Claude Agent SDK JS

npm install @anthropic-ai/claude-agent-sdk zod tsx typescript \
  @arizeai/openinference-instrumentation-claude-agent-sdk \
  @arizeai/openinference-semantic-conventions \
  @opentelemetry/exporter-trace-otlp-proto \
  @opentelemetry/resources \
  @opentelemetry/sdk-trace-base \
  @opentelemetry/sdk-trace-node \
  @opentelemetry/semantic-conventions

export ARIZE_SPACE_ID="<your-space-id>"
export ARIZE_API_KEY="<your-api-key>"
export ARIZE_PROJECT_NAME="claude-agent-sdk-js-tracing-example"
export ANTHROPIC_API_KEY="<your-anthropic-api-key>"

// instrumentation.ts
import * as ClaudeAgentSDK from "@anthropic-ai/claude-agent-sdk";
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-proto";
import { resourceFromAttributes } from "@opentelemetry/resources";
import { SimpleSpanProcessor } from "@opentelemetry/sdk-trace-base";
import { NodeTracerProvider } from "@opentelemetry/sdk-trace-node";
import { ATTR_SERVICE_NAME } from "@opentelemetry/semantic-conventions";
import {
  ClaudeAgentSDKInstrumentation,
} from "@arizeai/openinference-instrumentation-claude-agent-sdk";
import {
  SEMRESATTRS_PROJECT_NAME,
} from "@arizeai/openinference-semantic-conventions";

const projectName =
  process.env.ARIZE_PROJECT_NAME ?? "claude-agent-sdk-js-tracing-example";

export const provider = new NodeTracerProvider({
  resource: resourceFromAttributes({
    [ATTR_SERVICE_NAME]: projectName,
    [SEMRESATTRS_PROJECT_NAME]: projectName,
  }),
  spanProcessors: [
    new SimpleSpanProcessor(
      new OTLPTraceExporter({
        url: "https://otlp.arize.com/v1/traces",
        headers: {
          "arize-space-id": process.env.ARIZE_SPACE_ID ?? "",
          "arize-api-key": process.env.ARIZE_API_KEY ?? "",
        },
      }),
    ),
  ],
});

provider.register();

const instrumentation = new ClaudeAgentSDKInstrumentation({
  tracerProvider: provider,
});

export const claudeAgentSDK =
  instrumentation.manuallyInstrument(ClaudeAgentSDK);

console.log("Arize AX tracing initialized for Claude Agent SDK JS.");

// example.ts

// Importing instrumentation first ensures tracing is set up before the
// Claude Agent SDK is used.
import { claudeAgentSDK, provider } from "./instrumentation";

const messages = claudeAgentSDK.query({
  prompt: "What files are in this directory?",
  options: {
    allowedTools: ["Bash", "Glob"],
  },
});

for await (const message of messages) {
  if (message.type !== "result") continue;

  if (message.subtype === "success") {
    console.log(message.result);
  } else {
    console.error(message.errors.join("\n"));
  }
}

// Flush any pending spans before the process exits.
await provider.forceFlush();

// example.ts
import { claudeAgentSDK, provider } from "./instrumentation";
import { SpanStatusCode } from "@opentelemetry/api";
import { SemanticConventions } from "@arizeai/openinference-semantic-conventions";

const tracer = provider.getTracer("claude-agent-sdk-llm-spans");

await tracer.startActiveSpan("claude-agent-sdk run", async (parent) => {
  parent.setAttribute(SemanticConventions.OPENINFERENCE_SPAN_KIND, "CHAIN");

  const messages = claudeAgentSDK.query({
    prompt: "Why is the ocean salty? Answer in one sentence.",
    options: { maxTurns: 1 },
  });

  const llmSpans: ReturnType<typeof tracer.startSpan>[] = [];
  for await (const message of messages) {
    // Start an LLM span for each assistant turn.
    if (message.type === "assistant") {
      const m = (message as any).message;
      const text = (m.content ?? [])
        .filter((b: any) => b.type === "text")
        .map((b: any) => b.text)
        .join("");
      const span = tracer.startSpan(`${m.model} generation`);
      span.setAttribute(SemanticConventions.OPENINFERENCE_SPAN_KIND, "LLM");
      span.setAttribute(SemanticConventions.LLM_MODEL_NAME, m.model);
      span.setAttribute(SemanticConventions.LLM_PROVIDER, "anthropic");
      span.setAttribute(SemanticConventions.OUTPUT_VALUE, text);
      llmSpans.push(span);
    }
    // Accurate token counts arrive only on the final result message.
    if (message.type === "result") {
      const usage = (message as any).usage;
      const last = llmSpans[llmSpans.length - 1];
      if (last && usage) {
        last.setAttribute(SemanticConventions.LLM_TOKEN_COUNT_PROMPT, usage.input_tokens ?? 0);
        last.setAttribute(SemanticConventions.LLM_TOKEN_COUNT_COMPLETION, usage.output_tokens ?? 0);
      }
      if (message.subtype === "success") console.log(message.result);
    }
  }

  llmSpans.forEach((s) => {
    s.setStatus({ code: SpanStatusCode.OK });
    s.end();
  });
  parent.end();
});

await provider.forceFlush();