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POST
/
infer
curl -s -X POST "https://inference.impulselabs.ai/infer" \
  -H "Authorization: Bearer $IMPULSE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "deployment_id": "clf-titanic-survived",
    "inputs": {
      "Pclass": 3,
      "Sex": "male",
      "Age": 22,
      "SibSp": 1,
      "Parch": 0,
      "Fare": 7.25,
      "Embarked": "S"
    }
  }'

{
  "prediction": 0,
  "probability": 0.142,
  "target": "Survived"
}

​
Authentication

Pass your imp_ API key as a Bearer token: 
Authorization: Bearer imp_your_key_here
Your user_id is resolved server-side from the key — do not include it in the request body.

​
Request body

​
deployment_id
string
required
The ID of the deployed model to call. Find this on the Models page in the dashboard.Example: clf-titanic-survived
​
inputs
object
required
A JSON object mapping feature column names to their values, exactly as they appear in the training dataset.
{
  "Pclass": 3,
  "Sex": "male",
  "Age": 22,
  "Fare": 7.25
}

​
Response

​
prediction
any
The model’s output. For classification models this is the predicted class label (e.g. 0 or "yes"). For regression models it is a numeric value.
​
probability
number | null
Confidence score between 0 and 1 for the predicted class. Present for classification models, null for regression.
​
target
string | null
The name of the target column the model was trained to predict.

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Rate limit headers

Every response includes standard rate-limit headers:
HeaderDescription
X-RateLimit-LimitRequests allowed in the current 60-second window
X-RateLimit-RemainingRequests remaining in the current window
X-RateLimit-ResetUnix timestamp when the window resets
Retry-AfterSeconds to wait before retrying (only on 429)
curl -s -X POST "https://inference.impulselabs.ai/infer" \
  -H "Authorization: Bearer $IMPULSE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "deployment_id": "clf-titanic-survived",
    "inputs": {
      "Pclass": 3,
      "Sex": "male",
      "Age": 22,
      "SibSp": 1,
      "Parch": 0,
      "Fare": 7.25,
      "Embarked": "S"
    }
  }'

{
  "prediction": 0,
  "probability": 0.142,
  "target": "Survived"
}