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Einstein AI
Supported Operations
Chat

[Chat] Operations

[Chat] Answer Prompt

The Chat answer prompt operation is a simple prompt request operation to the configured LLM. It uses a plain text prompt as input and responds with a plain text answer.

Chat Answer Prompt

Input Fields

Module Configuration

This refers to the Einstein AI configuration set up in the getting started section.

General Operation Field

  • Prompt: This field contains the prompt as plain text for the operation.

Additional Properties

  • Model Name: The model name to be used (default is OpenAI GPT 3.5 Turbo).
  • Probability: The model's probability to stay accurate (default is 0.8).
  • Locale: Localization information, which can include the default locale, input locale(s), and expected output locale(s) (default is en_US).

XML Configuration

Below is the XML configuration for this operation:

<mac-einstein:chat-answer-prompt 
  doc:name="Chat answer prompt" 
  doc:id="66426c0e-5626-4dfa-88ef-b09f77577261" 
  config-ref="Einstein_AI" 
  prompt="#[payload.prompt]"
/>

Output Field

This operation responds with a string payload.

Example Use Cases

The chat answer prompt operation can be used in various scenarios, such as:

  • Customer Service Agents: For customer service teams, this operation can provide quick responses to customer queries, summarize case details, and more.
  • Sales Operation Agents: For sales teams, it can help generate quick responses to potential clients, summarize sales leads, and more.
  • Marketing Agents: For marketing teams, it can assist in generating quick responses for social media interactions, creating engaging content, and more.

[Chat] Generate from Messages

The Chat generate from messages operation is a prompt request operation with provided messages to the configured LLM. It uses a plain text prompt as input and responds with a plain text answer.

Chat Generate from Messages

Input Fields

Module Configuration

This refers to the Einstein AI configuration set up in the getting started section.

General Operation Field

  • Messages: This field contains the messages from which you would like to generate a chat. Example payload can be found here (opens in a new tab).

Additional Properties

  • Model Name: The model name to be used (default is OpenAI GPT 3.5 Turbo).
  • Probability: The model's probability to stay accurate (default is 0.8).
  • Locale: Localization information, which can include the default locale, input locale(s), and expected output locale(s) (default is en_US).

XML Configuration

Below is the XML configuration for this operation:

<mac-einstein:chat-generate-from-messages 
  doc:name="Chat generate from messages" 
  doc:id="94fa27f3-18ce-436c-8a5f-10b8dbfa4ea3" 
  config-ref="Einstein_AI" 
  messages="#[payload.messages]"
/>

Output Field

This operation responds with a json payload.

Example Use Cases

The chat generate from messages operation can be used in various scenarios, such as:

  • Customer Service Agents: For customer service teams, this operation can generate responses based on previous messages, providing context-aware support and summarizing conversations.
  • Sales Operation Agents: For sales teams, it can help in drafting follow-up messages, summarizing interactions with clients, and generating responses to inquiries.
  • Marketing Agents: For marketing teams, it can assist in creating engaging follow-up messages, summarizing customer interactions, and generating content based on previous conversations.

[Chat] Answer Prompt with Memory

The Chat answer prompt with memory operation is very useful when you want to provide memory upon the conversation history for a multi-user chat operation.

Chat Answer Prompt with Memory

Input Fields

Module Configuration

This refers to the Einstein AI configuration set up in the getting started section.

General Operation Fields

  • Data: This field contains the prompt for the operation.
  • Memory Name: The name of the conversation. For multi-user support, you can enter the unique user ID.
  • Dataset: This field contains the path to the in-memory database for storing the conversation history. You can also use a DataWeave expression for this field, such as mule.home ++ "/apps/" ++ app.name ++ "/chat-memory.db".
  • Memory Name: Number of max messages to remember for the conversation defined in Memory Name. This field expects an integer value.

Additional Properties

  • Model Name: The model name to be used (default is OpenAI GPT 3.5 Turbo).
  • Probability: The model's probability to stay accurate (default is 0.8).
  • Locale: Localization information, which can include the default locale, input locale(s), and expected output locale(s) (default is en_US).

XML Configuration

Below is the XML configuration for this operation:

<mac-einstein:chat-answer-prompt-with-memory 
  doc:name="Chat answer prompt with memory" 
  doc:id="a1d7d0e0-a568-4824-9849-6f1ff03d6dee" 
  config-ref="Einstein_AI" 
  prompt="#[payload.prompt]" 
  memoryPath="#[payload.memoryPath]" 
  memoryName="#[payload.memoryName]" 
  keepLastMessages="#[payload.lastMessages]"
/>

Output Field

This operation responds with a json payload.

Example Use Cases

Wherever you want to provide a conversation history and its context to the LLM, this operation will be very useful.

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