Treat a zero or negative worker count as every core, not a deadlock

[feiiiiii5]

Summary

upload_points(..., parallel=0) and upload_collection(..., parallel=0) can hang because a pool with no workers never consumes its queue. Normalize a non-positive worker count to os.cpu_count() or 1, following the existing ModelEmbedder behavior, before starting the pool.

Why it happens

Both upload clients pass parallel directly to ParallelWorkerPool; only parallel == 1 takes the sequential path. A zero-worker pool has no process producing results for unordered_map().

What this changes

Apply the normalization in ParallelWorkerPool so the sync and async upload paths use the same rule. Positive worker counts retain their behavior.

The regression helper rejects a still-running drain thread after the timeout and checks all expected results. A bounded fake pool yields one result and then blocks, proving that partial output cannot make the timeout test pass. The helper releases and joins that fake worker during cleanup.

Validation

At ba4a26bc:

• tests/test_parallel_worker_pool.py: 6 passed, with no Qdrant server needed.
• The original normalization regressions failed before the product fix. For this review follow-up, disabling the timeout guard makes the new partial-output regression fail; restoring it passes all 6 tests.
• Pinned Ruff formatting passed on both PR files.
• The repository's mypy command passed for 62 source files; pyright passed for tests/type_stub.py with 0 errors.

These checks used Python 3.12 and versions from the lockfile. Integration tests requiring a live Qdrant server were not run.

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No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

• Configuration used: Organization UI
• Review profile: CHILL
• Plan: Advanced
• Run ID: aa1113c3-9f88-4adc-b4aa-78ff129b4254

📥 Commits

Reviewing files that changed from the base of the PR and between 85b3932 and ba4a26b.

📒 Files selected for processing (1)

• tests/test_parallel_worker_pool.py

🚧 Files skipped from review as they are similar to previous changes (1)

• tests/test_parallel_worker_pool.py

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📝 Walkthrough

Walkthrough

When num_workers is less than one, ParallelWorkerPool sets it to the available CPU count, or one if the CPU count is unavailable. Tests cover zero and negative worker counts, timeout handling, and result processing with zero, one, or two workers.

Priority: ➖ Normal

Estimated code review effort: 2 (Simple) | ~10 minutes

Change: Bug fix

Merge Risk: ⚪ Minimal · up to ba4a2

No actionable issue remains from the reviewed change; it is mergeable after normal checks.

Security Architecture Review

Security architecture risk: 🔵 Low · up to 85b39

The change preserves existing access and credential boundaries while fixing workerless uploads. However, automatic sizing can leave started workers and the caller blocked if process creation fails partway through. The demonstrated exposure is within the calling application; external reachability and deployment limits are unknown.

Retained concerns

• Medium · reliability · inferred: Automatic sizing makes partial worker startup reachable for non-positive upload concurrency. If a later process fails to start, cleanup joins already-started workers without sending stop signals or invoking emergency termination, potentially blocking the caller and retaining child-process resources. This weakness already existed for explicit positive counts; the PR extends its exposure rather than introducing the cleanup defect.

Security review details

Security Blast Radius

• inferred — A caller controlling parallel can now activate CPU-sized worker fan-out with a non-positive value. The demonstrated incremental exposure is local process, CPU and queue consumption per invocation. Positive values already allowed larger explicit counts; external caller reachability and aggregate concurrent exposure are not established.

Trust Boundaries and Controls

• inferred — The inspected change preserves existing upload identity and authority propagation: workers continue using configuration supplied by the same client. It does not establish a new credential source, tenant transition or authorization bypass.

Resilience and Maintainability Implications

• inferred — Early generator closure can also enter ordinary join without sending stop signals. This is a preexisting lifecycle weakness, not a separate PR regression. The inspected upload callers normally drain the generator, providing counterevidence against that path during successful uploads.

Hardening Proposals

• proposed — Make startup failure cleanup transactional: terminate and reap already-started workers and release owned queues before propagating a process-creation failure, rather than entering an unbounded normal join.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 46.15% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 13 functions across 2 files.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Title check	✅ Passed	The title clearly summarizes the main change: non-positive worker counts use all available CPU cores instead of causing a deadlock.
Description check	✅ Passed	The description explains the worker-pool deadlock, the normalization change, regression tests, and validation results.

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Actionable comments posted: 1

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• 🪄 Fix CodeRabbit comments on this PR

🤖 Prompt to fix review comments

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Inline comments:
Review comments at @tests/test_parallel_worker_pool.py:
- Around line 40-41: Update _drain in test_parallel_worker_pool.py to fail if
its thread remains alive after the timed join, and make
test_zero_workers_does_not_hang assert that all three expected results are
returned.

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ℹ️ Review info

⚙️ Run configuration

• Configuration used: Organization UI
• Review profile: CHILL
• Plan: Advanced
• Run ID: 8f84aba8-e2f1-442c-9b1f-46f01a502ef8

📥 Commits

Reviewing files that changed from the base of the PR and between cf747f4 and 85b3932.

📒 Files selected for processing (2)

• qdrant_client/parallel_processor.py
• tests/test_parallel_worker_pool.py

Included review availability: This review used your included allowance. Your plan provides up to 4 included reviews per hour; 2 remain after this review.