Anthropic Integration

The SDK allows you to monitor Anthropic’s Claude models with zero code changes to your logic.

Setup

Enable instrumentation with a single function call. This automatically tracks all subsequent calls to both Anthropic and AsyncAnthropic clients.

import agentbasis
from agentbasis.llms.anthropic import instrument

# Initialize AgentBasis first
agentbasis.init(api_key="your-api-key", agent_id="your-agent-id")

# Enable Anthropic instrumentation (covers sync and async)
instrument()

A single instrument() call instruments both synchronous and asynchronous clients. You don’t need to call it twice.

Usage

Once instrumented, use the Anthropic client as you normally would. All messages.create calls are automatically traced.

Synchronous

from anthropic import Anthropic

client = Anthropic()

response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello there"}]
)

print(response.content[0].text)

Asynchronous

from anthropic import AsyncAnthropic
import asyncio

async def main():
    client = AsyncAnthropic()
    
    response = await client.messages.create(
        model="claude-3-5-sonnet-20241022",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Hello there"}]
    )
    
    print(response.content[0].text)

asyncio.run(main())

Streaming

Streaming responses are supported for both sync and async. The trace is recorded once the stream completes.

Sync Streaming

with client.messages.stream(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Tell me a story"}]
) as stream:
    for text in stream.text_stream:
        print(text, end="")

Async Streaming

async def stream_response():
    client = AsyncAnthropic()
    
    async with client.messages.stream(
        model="claude-3-5-sonnet-20241022",
        max_tokens=1024,
        messages=[{"role": "user", "content": "Tell me a story"}]
    ) as stream:
        async for text in stream.text_stream:
            print(text, end="")

Captured Data

The integration automatically records:

Field	Description
`gen_ai.system`	`anthropic`
`gen_ai.request.model`	Model ID (e.g., `claude-3-5-sonnet-20241022`)
`gen_ai.prompt`	System and user messages
`gen_ai.completion`	Response text
`gen_ai.usage.input_tokens`	Input token count
`gen_ai.usage.output_tokens`	Output token count
`duration`	Request latency

​Setup

​Usage

​Synchronous

​Asynchronous

​Streaming

​Sync Streaming

​Async Streaming

​Captured Data

Setup

Usage

Synchronous

Asynchronous

Streaming

Sync Streaming

Async Streaming

Captured Data