together-sandboxes

name	together-sandboxes
description	Remote Python execution in managed sandboxes on Together AI with stateful sessions, file uploads, data analysis, chart generation, and notebook-like runs via the Sandboxes API. Reach for it whenever the user wants managed remote Python execution instead of local execution, raw clusters, or full model hosting.

Together Sandboxes

Overview

Use Together Sandboxes when the user wants to execute Python remotely in a managed sandbox.

Typical fits:

• stateful Python sessions
• data analysis and chart generation
• agent-generated code execution
• file uploads into a remote runtime

When This Skill Wins

• The user wants remote execution rather than local shell execution
• Session state needs to persist across multiple calls
• The result may include display outputs such as charts
• A lightweight managed runtime is enough; no custom infra is required

Hand Off To Another Skill

• Use together-gpu-clusters for full infrastructure control or larger distributed jobs
• Use together-dedicated-containers for custom containerized runtime logic
• Use together-chat-completions if the user only wants generated code, not executed code

Quick Routing

• Remote execution with session reuse
  • Start with scripts/execute_with_session.py or scripts/execute_with_session.ts
• Response schema and session listing
  • Read references/api-reference.md
• MCP-style access for agent workflows
  • Read references/api-reference.md

Workflow

1. Decide whether the task needs code execution or only code generation.
2. Start a session with client.code_interpreter.execute().
3. Reuse session_id when the workflow depends on prior state.
4. Inspect stdout, stderr, structured outputs, and display outputs separately.
5. List sessions only when the user needs operational visibility or cleanup.

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".
• Treat session_id as part of the workflow state.
• Inspect response.errors before assuming a run succeeded.
• plt.show() with the Agg backend does not reliably produce display_data outputs. To retrieve charts, save the figure to a BytesIO buffer with fig.savefig(), base64-encode it, and print the encoded string to stdout. Parse it from the stdout output on the client side. See the chart example in scripts/execute_with_session.py.
• Use this skill when the user benefits from remote stateful execution, not just because Python is involved.
• If the task outgrows the sandbox model, hand off to GPU clusters or dedicated containers.

Resource Map

• API reference: references/api-reference.md
• Alternative access patterns: references/api-reference.md
• Python workflow: scripts/execute_with_session.py
• TypeScript workflow: scripts/execute_with_session.ts

Official Docs

• Together Sandboxes
• Sandboxes API