Allow cold model startup and configure embedding timeouts

[chrisae9]

Local MCP searches could fall back to keyword results while a cold model exceeded the fixed two-second wait, or immediately when another request occupied the worker. Allow 30 seconds for startup and 10 seconds for warm queries, configurable through the embedding JSON. Waiting and inference share one bounded per-call budget; outstanding work remains single-flight and reusable.

Remote embedding queries now default to 10 seconds, background requests to 30 seconds, and client reads to 30 seconds. Remote budgets are independent. Existing TimeoutError fallback metadata is preserved, with safe local reason codes distinguishing startup, query, contention, and stalled-worker limits.

Adds regression coverage for cold/warm budgets, pending-result reuse and failure isolation, bounded admission, and configuration validation. Native qualification now checks both normal cold startup and forced timeout recovery with OS networking denied. Usage documentation explains the settings and their limits. No schema or embedding-identity changes.

Validation: targeted tests, Ruff, actionlint, and diff checks passed. Full CI passed on Linux and macOS with Python 3.11 and 3.14, including offline and recovery checks. Native qualification passed cold startup and forced timeout recovery with OS networking denied. An independent subagent reviewed the implementation; both findings were fixed and regression-tested.

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Reviewing files that changed from the base of the PR and between a34e43e and 3b18d90.

📒 Files selected for processing (10)

• .github/workflows/qualification.yml
• docs/usage.md
• src/session_search/core/embeddings.py
• src/session_search/core/local_worker.py
• src/session_search/interfaces/cli.py
• src/session_search/interfaces/client.py
• src/session_search/storage/semantic.py
• tests/check_local_mcp.py
• tests/test_local_worker.py
• tests/test_semantic.py

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