⚡ Bolt: Optimize search core by caching and hoisting loop invariants

[ImChong]

💡 What:
In scripts/search_wiki_core.py, I pre-computed and cached properties like page_type_l, page_tags_l, status_boost, and path_l on the static doc instances during the initial for doc in docs: parsing pass. Additionally, I hoisted the dynamic evaluation of query_joined = " ".join(query_tokens).lower() out of the hot document processing loop.

🎯 Why:
Previously, the search() loop evaluated these properties recursively by extracting properties from dictionaries and applying intensive string operations (e.g. .lower(), .replace("\\", "/")) or floating-point status multipliers on every doc in docs for every search. Computing loop-invariant values inside a hot loop scales execution overhead exponentially as the document collection grows.

📊 Impact:
By caching the transformed strings and constants onto the doc object directly, the inner-most scoring and filtering helper functions (_filter_doc, _canonical_topic_boost, _sim2real_intent_boost, _query_has_comparison_intent) avoid redundant string allocations, .lower() conversions, and mathematical scalar recalcs completely. This significantly reduces GC thrashing and improves search processing latency per request.

🔬 Measurement:

• Run make test to ensure existing regression queries return exact matching items.
• Run make ci-preflight to ensure no search evaluations degrade.

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PR created automatically by Jules for task 16150203814616876593 started by @ImChong

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