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What is the AI Studio?

SINCE 11 - BETA

The AI Studio is a set of tools and UI components seamless integrated into PIPEFORCE to boost your process automation and data integration tasks to a next level using artificial intelligence such as LLM (Large Language Models) for example.

BETA

Note that the AI Studio components including all ai.* commands are in BETA. This means definitions, interfaces and documentation is not final and could change without further notice.

Configure AI Backend (secret)

Before you can start, an AI backend needs to be configured. Depending on your license, by default PIPEFORCE comes with it’s own built-in AI backend which is located in Germany.

If you do not specify otherwise, this AI backend is used by default.

But you can switch this default backend or use multiple AI backends in parallel. To do so, you have to configure the credentials and settings for those AI backends as secrets of type secret-text and place a JSON into the secret value which has a structure like this:

{
  "base_url": "string",
  "model": "string",
  "api_token": "string",
  "max_token": "integer",
  "custom_headers": { "name": "value" }
} 

Whereas:

  • base_url: The base url of the API (requried).

  • model: The AI model to be used (required).

  • api_token: The security token to be used.

  • max_token: The max token to be send (defaults to 800)

  • custom_headers: Key-value pairs to be passed along as HTTP headers on any request.

Connect to OpenAI (ChatGPT)

In case you would like to connect to the OpenAI services for example, you could use these settings in your secret:

{
  "base_url": "https://api.openai.com/v1",
  "model": "gpt-3.5-turbo",
  "api_token": "your_token",
  "max_token": 800
} 

Text-to-Command

This powerful feature of the AI Studio takes a non-structured text such as an email, a chat message or a PDF document for example, analyses it using AI and then automatically detects and executes the according PIPEFORCE command including its parameters which must be executed in order to take action and fulfill the use request. Here are some examples where this feature could be helpful:

  • Classify and auto-route customer emails
    Scan any email sent to a given inbox such as info@mycompany.abc

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