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fix: CodexLens model detection, hybrid search stability, and JSON logging

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- Fix model installation detection using fastembed ONNX cache names
- Add embeddings_config table for model metadata tracking
- Fix hybrid search segfault by using single-threaded GPU mode
- Suppress INFO logs in JSON mode to prevent error display
- Add model dropdown filtering to show only installed models

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
catlog22
2025-12-22 21:49:10 +08:00
parent cf58dc0dd3
commit 8203d690cb
11 changed files with 302 additions and 57 deletions
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37
codex-lens/src/codexlens/search/hybrid_search.py
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@@ -274,19 +274,32 @@ class HybridSearchEngine:
)
return []
# Auto-detect embedding dimension and select appropriate profile
detected_dim = vector_store.dimension
if detected_dim is None:
self.logger.info("Vector store dimension unknown, using default profile")
profile = "code" # Default fallback
elif detected_dim == 384:
profile = "fast"
elif detected_dim == 768:
profile = "code"
elif detected_dim == 1024:
profile = "multilingual" # or balanced, both are 1024
# Get stored model configuration (preferred) or auto-detect from dimension
model_config = vector_store.get_model_config()
if model_config:
profile = model_config["model_profile"]
self.logger.debug(
"Using stored model config: %s (%s, %dd)",
profile, model_config["model_name"], model_config["embedding_dim"]
)
else:
profile = "code" # Default fallback
# Fallback: auto-detect from embedding dimension
detected_dim = vector_store.dimension
if detected_dim is None:
self.logger.info("Vector store dimension unknown, using default profile")
profile = "code" # Default fallback
elif detected_dim == 384:
profile = "fast"
elif detected_dim == 768:
profile = "code"
elif detected_dim == 1024:
profile = "multilingual" # or balanced, both are 1024
else:
profile = "code" # Default fallback
self.logger.debug(
"No stored model config, auto-detected profile '%s' from dimension %s",
profile, detected_dim
)
# Use cached embedder (singleton) for performance
embedder = get_embedder(profile=profile)