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

# Templated LLM Calls

> Using templated messages in auto-traced OpenAI & Anthropic calls

It's good practice to use templated messages for your LLM calls.
In order to directly associate inputs to templated LLM calls, you can pass them into wrapped OpenAI and Anthropic calls via a `template_inputs` argument that contains key-value pairs of template variables and their corresponding values.
When you do this, the `template_inputs` will be visualized in the trace and used to format the messages in your LLM calls.
Note, that any variable in the template message needs to enclosed in double curly braces `{{}}` in order to get replaced.
See, below OpenAI example:

```python OpenAI theme={null}
from openai import OpenAI
from parea import Parea

client = OpenAI()
p = Parea(api_key="PAREA_API_KEY")
p.wrap_openai_client(client)

response = client.chat.completions.create(
    model="gpt-4",
    messages=[
        {"role": "user", "content": "Make up {{number}} people"},
    ],
    template_inputs={"number": "three"},
)
```

This will result in the following trace:

<img src="https://mintcdn.com/pareaai/3kurg3MZRrsWWk8t/observability/templated-llm-call.png?fit=max&auto=format&n=3kurg3MZRrsWWk8t&q=85&s=30243bed93a6f0e5e1179e558e48bf1a" alt="Templated LLM Call" width="1858" height="784" data-path="observability/templated-llm-call.png" />