Ahoo Wang
@ahoo-wang
Systems Architect focused on high-performance, scalable AI systems, using agent orchestration with DDD/CQRS/Event Sourcing.
9
Published Tools
15
Total Stars
1,180
Weekly Downloads
271
GitHub Followers
34
Public Repos
Published Tools
9 Skillsacross 3 categoriesGitHub Actions
Server-Sent Events (SSE) support for Fetcher HTTP client with native LLM streaming API support. Enables real-time data streaming and token-by-token LLM response handling.
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Type-safe OpenAI API client for Fetcher ecosystem. Provides seamless integration with OpenAI's Chat Completions API, supporting both streaming and non-streaming responses with full TypeScript support.
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A lightweight, cross-environment storage library with key-based storage and automatic environment detection. Provides consistent API for browser localStorage and in-memory storage with change notifications.
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TypeScript decorators for clean, declarative API service definitions with Fetcher HTTP client. Enables automatic parameter binding, method mapping, and type-safe API interactions.
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React integration for Fetcher HTTP client. React hooks that turn cancellable requests into component state, plus security, storage and event-bus bindings.
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Enterprise-grade CoSec authentication integration for the Fetcher HTTP client with comprehensive security features including automatic token management, device tracking, and request attribution.
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OpenAPI Specification TypeScript types for Fetcher - A modern, ultra-lightweight HTTP client for browsers and Node.js. Provides complete TypeScript support with type inference for OpenAPI 3.x schemas.
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Fetcher is not just another HTTP client—it's a complete ecosystem designed for modern web development with native LLM streaming API support. Built on the native Fetch API, Fetcher provides an Axios-like experience with powerful features while maintaining
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Generates TypeScript models, Fetcher decorator clients and Wow command and query clients from a local or remote OpenAPI 3 document. The Wow clients follow the CQRS model of the Wow DDD framework (https://github.com/Ahoo-Wang/Wow).
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