Creates a new AI session for interaction with Large Language Models (LLMs).
The session maintains conversation history and context between interactions.
Each session can be configured with different parameters to optimize for specific use cases like code analysis, content generation, or data processing.
Common usage patterns:
- Exception analysis and debugging assistance
- Code documentation generation
- Query optimization suggestions
- Security review assistance
- Performance optimization recommendations
The session persists until explicitly terminated or the application restarts.
Lucee Function Reference
luceecreateaisession,aicreatesession()
Example
luceecreateaisession,aicreatesession(string name,[string systemMessage,[numeric limit,[numeric temperature]]]):object
Arguments
The arguments for this function are set. You can not use other arguments except the following ones.
| Name | Type | Required | Default Value | Description |
|---|---|---|---|---|
| name | string | Yes |
Specifies which AI endpoint configuration to use. Can be provided in two formats: 1. Direct endpoint name: The name of an endpoint as defined in the Lucee Administrator (similar to how datasource names work) 2. Default reference: Using the format "default:category" to use the endpoint configured as the default for that specific category in the Lucee Administrator. Currently supported default categories: The endpoint configurations and their default category assignments are managed in the Lucee Administrator. |
|
| systemMessage | string | No |
Initial instruction set that defines the AI's behavior and expertise for this session. This message sets the context and rules for all subsequent interactions. Best practices: The system message persists throughout the session and influences all responses. |
|
| limit | numeric | No | 50 |
Maximum number of question-answer pairs to keep in the conversation history. Once reached, older messages will be removed. Consider: |
| temperature | numeric | No | 0.7 |
Controls response randomness (0.0 to 1.0). Lower values make responses more focused and deterministic, higher values make them more creative and varied. Recommended settings: For exception analysis and debugging, lower temperatures (0.2-0.3) are recommended for more consistent and precise responses. |