💡 GitHub Repository:
📌 1. Introduction: Do We Really Need Another Request Library?
In modern frontend engineering, network requests are much more complex than simply fetching some JSON data. Around every API call, developers must wrestle with four persistent daily headaches:
The "Human Converter" Interface Tax: When backend developers hand you nested JSON responses containing dozens or hundreds of fields, you either manually write TypeScriptinterfacesby hand, or constantly paste them into unstable online formatters. Whenever an API field changes, updating types turns into a maintenance nightmare.
Fragmentation Across Runtimes: Standard browser code usesfetchoraxios. But WeChat Mini-programs and uni-app require proprietary wrapper APIs (wx.requestoruni.request). Meanwhile, SSR contexts (like Nuxt/Next) require server-compatible clients. You end up maintaining three separate copies of headers, interceptors, and error handlers.
Concurrent 401 Silent Token Refresh: When an auth token expires and multiple parallel requests hit the backend simultaneously, how do you cleanly pause all requests, push them into an execution queue, send exactly one token refresh request, and replay the queue with the fresh credentials without causing deadlocks?
AI Assistant Hallucinations: In the era of AI-driven coding, tools like Cursor and GitHub Copilot frequently make up parameters, suggest obsolete APIs, or generate buggy fetch functions, wasting your time on debug cycles.
To solve these exact challenges, we built and open-sourced
endpoint-plus— a next-generation, cross-platform request client and developer tooling suite designed to free developers from manual typing, multi-platform runtime discrepancies, and repetitive API configurations.
🏗️ 2. Core Architecture: The Power of Decoupling
endpoint-plusavoids the monolithic overhead of traditional request clients by introducing a highly abstract physical Transport Layer alongside a pluggable middleware pipeline.
CODEgraph TD
A[API Calls in Application Code] --> B[endpoint-plus Core Client]
B --> C[Interceptors & Onion-Model Middleware]
C --> D[Transport Layer Interface]
D -- Web / Node SSR --> E[Fetch / Axios Transport]
D -- Miniapp / uni-app --> F[Miniapp Transport]
B <--> G[Vite DevTools Plugin]
G -- TS Compiler AST Scan --> H[Scan Source Code]
G -- Capture Real Response --> I[Schema Inference quicktype]
I --> J[Write local endpoint-types.d.ts]
1. Swappable Physical Transports
By splitting request definition from the actual underlying network implementation,
endpoint-plusprovides 100% unified code semantics. You simply swap the transport adapter upon client creation:
Standard Fetch (lightweight, zero external dependencies, recommended for modern browsers and Node 22+):
CODEimport { createInstance, createFetchTransport } from 'endpoint-plus';
const api = createInstance({ transport: createFetchTransport() });
Mini Program & uni-app (handles platform-specific requests, file uploads, and downloads):
CODEimport { createMiniappTransport } from 'endpoint-plus/miniapp';
const api = createInstance({ transport: createMiniappTransport({ runtime: wx }) });
Axios Transport (perfect for projects that require upload progress monitoring or legacy configurations):
CODEimport { createAxiosTransport } from 'endpoint-plus/transports/axios';
const api = createInstance({ transport: createAxiosTransport() });
2. Onion-Model Middleware
In addition to traditional request/response interceptors,
endpoint-plusintroduces a Koa/Express-style Onion-Model Middleware system. This lets you wrap the entire execution lifespan using async functions:
CODEapi.registerRequestMiddleware(async (config, next) => {
const start = Date.now();
try {
// 1. Outer Onion layer: Executed before request dispatch
const response = await next(config);
// 2. Inner Onion layer: Executed after response resolves
console.log(`Request to ${config.url} took ${Date.now() - start}ms`);
return response;
} catch (error) {
// 3. Centralized error catching and circuit-breaking
console.error('Middleware caught exception:', error);
throw error;
}
});
🔮 3. TypeScript Type Gymnastics: Compile-Time Path Pattern Matching
This is the killer type-safety feature of
endpoint-plus: You do not need to manually cast generic arguments on every request. TypeScript parses the URL string and infers the correct response type directly at compile-time.
