Add Kubernetes-based sandbox provider for multi-instance support (#19)

* feat: adds docker-based dev environment

* docs: updates Docker command help

* fix local dev

* feat(sandbox): add Kubernetes-based sandbox provider for multi-instance support

* fix: skills path in k8s

* feat: add example config for k8s sandbox

* fix: docker config

* fix: load skills on docker dev

* feat: support sandbox execution to Kubernetes Deployment model

* chore: rename web service name
This commit is contained in:
JeffJiang
2026-02-09 21:59:13 +08:00
committed by GitHub
parent 69c8b41186
commit 7b7e32f262
20 changed files with 981 additions and 94 deletions

View File

@@ -18,8 +18,7 @@ The fastest way to get started with a consistent environment:
2. **Initialize and start**:
```bash
make docker-init # First time only
make docker-dev # Start all services
make docker-start # Start all services
```
3. **Access**: http://localhost:2026
@@ -56,6 +55,35 @@ If you prefer running services locally:
See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed local development guide.
### Sandbox Configuration
DeerFlow supports multiple sandbox execution modes. Configure your preferred mode in `config.yaml`:
**Local Execution** (runs sandbox code directly on the host machine):
```yaml
sandbox:
use: src.sandbox.local:LocalSandboxProvider # Local execution
```
**Docker Execution** (runs sandbox code in isolated Docker containers):
```yaml
sandbox:
use: src.community.aio_sandbox:AioSandboxProvider # Docker-based sandbox
```
**Docker Execution with Kubernetes** (runs sandbox code in Kubernetes pods):
Setup Kubernetes sandbox as per [Kubernetes Sandbox Setup](docker/k8s/README.md).
```bash
./docker/k8s/setup.sh
```
Then configure `config.yaml` with the Kubernetes service URL:
```yaml
sandbox:
use: src.community.k8s_sandbox:AioSandboxProvider # Kubernetes-based sandbox
base_url: http://deer-flow-sandbox.deer-flow.svc.cluster.local:8080 # Kubernetes service URL
```
## Features
- 🤖 **LangGraph-based Agents** - Multi-agent orchestration with sophisticated workflows