Braintrust Exporter Bug: Missing Token Counts
Hey guys, this article dives into a critical bug affecting the Braintrust exporter. This issue is causing the exporter to drop essential token count data from API calls, which is super important for accurate cost tracking and performance analysis. Let's break down the problem, how to replicate it, and what we expect to see. I'll also share the environment details and verification steps. This is a pretty big deal, so let's get into it.
The Core Issue: Missing Data
So, what's the deal? The Braintrust exporter isn't capturing several key fields in its table view. This missing data includes crucial metrics used for calculating the total cost, such as the LLM duration, LLM calls, prompt tokens, completion tokens, and the total tokens. While the tool calls seem to be working just fine, the other essential metrics are MIA. The really strange part is that these values are available in the trace details. Plus, they show up normally when you send the data through Mastra Studio. That's a huge red flag, right?
This discrepancy makes it impossible to get an accurate picture of the API call performance within Braintrust. This makes it challenging to accurately assess the cost and efficiency of your projects. Without these metrics, we're basically flying blind when trying to optimize our API usage, and it's super frustrating. The screenshot in the original bug report visually highlights what's missing, emphasizing the importance of these values in the overall analysis. We're talking about essential data here that helps us understand how our systems are working and how much they're costing. Understanding the costs associated with token usage is crucial for any project using LLMs, which makes this bug quite impactful.
This bug makes it really difficult to monitor and optimize costs, which can lead to unexpected expenses. We all know how important it is to control costs, especially when using LLMs. This bug really messes with the ability to do just that, impacting the ability to effectively measure the efficiency and expense of our projects. Imagine not knowing how many tokens you're using or the total cost of each API call! You'd be totally lost, right? This is why it's so important that we get this fixed. The lack of these metrics creates blind spots in our data analysis, making it harder to make informed decisions and optimize workflows. Think about the implications: you can't accurately track your spending, and you can't identify areas for improvement. It's like trying to drive a car without a speedometer or fuel gauge. Not a great situation, to say the least.
Steps to Reproduce the Bug
Reproducing this bug is fairly straightforward, so let's get into it. Here’s how you can see the issue yourself. It's important to be able to replicate the issue to confirm it, right?
- Install the Braintrust exporter: Make sure you have the Braintrust exporter installed and set up correctly within your environment.
- Utilize API via Assistant UI: Use the API through the Assistant UI to generate the API calls. This is the crucial step where the data should be captured by the exporter.
By following these steps, you should be able to trigger the issue, which highlights the absence of the key metrics in the Braintrust exporter’s table view. The goal here is to make it super easy for anyone to reproduce the error and see it firsthand, so they know what to look for. When you perform these steps, it should be pretty obvious that the data isn't showing up as expected. The ease of reproducing this bug underscores how important it is to fix it quickly to prevent cost-related problems. The fact that the steps are so simple to follow means that anyone can quickly verify the problem.
Expected Behavior: What Should Happen?
So, what should we expect to see when everything's working correctly? The Braintrust exporter should capture and pass all of these metadata details for the top-level values. That means the exporter should be collecting LLM duration, LLM calls, prompt tokens, completion tokens, and total tokens. The exporter's main job is to collect and pass these important data points. This information is essential for accurately calculating total costs and gaining insight into the performance of your API calls. We need the data to be properly extracted and presented so we can see it and use it, understand how much each call costs, and spot areas where we can make improvements. This ensures you have all the information you need to make informed decisions about your projects.
Having access to the prompt tokens, completion tokens, and total tokens data is a game-changer. These metrics allow you to accurately measure the costs associated with each API call, which is a key part of effective cost management. Being able to track and understand these metrics helps you optimize your projects, making them more cost-effective. Without these details, you're left in the dark, unable to manage your budget effectively. With everything working as intended, you can quickly analyze the cost of each API call, spot any unusual expenses, and take corrective action. This gives you complete control over your resources.
Environment Information
Here’s a look at the environment details where this issue was identified. This is super useful for anyone trying to replicate the bug or debug it. Knowing the exact versions of the packages involved is super helpful for developers when they're trying to solve the problem. The environment details provide a snapshot of the setup, which helps pinpoint the possible cause. This information also gives the development team a starting point for troubleshooting and testing fixes.
Here's a breakdown of the packages that are involved:
@mastra/auth: ^0.1.5@mastra/braintrust: 0.2.3@mastra/core: 0.24.0@mastra/evals: ^0.14.3@mastra/libsql: ^0.16.2@mastra/loggers: ^0.10.19@mastra/pg: ^0.17.8
Next 22.10
The details are crucial for understanding the setup and context. They're essential for anyone looking into the issue, as they highlight the environment the problem occurred in.
Verification and Conclusion
This bug is a significant issue because it directly impacts the accuracy of data related to token usage and cost tracking within the Braintrust exporter. The inability to properly measure and track costs can lead to financial inefficiencies and challenges in resource management. This bug can lead to hidden costs, making it difficult to optimize operations and manage budgets effectively. Addressing this issue will improve cost monitoring and provide more reliable insights for users. I've confirmed that I have searched the existing issues to make sure this is not a duplicate, and I’ve included all the necessary info to reproduce and understand the problem.
By fixing this bug, we'll ensure that the Braintrust exporter accurately captures and displays the necessary metrics for API calls, providing users with the insights they need to optimize their projects and manage their costs effectively. The impact of this fix is significant, as it enhances data accuracy and ensures that users can depend on the reliability of the tools. It’s all about empowering users with the right data to make informed decisions, improve their workflows, and keep their costs down. It also ensures the overall integrity of the platform’s metrics.