fix: make workflow worker batch size configurable

[vishnurk6247]

Summary by CodeRabbit

• Improvements
  • Batch size for workflow job processing is now configurable through application settings rather than using a fixed value.

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[coderabbitai]

Walkthrough

Configuration externalization: A hardcoded batch size value (5) in the workflow job is replaced with a dynamic configuration parameter. The batch_size option is added to config.ini and read at runtime from main.py, allowing environment-based customization without code changes.

Changes

Cohort / File(s)	Summary
Batch Size Configuration Externalization wavefront/server/background_jobs/workflow_job/workflow_job/config.ini, wavefront/server/background_jobs/workflow_job/workflow_job/main.py	Added batch_size configuration option with default value 5 in config.ini; updated main.py to read streaming_batch_size from configuration instead of using hardcoded constant.

Estimated code review effort

🎯 1 (Trivial) | ⏱️ ~3 minutes

• Configuration addition is straightforward with sensible defaults
• Single line modification in main.py to read from config (minimal logic change)

Poem

🐰 A batch size once rigid and bound,
Now flexes through config, so sound!
No hardcoding's chains,
Just environment's gains,
Configuration magic, we've found! ✨

Pre-merge checks and finishing touches

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	You can run @coderabbitai generate docstrings to improve docstring coverage.

✅ Passed checks (2 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title accurately describes the main change: making the workflow worker batch size configurable by moving it from a hardcoded value to a configuration parameter.

✨ Finishing touches

• 📝 Generate docstrings

🧪 Generate unit tests (beta)

• Create PR with unit tests
• Post copyable unit tests in a comment
• Commit unit tests in branch fix/workflow-worker-count

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[coderabbitai]

Actionable comments posted: 0

🧹 Nitpick comments (1)

wavefront/server/background_jobs/workflow_job/workflow_job/main.py (1)

106-106: LGTM! Change follows existing configuration patterns.

The dynamic batch size configuration is implemented consistently with the thread_count pattern (line 109) and replaces the hardcoded value with a configurable option.

Optional: Consider adding validation for positive batch size values.

StreamListener.__init__ accepts streaming_batch_size without validation. Adding a check like:

if batch_size <= 0:
    raise ValueError(f"batch_size must be positive, got {batch_size}")

would prevent edge cases from propagating to event_manager.receive_messages().

📜 Review details

Configuration used: defaults

Review profile: CHILL

Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between a205861 and 2df4c9a.

📒 Files selected for processing (2)

• wavefront/server/background_jobs/workflow_job/workflow_job/config.ini (1 hunks)
• wavefront/server/background_jobs/workflow_job/workflow_job/main.py (1 hunks)

⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (1)

• GitHub Check: build-push-artifact

🔇 Additional comments (1)

wavefront/server/background_jobs/workflow_job/workflow_job/config.ini (1)

5-5: LGTM! Configuration follows established patterns.

The new batch_size configuration option follows the same pattern as other config values (e.g., thread_count), using environment variable substitution with a sensible default of 5.