Function calling

In the playground, you can describe functions and have the LLM model intelligently choose to output a JSON object containing arguments to call one or many functions.

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Common use cases

Function calling allows you to get structured data back from the model more reliably. For example, you can:

• Create assistants that answer questions by calling external APIs (e.g., like ChatGPT Plugins)
  • e.g. define functions like send_email(to: string, body: string), or get_current_weather(location: string, unit: ‘Celsius’ | ‘Fahrenheit’)
• Convert natural language into API calls
  • e.g., convert “Who are my top customers?” to get_customers(min_revenue: int, created_before: string, limit: int) and call your internal API
• Extract structured data from text
  • e.g. define a function called extract_data(name: string, birthday: string), or sql_query(query: string)
• Classification tasks
  • e.g., define a function schema that has an enum for the class [“Type1”, “Type2”] and instruct the model to select only one based on some input

…and much more!

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Adding functions to your prompt

For supported models, you can click the Add function(s) button, which will open a modal to add existing functions to your prompt or allow you to create a new one.

Functions are version-controlled. You can select the version of the functions you want and then click the switch to enable the functions.

You can also create a new function by defining your function JSON schema in the editor. The parameters the function accepts should be described as a JSON Schema object. See the OpenAI guide for examples, and the JSON Schema reference for documentation about the format. To describe a function that accepts no parameters, provide the value { "type": "object", "properties": {} }.

Copying an existing from your IDE, click the Fix schema button to fix the formatting automatically. Fix schema ensures you are following OpenAI json schema requirements. Changes made include:

• Ensuring name matches regex: ^[a-zA-Z0-9_-]{1,64}$
• Replacing spaces and special characters in property names with hyphens
• Ensuring the required list has updated property names and has the correct placement

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Setting Response format to JSON

Alternatively, you can force some OpenAI & Mistral models to response with JSON by setting the response format to json_object. Note, setting response format to json_object will require you to use the word JSON in your prompt.