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OpenAI (DALL-E & ChatGPT)

With OpenAI (DALL-E & ChatGPT) modules in Make, you can:

  • create chat or prompt completions

  • create edits and moderation

  • generate images

  • call APIs

To get started with OpenAI, you need an OpenAI account.

Note

Make modules support GPT-3.5, and GPT-4 models provided the user has access. If you do not have access, please join the waitlist to get access when capacity is available.

GPT-4 is currently in a limited beta version and is only accessible to those who have been granted access.

Connect OpenAI to Make

To connect OpenAI to Make, you need to obtain API Key and Organization ID from your account and insert them into the OpenAI module scenario.

  1. Log in to your OpenAI (DALL-E & ChatGPT) account.

  2. Go to your account page, click Create new Secret key, and copy it to a safe place.

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  3. Go to your account settings page and copy the Organization ID to your clipboard.

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  4. Log in to your Make account, insert an OpenAI (DALL-E & ChatGPT) module in your scenario, and click the Add button next to the Connection field.

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  5. In the Connection name field, enter a name for the connection.

  6. In the API Key field, enter the Secret Key copied in step 2.

  7. In the Organization ID field, enter the ID copied in step 3, and click Save.

You have successfully established the connection. You can now edit your scenario and add more OpenAI (DALL-E & ChatGPT) modules. If your connection needs reauthorization at any point, follow the connection renewal steps here.

Actions

Creates a completion for the provided prompt or chat

See the OpenAI model endpoint compatibility section for the list of supported models.

Note

If you do not have access to the GPT-4 models, please join the waitlist to get access when capacity is available.

GPT-4 is currently in a limited beta version and is only accessible to those who have been granted access.

Connection

Establish a connection to your OpenAI account.

Select Method

Select the option to choose the method to create a completion for the chat.

  • Create a Prompt Completion: supports models, gpt-4, gpt-4-0314, gpt-4-32k, gpt-4-32k-0314, gpt-3.5-turbo, gpt-3.5-turbo-0301

  • Create a Chat Completion: supports text-davinci-003, text-davinci-002, text-curie-001, text-babbage-001, text-ada-001, davinci, curie, babbage, ada

Note

Ensure you have access to the model you want to work with, and only models available for the account are listed for selection.

Model

Select or map the model you want to use.

Prompt

Enter the prompt for which you want to generate the completions.

Messages

Add the messages for which you want to create the completion by selecting the role and entering the message content.

For more information about chat completion, refer to the OpenAI documentation.

Max Token

The maximum number of tokens to generate in the completion. the default value is 16.

Temperature

Specify the sampling temperature to use.

A higher value means the model will take more risks. Try 0.9 for more creative applications and 0 (argmax sampling) for ones with a well-defined answer. Defaults to 1.

Top p

An alternative to sampling with temperature is called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. Defaults to 1.

N

The number of completions to generate for each prompt. Defaults to 1.

Creates a new edit for the provided input, instruction, and parameters.

Connection

Establish a connection to your OpenAI account.

Model

Select or map the model for which you want to create the edit.

Instruction

Instruction that tells the model about the process of editing the input.

Input

Text to use as a starting point for creating the edit.

Temperature

Specify the sampling temperature to use.

A higher value means the model will take more risks. Try 0.9 for more creative applications and 0 (argmax sampling) for ones with a well-defined answer. The default value is 1.

Top p

Specifies an alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass.

A value of 0.1 means only the tokens comprising the top 10% probability mass are considered.

The default value is 1.

N

Specifies the number of edits to generate for the input and instruction. The default value is 1.

Classifies if text violates OpenAI's Content Policy.

Connection

Establish a connection to your OpenAI account.

Input

Enter the text for which you want to create the moderation. The module will classify the content against OpenAI's Content Policy.

Generates an image with DALL E given a prompt.

Connection

Establish a connection to your OpenAI account.

Prompt

Details of the images you want to generate. The maximum number of characters allowed is 1000.

Size

The size of the images to generate. It must be one of 256x256512x512, or 1024x1024.

Response Format

The format in which the generated images are returned.

If you select Base64-encoded PNG, the raw PNG image can be obtained by using the IML function, toBinary(<module_no>.data[].b64_json; base64) in the subsequent modules.

N

The number of images to generate. Enter a number between 1 and 10.

Performs an arbitrary authorized API call.

Note

For the list of available endpoints, see OpenAI ChatGPT API Documentation.

Connection

Establish a connection to your OpenAI account.

URL

Enter a path relative to https://api.openai.com. For example, /v1/models.

Method

GET

to retrieve information for an entry.

POST

to create a new entry.

PUT

to update/replace an existing entry.

PATCH

to make a partial entry update.

DELETE

to delete an entry.

Headers

Enter the desired request headers. You don't have to add authorization headers; we already did that for you.

Query String

Enter the request query string.

Body

Enter the body content for your API call.

Examples of Use - List Models

The following API call returns all pages from your OpenAI account.

URL: /v1/models

Method: GET

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The search matches can be found in the module's Output under Bundle > Body > data

In our example, 69 models were returned:

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