To ensure that the `LiteLLMInstrumentor` can instrument specific methods like `acompletion` and `aembedding` without importing the entire `litellm` package, you would need to ensure that the instrumentation is applied after the functions are imported. However, the current implementation of `LiteLLMInstrumentor` relies on monkey-patching the entire `litellm` module, which means it modifies the functions directly on the module.
Unfortunately, based on the available data sources, there is no direct support for instrumenting only specific functions without importing the entire module. The instrumentation is designed to work by modifying the functions on the `litellm` module itself, so importing the module is necessary for the instrumentation to take effect.
If you want to avoid importing the entire module in your tests, you might consider creating a wrapper or a mock that imports the module, applies the instrumentation, and then exposes only the functions you need. This way, you can control the scope of the import while still benefiting from the instrumentation.
Would you like more detail on how to implement such a wrapper or mock?
Sources:
- <https://github.com/Arize-ai/openinference/blob/main/python/instrumentation/openinference-instrumentation-litellm/src/openinference/instrumentation/litellm/__init__.py|https://github.com/Arize-ai/openinference/blob/main/python/instrumentation/openinference-instrumentation-litellm/src/openinference/instrumentation/litellm/__init__.py>
- <https://github.com/Arize-ai/phoenix/issues/4963|https://github.com/Arize-ai/phoenix/issues/4963>
