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Clarifai API Python Client

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This Python client provides a simple wrapper around our powerful image recognition API.

The client supports basic tagging with existing models.

The client also uses Applications to store images and visually search across them. You can either do a simple visual search or also add predictions for any, all or none, as noted in the directions below.


The API client is available on Pip. You can simply install it with a pip install

pip install clarifai --upgrade

For more details on the installation, please refer to


The client uses your "CLARIFAI_API_KEY" to get an access token. Since this expires every so often, the client is setup to renew the token for you automatically using your credentials so you don't have to worry about it.

You can get the api_key from and config them for client's use by

$ clarifai config
CLARIFAI_API_KEY: []: ************************************YQEd

The config will be stored under ~/.clarifai/config for client's use

Environmental variable CLARIFAI_API_KEY will override the settings in the config file.

For AWS or Windows users, please refer to for more instructions.

Getting Started

The following example will setup the client and predict from our general model

from import ClarifaiApp

app = ClarifaiApp()
model = app.public_models.general_model
response = model.predict_by_url(url='')

If wanting to predict a local file, use predict_by_filename.

The response is a JSON structure. Here's how to print all the predicted concepts associated with the image, together with their confidence values.

concepts = response['outputs'][0]['data']['concepts']
for concept in concepts:
    print(concept['name'], concept['value'])


Read more code examples and references at