Together Dedicated Containers
Overview
Use Dedicated Container Inference when the user needs a custom runtime, not just managed model hosting.
Core building blocks:
- Jig CLI for build and deployment
- Sprocket SDK for request handling inside the container
- Queue API for async jobs
When This Skill Wins
- Deploy a custom inference worker
- Bundle custom dependencies or runtime logic into a container
- Use queue-based async processing with progress tracking
- Run a specialized image, video, or multimodal pipeline
Hand Off To Another Skill
- Use
together-dedicated-endpointsfor standard model hosting without custom containers - Use
together-gpu-clustersfor full cluster ownership and orchestration control - Use
together-chat-completions,together-images, ortogether-videowhen a serverless product already covers the task
Quick Routing
- Minimal worker template
- Start with scripts/sprocket_hello_world.py
- Read references/sprocket-sdk.md
- Build, deploy, logs, queue, and secrets
- Read references/jig-cli.md
- Queue submission and polling
- Start with scripts/queue_client.py or scripts/queue_client.ts
Workflow
- Confirm that the user truly needs a custom container runtime.
- Implement the worker with Sprocket's request lifecycle.
- Configure
pyproject.tomlfor image, runtime, autoscaling, and mounts. - Deploy with Jig.
- Submit jobs through the queue API and poll until completion.
High-Signal Rules
- Python scripts require the Together v2 SDK (
together>=2.0.0). If the user is on an older version, they must upgrade first:uv pip install --upgrade "together>=2.0.0". - Prefer dedicated endpoints over containers unless the runtime or pipeline is genuinely custom.
- Treat the worker contract and
pyproject.tomlas the source of truth for deployment behavior. - Parameterize deployment name, queue inputs, and resource sizing instead of hardcoding them.
- Queue-based jobs are asynchronous by default; account for polling and result retrieval in client code.
Resource Map
- Jig CLI: references/jig-cli.md
- Sprocket SDK: references/sprocket-sdk.md
- Python queue client: scripts/queue_client.py
- TypeScript queue client: scripts/queue_client.ts
- Worker template: scripts/sprocket_hello_world.py