Step 1: Select Your AI/ML Source
- Navigate to Sources → AI/ML Sources in the sidebar.
- Click “Add Source”.
- Select the AI/ML source connector from the list.
📸 Add screenshot of “Add AI/ML Source” UI
Step 2: Define and Connect the Endpoint
Fill in the required connection details:- Endpoint Name – A descriptive name for easy identification.
- Endpoint URL – The hosted URL of your AI/ML model.
- Authentication Method – Choose between
OAuth
,API Key
, etc. - Authorization Header – Format of the header (if applicable).
- Secret Key – For secure access.
- Request Format – Define the input structure (e.g., JSON).
- Response Format – Define how the model returns predictions.
📸 Add screenshot of endpoint configuration UI
Step 3: Test the Source
Before saving, click “Test Connection” to verify that the endpoint is reachable and properly configured.⚠️ If the test fails, check for errors in the endpoint URL, headers, or authentication values.
📸 Add screenshot of test results with success/failure examples
Step 4: Save the Source
Once the test passes:- Provide a name and optional description.
- Click “Save” to finalize setup.
- Your model source will now appear under AI/ML Sources.
📸 Add screenshot showing saved model in the source list
Step 5: Define Input Schema
The Input Schema tells AI Squared how to format data before sending it to the model. Each input field requires:- Name – Matches the key in your model’s input payload.
- Type –
String
,Integer
,Float
, orBoolean
. - Value Type –
Dynamic
(from data/apps) orStatic
(fixed value).
📸 Add screenshot of input schema editor
Step 6: Define Output Schema
The Output Schema tells AI Squared how to interpret the model’s response. Each output field requires:- Field Name – The key returned by the model.
- Type – Define the type:
String
,Integer
,Float
,Boolean
.
📸 Add screenshot of output schema editor