bx-ai-chatting

Wrap BoxLang aiChat, aiChatAsync, and aiChatStream with provider and parameter management.

Updated Apr 10, 2026
One-click install
npx skills add https://github.com/ortus-boxlang/skills --skill bx-ai-chatting
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: bx-ai-chatting
Source: https://github.com/ortus-boxlang/skills/tree/main/boxlang-modules/bx-ai/bx-ai-chatting
Command: npx skills add https://github.com/ortus-boxlang/skills --skill bx-ai-chatting

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Writing BoxLang AI chat integrations often requires repeated boilerplate to wire aiChat(), aiChatAsync(), and aiChatStream() with standardized parameters, provider handling, and error management.

Core Features & Use Cases

  • aiChat(), aiChatAsync(), and aiChatStream() wrappers that unify interaction with different providers.
  • Parameter management for temperature, max_tokens, model, top_p, and stop sequences.
  • Provider selection and API key management, including return formats and streaming support.
  • Support for multi-turn conversations and robust error handling to recover gracefully in production.

Quick Start

Call aiChat with a user message and optional params to obtain a response.

Frequently Asked Questions about bx-ai-chatting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement multi-turn AI chat in BoxLang without writing repetitive boilerplate?

Multi-turn AI chat in BoxLang is simplified by wrapping aiChat() calls with standardized parameters for provider handling and error management. This eliminates repetitive boilerplate wiring by unifying interaction across different providers and managing conversation state automatically.

How do I stream AI chat responses in BoxLang?

Streaming AI chat responses in BoxLang is handled by the aiChatStream() wrapper. It manages provider selection, API keys, and return formats to deliver continuous response chunks, allowing real-time output processing while maintaining standardized error handling.

Can I manage temperature, max_tokens, and model selection for AI chat in BoxLang?

Temperature, max_tokens, model selection, top_p, and stop sequences are fully supported as manageable parameters within BoxLang AI chat wrappers. These settings can be passed directly to aiChat() or aiChatAsync() to control response generation behavior across chosen providers.

What is the best way to handle asynchronous AI chat calls in BoxLang?

Asynchronous AI chat calls in BoxLang are best handled using the aiChatAsync() wrapper. It unifies provider interaction and API key management while executing non-blocking requests, returning results in a standardized format with built-in error recovery for production environments.

Does BoxLang AI chat support multiple API providers with different return formats?

BoxLang AI chat wrappers support multiple API providers by unifying interaction across them. Provider selection and API key management are handled internally, including mapping different return formats and streaming support to ensure consistent output handling.

How do I handle errors and API key configuration when integrating AI chat in BoxLang?

Error handling and API key configuration for BoxLang AI chat integration are managed through the unified wrappers. They support robust error recovery to gracefully handle production failures while securely managing provider-specific API keys and return formats.