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Apheris Hub - Known Issues🔗

Below, we list known issues with Apheris Hub. If available, we list a workaround to help troubleshoot the issue.

This list will be constantly evolving with input from our different users and with the evolution of our product in future releases.

Known Issues with Apheris Hub 1.0.0🔗

OpenFold3🔗

Issue Description Additional information
Unexpected Behavior on some Batch Requests Due to an unresolved MSA cache bug in the OpenFold3 code base, batch requests (i.e. requests with more than one query) with more than a single unique protein sequence and counterpart MSA may cause unexpected behavior. Please submit individual requests with a single query for these complexes.
MSA Files Cannot Be Used with OpenFold3 An issue prevents the reliable usage of MSA files with the current OpenFold3 model. Do not use MSA files with the OpenFold3 model version. The public MSA server version is available, but you should not use MSA files with it.

Inference and Processing🔗

Issue Description Additional information
ColabFold Server Rate Limiting When using public models, the ColabFold server applies rate limiting, which can significantly slow down processing of even simple queries. If you encounter slower than anticipated query times it is likely due to using the public ColabFold server. Please wait a few minutes and try again or use MSAs from file if the model supports it.
Request Status Tracking Inference requests can get stuck in a "running" state if the corresponding model is stopped or uninstalled during processing. After an instance restart, the request is transitioned to done, but the results are not displayed.
Sequence Visualization On the sequence view, chains display only once.
Sequence Selection Selection in sequence viewer is done in groups of 10 amino acids instead of individual ones, and selection doesn't apply properly to the pLDDT or cartoon views.
Results Polling When going to the results page before a prediction completed, you might have to refresh the page for the results to load.
Delayed Execution on Shared GPU When we have a single GPU being shared between two running model versions, parallel jobs can be started on each of those models. However, because they share the same GPU, the execution can be blocked and delayed. Additionally, the UI shows the delayed requests as "Running" instead of "Pending", as they are waiting for the GPU to become available.
Error Log Display Error logs are shown even for successful inference runs. However, they don't always contain errors per se but just the stderr output.
Log Presentation Empty log content lacks proper placeholder text, and the copy button is still displayed even when no content is available.
Job Duration Metrics Job duration doesn't distinguish between waiting time and actual running time, which can be misleading when multiple jobs are queued.

Security🔗

Issue Description Additional information
Container User Privileges Docker containers are currently running with root user privileges, which is not a security best practice.
Input Path Validation There are several instances where input validation should be improved to prevent potential path traversal issues. Some of the issues stem from the original models implementation.

User Interface🔗

Issue Description Additional information
Status Display Inconsistencies Running state is not consistently color-coded between the results list and details screens.
Settings Tab Highlight The Settings tab isn't highlighted when selected, unlike the Information tab.
Empty Settings Information The Model settings screen appears with empty information after first installation, without feedback explaining why.
PAE/PDE Plot Selection When trying to select areas of the PAE/PDE plot, the selection box behaves erratically and lower areas cannot be selected.

Form and Input Handling🔗

Issue Description Additional information
Asset Upload Experience When adding assets for upload during request creation, drag and drop shows flickering and sometimes fails to complete.
Field Validation The msa field in private MSA requests is not properly marked as required, causing failures when omitted.
Path Copy Functionality Copy buttons for 'Input path' and 'Output path' may show an outdated browser error message even on updated browsers.

Installation and Configuration🔗

Issue Description Additional information
Port Allocation The installation script uses a fixed port (8080) which may already be in use on some systems. As a workaround, ensure port 8080 is available before installation or modify the port in the installation script.
CloudFormation Upgrade Using the CloudFormation template, upgrading an existing stack to a newer version fails.
CloudFormation CIDR Range Parameter Limitations The CloudFormation template doesn't allow specifying multiple CIDR ranges in the AllowIngressFromCidr parameter, limiting access control options.
CloudFormation Deployment Failures CloudFormation deployments occasionally fail without clear error messages.
CloudFormation Roll Back Limitation If the Hub doesn't start, the CloudFormation stack is not rolled back.
Feedback on Wrong Configuration or Systems Faults On installation, if a configuration item is wrong (e.g. the API key) or a system fault occurs (e.g. no space left on device), there is no feedback to the user on UI. Inspect the Hub logs (see View Docker Logs to troubleshoot the issue.