---
title: "Sentry - Log LLM Exceptions"
description: "Sentry - Log LLM Exceptions — reference document from Claude Code knowledge pack."
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/sentry
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:46:38.647Z
license: CC-BY-4.0
attribution: "Sentry - Log LLM Exceptions — Claudary (https://claudary.paisolsolutions.com/skills/sentry)"
---

# Sentry - Log LLM Exceptions
Sentry - Log LLM Exceptions — reference document from Claude Code knowledge pack.

## Overview

# Sentry - Log LLM Exceptions
import Image from '@theme/IdealImage';


:::tip

This is community maintained, Please make an issue if you run into a bug
https://github.com/BerriAI/litellm

:::


[Sentry](https://sentry.io/) provides error monitoring for production. LiteLLM can add breadcrumbs and send exceptions to Sentry with this integration

Track exceptions for:
- litellm.completion() - completion()for 100+ LLMs
- litellm.acompletion() - async completion()
- Streaming completion() & acompletion() calls

<Image img={require('../../img/sentry.png')} />


## Usage

### Set SENTRY_DSN & callback

```python
import litellm, os
os.environ["SENTRY_DSN"] = "your-sentry-url"
litellm.failure_callback=["sentry"]
```

### Sentry callback with completion
```python
import litellm
from litellm import completion 

litellm.input_callback=["sentry"] # adds sentry breadcrumbing
litellm.failure_callback=["sentry"] # [OPTIONAL] if you want litellm to capture -> send exception to sentry

import os 
os.environ["SENTRY_DSN"] = "your-sentry-url"
os.environ["OPENAI_API_KEY"] = "your-openai-key"

# set bad key to trigger error 
api_key="bad-key"
response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hey!"}], stream=True, api_key=api_key)

print(response)
```

#### Sample Rate Options

- **SENTRY_API_SAMPLE_RATE**: Controls what percentage of errors are sent to Sentry
  - Value between 0 and 1 (default is 1.0 or 100% of errors)
  - Example: 0.5 sends 50% of errors, 0.1 sends 10% of errors

- **SENTRY_API_TRACE_RATE**: Controls what percentage of transactions are sampled for performance monitoring
  - Value between 0 and 1 (default is 1.0 or 100% of transactions)
  - Example: 0.5 traces 50% of transactions, 0.1 traces 10% of transactions

These options are useful for high-volume applications where sampling a subset of errors and transactions provides sufficient visibility while managing costs.

#### Sentry Environment
- **SENTRY_ENVIRONMENT**: Specifies the environment name for your Sentry events (e.g., "production", "staging", "development")
  - Helps organize and filter errors by deployment environment in Sentry dashboard
  - Example: `os.environ["SENTRY_ENVIRONMENT"] = "staging"`
  - If not set, Sentry will use 'production' as the default environment

## Redacting Messages, Response Content from Sentry Logging 

Set `litellm.turn_off_message_logging=True` This will prevent the messages and responses from being logged to sentry, but request metadata will still be logged.

[Let us know](https://github.com/BerriAI/litellm/issues/new?assignees=&labels=enhancement&projects=&template=feature_request.yml&title=%5BFeature%5D%3A+) if you need any additional options from Sentry.

---

Source: [Claudary](https://claudary.paisolsolutions.com/skills/sentry) · https://claudary.paisolsolutions.com