Introduction

Let me preface this blog by saying this isn't like my other blogs where I was able to walk through the steps I took to complete a task. Instead, this is more of a reflection on the challenges I've encountered while trying to add tests to my project, gimme_readme, and what I've learned about testing LLM-powered applications along the way.

The Context

This week, my Open Source Development classmates and I were tasked with adding tests to our command-line tools that incorporate Large Language Models (LLMs). This seemed straightforward at first, but it led me down a rabbit hole of testing complexities I hadn't anticipated.

My Testing Journey

The Initial Approach

When I first built gimme_readme, I added some basic tests using Jest.js. These tests were fairly simple, focusing mainly on:

• Verifying function outputs
• Checking basic error handling
• Testing simple utility functions

While these tests provided some coverage, they weren't testing one of the most critical parts of my application: the LLM interactions.

The Challenge: Testing LLM Interactions

As I tried to add more comprehensive tests, I ran into an interesting realization about how my application communicates with LLMs. Initially, I thought I could use Nock.js to mock the HTTP requests to these language models. After all, that's what Nock is great at - intercepting and mocking HTTP requests for testing.

However, I discovered that the way I am using the LLM is making it hard for me to write tests using Nock.

The SDK vs Direct HTTP Requests Dilemma

Here's where things get interesting. My application uses official SDK clients provided by LLM services like Google's Gemini and Groq. These SDKs act as abstraction layers that handle all the HTTP communication behind the scenes. While this makes the code cleaner and easier to work with in production, it creates an interesting testing challenge.

Consider these two approaches to implementing LLM functionality:

The SDK approach is cleaner and provides better developer experience, but it makes traditional HTTP mocking tools like Nock less useful. The HTTP requests are happening inside the SDK, making them harder to intercept with Nock.

Lessons Learned

1. Consider Testing Strategy Early: When choosing between SDKs and direct HTTP requests, consider how you'll test the implementation. Sometimes the "cleaner" production code might make testing more challenging.

2. SDK Testing Requires Different Tools: When using SDKs, you need to mock at the SDK level rather than the HTTP level. This means:

   • Mocking the entire SDK client
   • Focusing on the SDK's interface rather than HTTP requests
   • Using Jest's module mocking capabilities instead of HTTP interceptors

3. Balance Between Convenience and Testability: While SDKs provide great developer experience, they can make certain testing approaches more difficult. It's worth considering this trade-off when architecting your application.

Going Forward

While I haven't yet fully resolved my testing challenges, this experience has taught me valuable lessons about testing applications that rely on external services via SDKs. For anyone building similar applications, I'd recommend:

1. Think about testing strategy when choosing between SDKs and direct API calls
2. If using SDKs, plan to mock at the SDK level rather than the HTTP level
3. Consider writing thin wrappers around SDKs to make them more testable
4. Document the testing approach for others who might work on the project

Conclusion

Testing LLM applications presents unique challenges, especially when balancing modern development conveniences like SDKs with the need for thorough testing. While I'm still working on improving the test coverage for gimme_readme, this experience has given me a better understanding of how to approach testing in future projects that involve external services and SDKs.

Has anyone else encountered similar challenges when testing applications that use LLM SDKs? I'd love to hear about your experiences and solutions in the comments!

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