amazon-bedrock-tracing.md•2.72 kB
---
description: >-
Instrument LLM calls to AWS Bedrock via the boto3 client using the
BedrockInstrumentor
---
# Amazon Bedrock Tracing
boto3 provides Python bindings to AWS services, including Bedrock, which provides access to a number of foundation models. Calls to these models can be instrumented using OpenInference, enabling OpenTelemetry-compliant observability of applications built using these models. Traces collected using OpenInference can be viewed in Phoenix.
OpenInference Traces collect telemetry data about the execution of your LLM application. Consider using this instrumentation to understand how a Bedrock-managed models are being called inside a complex system and to troubleshoot issues such as extraction and response synthesis.
## Launch Phoenix
{% include "../../../../phoenix-integrations/.gitbook/includes/sign-up-for-phoenix-sign-up....md" %}
## Install
```bash
pip install openinference-instrumentation-bedrock opentelemetry-exporter-otlp
```
## Setup
Connect to your Phoenix instance using the register function.
```python
from phoenix.otel import register
# configure the Phoenix tracer
tracer_provider = register(
project_name="my-llm-app", # Default is 'default'
auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)
```
After connecting to your Phoenix server, instrument `boto3` prior to initializing a `bedrock-runtime` client. All clients created after instrumentation will send traces on all calls to `invoke_model`.
```python
import boto3
session = boto3.session.Session()
client = session.client("bedrock-runtime")
```
## Run Bedrock
From here you can run Bedrock as normal
```python
prompt = (
b'{"prompt": "Human: Hello there, how are you? Assistant:", "max_tokens_to_sample": 1024}'
)
response = client.invoke_model(modelId="anthropic.claude-v2", body=prompt)
response_body = json.loads(response.get("body").read())
print(response_body["completion"])
```
## Observe
Now that you have tracing setup, all calls to invoke\_model will be streamed to your running Phoenix for observability and evaluation.
{% embed url="https://storage.googleapis.com/arize-phoenix-assets/assets/gifs/bedrock_tracing_eval_medium.gif" %}
## Resources
* [Example Tracing & Eval Notebook](https://colab.research.google.com/github/Arize-ai/phoenix/blob/c02f0e7d807129952afa5da430299aec32fafcc9/tutorials/evals/bedrock_tracing_and_evals_tutorial.ipynb#L24)
* [OpenInference package](https://github.com/Arize-ai/openinference/blob/main/python/instrumentation/openinference-instrumentation-bedrock)
* [Working examples](https://github.com/Arize-ai/openinference/blob/main/python/instrumentation/openinference-instrumentation-bedrock/examples)