OpenCode

OpenCode is an open-source coding agent that runs in your terminal. It has no built-in Tensor Machine provider, but it supports custom OpenAI-compatible providers — which is exactly what our endpoint is. Adding one is a config-file change; no plugin or fork required.

1. Get your endpoint and key

From the console:

• Base URL — API Keys page, OpenAI format: https://edge.tensormachine.ai/<org>/v1
• Key — Create key, then copy the sk-tm-… secret (shown once)
• Model IDs — My Team → Model access, the tm/… aliases

Keep the key out of the config file. Export it instead:

export TENSOR_MACHINE_API_KEY="sk-tm-..."

Add that line to your shell profile (~/.zshrc, ~/.bashrc) so it survives new terminals.

2. Add the provider

OpenCode reads opencode.json from your project root, and falls back to ~/.config/opencode/opencode.json for a global config. Use the global file if you want Tensor Machine available in every project.

{
  "$schema": "https://opencode.ai/config.json",
  "provider": {
    "tensormachine": {
      "npm": "@ai-sdk/openai-compatible",
      "name": "Tensor Machine",
      "options": {
        "baseURL": "https://edge.tensormachine.ai/<org>/v1",
        "apiKey": "{env:TENSOR_MACHINE_API_KEY}"
      },
      "models": {
        "tm/qwen3-5-9b": {
          "name": "Qwen3 5 9B"
        }
      }
    }
  }
}

Four things decide whether this works:

• npm must be @ai-sdk/openai-compatible. That package targets /v1/chat/completions, which is what our OpenAI endpoint serves. The other common choice, @ai-sdk/openai, targets /v1/responses and will not work here. This is the single most common mistake.
• baseURL ends at /v1. OpenCode appends /chat/completions itself. Adding the path yourself produces a doubled URL and a 404.
• Each key under models is a real model ID sent verbatim to us — use the tm/… alias from Model access, not a display name. The name field is only the label in the picker.
• {env:…} reads an environment variable. If the variable isn't set, OpenCode substitutes an empty string rather than erroring, so a missing key surfaces later as a 401 — check the export first when you see one.

Add more models by adding more entries under models.

3. Select the model

Start OpenCode and run /models, then pick the Tensor Machine entry. To make it the default, set the model key to <provider>/<model-id>:

{
  "model": "tensormachine/tm/qwen3-5-9b"
}

The provider part (tensormachine) is your key from the provider block; the rest is the model ID. Both slashes are expected — the model ID contains one of its own.

4. Verify

Ask it something trivial and confirm the answer comes back:

opencode run "reply with the word: connected"

Then check the console: Usage should show the request against your team, and your balance should have moved. If the request never reaches us, the problem is local (base URL, key, or npm package) rather than a workspace setting.

Optional: declare context limits

OpenCode tracks how much context you have left. For built-in providers it pulls those figures automatically; for a custom provider it only knows what you declare:

"models": {
  "tm/qwen3-5-9b": {
    "name": "Qwen3 5 9B",
    "limit": { "context": 32768, "output": 4096 }
  }
}

Set these to the real context window and max output of the model you chose — they're on the model's card in Model access. The values above are placeholders, not the values for any particular model. Getting them wrong doesn't break requests; it makes OpenCode's remaining-context estimate wrong, so it compacts at the wrong time.

Troubleshooting

What we've verified

The configuration above follows OpenCode's documented custom-provider format, and the endpoint, auth scheme and error codes it relies on are the ones our API serves and are covered by our own tests. We have not published a certification of any particular model's performance as a coding agent — which model to use is a judgement call, and the Models page is the place to compare.