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Tools & releases

Grafana Open-Sources Go LLM SDK Compatible with Vercel AI SDK React Hooks

July 30, 2026· 4 min read
OKCurated by Oleksandr Kuzmenko, AI Product Engineer·Updated July 30, 2026·Sources cited on every story
AI-assisted · editor-reviewed·How we use AI
Grafana Open-Sources Go LLM SDK Compatible with Vercel AI SDK React Hooks

Grafana released an open-source Go SDK for building streaming AI backends with tool calling and multi-step agents. The library is wire-compatible with Vercel AI SDK frontend React hooks like useChat via Server-Sent Events.

Impact: Medium

Why it matters

Go developers can now build AI backends using native Go concurrency and production controls without adding custom protocol adapters for Vercel React frontends.

TL;DR

  • 01Grafana open-sourced a Go LLM SDK wire-compatible with Vercel's React hooks.
  • 02Supports Anthropic, OpenAI, Bedrock, and OpenAI-compatible endpoints.
  • 03Includes Prometheus metrics, timeouts, and fallback routing for Go backends.

Key facts

License
Apache-2.0
Primary Protocol
Server-Sent Events (SSE)
Frontend Compatibility
Vercel AI SDK React Hooks (useChat, useCompletion, useObject)
Supported Providers
Anthropic, OpenAI, Amazon Bedrock, OpenAI-compatible

Wire-Compatible Go Streaming for React Frontends

Grafana's ai-sdk implements the protocol used by Vercel AI SDK, allowing Go backends to serve frontend React components without additional translation layers. By calling aisdk.StreamText() or aisdk.WriteUIMessageStream(w, ...), a Go service emits Server-Sent Events (SSE) directly consumed by React hooks such as useChat, useCompletion, and useObject.

Provider Support and Production Controls

The library provides a unified interface across multiple LLM providers, including Anthropic (claude-sonnet-5), OpenAI, Amazon Bedrock, and custom OpenAI-compatible endpoints. For infrastructure readiness, it ships built-in support for timeouts, automated retries, fallback model routing, structured logging, and Prometheus metrics for operational observability.

Tool Execution and Structured Outputs

Go developers can define composable tools as standard Go functions that language models execute during agentic workflows. It also handles schema-validated structured output generation for JSON objects, arrays, and choices, adhering to Spec-Driven Development standards.

Try it in 2 minutes

go get github.com/grafana/ai-sdk/providers/anthropic

model := anthropic.New(apiKey, "claude-sonnet-5")
result, err := aisdk.GenerateText(ctx, model,
    aisdk.WithModelMessages(provider.UserText("Explain goroutines in one sentence.")),
)

go

✓ When to use

  • You are building Go microservices that serve AI features to React frontends using Vercel AI SDK.
  • You need native Go observability (Prometheus) and resilient production controls (retries, fallbacks) for LLM calls.

✕ When NOT to use

  • Your backend stack is entirely TypeScript or Python with existing native framework tooling.
  • You do not require server-sent streaming or multi-provider model routing.

What to do today

  • →Install github.com/grafana/ai-sdk in your Go project.
  • →Connect Go SSE streams directly to React useChat components without custom protocol code.
#Grafana#Go#Vercel AI SDK#React#Anthropic#OpenAI#Amazon Bedrock#Prometheus

Sources

  • Grafana AI SDK GitHub Repository
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