Troubleshooting

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Common Issues

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Function Timeout

1. Increase the timeout - Set a higher timeout value in your @function decorator
2. Report progress - Use ctx.progress.update() to reset the timeout. See Streaming Progress Updates
3. Check the logs - Use the Logs API above to see what your function was doing before it timed out

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Request Failed

1. Check request state - Get the full request state including failure reason:

curl -X GET \
  "https://api.tensorlake.ai/applications/{application}/requests/{request_id}" \
  -H "Authorization: Bearer $TENSORLAKE_API_KEY"

2. Review logs - Filter logs by the request ID to see what happened:

curl -X GET \
  "https://api.tensorlake.ai/applications/{application}/logs?requestId={request_id}" \
  -H "Authorization: Bearer $TENSORLAKE_API_KEY"

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Out of Memory

1. Check current allocation - Review the memory setting in your @function decorator
2. Increase memory - Set memory to a higher value (up to 32 GB). See Memory
3. Process in batches - Break large datasets into smaller chunks

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Debugging Tips

• Add print() statements in your code to log intermediate values
• Use ctx.request_id to correlate logs across function calls. See Request ID
• Check that your function has sufficient CPU, memory, and disk resources
• Review retry settings if functions are failing intermittently. See Retries