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bk-chat-helper

Provide a modular chat-helper SDK for agent, session, and message workflows.

Updated Feb 2, 2026
Search Tags:#integration#vue#sdk#streaming#session-management#http#ai-chat
One-click install
npx skills add https://github.com/forrany/Agent-configs --skill bk-chat-helper
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bk-chat-helper
Source: https://github.com/forrany/Agent-configs/tree/main/skills/bk-chat-helper
Command: npx skills add https://github.com/forrany/Agent-configs --skill bk-chat-helper

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Building AI chat applications requires orchestrating UI, API calls, streaming responses, and session management across components. This Skill provides a modular chat-helper SDK that centralizes agent, session, and message workflows to accelerate development and ensure consistent behavior.

Core Features & Use Cases

  • Modular architecture: separate agent, session, message, and http modules with clear boundaries.
  • Streaming support: handle streaming responses to render AI messages in real time.
  • UI integration: seamless cooperation with bk-chat-x to build end-to-end AI chat experiences.
  • Use Case: quickly prototype a multi-user chat assistant by wiring an HTTP backend to agent.chat and managing sessions.

Quick Start

  • Install the SDK: pnpm add @blueking/chat-helper
  • Initialize with a minimal configuration: use useChatHelper with requestData.urlPrefix and optional interceptors (see references/api-reference.md)
  • Start a simple flow: agent.getAgentInfo(), session.getSessions(), and agent.chat("hello", session.current.value?.sessionCode || "default")

Frequently Asked Questions about bk-chat-helper

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

FAQPage Schema
How do I manage AI chat sessions and streaming responses in a Vue application?▼

To manage AI chat sessions and streaming responses in a Vue application, you can use a modular chat-helper SDK that centralizes agent, session, and message workflows while providing real-time streaming UI integration.

What is the best way to structure an AI chat SDK for multi-user session management?▼

The best way to structure an AI chat SDK for multi-user session management is using a modular architecture with separate agent, session, message, and http modules, ensuring clear boundaries and scalable end-to-end conversation handling.

How do I configure HTTP interceptors for an AI chat API integration?▼

You configure HTTP interceptors for an AI chat API integration by initializing the SDK with a request data URL prefix and optional interceptors, allowing customizable request and response handling across the http module.

Can I use this chat-helper SDK to wire an HTTP backend for real-time agent conversations?▼

Yes, you can use this chat-helper SDK to wire an HTTP backend for real-time agent conversations by calling agent.chat and managing sessions, quickly prototyping multi-user chat assistant experiences with configurable protocol events.

Does this AI chat integration library support extensible protocol events for scalable development?▼

Yes, this AI chat integration library supports extensible protocol events for scalable development, allowing developers to customize agent, session, and message workflows alongside configurable request and response interceptors.

Why are my streaming AI messages not rendering correctly during end-to-end conversations?▼

Streaming AI messages may not render correctly if the chat-helper SDK's streaming support is improperly configured with the bk-chat-x UI integration, requiring proper session and message workflow synchronization across modules.

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