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fix(filesystem): reject mismatched existing projection indexes

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BukeLy 2026-05-31 21:10:23 +08:00
parent decfe29fe4
commit e293814bc0
2 changed files with 95 additions and 39 deletions
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34
pageindex/filesystem/core.py
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@ -249,33 +249,29 @@ class PageIndexFileSystem:
"""Attach semantic retrieval to already-built projection indexes.
Register-time generation owns building the index files. Opening an
existing workspace should still expose semantic browse, without forcing
a re-register step.
existing workspace should still expose semantic retrieval when the
configured embedding dimensions match the existing index.
"""
if self.semantic_retrieval_backend is not None:
return bool(self.semantic_retrieval_channels())
index_config = self._existing_projection_index_config()
if index_config is None:
return False
metadata = dict(index_config.get("metadata") or {})
embedding_provider = str(
metadata.get("embedding_provider")
or self.summary_projection_embedding_provider
)
embedding_model = str(
metadata.get("embedding_model")
or self.summary_projection_embedding_model
)
embedding_dimensions = int(
metadata.get("embedding_dimensions")
or index_config.get("dimension")
or self.summary_projection_embedding_dimensions
)
existing_dimension = int(index_config.get("dimension") or 0)
if existing_dimension != self.summary_projection_embedding_dimensions:
raise RuntimeError(
"summary projection index dimension mismatch: "
f"{index_config.get('db_path') or self.summary_projection_index_dir} "
f"was built with dimension {existing_dimension}, but configured "
"summary_projection_embedding_dimensions is "
f"{self.summary_projection_embedding_dimensions}. Rebuild the "
"projection index or use a matching embedding configuration."
)
self.configure_hybrid_projection_retrieval(
self.summary_projection_index_dir,
embedding_provider=embedding_provider,
embedding_model=embedding_model,
embedding_dimensions=embedding_dimensions,
embedding_provider=self.summary_projection_embedding_provider,
embedding_model=self.summary_projection_embedding_model,
embedding_dimensions=self.summary_projection_embedding_dimensions,
embedding_timeout=self.summary_projection_embedding_timeout,
)
return bool(self.semantic_retrieval_channels())