POST
/
api
/
projects
/
{projectName}
/
models
/
{modelName}
/
predict
This endpoint fetches predictions from the model.
curl --request POST \
  --url http://127.0.0.1:47334/api/projects/{projectName}/models/{modelName}/predict \
  --header 'Content-Type: application/json' \
  --data '[
  "<any>"
]'
import requests
url = 'http://127.0.0.1:47334/api/projects/mindsdb/models/home_rentals_model/predict'

data = [{'number_of_rooms': 2,
  'number_of_bathrooms': 1,
  'sqft': 917,
  'location': 'great',
  'days_on_market': 13,
  'neighborhood': 'berkeley_hills',
  'rental_price': 3901,
  'created_at': '2024-02-24 02:28:21.746167'},
 {'number_of_rooms': 0,
  'number_of_bathrooms': 1,
  'sqft': 194,
  'location': 'great',
  'days_on_market': 10,
  'neighborhood': 'berkeley_hills',
  'rental_price': 2042,
  'created_at': '2024-02-19 06:10:59.693052'},
 {'number_of_rooms': 1,
  'number_of_bathrooms': 1,
  'sqft': 543,
  'location': 'poor',
  'days_on_market': 18,
  'neighborhood': 'westbrae',
  'rental_price': 1871,
  'created_at': '2024-02-12 07:53:45.914146'}]

r = requests.post(url, json={'data': data})
print(r.json())

There are two ways to get batch predictions:

  1. Join the model with data tables and use the query endpoint to query for batch predictions.
  2. Query the model using this endpoint and provide data to be used by the model in the request.
import requests
url = 'http://127.0.0.1:47334/api/projects/mindsdb/models/home_rentals_model/predict'

data = [{'number_of_rooms': 2,
  'number_of_bathrooms': 1,
  'sqft': 917,
  'location': 'great',
  'days_on_market': 13,
  'neighborhood': 'berkeley_hills',
  'rental_price': 3901,
  'created_at': '2024-02-24 02:28:21.746167'},
 {'number_of_rooms': 0,
  'number_of_bathrooms': 1,
  'sqft': 194,
  'location': 'great',
  'days_on_market': 10,
  'neighborhood': 'berkeley_hills',
  'rental_price': 2042,
  'created_at': '2024-02-19 06:10:59.693052'},
 {'number_of_rooms': 1,
  'number_of_bathrooms': 1,
  'sqft': 543,
  'location': 'poor',
  'days_on_market': 18,
  'neighborhood': 'westbrae',
  'rental_price': 1871,
  'created_at': '2024-02-12 07:53:45.914146'}]

r = requests.post(url, json={'data': data})
print(r.json())

The REST API endpoints can be used with MindsDB running locally at http://127.0.0.1:47334/api.

Path Parameters

​
projectName
string
required

The name of the project

​
modelName
string
required

The name of the model

Body

application/json · any[]

The body is of type any[].

Response

200
application/json

Model queried succesfully

The response is of type object.