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In this section, we present how to bring Cohere models to MindsDB. Cohere offers world-class generative models and industry-best retrieval capabilities, which is the key combination to unlocking Generative AI value for the enterprise. Read on to find out how to use Cohere models within MinsdDB.

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Setup

MindsDB provides the Cohere handler that enables you to create Cohere models within MindsDB.

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AI Engine

Before creating a model, it is required to create an AI engine based on the provided handler.
If you installed MindsDB locally, make sure to install all Cohere dependencies by running pip install .[cohere] or from the requirements.txt file.
You can create an Cohere engine using this command: 
CREATE ML_ENGINE cohere_engine
FROM cohere
USING
    api_key = 'your-cohere-api-key';
Please note that you need to provide your Cohere API key. Once you sign up for a Cohere account, an API key can be requested from the Cohere dashboard. Learn more here.
The name of the engine (here, cohere_engine) should be used as a value for the engine parameter in the USING clause of the CREATE MODEL statement.

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AI Model

The CREATE MODEL statement is used to create, train, and deploy models within MindsDB. 
CREATE MODEL cohere_model
PREDICT language
USING
    task = 'language-detection',
    column = 'text',
    engine = 'cohere_engine'
Where:
NameDescription
taskIt defines the task to be accomplished.
columnIt defines the column with the text to be acted upon.
engineIt defines the Cohere engine.
api_keyIt is used to provide your Cohere API key to gain access to the model.

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Usage

Once you have created an Cohere model, you can use it to make predictions. 
SELECT text, language
FROM mindsdb.cohere_model
WHERE question = 'Здравствуй, Мир';
On execution, we get: 
+----------------------------+
| text            | language |
+----------------------------+
| Здравствуй, Мир |  Russian |
+----------------------------+

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Supported Tasks

The following tasks are supported by the Cohere handler:
  • language-detection: detect the language of a given text.
  • text-generation: generate text based on a given prompt.
  • text-summarization: summarize a given text.
For more information about the Cohere handler, visit the repository here.
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