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Node Details

  • Name: chatPromptTemplate

  • Type: ChatPromptTemplate

  • Version: 2.0

  • Category: Prompts

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Base Classes

  • ChatPromptTemplate

  • BasePromptTemplate

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Parameters

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Inputs

  1. System Message (Required)

    • Type: string

    • Description: Initial system message that sets the context or role for the AI

    • Example: "You are a helpful assistant that translates {input_language} to {output_language}."

  2. Human Message (Required)

    • Type: string

    • Description: Human message prompt added at the end of the message sequence

    • Example: “{text}”

  3. Format Prompt Values (Optional)

    • Type: JSON

    • Description: Variables specification for use in prompts

    • Example:

      {
  "input_language": "English",
  "output_language": "Spanish"
}

  4. Messages History (Optional)

    • Type: Tabs

    • Default: messageHistoryCode

    • Description: Additional messages after System Message for few-shot examples

    • Tabs:

      • Add Messages (Code)

        • Type: code

        • Description: Custom message history using JavaScript code

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Functionality

  1. Message Management

    • System message handling

    • Human message formatting

    • History integration

    • Variable substitution

  2. Template Processing

    • Dynamic execution

    • Code sandboxing

    • Context building

    • Error handling

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Use Cases

  1. Conversational AI

    • Customer service

    • Language translation

    • Task assistance

    • Knowledge base queries

  2. Context Management

    • Role definition

    • Few-shot learning

    • Conversation history

    • Dynamic responses

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Integration Notes

  • Uses @langchain/core/prompts

  • Supports JavaScript execution

  • Handles JSON parsing

  • Implements sandboxed environments

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Best Practices

  1. System Message Design

    • Clear instructions

    • Specific role definition

    • Consistent context

    • Appropriate constraints

  2. Message History

    • Relevant examples

    • Progressive complexity

    • Clear structure

    • Safe code execution

  3. Variable Management

    • Clear naming

    • Type consistency

    • Error handling

    • Default values

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Input/Output

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Input

  • The node takes in the defined parameters (system message, human message, prompt values, and optional message history).

  • If message history code is provided, it is executed in a sandboxed environment.

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Output

  • The node outputs a ChatPromptTemplate object that includes:

    • A system message

    • Optional message history (if provided and valid)

    • A human message

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Usage

This node is used to create structured chat prompts for language models. It’s particularly useful for:

  1. Setting up consistent system instructions across multiple interactions.

  2. Defining a standard format for human inputs.

  3. Incorporating few-shot examples or specific conversation context through the message history feature.

  4. Allowing for dynamic prompt creation by using variables in the system and human messages.

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Implementation Details

  • The node uses the @langchain/core/prompts library to create the chat prompt template.

  • It supports dynamic execution of JavaScript code for creating custom message histories.

  • The node handles JSON parsing for prompt values, allowing for variable substitution in the prompts.

  • Error handling is implemented for invalid JSON or message history code execution.

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Notes

  • The message history feature uses a sandboxed VM for executing user-provided code, ensuring safety and isolation.

  • The node is designed to be flexible, allowing for both simple prompt creation and more complex setups with custom message histories.

  • It integrates with a database (likely for storing or retrieving additional context), as indicated by the use of DataSource and IDatabaseEntity.