UI Bug: Model Test Fails With LLM Provider NOT Provided

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UI Bug: Model Test Fails with "LLM Provider NOT provided"

Hey guys! Today, we're diving deep into a peculiar bug that's been causing some headaches in the UI, specifically when testing new models. It's all about that dreaded "LLM Provider NOT provided" error, and trust me, it's as annoying as it sounds. Let's break down what's happening, how to reproduce it, and what might be going on under the hood.

What's the Fuss About? The Problem Explained

So, here's the deal: when you're adding a shiny new model in the UI and you eagerly hit that "Test connect" button, you might be greeted with the rather unhelpful error message: "LLM Provider NOT provided." Now, the kicker is, if you save the model and then test it in the "Test key" section, it works perfectly fine! Talk about frustrating, right?

This issue seems to pop up specifically when you're dealing with an openai-compatible self-hosted provider. You've got everything set up, you've chosen the provider in the dropdown menu, but the "Test connect" button just refuses to cooperate. It's like it's deliberately trying to ruin your day. Even weirder, this also happens if you mistakenly include a provider name in the model name field. It's as if the system gets confused and throws a tantrum.

But wait, there's more! The most infuriating part is that after saving the model, you can use it without any hiccups. This suggests that the configuration is actually correct, but the initial test is somehow misinterpreting something. It's a classic case of "it works after you save it," which is about as helpful as a chocolate teapot when you're trying to debug.

Why is this happening? Well, it seems like the "Test connect" function might not be correctly picking up the provider information during the initial test. It could be a problem with how the UI is passing the data, or perhaps there's a validation step that's too strict or simply misplaced. Whatever the reason, it's clear that something is amiss, and it's causing unnecessary frustration for users trying to integrate their models.

To summarize, this bug is particularly problematic because:

  1. It creates a false negative, making users think there's an issue with their configuration when there isn't.
  2. It wastes time, as users have to save the model and test it again to confirm it works.
  3. It's inconsistent, which makes it hard to diagnose and fix.

In short, it's a pain in the neck, and we need to get to the bottom of it!

How to Reproduce This Nuisance

Okay, so you want to see this bug in action for yourself? No problem! Here’s a step-by-step guide to reproducing the "LLM Provider NOT provided" error:

  1. Set up an OpenAI-Compatible Self-Hosted Provider:

    • First things first, you’ll need an OpenAI-compatible self-hosted provider. This could be anything like a custom API endpoint that mimics the OpenAI API or a service like vLLM running locally.
    • Make sure you have the necessary credentials (API key, endpoint URL, etc.) handy.

  2. Navigate to the Model Configuration in the UI:

    • Head over to the section in the UI where you can add or configure new models. This is usually found in the settings or admin panel.

  3. Add a New Model:

    • Click on the button to add a new model. You’ll typically be presented with a form to fill out.

  4. Fill in the Model Details:

    • Enter the model name. This is where things can get tricky. Avoid including the provider name in the model name field, as this can trigger the bug.
    • Select your openai-compatible self-hosted provider from the “provider” dropdown menu. This is crucial.
    • Provide the necessary API key or credentials for your provider.
    • Enter the endpoint URL for your provider.

  5. Click on "Test connect":

    • Now, with all the details filled in, click on the "Test connect" button. This is the moment of truth.

  6. Observe the Error:

    • If you’ve done everything correctly (or rather, incorrectly, to reproduce the bug), you should see the dreaded error message:
    LLM Provider NOT provided. Pass in the LLM provider you are trying to call.
You passed model=deepseek-r1-distill-qwen-1.5B-q4
Pass model as E.g. For 'Huggingface' inference endpoints pass in `completion(model='huggingface/starcoder',..)`
Learn more: https://docs.litellm.ai/docs/providers

  7. Save the Model (Optional):

    • If you haven’t already, save the model configuration.

  8. Test the Model in the "Test key" Section:

    • Go to the "Test key" section (or wherever you can test the model after saving it).
    • Select the model you just configured.
    • Run a test query.
    • You should see that the model works perfectly fine, despite the initial error message.

Tips for Reproduction:

  • Provider Name in Model Name: Try including the provider name in the model name field. This can sometimes trigger the bug.
  • Correct Credentials: Double-check that you’ve entered the correct API key and endpoint URL.
  • Self-Hosted Provider: Ensure that your self-hosted provider is correctly configured and accessible.

By following these steps, you should be able to consistently reproduce the "LLM Provider NOT provided" error. This is super helpful for developers trying to debug and fix the issue.

Diving into the Details: Log Output and Environment

Alright, let's get a bit more technical and look at some of the nitty-gritty details that might help us understand what's going on. In this section, we'll explore the relevant log output and the environment in which this bug is occurring.

Relevant Log Output

Unfortunately, the user who reported this bug didn't provide any specific log output. However, if you're encountering this issue, here's what you should look for in your logs:

  1. UI Logs: Check the logs for the UI component that handles the model configuration and testing. Look for any errors or warnings that occur when you click the "Test connect" button. These logs might give you clues about why the provider information is not being correctly passed.
  2. Backend Logs: Examine the logs for the backend service that processes the model configuration and interacts with the LLM provider. Look for any errors related to authentication, authorization, or provider validation.
  3. Network Logs: Use your browser's developer tools to inspect the network requests that are sent when you click the "Test connect" button. Check the request payload to see if the provider information is included. Also, look at the response from the server to see if there are any error messages or clues.

