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Description
Summary
I’m evaluating the GitHub Copilot SDK and would like clarification on its intended use cases, particularly around cloud-deployed and public-facing applications.
Current Understanding
From the documentation and experimentation, the Copilot SDK authenticates via:
- Local Copilot CLI login
This works well for:
- CLI tools used by individual developers
- Local applications tied to a signed-in GitHub user
Point of Confusion
It’s unclear how the Copilot SDK is intended to be used in cloud or server-side environments.
For example, in a public web application where:
- Any user can access the app (not limited to Copilot subscribers)
- Users do not authenticate with GitHub
- The backend handles AI requests on behalf of users
…the SDK does not appear to support this model. In such cases, developers would need to integrate directly with OpenAI, Anthropic, or Gemini APIs instead of using the Copilot SDK.
Questions
- Is the Copilot SDK intentionally scoped to local and developer tooling use cases?
- Are there plans to support cloud deployment scenarios (e.g., service accounts, server-side credentials, or API keys)?
- For public-facing applications, what is the recommended approach for achieving multi-model support similar to Copilot’s abstraction layer?
Why This Matters
One of the SDK’s main value propositions is a unified API across multiple AI providers (GPT, Claude, Gemini). If the SDK is limited to local or authenticated developer environments, teams building cloud applications must:
- Integrate with each AI provider separately
- Manage multiple API keys and billing accounts
- Miss out on Copilot’s unified model selection experience
Clarifying the intended scope and roadmap would help developers choose the right tool early and avoid incorrect architectural assumptions.
Thanks