Anthropic

Trace every Anthropic client call with Rius without touching your call sites.

Setup

pip install "glassflow-rius[anthropic]" anthropic

import rius
from anthropic import Anthropic
 
rius.init(api_key="ri_...", service_name="my-agent")
client = Anthropic()  # use the client exactly as before

npm install @arizeai/openinference-instrumentation-anthropic

import { init } from '@glassflow-ai/rius'
import Anthropic from '@anthropic-ai/sdk'
 
const rius = init({ apiKey: 'ri_...', serviceName: 'my-agent' })
const client = new Anthropic()  // use the client exactly as before

What gets captured

Each messages.create call becomes an LLM-kind span carrying the model (for example claude-haiku-4-5-20251001), input/output token usage from the response including cache reads and writes, and the request/response messages; cost is computed server-side from the model and tokens.

The SDK reassembles the messages into the GenAI message shape: text blocks become text parts, tool calls become tool_call parts, and any other block (an image or a reasoning block, say) is kept as a text part holding the block serialized, so nothing is lost. Anthropic takes the system prompt as a separate system parameter rather than as a message; it lands as the leading system message of gen_ai.input.messages, where the console and context attribution read it. A failed call records error.type as the error class, such as anthropic.NotFoundError. See what the SDK normalizes.

Streaming

Token usage is captured on streamed calls too (Anthropic reports it in the message lifecycle events). One gap to know about: unlike the Python OpenAI integration, the Anthropic integration’s OpenInference  packages, Python and TypeScript alike, do not record time to first token, so it is not available for auto-instrumented Anthropic streams. If it matters for a call, trace it as a manual generation with record_first_token() instead.

Verify

Run one call, then open the trace in the console: the span shows the model, token counts, and a cost. Wrap the call in observe to see it nested inside your agent’s run.