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Logs, Runtime Files and Error Reports#

Overview#

AI Workbench creates application log files that can be used to analyze and debug problems.

The log files are:

  • main: Logfile for the Desktop App.

  • workbench.log: Logfile for the Workbench Service. Host specific.

  • nvwb.log: Logfile for the Workbench CLI.

  • credential-manager: Logfile for the Workbench Credential Manager. Host specific.

  • traefik.log: Logfile for the traefik proxy container. Host specific.

You can find the files individually on your system, and error messages will often have a link to open the relevant file.

There are also project specific runtime files for debugging problems in the container or applications.

These files are project and host specific and are in the ~/.nvwb/project-runtime-info/ folder on the relevant host. The files are found in the subfolder with the project’s name, and applications within the container need to be configured to post logs appropriately.

You can create error reports with complete information for analysis and debugging.

The Desktop App and the CLI let you create a zipfile of all logs runtime files for a host. Error messages typically have a link to create a report as well.

Reports can be opened and analyzed by your or an agent. You can also send them to our support email.

Access Application Logs and Project Runtime Files#

The location of application logs and runtime files depends on the operating system.

File Type

Location

Desktop application log files

C:\Users\<USERNAME>\AppData\Local\NVIDIA Corporation\AI Workbench\logs\main.log

Server log files

Linux\NVIDIA-Workbench\home\workbench\.nvwb\logs\workbench.log

CLI log files

Linux\NVIDIA-Workbench\home\workbench\.nvwb\logs\nvwb.log

Project runtime files

Linux\NVIDIA-Workbench\home\workbench\.nvwb\project-runtime-info\<PROJECT-NAME-AND-HASH>\

File Type

Location

Desktop application log files

/home/<USERNAME>/.config/NVIDIA/AI Workbench/logs/main.log

Server log files

/home/<USERNAME>/.nvwb/logs/workbench.log

CLI log files

/home/<USERNAME>/.nvwb/logs/nvwb.log

Project runtime files

/home/<USERNAME>/.nvwb/project-runtime-info/<PROJECT-NAME-AND-HASH>/

File Type

Location

Desktop application log files

/Users/<USERNAME>/Library/Application Support/NVIDIA/AI Workbench/logs/main.log

Server log files

/Users/<USERNAME>/.nvwb/logs/workbench.log

CLI log files

/Users/<USERNAME>/.nvwb/logs/nvwb.log

Project runtime files

/Users/<username>/.nvwb/project-runtime-info/<PROJECT-NAME-AND-HASH>/

Create an Error Report for Troubleshooting#

Error reports should exclude sensitive or identifiable information but it’s not always possible.

Creating an error report automatically tries to exclude sensitive or identifiable information, but there are many ways such information can be included. You should review the contents of an error report before you share it with anyone.

Creating an error report from the Desktop App only reports on your local location.

  1. Select the system-tray/status-menu

  2. Right click on the AI Workbench icon

  3. Select “Generate Error Report”

  4. Find the error report on your desktop

You can create an error report for a remote location using the CLI.

The CLI is only available locally if you’ve done the full local install.

  1. Open a local terminal

  2. Create the report: nvwb support create-bundle --context <location name>

  3. The report is at printed path in the success message.

AI Workbench Project Runtime Files#

AI Workbench creates files to track progress while building, configuring, and running each project.

The files are in the project’s folder in ~/.nvwb/project-runtime-info.

The files found in that folder are in the table below.

File/Directory

Description

Containerfile

Generated on demand during the project build (can also be called a Dockerfile).

build-output.success

Build logs from the last successful build.

build-output.error

Build logs from the last failed build.

build-output.building

Build logs from the currently in-progress build.

cache/

Directory that acts as the build context for the container build.

edit.cache

The cache value of the last edit of the container image made by the library.

fetch-output.success

Fetch logs from the last successful fetch.

fetch-output.error

Fetch logs from the last failed fetch.

fetch-output.fetching

Fetch logs from the currently in-progress fetch.

mount/

Directory that stores mount definitions for the project’s configured mounts, as well as mount directories and unmount scripts for each mount. For more information, see Runtime Configuration (Environment Variables and Mounts).

rebuild.cache

The cache value of the last build of the container image.

runtime-flags.json

Flags used by AI Workbench.

secrets.env

The project’s secret environment variables and their values. For more information, see Environment Variables.