Common Log Messages to Look For:

  • "LLM Provider NOT provided" (obviously)
  • "Invalid API key" or "Authentication failed"
  • "Missing provider parameter"
  • "Failed to connect to the LLM provider"

Environment Details

Knowing the environment in which the bug occurs can also be helpful. Here are some key details to consider:

  • LiteLLM Version: The user reported that they were using version v1.80.0. This means that the bug is likely present in that version. If you're using a different version, it's worth checking if the bug has been fixed (or introduced) in that version.
  • Operating System: The user didn't specify their operating system, but this could be relevant. If you're encountering the bug on a specific OS (e.g., Windows, macOS, Linux), it's worth noting.
  • Browser: The browser you're using could also play a role. Try reproducing the bug in different browsers (e.g., Chrome, Firefox, Safari) to see if it's browser-specific.
  • Self-Hosted Provider: The type of self-hosted provider you're using is also important. Are you using vLLM, a custom API, or something else? The specific provider might have its own quirks that are contributing to the bug.

By gathering this information, you can provide a more complete picture of the environment in which the bug is occurring. This can help developers reproduce the bug more easily and identify the root cause.

Are you a ML Ops Team?

The user explicitly stated that they are not an ML Ops team. This suggests that the bug is affecting individual users or small teams who are not necessarily experts in machine learning operations. This means that the bug is likely to be more widespread and impactful, as it's affecting users who may not have the expertise to work around it.

Potential Causes and Solutions

Okay, folks, let's put on our detective hats and try to figure out what's causing this pesky bug and, more importantly, how we can fix it!

Potential Causes

Based on the information we have, here are some potential causes for the "LLM Provider NOT provided" error:

  1. UI Data Passing Issue:
    • The UI might not be correctly passing the provider information to the backend when the "Test connect" button is clicked.
    • The data might be missing, incomplete, or in the wrong format.
  2. Backend Validation Error:
    • The backend might be performing a validation check that's too strict or incorrect.
    • The validation logic might be expecting the provider information in a specific format that's not being met.
  3. Provider Name Conflict:
    • If the provider name is included in the model name field, it might be confusing the system.
    • The system might be trying to interpret the model name as the provider, leading to the error.
  4. Asynchronous Issue:
    • The "Test connect" function might be running asynchronously, and the provider information might not be available when the test is executed.
    • This could be due to a race condition or a timing issue.
  5. Configuration Caching:
    • The UI or backend might be caching the model configuration, and the cached version might not include the provider information.
    • This could explain why the model works after saving, as saving might refresh the cache.

Possible Solutions

Now that we have some potential causes, let's brainstorm some possible solutions:

  1. UI Data Passing Fix:
    • Ensure that the UI is correctly passing the provider information to the backend.
    • Double-check the data format and make sure all required fields are included.
    • Use debugging tools to inspect the data being sent and received.
  2. Backend Validation Adjustment:
    • Review the backend validation logic and make sure it's not too strict.
    • Adjust the validation rules to correctly handle the provider information.
    • Add more informative error messages to help users diagnose the issue.
  3. Provider Name Handling:
    • Implement a check to prevent users from including the provider name in the model name field.
    • If the provider name is included, display a warning message and suggest a different model name.
  4. Asynchronous Handling:
    • Ensure that the "Test connect" function is waiting for the provider information to be available before executing the test.
    • Use asynchronous programming techniques to handle the data loading and processing.
  5. Cache Busting:
    • Implement a cache-busting mechanism to ensure that the UI and backend are always using the latest model configuration.
    • Clear the cache when the model is saved or updated.

By implementing these solutions, we can hopefully eliminate the "LLM Provider NOT provided" error and make the UI more user-friendly.

Conclusion: Taming the "LLM Provider NOT provided" Beast

Alright, folks, we've reached the end of our deep dive into the mysterious "LLM Provider NOT provided" bug. We've explored what's happening, how to reproduce it, potential causes, and possible solutions. It's been a wild ride, but hopefully, we're now better equipped to tackle this issue.

To recap, the bug occurs when you're adding a new model in the UI and click the "Test connect" button. It throws an error saying that the LLM provider is not provided, even though you've selected it in the dropdown menu. This is particularly annoying because the model works fine after you save it and test it in the "Test key" section.

We've identified several potential causes, including UI data passing issues, backend validation errors, provider name conflicts, asynchronous problems, and configuration caching. And we've come up with a range of solutions, from fixing the UI data passing to adjusting the backend validation logic.

So, what's next? Well, if you're a developer, it's time to roll up your sleeves and start implementing these solutions. If you're a user, keep reporting these bugs and providing feedback. Together, we can make the UI more robust and user-friendly.

Remember, every bug is an opportunity to learn and improve. And with a bit of detective work and some clever coding, we can tame the "LLM Provider NOT provided" beast and make our lives a little bit easier. Keep coding, keep testing, and keep reporting those bugs!