or to create a cluster on AWS.
        
        ## Deploy an example
        
        <!-- CORTEX_VERSION_MINOR -->
        ```bash
        # clone the Cortex repository
        git clone -b master https://github.com/cortexlabs/cortex.git
        ```
        
        ### Using the CLI
        ```bash
        # deploy the model as a realtime api
        cortex deploy cortex/examples/pytorch/text-generator/cortex.yaml
        
        # view the status of the api
        cortex get --watch
        
        # stream logs from the api
        cortex logs text-generator
        
        # get the api's endpoint
        cortex get text-generator
        
        # generate text
        curl <API endpoint> \
          -X POST -H "Content-Type: application/json" \
          -d '{"text": "machine learning is"}' \
        
        # delete the api
        cortex delete text-generator
        ```
        
        ### In Python
        ```python
        import cortex
        import requests
        
        local_client = cortex.client("local")
        
        # deploy the model as a realtime api and wait for it to become active
        deployments = local_client.deploy("cortex/examples/pytorch/text-generator/cortex.yaml", wait=True)
        
        # get the api's endpoint
        url = deployments[0]["api"]["endpoint"]
        
        # generate text
        print(requests.post(url, json={"text": "machine learning is"}).text)
        
        # delete the api
        local_client.delete_api("text-generator")
        ```
        
        ## Running at scale on AWS
        
        Run the command below to create a cluster with basic configuration, or see [cluster configuration](config.md) to learn how you can customize your cluster with `cluster.yaml`.
        
        See [EC2 instances](ec2-instances.md) for an overview of several EC2 instance types. To use GPU nodes, you may need to subscribe to the [EKS-optimized AMI with GPU Support](https://aws.amazon.com/marketplace/pp/B07GRHFXGM) and [file an AWS support ticket](https://console.aws.amazon.com/support/cases#/create?issueType=service-limit-increase&limitType=ec2-instances) to increase the limit for your desired instance type.
        
        ```bash
        # create a Cortex cluster on your AWS account
        cortex cluster up
        
        # set the default CLI environment (optional)
        cortex env default aws
        ```
        
        You can now run the same commands shown above to deploy the text generator to AWS (if you didn't set the default CLI environment, add `--env aws` to the `cortex` commands).
        
Platform: UNKNOWN
Classifier: Operating System :: MacOS
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Intended Audience :: Developers
Requires-Python: >=3.6.1
Description-Content-Type: text/markdown
