Anthropic

This integration connects Sentry with the Anthropic Python SDK and works with Anthropic versions 0.16.0 and above.

Once you've installed this SDK, you can use Sentry LLM Monitoring, a Sentry dashboard that helps you understand what's going on with your AI pipelines.

Sentry LLM Monitoring will automatically collect information about prompts, tokens, and models from providers like OpenAI. Learn more about it here.

Install

Install sentry-sdk from PyPI with the anthropic extra:

pip install --upgrade 'sentry-sdk[anthropic]'

Configure

If you have the anthropic package in your dependencies, the Anthropic integration will be enabled automatically when you initialize the Sentry SDK.

import sentry_sdk

sentry_sdk.init(
    dsn="https://examplePublicKey@o0.ingest.sentry.io/0",
    # Set traces_sample_rate to 1.0 to capture 100%
    # of transactions for tracing.
    traces_sample_rate=1.0,
    # Set profiles_sample_rate to 1.0 to profile 100%
    # of sampled transactions.
    # We recommend adjusting this value in production.
    profiles_sample_rate=1.0,
)

Verify

Verify that the integration works by creating an AI pipeline. The resulting data should show up in your LLM monitoring dashboard.

import sentry_sdk
from sentry_sdk.ai.monitoring import ai_track
from anthropic import Anthropic


sentry_sdk.init(...)  # same as above

client = Anthropic(api_key="(your Anthropic API key)")

@ai_track("My AI pipeline")
def my_pipeline():
    with sentry_sdk.start_transaction(op="ai-inference", name="The result of the AI inference"):
        print(
            client.messages.create(
                max_tokens=42,
                model="some-model",
                messages=[{"role": "system", "content": "Hello, Anthropic!"}]
            )
        )

After running this script, a pipeline will be created in the LLM Monitoring section of the Sentry dashboard.

The pipeline will have an associated Anthropic span for the messages.create operation.

It may take a couple of moments for the data to appear in sentry.io.

Behavior

• The supported modules are currently chat.messages.create with stream=True and stream=False.

• All exceptions leading to an AnthropicError are reported.

• Sentry considers LLM and tokenizer inputs/outputs as PII and doesn't include PII data by default. If you want to include the data, set send_default_pii=True in the sentry_sdk.init() call. To explicitly exclude prompts and outputs despite send_default_pii=True, configure the integration with include_prompts=False as shown in the Options section below.

Options

The AnthropicIntegration takes an optional include_prompts parameter. If set to False, prompts are excluded from being sent to Sentry, despite send_default_pii=True.

import sentry_sdk
from sentry_sdk.integrations.anthropic import AnthropicIntegration

sentry_sdk.init(
    # same options as above
    send_default_pii=True,
    integrations=[
        AnthropicIntegration(
            include_prompts=False, # Exclude prompts from being sent to Sentry, despite send_default_pii=True
        ),
    ],
)

Supported Versions

• Anthropic: 0.16.0+
• Python: 3.7+