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Node Inputs

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Required Fields

Instructions:
Custom instructions provided to the LLM for task execution. Use dynamic variables ({{myVariable}}) to personalize input.
Example: "Write a story about F1 driver loosing the championship for this driver {{driver}} with the team {{team}}"

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Optional Fields

Tools:
Defines the tools or functions the agent can call during its execution.
Example: "Scrapper" Datasources:
Specifies the data sources the agent can access or query.
Example:
  Datasource: "Internal company knowledge"
  Instructions block: 
{Your instruction}  

Here is the data source you will be working with: "Internal company knowledge"
Advanced Settings:
Allows configuration of advanced LLM parameters such as temperature, token limits, and output formats. (see “Node AI Settings” for more information)

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Node AI Settings

Model:
Select the LLM model to be used.
Example: GOOGLE_VERTEXAI - gemini-1.5-pro-002 Temperature:
Controls creativity and randomness in responses.
  • Lower values (e.g., 0.2) make outputs more deterministic.
  • Higher values (e.g., 0.8) increase creativity.
Max Output Tokens:
Sets the maximum number of tokens in the response.
Example: 1000 Top K:
Restricts the response to the top K most likely tokens.
Example: 40 Top P:
Adjusts the probability distribution for token selection.
Example: 1 (uses the full distribution). Output JSON Schema:
Define the format of the response in JSON schema if structured output is required.
Example: 
{
  "summary": "string",
  "keywords": ["string"]
}

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Node Output

Output:
The response generated by the LLM based on the provided instructions, tools, and datasources.
Example Output: 
{
  "summary": "Coffee beans are essential for brewing high-quality espresso.",
  "keywords": ["coffee beans", "espresso", "grinding"]
}

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Node Functionality

The Agent node:
  • Leverages LLMs for dynamic task processing and natural language interactions.
  • Integrates tools and datasources to expand functionality and enrich outputs.
  • Offers customization through advanced LLM settings for tailored responses.
  • Supports structured outputs via JSON schema for compatibility with other systems.