root
44406b72db
Moteva-style AI design workbench replica. Home prompt creates a project; the project page provides an infinite canvas with node drag, zoom/pan, a design chat panel, history replay, image asset upload, and project save/regenerate. - Backend: go-zero, DDD layering, sqlc/pgx, optional PostgreSQL; memory or Redis cache; asynq job queue; MinIO/S3/R2/OSS object storage; sky-valley/pi agent runtime adapter. - Frontend: Next.js App Router + Vite artifact build, TypeScript, i18n, shadcn/ui components, auth (OTP/Turnstile/Google/WeChat). - Deploy: Docker Compose and k3s manifests. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
140 lines
3.2 KiB
Markdown
140 lines
3.2 KiB
Markdown
# img-infinite-canvas API
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go-zero backend for the Moteva-style infinite canvas MVP.
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## Features
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- Dashboard data for the Moteva home page
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- Project creation from prompt
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- Project title rename
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- Full canvas project reads
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- Moteva-style generation mock for image/design workflows
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- Canvas layout save
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- Chat history replay
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- DDD layout with domain, application, infrastructure, and generated handler layers
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- sky-valley/pi Go agent adapter with local desktop agent disabled
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- Optional PostgreSQL persistence through pgx/sqlc
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- Optional Redis cache, default memory cache
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- Asynq job queue for generation, OCR, layer merge, and asset cleanup workers
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- Image asset upload URLs for memory, MinIO, AWS S3, Cloudflare R2, and Aliyun OSS
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## Configuration
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```yaml
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Name: img_infinite_canvas-api
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Host: 0.0.0.0
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Port: 8888
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Timeout: 1200000
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Storage:
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Driver: postgres
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DataSource: postgres://canvas:canvas@localhost:15432/canvas?sslmode=disable
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Cache:
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Driver: redis
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Addr: localhost:16379
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Password: ""
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DB: 0
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TTLSeconds: 300
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JobQueue:
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Driver: asynq
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Addr: localhost:16379
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Password: ""
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DB: 0
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Queue: default
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Concurrency: 10
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MaxRetry: 3
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TimeoutSeconds: 900
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ShutdownTimeoutSeconds: 30
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Agent:
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Driver: pi
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Text:
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Driver: vision
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Model: gpt-5.4-mini
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TimeoutSeconds: 240
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CacheTTLSeconds: 600
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Planner:
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Driver: vision
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Model: gpt-5.5
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TimeoutSeconds: 240
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Image:
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BaseURL: http://154.21.87.3:8080
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APIKeyEnv: GPT_IMAGE_API_KEY
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TimeoutSeconds: 600
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ObjectStorage:
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Driver: minio
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Bucket: canvas-assets
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Endpoint: localhost:19000
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Region: us-east-1
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AccessKey: canvas
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SecretKey: canvas-secret
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PublicBase: http://localhost:19000/canvas-assets
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UseSSL: false
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ExpiresIn: 900
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```
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Start local Docker dependencies for debugging:
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```bash
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docker compose -f ../deploy/docker-compose.yml up -d postgres redis minio
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```
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Use PostgreSQL, Redis, and MinIO inside Docker Compose. The compose file runs the API and Asynq worker as separate processes:
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```yaml
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Storage:
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Driver: postgres
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DataSource: postgres://canvas:canvas@postgres:5432/canvas?sslmode=disable
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Cache:
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Driver: redis
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Addr: redis:6379
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TTLSeconds: 300
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JobQueue:
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Driver: asynq
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Addr: redis:6379
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Queue: default
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TimeoutSeconds: 900
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ObjectStorage:
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Driver: minio
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Bucket: canvas-assets
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Endpoint: minio:9000
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Region: us-east-1
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AccessKey: canvas
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SecretKey: canvas-secret
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PublicBase: http://localhost:19000/canvas-assets
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UseSSL: false
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```
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## Running
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```bash
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go run . -f etc/config.yaml -mode all
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go run . -f etc/config.yaml -mode api
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go run . -f etc/config.yaml -mode worker
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```
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## Testing
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```bash
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go test ./...
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go build ./...
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```
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## Example
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```bash
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curl http://localhost:8888/api/dashboard
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curl -X POST http://localhost:8888/api/projects \
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-H "Content-Type: application/json" \
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-d '{"prompt":"为 still day 品牌服装独立站设计官网视觉方向"}'
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curl -X PATCH http://localhost:8888/api/projects/<project-id>/title \
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-H "Content-Type: application/json" \
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-d '{"title":"夏季活动主视觉"}'
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curl -X POST http://localhost:8888/api/assets/upload-url \
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-H "Content-Type: application/json" \
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-d '{"fileName":"ref.png","contentType":"image/png"}'
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```
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Detailed endpoint docs are in [API.md](API.md).
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