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

# OpenLLMetry

Literal AI supports [OpenLLMetry](https://github.com/traceloop/openllmetry) and its integrations.

You can use the OpenLLMetry integration to log your LLM, AI framework, and RAG pipeline calls to Literal AI.

```python theme={null}
from literalai import AsyncLiteralClient
import os
lai = AsyncLiteralClient(api_key=os.environ["LITERAL_API_KEY"])
lai.initialize()
```

Here is an example of how to log a regular OpenAI chat completion:

```python theme={null}
from literalai import AsyncLiteralClient
import os
lai = AsyncLiteralClient(api_key=os.environ["LITERAL_API_KEY"])
lai.initialize()
# Run a regular OpenAI chat completion

@lai.thread()
async def run_openai_chat_completion():
    lai.set_properties(
        tags=["hello", "world"],
        metadata={"foo": 1},
    )

    oai = AsyncOpenAI(api_key=os.environ["OPENAI_API_KEY"])

    await oai.chat.completions.create(
        model="gpt-4o",
        messages=[{ "role": "user", "content": "Hello, how are you?" }]
    )

asyncio.run(run_openai_chat_completion())
```

Here are examples: [Example 1](https://github.com/Chainlit/literalai-python/blob/cafe70ddd5838a2cf35193ac922c9b1fd85f79e7/examples/langchain_variable.py#L40) and [Example 2](https://github.com/Chainlit/literalai-python/blob/cafe70ddd5838a2cf35193ac922c9b1fd85f79e7/examples/multimodal.py#L25)