For instance, once you declare your routes in a
.d.tsfile:
CODEdeclare module 'endpoint-plus' {
namespace YwEndpoint {
interface Routes {
'GET /users': { response: User[] };
'GET /users/:userId': { response: User };
'POST /users': { response: User };
}
}
}
Your editor instantly provides type-safety and autocompletion:
CODE// 🌟 TypeScript 5.0+ const generic parameter pattern matching
const userList = await api.get('/users');
// ^? User[] (Inferred from GET /users)
const user = await api.get('/users/123');
// ^? User (Even with a concrete ID '123', the parser matches it against ':userId' to return User)
// ❌ Typos and invalid paths are caught instantly by the compiler!
const err = await api.get('/usrs'); // TS Compiler Error
🧠 How the Type Parser Works Under the Hood
We leverage recursive conditional types to strip URL queries, hash anchors, and domain prefixes, parsing the path into segments and pattern-matching them against parameter templates:
CODEtype EndpointRoutePathMatches<
TRoutePath extends string,
TUrl extends string,
> = EndpointPathSegmentsMatch<
EndpointSplitPath<TRoutePath>,
EndpointSplitPath<EndpointUrlPath<TUrl>>
>;
This ensures strict backend-to-frontend type alignment without requiring heavy code-generation steps during hot-reloads.
⚡ 4. Killer Feature: Vite DevTools & Quiet Code Generator
Writing interface types by hand is tedious. That's why we built
endpoint-plus-devtools(a Vite plugin).
Just add it to your
vite.config.ts:
CODEimport { endpointPlusDevtools } from 'endpoint-plus-devtools/vite';
export default defineConfig({
plugins: [endpointPlusDevtools()],
});
1. How It Operates
AST Scanning: When the Vite dev server boots, the plugin parses your source tree (.ts,.tsx,.vue) in the background, identifying allapi.get/api.postcalls to build a visual endpoint map.
Live Response Capture: Open the in-browser DevTools overlay, select an endpoint, and test it. The overlay captures the real JSON response payload returned by your backend.
Schema Generation: Click "Save", and the Node-sidequicktype-coreengine runs schema analysis to write clean, type-safe ambient declarations into your project.
2. Vite HMR Watcher Bypass & Editor Integration
Solving the HMR Loop: Writing types insidesrc/ordinarily triggers Vite's hot-reload, which reloads the page and destroys the active DevTools state. We resolved this by explicitly invoking Vite's watcher API (server.watcher.unwatch(typegenAbsFile)) to temporarily exclude the generated.d.tsfile from HMR loops, ensuring silent, instantaneous type updates.
Launch Editor: Next to each endpoint in the DevTools UI is an "Open in Editor" button. Clicking it triggers thelaunch-editorNode utility, instantly opening your local VS Code/Cursor/WebStorm and focusing directly on the line of code where the API call was declared!
🌊 5. High-Performance SSE (Server-Sent Events) Buffering for AI Apps
With the explosion of LLMs (like ChatGPT and Claude), Server-Sent Events are standard for token streaming. However, rendering updates on every single token (which can fire 30–50 times per second) results in high CPU usage and severe UI lag.
endpoint-plusprovides a native SSE extension with an integratedeventBufferbatching queue:
CODEimport { createSseExtension } from 'endpoint-plus/extensions/sse';
const apiWithSse = api.use(createSseExtension());
await apiWithSse.sse<string>('/api/chat/stream', {
method: 'POST',
data: { prompt: 'Explain Quantum Computing' },
// 🌟 High-performance animation frame rendering batcher
eventBuffer: {
maxDelay: 16, // Flush every 16ms (matches 60Hz display frame rate)
maxSize: 50, // Max queue size
strategy: 'animation-frame', // Batching strategy
},
// Token events are automatically accumulated and flushed, keeping UI frame rates stable!
onBatch: (events) => {
const chunkText = events.map(e => e.data).join('');
appendChatText(chunkText);
},
});
Furthermore, SSE streams automatically reuse global client headers, interceptors, authentication context (
auth-token), and telemetry configurations.
