Performance Enhancement Solutions for Real-Time Code Analysis
typical problem: Traditional splitter latency is noticeable when IDE plug-ins or code review tools require millisecond responses.
Key technologies::
- preloaded word list: By
encoder.preload_vocab()Memory-resident BPE word lists to reduce first-run latency - Local update mechanism: reclassify only the modified code blocks, combining the
get_changed_ranges()Enabling incremental processing - language cache: Create a separate cache pool for Python/JS and other languages, with a hit rate of up to 90%+.
carry out in practice::
- Preloaded at initialization:
encoder = encoding_for_model("codex"); encoder.preload() - Handles editor events:
on_change事件中调用encoder.encode(diff_text, is_delta=True) - Monitor performance: by
perf_counter()Record critical path elapsed time, target <10ms/thousand lines
This answer comes from the articleTokenDagger: High Performance Text Segmentation ToolThe
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