> ## Documentation Index
> Fetch the complete documentation index at: https://docs.openlit.io/llms.txt
> Use this file to discover all available pages before exploring further.
# Go SDK Overview
> OpenTelemetry-native observability for Go AI applications. Monitor OpenAI and Anthropic with automatic token tracking, cost calculation, and distributed tracing.
The OpenLIT Go SDK provides **OpenTelemetry-native observability** for Go applications using LLM APIs. It wraps your provider clients with lightweight instrumentation that automatically collects traces, metrics, and cost data without requiring any changes to your application logic.
## Supported providers
Chat completions, streaming, embeddings, and image generation — with full token usage and cost tracking.
Claude messages and streaming — with cache token tracking and full OpenTelemetry semantic conventions.
## What gets collected
Every instrumented call automatically records:
* **Distributed traces** — spans with request/response details, model name, token counts, and cost
* **OTel metrics** — `gen_ai.client.token.usage`, `gen_ai.client.operation.duration`, `gen_ai.server.time_to_first_token`, `gen_ai.server.time_per_output_token`, `gen_ai.server.request.duration`
* **Streaming metrics** — time-to-first-chunk and per-chunk latency observations
* **Cost tracking** — automatic cost calculation using the built-in pricing data
## Installation
```shell theme={null}
go get github.com/openlit/openlit/sdk/go
```
```shell theme={null}
go get github.com/openlit/openlit/sdk/go@v1.2.3
```
Replace `v1.2.3` with the version you want to install.
## Quick start
```go theme={null}
package main
import (
"context"
"fmt"
"log"
openlit "github.com/openlit/openlit/sdk/go"
"github.com/openlit/openlit/sdk/go/instrumentation/openai"
)
func main() {
// 1. Initialize OpenLIT (once, at startup)
if err := openlit.Init(openlit.Config{
OtlpEndpoint: "http://127.0.0.1:4318",
ApplicationName: "my-ai-app",
Environment: "production",
}); err != nil {
log.Fatal(err)
}
defer openlit.Shutdown(context.Background())
// 2. Create an instrumented client
client := openai.NewClient("your-openai-api-key")
// 3. Use it exactly like a normal client
resp, err := client.CreateChatCompletion(context.Background(), openai.ChatCompletionRequest{
Model: "gpt-4o",
Messages: []openai.Message{
{Role: "user", Content: "Hello, world!"},
},
MaxTokens: 100,
})
if err != nil {
log.Fatal(err)
}
fmt.Println(resp.Choices[0].Message.Content)
}
```
Replace `YOUR_OTEL_ENDPOINT` with the URL of your OpenTelemetry backend, such as `http://127.0.0.1:4318` for a local OpenLIT deployment.
## Configuration
Pass a `Config` struct to `openlit.Init()`:
| Field | Environment Variable | Description | Default |
| ------------------------------ | ----------------------------- | ----------------------------------------- | ----------------------- |
| `OtlpEndpoint` | `OTEL_EXPORTER_OTLP_ENDPOINT` | OTLP backend URL | `http://127.0.0.1:4318` |
| `OtlpHeaders` | — | Additional HTTP headers for OTLP requests | `{}` |
| `ApplicationName` | — | Name of your application | `default` |
| `Environment` | — | Deployment environment label | `default` |
| `ServiceVersion` | — | Service version string | `""` |
| `DisableTracing` | — | Disable trace collection | `false` |
| `DisableMetrics` | — | Disable metrics collection | `false` |
| `DisableBatch` | — | Disable batch export (useful for testing) | `false` |
| `DisableCaptureMessageContent` | — | Omit prompt/completion text from spans | `false` |
| `DetailedTracing` | — | Enable component-level tracing detail | `false` |
| `DisablePricingFetch` | — | Skip fetching remote pricing data | `false` |
| `PricingEndpoint` | — | URL for custom pricing JSON | built-in |
| `PricingInfo` | — | In-process pricing overrides | `{}` |
| `TraceExporterTimeout` | — | Timeout for trace exports | `10s` |
| `MetricExporterTimeout` | — | Timeout for metric exports | `10s` |
| `MetricExportInterval` | — | Interval for metric exports | `30s` |
### Via environment variable
```go theme={null}
// If OTEL_EXPORTER_OTLP_ENDPOINT is set, no endpoint config is needed
openlit.Init(openlit.Config{
ApplicationName: "my-ai-app",
})
```
```shell theme={null}
export OTEL_EXPORTER_OTLP_ENDPOINT=http://127.0.0.1:4318
```
## Getting started
Monitor chat completions, streaming, embeddings, and image generation
Monitor Claude messages and streaming with cache token tracking
Send telemetry to Datadog, Grafana, New Relic, and other observability stacks
Configure the OpenLIT SDK according to your requirements