[ci][smg] fix docker release ci and add it to pr test (#14683)

This commit is contained in:
Simo Lin
2025-12-08 20:56:38 -08:00
committed by GitHub
parent ce4e836be5
commit af60cad05d
3 changed files with 26 additions and 3 deletions

View File

@@ -330,8 +330,31 @@ jobs:
docker rm oracle-db || true
docker-build-test:
if: |
github.event_name != 'pull_request' ||
(github.event.action != 'labeled' && contains(github.event.pull_request.labels.*.name, 'run-ci')) ||
(github.event.action == 'labeled' && github.event.label.name == 'run-ci')
runs-on: ubuntu-24.04
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v3
- name: Build Docker image (no push)
uses: docker/build-push-action@v5
with:
context: .
file: docker/gateway.Dockerfile
push: false
tags: sglang-router:test
cache-from: type=gha
cache-to: type=gha,mode=max
finish:
needs: [maturin-build-test, router-unit-tests, router-http-tests, router-grpc-response-api-tests]
needs: [maturin-build-test, router-unit-tests, router-http-tests, router-grpc-response-api-tests, docker-build-test]
runs-on: ubuntu-latest
steps:
- name: Finish

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@@ -4,7 +4,7 @@ on:
branches:
- main
paths:
- "sgl-model-gateway/bindings/python/sglang_router/version.py"
- sgl-model-gateway/bindings/python/pyproject.toml
workflow_dispatch:
jobs:

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@@ -27,7 +27,7 @@ High-performance model routing control and data plane for large-scale LLM deploy
- Advanced load balancing with cache-aware request reuse, load-aware (power-of-two) selection, and per-model policy overrides.
## Feature Highlights
- Multiple load balancing strategies (`random`, `round_robin`, `cache_aware`, `power_of_two`) with DP-aware scheduling.
- Multiple load balancing strategies (`random`, `round_robin`, `cache_aware`, `power_of_two`, `bucket`) with DP-aware scheduling.
- Multi-model HTTP serving and inference gateway routing with model-specific policies.
- Prefill/decode disaggregation, including bootstrap port handling and cache-aware merging.
- gRPC routing with fully Rust tokenizer loading, reasoning parser selection, and tool parser integration for OpenAI-compatible endpoints—supporting streaming and non-streaming modes across DeepSeek, Llama, Kimi K2, Qwen, GPT-OSS, Mistral, Step-3, GLM4, and other reasoning-capable models.