> ## Documentation Index
> Fetch the complete documentation index at: https://mintlify.com/Arize-ai/openinference/llms.txt
> Use this file to discover all available pages before exploring further.

# Anthropic

> Python auto-instrumentation for Anthropic SDK

Python autoinstrumentation library for the [Anthropic](https://www.anthropic.com/api) package.

This package implements the following Anthropic clients:

* `Messages`
* `Completions`
* `AsyncMessages`
* `AsyncCompletions`

These traces are fully OpenTelemetry compatible and can be sent to an OpenTelemetry collector for viewing, such as [Arize Phoenix](https://github.com/Arize-ai/phoenix).

## Installation

```bash theme={null}
pip install openinference-instrumentation-anthropic
```

## Quickstart

Install required packages:

```bash theme={null}
pip install openinference-instrumentation-anthropic anthropic arize-phoenix opentelemetry-sdk opentelemetry-exporter-otlp
```

### Start Phoenix server

```bash theme={null}
python -m phoenix.server.main serve
```

By default, Phoenix listens on `http://localhost:6006`. You can visit the app via a browser at the same address. (Phoenix does not send data over the internet. It only operates locally on your machine.)

### Setup instrumentation

Set up `AnthropicInstrumentor` to trace your application and send traces to Phoenix:

```python theme={null}
import os
from anthropic import Anthropic
from openinference.instrumentation.anthropic import AnthropicInstrumentor
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk import trace as trace_sdk
from opentelemetry.sdk.trace.export import SimpleSpanProcessor

# Configure AnthropicInstrumentor with Phoenix endpoint
endpoint = "http://127.0.0.1:6006/v1/traces"
tracer_provider = trace_sdk.TracerProvider()
tracer_provider.add_span_processor(SimpleSpanProcessor(OTLPSpanExporter(endpoint)))

AnthropicInstrumentor().instrument(tracer_provider=tracer_provider)

os.environ["ANTHROPIC_API_KEY"] = "YOUR_KEY_HERE"

client = Anthropic()

response = client.messages.create(
    max_tokens=1024,
    messages=[
        {
            "role": "user",
            "content": "Tell me about the history of Iceland!",
        }
    ],
    model="claude-3-opus-20240229",
)
print(response)
```

Now, on the Phoenix UI in your browser, you should see the traces from your Anthropic application. Click on a trace, then the "Attributes" tab will provide you with in-depth information regarding execution.

## More Info

* [OpenInference and Phoenix documentation](https://docs.arize.com/phoenix)
* [How to customize spans to track sessions, metadata, etc.](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#customizing-spans)
* [How to account for private information and span payload customization](https://github.com/Arize-ai/openinference/tree/main/python/openinference-instrumentation#tracing-configuration)
* [PyPI package](https://pypi.org/project/openinference-instrumentation-anthropic/)