Logs

The GenAI Stack provides a comprehensive logging feature that allows users to view and manage logs generated during the deployment and execution of their AI workflows. These logs are essential for monitoring performance, debugging issues, and ensuring the smooth operation of your AI stacks. This documentation covers the steps to access and understand the logging features in GenAI Stack.

Accessing Logs

1. Deploying Your Stack:

   • After configuring your workflow and ensuring all components are correctly set up, click on the "Deploy" button to deploy your stack.

   

   • Once the deployment is successful, the status will change to "Deployed," as indicated in the top bar of the interface.

2. Navigating to Logs:

   • In the top bar of the GenAI Stack interface, you will see an option labeled "View Logs." This button becomes available once your stack is deployed.

   

   • Click on "View Logs" to access the logs for the deployed stack.

Using the Logs Feature

1. Log Overview:

   • The logs interface provides a comprehensive view of all activities and events that occur during the execution of your stack.

   • You can see details such as timestamps, event types, and any error messages that might have been generated.

   
2. Session Management:

   • The logs are organized by sessions. Each session represents a distinct execution of your deployed workflow.

   • You can view the list of sessions in the "Text Generation Sessions" section, where each session has a unique identifier and a timestamp of when it was created.

3. Viewing Specific Sessions:

   • To view the details of a specific session, click on the "View" button next to the session ID.

   • This will open a detailed log of that particular session, where you can analyze the execution flow, inspect input and output data, and identify any issues.

Log Interface

The log interface is divided into two main sections:

1. Build Logs: These logs provide information about the build process of your AI workflows. It includes details about each component's initialization, data loading, and any errors or warnings encountered during the build process.

2. Chain Logs: These logs provide information about the execution of your AI workflows. It includes details about the data processing, model inference, and any outputs generated by the workflow components.

Summary

By providing detailed logs and an intuitive interface, GenAI Stack ensures that users can efficiently monitor and manage their AI workflows. The logs feature is crucial for maintaining the performance and reliability of your AI stacks, offering insights into both the build and execution phases. With the ability to view detailed session logs, users can better understand their workflows and address any issues that arise.

By following this guide, users can leverage the logging capabilities of GenAI Stack to their full potential, ensuring a smooth and effective AI development process.