> ## Documentation Index
> Fetch the complete documentation index at: https://arizeai-433a7140.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# LiteLLM Tracing

export const projectName_0 = "my-llm-app"

[LiteLLM](https://github.com/BerriAI/litellm) allows developers to call all LLM APIs using the openAI format. [LiteLLM Proxy](https://docs.litellm.ai/docs/simple_proxy) is a proxy server to call 100+ LLMs in OpenAI format. Both are supported by this auto-instrumentation.

Any calls made to the following functions will be automatically captured by this integration:

* completion()

* acompletion()

* completion\_with\_retries()

* embedding()

* aembedding()

* image\_generation()

* aimage\_generation()

## Install

```bash theme={null}
pip install openinference-instrumentation-litellm "litellm<1.82.7"
```

## Setup

Connect your application to Phoenix with the `register` function:

<CodeBlock language="python">
  {`from phoenix.otel import register

    # configure the Phoenix tracer
    tracer_provider = register(
    project_name="${projectName_0}", # Default is 'default'
    auto_instrument=True # Auto-instrument your app based on installed OI dependencies
    )`}
</CodeBlock>

Add any API keys needed by the models you are using with LiteLLM.

```python theme={null}
import os
os.environ["OPENAI_API_KEY"] = "PASTE_YOUR_API_KEY_HERE"
```

## Run LiteLLM

You can now use LiteLLM as normal and calls will be traces in Phoenix.

```python theme={null}
import litellm
completion_response = litellm.completion(model="gpt-3.5-turbo",
                   messages=[{"content": "What's the capital of China?", "role": "user"}])
print(completion_response)
```

## Observe

Traces should now be visible in Phoenix!

## Resources

* [OpenInference Instrumentation](https://github.com/Arize-ai/openinference/tree/main/python/instrumentation/openinference-instrumentation-litellm)