🔌 6. Pluggable Enterprise-Grade Middleware
We believe in keeping bundles small. Everything in
endpoint-plusis modular, allowing you to opt-in to plugins on-demand:
Plugin Name
Import Path
Core Problem Solved
refresh-token
endpoint-plus/plugins/refresh-token
Concurrency-safe request buffering, silent token refresh, and request replay
request-gate
endpoint-plus/plugins/request-gate
Request-level debounce,throttle, and duplicate form submission rejection
request-cache
endpoint-plus/plugins/request-cache
GET/HEAD in-memory TTL caching and in-flight duplicate request merging
auth-token
endpoint-plus/plugins/auth-token
Asynchronous/Synchronous dynamic header authentication injection
retry
endpoint-plus/plugins/retry
Safe automatic retries using exponential backoffs for transient errors (e.g., 429, 503)
typegen
endpoint-plus/plugins/typegen
Lightweight development-mode TS type generator
Concurrency-Safe Silent Token Refresh Example:
CODEimport { createRefreshTokenPlugin } from 'endpoint-plus/plugins/refresh-token';
api.use(
createRefreshTokenPlugin({
refreshRequest: {
method: 'POST',
url: '/auth/refresh-token',
},
resolveAccessToken: (res) => res.newAccessToken,
onRefresh: async (session) => {
// Safely saves the new token.
// All other parallel requests are queued and automatically replayed.
await saveSession(session);
},
})
);
🤖 7. AI-Native: Preloaded Skills for LLM Copilots
To make AI assistants write accurate code,
endpoint-plusincludes preloaded AI Skills inside the package folder.
Copy them to your local customizations directory:
CODE# Create local customizations folder
mkdir -p .agents/skills
# Copy instructions from node_modules
cp -r node_modules/endpoint-plus/skills .agents/skills/endpoint-plus
Once copied, your AI assistant (e.g. Cursor or Antigravity) will instantly read these files and learn our API layouts, SSE buffering options, and middleware patterns. You can prompt Cursor:
"Write an endpoint configuration with silent token refresh, deduplication gating, and export a get method"
The AI will output 100% accurate, compile-safe configurations without any hallucinated methods or parameters!
🤝 8. Join Us & Co-Create the Future
endpoint-plusis published under the permissive MIT License and is already powering complex, high-traffic cross-platform apps in production.
We welcome community feedback, pull requests, and ideas! We are actively seeking contributors for:
More Transports: Adapters for Taro, React Native, or specific serverless edge environments.
DevTools Enhancements: Richer UI dashboards, response speed graphs, and cache hits statistics.
New Middleware: Plugins for payload validation, request signature generation, or mock response adapters.
If you like the project, check out our repository and drop us a Star ⭐️!
- 🔗 GitHub Repository: https://github.com/zandko/endpoint-plus
- 📦 NPM Registry:
pnpm add endpoint-plus
↗ Original-Artikel auf dev.to lesenVollständiger Original-BerichtAusführliche Details, Code-Beispiele & Hersteller-Stellungnahme auf dev.to.
A Deep Dive into endpoint-plus: A Next-Gen, AI-Native Request Suite
- ▸ 📌 1. Introduction: Do We Really Need Another Request Library?
- ▸ 🏗️ 2. Core Architecture: The Power of Decoupling
- ↳ 1. Swappable Physical Transports
- ↳ 2. Onion-Model Middleware
- ▸ 🔮 3. TypeScript Type Gymnastics: Compile-Time Path Pattern Matching
- ↳ 🧠 How the Type Parser Works Under the Hood
- ▸ ⚡ 4. Killer Feature: Vite DevTools & Quiet Code Generator
- ↳ 1. How It Operates
- ↳ 2. Vite HMR Watcher Bypass & Editor Integration
- ▸ 🌊 5. High-Performance SSE (Server-Sent Events) Buffering for AI Apps
- ▸ 🔌 6. Pluggable Enterprise-Grade Middleware
- ↳ Concurrency-Safe Silent Token Refresh Example:
- ▸ 🤖 7. AI-Native: Preloaded Skills for LLM Copilots
- ▸ 🤝 8. Join Us & Co-Create the Future
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