SAVVI has resources to support implementing and managing your ML App.

Step 1: Test the ML App

ML Apps are functional with just two APIs:

POST to DECIDE or PREDICT
POST to enter RESULTS, thus updating the ML App for continuous learning

On the Implement tab of your ML App, you will find resources for testing and implementing the ML App. Select the drop-down arrow and click the Try It Now button. Update the entry(-ies) in the request body and click the Execute button.

Step 2: Share Documentation

Your software engineers may prefer implementing the ML App with Javascript or the APIs.

To share the Javascript snippet in your task management tool...

Copy the code and paste it.

To share the APIs in your task management tool...

Select the ReDoc or Swagger button to open a new tab, then copy and paste the link.

NOTE: To access the link, your colleague will need to be an active user of your SAVVI AI account.

The API Key authenticates the server request on API calls. The API Key is unique to each environment and adds an important layer of security for your SAVVI client container and ML Applications. Thus, it can not be reset nor is it accessible to anyone outside of your SAVVI AI account.

Click to copy your API Key and paste it into the x-api-key header to make server requests from each of your environments to reinforce the security of your data. Here is an example of the API Key being implemented in Python on a POST call:

Python POST:
import requests
url = "https://1234-abcdef01.cc.savvi-ai.com/my-mlapp"
api_key = "my-api-key"
params = {"influencer1": "1", "influencer2": "2"}
headers = {"X-Api-Key": api_key}
response = requests.get(url, params=params, headers=headers)

cURL:
curl "https://1234-abcdef01.cc.savvi-ai.com/my-mlapp?influencer1=1&influencer2=2" -H
"X-Api-Key: my-api-key"

Congratulations, you've designed and implemented an ML App! 🎉

You can explore some of our Advanced Features to get savvy with SAVVI's ML Apps.