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

# Tracing Anthropic models via LiteLLM with Braintrust

export const plans_0 = "Any"

export const deployments_0 = "Any"

export const data_plane_version_0 = undefined

export const use_case_0 = "Use case - Using patch_litellm or wrap_litellm to trace Claude/Anthropic model calls and encountering missing spans or confusion about which LiteLLM entrypoints are instrumented"

<Note>
  **Applies to:**

  * Plan - {plans_0}
  * Deployment - {deployments_0}
  * {data_plane_version_0}
  * {use_case_0}
</Note>

## Summary

**Issue:** Traces are not created when calling `litellm.anthropic_messages()` or routing through the `/anthropic/v1/messages` passthrough. Calls to `litellm.completion(model="anthropic/claude-...")` are traced correctly.

**Cause:** `patch_litellm` wraps `litellm.completion`, `acompletion`, `responses`, `embedding`, and related entrypoints — it does not wrap `litellm.anthropic_messages` or the `/anthropic/v1/messages` passthrough route.

**Resolution:** Use `litellm.completion` for standard Claude tracing, or use the Anthropic SDK directly with `wrap_anthropic` if you need native Anthropic Messages API features.

## Resolution steps

### If you are calling `litellm.completion` with a Claude model and seeing no spans

#### Step 1: Verify setup order

`patch_litellm()` must be called before importing or using `litellm`. Confirm the following are also in place:

* `init_logger(project="...")` is called
* `BRAINTRUST_API_KEY` is set in your environment

#### Step 2: Confirm the call pattern

```python theme={"theme":{"light":"github-light","dark":"github-dark-dimmed"}}
from braintrust import init_logger, patch_litellm

init_logger(project="my-project")
patch_litellm()

import litellm

response = litellm.completion(
    model="anthropic/claude-3-5-sonnet-20241022",
    messages=[{"role": "user", "content": "Hello"}]
)
```

This path is fully traced. LiteLLM translates the call to Anthropic's `/messages` API internally, and the Braintrust wrapper operates at the `litellm.completion` layer.

### If you need native Anthropic Messages API features (extended thinking, prompt caching, etc.)

#### Step 1: Use `wrap_anthropic` with the Anthropic SDK directly

`litellm.anthropic_messages` is not wrapped by `patch_litellm`. Use this path instead:

```python theme={"theme":{"light":"github-light","dark":"github-dark-dimmed"}}
import anthropic
from braintrust.wrappers.anthropic import wrap_anthropic

client = wrap_anthropic(anthropic.Anthropic())

response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Hello"}]
)
```

### If you are building a gate pattern on top of `patch_litellm`

#### Step 1: Save original function references before wrapping

`patch_litellm` patches the `litellm` module in-place. If you save references after calling `patch_litellm`, both your original and traced refs point to the already-wrapped function, and the gate has no effect.

Save refs first:

```python theme={"theme":{"light":"github-light","dark":"github-dark-dimmed"}}
from braintrust import patch_litellm

import litellm
original_completion = litellm.completion
original_acompletion = litellm.acompletion

patch_litellm()

litellm.completion = _gate_sync(original_completion, litellm.completion)
litellm.acompletion = _gate_async(original_acompletion, litellm.acompletion)
```

## Notes

* Native `anthropic_messages` wrapper support in `patch_litellm` is not currently available. If this is a requirement, submit a feature request.
* Do not use LiteLLM's `BraintrustLogger` callback for tracing. Use `patch_litellm()` or `braintrust.auto_instrument()` instead — only function-wrapping preserves span context.