Configuring Models
Multiple models can be stacked together as a list in a single request. Each model has a modelType and a modelConfig key.
Key
Description
modelType
Used to identify the type/name of model being enabled
modelConfig
Used to send additional configuration specific to the model
Some of the models are dependant on the outputs of other models. This dependency can be understood under the Flow of Data and Stacking Models Section.

Quick Links to Configure Models

Example: How to Request for Question & Responses model on a Transaction ID.

Step 1: Finding out the Dependencies.

Model Dependency and flow of data
As shown in the above Flow Diagram question_response model is dependant on the outputs of emotion_analysis , sentiment_analysis, speech_type_analysis models and these models are dependants on the outputs of speech_to_text with speaker_seperation enabled.
Therefore a sample request for question_response modelwould look like this. (refer to the Example given below)

Sample Model Configuration

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{
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"txnId": "txn-dummy-1623245791219",
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"enableModels":[
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{
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"modelType":"speech_to_text",
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"modelConfig":{
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"speaker_seperation":{
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"num_speakers":2
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}
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}
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},
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{
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"modelType":"emotion_analysis"
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},
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{
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"modelType":"sentiment_analysis"
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},
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{
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"modelType":"speech_type_analysis"
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},
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# Question-response Model
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{
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"modelType":"question_response",
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"modelConfig":{
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"quality" : 1
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}
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}
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]
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}
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