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Maitai’s Portal exposes a Configuration panel at multiple scopes so you can tune behavior without shipping code changes.

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Where to configure

In the Portal, configuration appears in these places:
  • Application: /application/:applicationId → Configuration
  • Intent Group: /intent-group/:intentGroupId → Configuration
  • Intent (ApplicationAction): /application/:applicationId/intent/:actionId → Configuration
  • Test Run: the Test Run wizard includes a configuration step used for that run
config portal

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Common patterns

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Enable evaluations + corrections

  • Turn on Evaluations
  • Optionally turn on Apply Corrections
    • This toggle is only available when evaluations are enabled.
    • Enabling corrections unlocks Safe Mode.

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Add a secondary model + fallback behavior

  • Select a Secondary Model
  • Choose a Fallback Strategy
  • Optionally set a Fallback Timeout (only appears for timeout strategy)

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Make output more deterministic

  • Lower Temperature
  • Use a Stop Sequence
  • Set Max Tokens

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Parameters available in the Portal Configuration panel

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Inference Location
Client or Server
Controls where inference is executed.
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Reasoning Effort
string
Controls the model’s reasoning depth when supported by the selected model.
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Evaluations
boolean
default:true
Enables Sentinel evaluation for requests at this scope.
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Apply Corrections
boolean
default:false
Corrections are only available for Server inference, and require Evaluations to be turned on.
Enables automatic correction behavior when evaluations identify faults.
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Safe Mode
boolean
default:false
Safe mode prioritizes accuracy over latency. Only available when Apply Corrections is enabled.
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Model
string
Primary AI model to be used for inference. Models are grouped by provider and sorted alphabetically, with Maitai models (recommended) appearing first.
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Secondary Model
string
Optional fallback model to use if the primary model is not available or has degraded performance.
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Fallback Strategy
string
default:"reactive"
Strategy to use when falling back to secondary model. Options:
  • reactive: Falls back on primary model failure
    • If a timeout is specified, it will initiate the fallback request after the timeout period
  • timeout: Falls back after specified timeout period
  • first_response: Uses whichever model responds first
    • If a timeout is specified, it will only use the fallback model after the timeout period
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Fallback Timeout
number
Timeout in seconds before falling back to secondary model. Only applicable when using the “timeout” fallback strategy.
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Temperature
number
default:1
Controls randomness in the model’s output. Range 0-2, where:
  • Lower values (e.g., 0): More deterministic output
  • Higher values (e.g., 2): More random output
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Stop Sequence
string
Sequences where the API will stop generating further tokens.
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Log Probs
boolean
default:false
Include the log probabilities of the output tokens.
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N
integer
default:1
How many completions to generate for each prompt.
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Max Tokens
integer
The maximum number of tokens to generate in the completion.
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Presence Penalty
number
default:0
Range -2 to 2. Increases the model’s likelihood to talk about new topics.
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Frequency Penalty
number
default:0
Range -2 to 2. Decreases the model’s likelihood to repeat the same line verbatim.