QwenBridge
GitHubTry demo
Open-source AI orchestration platform

Build AI workflows your production systems can trust.

QwenBridge gives teams a clean platform layer for retrieval, model orchestration, streaming events, SDK integrations, and production-safe AI application flows.

Try live demoInstall packagesView GitHub
Designed forSpring BootTypeScript SDKsRetrievalStreaming APIs
Platform primitives

The building blocks for production AI systems.

QwenBridge focuses on the infrastructure layer around AI: orchestration, retrieval, streaming, SDKs, contracts, and operational safety.

Orchestration

Coordinate model providers, retries, timeouts, cancellation, and lifecycle boundaries.

Retrieval

Connect search, hybrid retrieval, ranking, and context assembly into application flows.

Streaming

Expose lifecycle events and AI output streams through clear developer-facing contracts.

SDKs

Integrate through Java, Spring Boot, and TypeScript entry points built for real projects.

API contracts

Keep request, response, error, and event behavior explicit and testable.

Production safety

Design for fallback behavior, failure visibility, limits, and predictable runtime behavior.

Architecture

A bridge between applications, data, models, and developer tooling.

QwenBridge sits between product applications and AI infrastructure. It gives teams a stable integration layer instead of scattering model, retrieval, and streaming logic across every service.

Applications
↓
QwenBridge Core
↓
Retrieval + Models + Streams
Quick start

Install once the public packages are available.

QwenBridge is being prepared for public distribution through Maven Central and npm.

Maven
<dependency>
  <groupId>io.qwenbridge</groupId>
  <artifactId>qwenbridge-spring-boot-starter</artifactId>
  <version>0.9.1</version>
</dependency>
TypeScript
npm install @qwenbridge/sdk
Live demo

An interactive QwenBridge playground is coming.

The demo environment will show retrieval, AI analysis, streaming events, and lifecycle visibility in one public playground.

Preparing demo.qwenbridge.io

Search → Retrieval → AI analysis → Streaming lifecycle

Documentation

Guides, examples, SDK references, and API contracts are next.

The documentation will cover Java starter usage, TypeScript SDK integration, streaming event contracts, retrieval behavior, deployment patterns, and operational guidance.