Mastra-AI Memory Pagination Bug: Troubleshooting & Solutions

Hey guys, let's break down a tricky little bug report concerning Mastra-AI's memory feature. It looks like the pagination functionality in the query() method isn't behaving as expected. This is a pretty important feature, so let's dig into the details and figure out what's going on.

The Bug: Pagination Problems in Mastra-AI Memory

So, the core issue here is that when you try to use pagination with the query() method in Mastra-AI's memory component, it's not working as intended. Specifically, the user is expecting to get paginated data back when they specify selectBy: { pagination: { page: 1, perPage: 1 } }. Basically, they're asking for one item per page, but something's going wrong.

This is a significant problem because pagination is super important for managing large datasets efficiently. Without it, you could run into performance issues and struggle to retrieve specific chunks of data. The user has provided a clear description of the problem, which is awesome. The bug report includes a screenshot of the code and the expected behavior, along with the environment information, making it easy to understand and, hopefully, reproduce the issue. Let's go a little deeper, shall we?

Understanding the Code and the Expected Outcome

The user's provided code snippet shows how they're trying to use the query() method. They're setting up a Memory instance, and then they're trying to fetch messages using the query function, specifying the pagination parameters. Let's take a peek: the page parameter is set to 1, and the perPage is set to 1. This should, in theory, return the first message from the dataset. The actual observed behavior, according to the bug report, is that the pagination isn't working, which means the user is not getting the desired, paginated result. The user has clearly stated that when running the code, they should receive one message, but it's not happening.

Importance of Reproducibility and Environment Details

Reproducing a bug is the first step in resolving it. The user has done a great job of including all the relevant information, such as the Mastra-AI package versions, node version, and Postgres version. Having these environmental details is super important. The versions of @mastra/core, @mastra/memory, and @mastra/pg that are listed are key. Along with the Node and Postgres versions, these details allow anyone looking into the problem to set up an identical environment, and ideally, reproduce the bug locally. The user also confirmed that they checked for existing issues, which is a great way to avoid duplicating efforts. Reproducibility makes the debugging process much easier, so this is a very well-written bug report!

Steps to Reproduce the Bug and What to Expect

To recreate this issue, you'll need to set up a Mastra-AI environment with the specified package versions. Here's a breakdown of the steps the original bug reporter provided:

1. Set Up the Environment: You'll need to initialize a PostgresStore and a Memory instance. The PostgresStore will likely require a connection string to your PostgreSQL database. Ensure that the database is accessible and configured correctly.
2. Populate the Memory: The code assumes you have some data (messages) stored in your Mastra-AI memory. This might involve saving messages using the memory.saveMessages() method (as indicated by the comment in the code). You will need to insert data into your memory component.
3. Run the Query: Execute the memory.query() method with the pagination parameters: { resourceId: resourceId, threadId: threadId, selectBy: { pagination: { page: 1, perPage: 1 } } }. Replace resourceId and threadId with your actual resource and thread identifiers.
4. Verify the Output: The expected behavior is that the query should return only one message, as specified by the pagination settings. If you receive more than one message or the pagination seems to be ignored, then the bug is happening.

Further Investigation: Digging Deeper into the Root Cause

To solve this bug, the developers will likely need to dive into the query() method's implementation. They'll probably want to check how the pagination parameters are being processed. Is the code correctly applying the page and perPage values to the database query? Are there any logical errors in how the pagination is being calculated? Checking the SQL queries being generated will be an important part of the debugging process. It's possible that there's a problem with how the database interacts with the pagination parameters. Another area to explore is the interaction between the @mastra/memory package and the @mastra/pg package. Maybe there's an issue in how the pagination information is being passed from the memory component to the database. Good luck, devs!

Impact of the Bug and Potential Workarounds

The bug can have a major impact on applications that depend on Mastra-AI for handling large volumes of data. If pagination doesn't work, then the app might experience performance issues, and it becomes difficult to navigate through the data. This will make it harder to find particular messages or information. For the time being, if you hit this bug, here are some workarounds:

1. Manual Pagination: The user could manually paginate the results after retrieving all the data. This is not ideal for large datasets because it would involve fetching the full dataset first.
2. Custom Queries: Users could try to build custom SQL queries that include pagination logic. This is a more complex solution. It requires a deeper understanding of the database and the Mastra-AI data model.
3. Review and Use Older Versions: If an older version of the package doesn't have this issue, it could be a temporary solution. However, this is not a long-term fix.

Conclusion: Addressing the Pagination Issue

This is a detailed and thorough bug report. The user clearly identified the problem, provided all the information needed to replicate the bug, and described the expected and actual behaviors. The team will hopefully be able to isolate the problem quickly, and implement a fix.

The bug affects the basic functionality of the Mastra-AI memory component, so it's super important for the developers to address it to ensure a good user experience. Guys, let's hope the fix rolls out soon. Until then, keep on coding, and happy debugging!