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Introduces connection pooling for QdrantClient and uses orjson for faster JSON serialization when available. Adds a shared ThreadPoolExecutor for parallel queries and implements a cache for filter sanitization to improve performance.
Adds 'orjson' to requirements. Improves hybrid_search.py with cached regex compilation, filter object caching, and parallel dense query execution. In ingest_code.py, increases default batch size for indexing. In rerank_local.py, adds background warmup for ONNX reranker session to reduce initial latency.
Introduces list_workspaces to enumerate workspaces and their states by scanning for state.json files, supporting both single and multi-repo modes. Adds _invalidate_router_scratchpad stub to allow router cache invalidation after indexing. Fixes progress reporting in ingest_code.py and minor logging improvements in mcp_indexer_server.py.
voarsh2
reviewed
Dec 9, 2025
| batch_ids: list[int] = [] | ||
| batch_lex: list[list[float]] = [] | ||
| BATCH_SIZE = int(os.environ.get("INDEX_BATCH_SIZE", "64") or 64) | ||
| BATCH_SIZE = int(os.environ.get("INDEX_BATCH_SIZE", "256") or 256) |
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This was a performance optimization - larger batches = fewer Qdrant upsert roundtrips = faster indexing. Trade-off is higher memory per batch... we can leave at default though
voarsh2
reviewed
Dec 9, 2025
scripts/workspace_state.py
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| def list_workspaces(search_root: Optional[str] = None) -> List[Dict[str, Any]]: |
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@m1rl0k Probably won't be working with client -> remote stack semantics
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