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Documentation Index

Fetch the complete documentation index at: https://teamcopilot.ai/docs/llms.txt

Use this file to discover all available pages before exploring further.

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Setting up with GPT / OpenAI

Once you have created your first user and signed in, the dashboard will ask you to give access to an OpenAI account via:
  • Adding an API key: You can get an OpenAI key via the OpenAI developer console.
  • Signing into a subscription account: If you pick this method, OpenAI will give you an error during sign in to enable the device flow login method. You need to follow the instructions on that popup and then try signing into TeamCopilot again.
OpenAI setup

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Setting up with Azure OpenAI

Azure OpenAI is configured by the TeamCopilot service administrator through environment variables instead of the in-app auth flow. To use Azure OpenAI:
  • Stop the running TeamCopilot instance
  • In the .env file created by TeamCopilot (in your workspace directory), set the Azure credentials and deployment details:
AZURE_API_KEY=<your-azure-openai-api-key>
AZURE_OPENAI_ENDPOINT=https://<your-resource>.openai.azure.com/
OPENCODE_MODEL=azure-openai/<your-deployment-name>
  • Replace <your-resource> with your Azure OpenAI resource name
  • Replace <your-deployment-name> with the Azure deployment name you created in Azure OpenAI
  • Restart the server using npx teamcopilot start
After the server restarts, TeamCopilot will use the Azure OpenAI deployment configured in those environment variables. In the UI this provider is shown as managed by the administrator and is read-only for regular users.

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Setting up with Gemini

Gemini is configured by the TeamCopilot service administrator through environment variables instead of the in-app auth flow. To use Gemini:
  • Stop the running TeamCopilot instance
  • In the .env file created by TeamCopilot (in your workspace directory), set the Vertex project, credentials, location, and model details:
GOOGLE_CLOUD_PROJECT=<your-gcp-project-id>
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json
VERTEX_LOCATION=global
OPENCODE_MODEL=google-vertex/<your-model-id>
  • Replace <your-gcp-project-id> with your Google Cloud project ID
  • Point GOOGLE_APPLICATION_CREDENTIALS to a readable Google Cloud service account JSON key file
  • Set VERTEX_LOCATION to a Vertex region or endpoint such as global or us-central1
  • Replace <your-model-id> with the Gemini model id you want to use
  • If you are using a provider-specific OpenCode Vertex backend, keep that provider prefix in OPENCODE_MODEL
  • Restart the server using npx teamcopilot start
After the server restarts, TeamCopilot will use the Gemini model configured in those environment variables. In the UI this provider is shown as managed by the administrator and is read-only for regular users.

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Setting up with Claude / Anthropic

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Using Anthropic API key

If instead, you want to use Claude:
  • Stop the running TeamCopilot instance
  • In the .env file created by TeamCopilot (in your workspace directory), modify the OPENCODE_MODEL to be OPENCODE_MODEL=anthropic/claude-opus-4-6
  • Restart the server using npx teamcopilot start
  • Now when you visit the dashboard, it will ask you to give access to your Claude account.
With Anthropic, the only available method is via an API key. Claude setup

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Using Google Vertex

If you want to use Anthropic models through Google Vertex, configure the service administrator environment variables and set the provider-specific model id: 
GOOGLE_CLOUD_PROJECT=<your-gcp-project-id>
GOOGLE_APPLICATION_CREDENTIALS=/path/to/service-account.json
VERTEX_LOCATION=global
OPENCODE_MODEL=google-vertex-anthropic/<your-model-id>
  • google-vertex-anthropic is the provider prefix for Anthropic models on Google Vertex
  • Use the Anthropic model id you want to run through Vertex in OPENCODE_MODEL
  • Keep the Google Cloud project, credentials, and location variables configured for the workspace

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General recommendations

  • We recommend using the API key method since this will ensure no interruptions during workflows as long as you have credits in your account (as opposed to subscription which can have very heavy rate limits, especially if many people are using this tool). This is especially true for Claude since their terms of use states that their subscription account should only be used when using Claude code.
  • Use any model that is equal to or more capable than:
    • For OpenAI: Codex 5.3+ or GPT 5.4+
    • For Azure OpenAI: a deployment backed by Codex 5.3+ or GPT 5.4+
    • For Gemini: a model that matches your team’s needs and is supported by the configured Vertex provider
    • For Anthropic: Claude Opus 4.6+

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Changing models after initial setup

If you want to change the model or model provider used after the initial setup, you can do so by changing the OPENCODE_MODEL value in the .env file in the workspace directory and then restarting the TeamCopilot service. In addition to this, if you ever want to change the auth method (switch to API method from subscription method or vice versa):
  • Login as an Engineer into TeamCopilot
  • Navigate to the AI chat section
  • Click on the “Reconfigure Opencode Auth” button
  • Follow the instructions to setup new auth.
Reconfigure Opencode Auth button in the AI chat section