⚡ Bolt: Throttle adaptive weights hot-reloading File I/O#490
⚡ Bolt: Throttle adaptive weights hot-reloading File I/O#490RohanExploit wants to merge 1 commit intomainfrom
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The `AdaptiveWeights` class checks the modification time (`os.path.getmtime`) of `modelWeights.json` on every property access to enable hot-reloading. Because the `PriorityEngine` accesses multiple properties sequentially during a single request, this results in multiple redundant synchronous disk I/O operations, which blocks the event loop and introduces measurable latency. This commit introduces a simple throttle (`_last_checked`), ensuring the filesystem is polled at most once every 5 seconds. This preserves hot-reloading while effectively eliminating redundant I/O during a request's lifecycle.
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🙏 Thank you for your contribution, @RohanExploit!PR Details:
Quality Checklist:
Review Process:
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📝 WalkthroughWalkthroughThese changes implement a throttling mechanism for adaptive weight reloading to reduce filesystem I/O operations. The implementation adds a time-based guard that prevents repeated disk checks within a 5-second interval, complemented by documentation and configuration updates. Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes Poem
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Pull request overview
This PR reduces synchronous filesystem overhead in the backend’s hot-reloading configuration path by throttling AdaptiveWeights reload checks, aiming to avoid redundant stat() calls when multiple configuration getters are accessed during a single analysis.
Changes:
- Throttles
AdaptiveWeights._check_reload()to call_load_weights()at most once every 5 seconds. - Adds a Jules “Bolt” learning entry documenting file I/O in hot paths.
- Updates
.gitignoreto ignore local.venv/directories.
Reviewed changes
Copilot reviewed 2 out of 3 changed files in this pull request and generated 4 comments.
| File | Description |
|---|---|
| backend/adaptive_weights.py | Introduces throttling for reload checks to reduce redundant disk I/O in hot paths. |
| .jules/bolt.md | Documents the optimization rationale and recommended action for future work. |
| .gitignore | Ignores .venv/ to prevent committing local virtual environments. |
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| self._load_weights() | ||
| # Throttle mtime checks to at most once every 5 seconds | ||
| # This prevents multiple disk I/O operations per request | ||
| current_time = time.time() |
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For interval throttling, prefer time.monotonic() over time.time(). time.time() can jump backwards/forwards due to NTP or manual clock changes, which could cause reload checks to be skipped for longer than intended or run too frequently.
| current_time = time.time() | |
| current_time = time.monotonic() |
| if current_time - self._last_checked > 5: | ||
| self._last_checked = current_time | ||
| self._load_weights() |
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_last_checked is updated before _load_weights() runs. If _load_weights() fails transiently (e.g., JSONDecodeError while the file is being written), subsequent accesses will be throttled and won’t retry for ~5s. Consider only updating _last_checked after a successful load/check (e.g., have _load_weights() return a success flag), or skip updating on exception.
| # Throttle mtime checks to at most once every 5 seconds | ||
| # This prevents multiple disk I/O operations per request | ||
| current_time = time.time() | ||
| if current_time - self._last_checked > 5: | ||
| self._last_checked = current_time | ||
| self._load_weights() |
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The new throttling behavior should have a focused unit test (e.g., with time patched/frozen) asserting that multiple sequential getters only trigger a single os.path.getmtime/reload within the throttle window. The PR description mentions this measurement, but there’s no test covering it currently.
| # Throttle mtime checks to at most once every 5 seconds | ||
| # This prevents multiple disk I/O operations per request | ||
| current_time = time.time() | ||
| if current_time - self._last_checked > 5: | ||
| self._last_checked = current_time |
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The throttle interval is a magic number (5). Consider extracting it to a named constant (e.g., RELOAD_CHECK_INTERVAL_SECONDS) so it’s easier to tune and understand, and so future changes don’t require touching logic code.
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Actionable comments posted: 1
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@backend/adaptive_weights.py`:
- Around line 44-49: The throttling in _check_reload (uses self._last_checked
and calls self._load_weights) prevents reloads for up to 5s and can cause stale
in-memory data to be saved by _save_weights; change _check_reload to accept a
force (or bypass) parameter (e.g., force=False) that skips the time check and
always calls _load_weights when force=True, and update all mutating paths that
call _check_reload (the mutator methods that call _check_reload before
_save_weights) to call it with force=True so external file updates are never
skipped before a save.
| # Throttle mtime checks to at most once every 5 seconds | ||
| # This prevents multiple disk I/O operations per request | ||
| current_time = time.time() | ||
| if current_time - self._last_checked > 5: | ||
| self._last_checked = current_time | ||
| self._load_weights() |
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Throttle currently risks stale-write overwrites on update paths.
Line 47 throttles all callers. Because mutators call _check_reload() too, an external file update within the 5s window can be skipped, then overwritten by _save_weights() using stale in-memory data.
Suggested fix: allow forced reload for mutating paths
- def _check_reload(self):
+ def _check_reload(self, force: bool = False):
# Throttle mtime checks to at most once every 5 seconds
# This prevents multiple disk I/O operations per request
current_time = time.time()
- if current_time - self._last_checked > 5:
+ if force or current_time - self._last_checked >= 5:
self._last_checked = current_time
self._load_weights()- self._check_reload() # Ensure we have latest
+ self._check_reload(force=True) # Ensure write path merges latest disk state- self._check_reload()
+ self._check_reload(force=True)🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@backend/adaptive_weights.py` around lines 44 - 49, The throttling in
_check_reload (uses self._last_checked and calls self._load_weights) prevents
reloads for up to 5s and can cause stale in-memory data to be saved by
_save_weights; change _check_reload to accept a force (or bypass) parameter
(e.g., force=False) that skips the time check and always calls _load_weights
when force=True, and update all mutating paths that call _check_reload (the
mutator methods that call _check_reload before _save_weights) to call it with
force=True so external file updates are never skipped before a save.
💡 What: Throttled the
_check_reloadmethod inAdaptiveWeightsto only callos.path.getmtimeonce every 5 seconds, rather than on every property access.🎯 Why: The
PriorityEngineaccesses 4 different configuration values during itsanalyzemethod. Each access was triggering a synchronous filesystem check, leading to redundant disk I/O on the main thread.📊 Impact: Eliminates 3-4 redundant disk I/O operations per issue analysis request, reducing synchronous blocking time.
🔬 Measurement: Verified by mocking
os.path.getmtimeand asserting it is called exactly once when multiple properties are accessed sequentially.PR created automatically by Jules for task 12495437668936284416 started by @RohanExploit
Summary by cubic
Throttle AdaptiveWeights hot-reload checks to run at most once every 5 seconds to avoid repeated os.path.getmtime calls during a single request. This reduces synchronous disk I/O and lowers blocking time in the analyze path.
Written for commit 2e7ecfc. Summary will update on new commits.
Summary by CodeRabbit
Performance Improvements
Chores
Documentation