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. The secret name of this is openai-default-secret
.
If you do not specify otherwise, this AI backend secret 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 user’s request.
Here are some examples where this feature could be helpful:
Automatically forward emails with a summary to the responsible internal team
Scan any email sent to a given inbox such as info@mycompany.tld for example, find out the intention of the sender, then forward the email to the internal team such as support, sales, … which can handle the request. The AI can find out the type of request, whether it is a support request, an order request, a question regarding an invoice or any other type just by writing an advice to the AI and without any programming. It can also detect and extract all required data such ascustomerId
,invoiceNumber
and more from the sender’s email. Furthermore, it can also create a short summary about what the core intent of the sender is to make it easier for the internal team to process the request.Automatically validate and start an internal workflow by email
Scan any email sent to a given inbox such as invoice@mycompany.tld for example and if this email matches to an existing workflow, extract all variables required for this workflow from the email, start the workflow and pass these variables along with it. For example to start an accounts payable workflow based on an given payable invoice. The AI can validate whether all required data exist and is valid in order to start the workflow.Automatically call endpoints of other systems by email
Scan any email sent to a given inbox such as info@mycompany.tld for example and if this email is related to a service, offered by a third party system which provides an remote API, call this remote API (for example REST) and pass along parameters extracted from the email. For example create a new ticket on an external ticket system.
Using command ai.intent.detect
In order to integrate Text-to-Command functionality into your automation pipelines, you can use the command ai.intent.detect
. It will
take a text, for example like an email as input,
will apply the given AI instructions on this text and
finally will select a command to be executed.
Here is a first example how this could look like in an automation pipeline:
body: | From: customer@somedomain.tld Subject: I have a problem with your product Hello, I have a big problem with your product and need support. My customer id is 123456. Cheers, Valued Customer pipeline: - ai.command.detect: runDetectedCommand: true advice: intentCandidates: - intentId: "forwardToSupport" instruction: "Use this intent in case the sender needs product support." targetCommand: "mail.send" params: to: value: "support@internal.tld" from: instruction: "The email address of the sender." subject: instruction: "Use the subject of the sender's email." message: instruction: "Use the message of the sender's email." - intentId: "forwardToInfo" instruction: > Use this intent in case the sender's intent could not be detected. targetCommand: "mail.send" params: to: value: "info@internal.tld" from: instruction: "The email address of the sender." subject: instruction: "Use the subject of the sender's email." message: instruction: "Use the message of the sender's email."
As you can see in this example, there are two command intents configured:
One intent will forward the customer email to the support team (=
forwardToSupport
) andthe other one to the info team in case it is related to any other topic (=
forwardToInfo
).
Each intent has an instruction
in order to instruct the AI about the criteria to select this intent. In case such an intent is selected by AI, there is the targetCommand
field defining the name of the command which must be called. In this example this is the mail.send
command.
Intent Parameters
The params
section on each intent lists the parameters required to call the command. For the mail.send
command these are for example the parameters to
, from
, subject
and message
. The values of these parameters can be fixed, templated or can be detected by the AI.
All parameter attributes are explained below.
name
(optional)
The name of the parameter. Under this name it will be passed to the command.
This attribute is optional. If not set, the params id will be used.
required
(optional)
Defines whether this parameter is required. In case it is required and its value is finally missing or cannot be detected by AI, an error is thrown and further execution stops.
The default value is false
.
type
(optional)
The data type of the parameter such as string
, boolean
, integer
, number
.
If different from string and parameter is detected by AI, the AI also tries to convert to this format.
The default value is string
.
value
(optional)
The value
of an intent parameter defines the value to be passed to the command.
This can be a fixed value (literal) or a template. By default the Mustache template syntax can be used which starts with {{
and ends with }}
. The variables advice
and intent
are passed as model context to the template. This way you can access for example settings and values of other parameters after they have been resolved by the AI in order to formulate the final parameter for a command.
See this example to construct a message out of advice parameters using a template:
... targetCommand: "mail.send" ... params: message: value: "The customerId is: {{advice.params.customerId}}" ...
Here is a more advanced example to pass auto-detected parameters into the command worklow.start
as workflow variables using the parameter variables
:
... targetCommand: "workflow.start" ... params: variables: value: customerId: "{{advice.params.customerId}}" customerName: "{{advice.params.customerName}}" ...
instruction
(optional)
For each parameter, an attribute instruction
instead of a value
can be set. Not both!
In this case the AI will auto-detect the parameter value by reading and applying this instruction on the input and setting the result on the value field automatically.
See this example where the subject
parameter for the mail.send
command will be auto-detected by AI:
... targetCommand: "mail.send" ... params: subject: instruction: "Use the subject from initial sender email" ...
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