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CONFIGURABLE_TIMEOUT_IMPLEMENTATION.md

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Configurable Installation Review Timeout - Implementation Summary

User Request

User requested making the installation review timeout configurable instead of hardcoded, with a default of 20 minutes. The rationale:

  • Local AI can be slow
  • AI may have queued requests
  • Reviews run overnight, so urgency is not a concern
  • The app doesn't need results immediately

Implementation

1. Configuration Parameter Added

Parameter: installation_review_timeout

  • Default: 1200 seconds (20 minutes)
  • Range: 60-3600 seconds (1 minute to 1 hour)
  • Type: Integer

2. Files Modified

ha_sentry/config.yaml

  • Added installation_review_timeout to options with default of 1200
  • Added schema validation: int(60,3600)
  • Added comprehensive documentation explaining:
    • When to increase (slow AI, reasoning models, queued requests)
    • When to decrease (fast AI, quick failure detection)
    • That reviews run overnight so longer timeouts are acceptable
    • Example values for different scenarios

ha_sentry/rootfs/app/config_manager.py

  • Added self.installation_review_timeout configuration property
  • Reads from INSTALLATION_REVIEW_TIMEOUT environment variable
  • Default: 1200 seconds if not specified
  • Added validation in _validate_config():
    • Ensures value is between 60 and 3600 seconds
    • Resets to default (1200) if out of range
    • Logs error if invalid

ha_sentry/rootfs/app/installation_reviewer.py

  • Changed from hardcoded timeout_seconds = 300.0
  • Now uses timeout_seconds = float(self.config.installation_review_timeout)
  • Updated comments to reflect configurability
  • Removed TODO comment about making it configurable

tests/test_installation_review_timeout.py

  • Renamed test from test_timeout_value_is_300_seconds to test_timeout_is_configurable
  • Verifies timeout is read from config, not hardcoded
  • Verifies config.yaml has the parameter
  • Verifies default value is 1200 seconds
  • All assertions updated for new behavior

Testing Results

All tests pass (9/9):

  • ✅ Timeout configurability test (4/4)
  • ✅ Log message tests (2/2)
  • ✅ Scheduling tests (3/3)
  • ✅ Python syntax validation passed

Backward Compatibility

Fully backward compatible:

  • Existing installations will use default of 1200 seconds (20 minutes)
  • Previous hardcoded 300 seconds was too short; new 1200 default is better
  • No configuration changes required for existing users
  • Optional configuration for users who want to customize

Configuration Examples

Default (Recommended)

installation_review_timeout: 1200  # 20 minutes

For Slow AI or Queued Systems

installation_review_timeout: 1800  # 30 minutes
installation_review_timeout: 2400  # 40 minutes

For Fast Local AI

installation_review_timeout: 600   # 10 minutes
installation_review_timeout: 900   # 15 minutes

Maximum Allowed

installation_review_timeout: 3600  # 1 hour

Benefits

  1. Flexibility: Users can adjust based on their specific AI provider and hardware
  2. Better Default: 20 minutes (vs previous 5 minutes) accommodates reasoning models
  3. Queue-Friendly: Long enough for local AI with request queues
  4. No Urgency: Since reviews run overnight, longer timeouts don't impact UX
  5. Validation: Ensures timeout stays within reasonable bounds (1 min to 1 hour)

User Communication

Replied to user's comment (ID: 3649430639) confirming:

  • Timeout is now configurable
  • Default is 20 minutes as requested
  • Range is 60-3600 seconds
  • Accommodates slow/queued local AI
  • Commit hash: 95ed825

Commit Details

Commit: 95ed825 Message: Make installation review timeout configurable with 20 minute default Changes:

  • Configuration parameter added with validation
  • Documentation added to config.yaml
  • Implementation updated to use configured value
  • Tests updated to verify configurability
  • All tests pass

Documentation

Configuration documentation added to ha_sentry/config.yaml includes:

  • Parameter description and purpose
  • Default value and range
  • When to increase timeout (slow AI, reasoning models, queues)
  • When to decrease timeout (fast AI, quick failure detection)
  • Examples for different scenarios
  • Explanation that reviews run overnight so longer timeouts are acceptable