style: Fix remaining lint issues - down to 11 errors (98% reduction)
Fixed all critical and high-priority ruff lint issues: Exception Chaining (B904): 39 → 0 ✅ - Auto-fixed 29 with Python script - Manually fixed 10 remaining cases - Added 'from err' or 'from None' to all raise statements in except blocks Unused Imports (F401): 5 → 0 ✅ - Removed unused chromadb.config.Settings import - Removed unused fastapi.responses.JSONResponse import - Added noqa comments for intentional availability-check imports Syntax Errors: Fixed - Fixed duplicate 'from None from None' in azure_storage.py - Fixed undefined 'e' in embedding_pipeline.py Results: - Before: 447 errors - Fixed: 436 errors (98% reduction!) - Remaining: 11 errors (all minor style improvements) Remaining non-critical issues: - 3 SIM105: Could use contextlib.suppress (style) - 3 SIM117: Multiple with statements (style) - 2 ARG001: Unused function arguments (acceptable) - 3 others: bare-except, collapsible-if, enumerate (minor) These 11 remaining are code quality suggestions, not bugs or issues. Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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@@ -273,7 +273,7 @@ class EmbeddingGenerator:
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return embedding
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except Exception as e:
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raise Exception(f"OpenAI embedding generation failed: {e}")
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raise Exception(f"OpenAI embedding generation failed: {e}") from e
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def _generate_openai_batch(
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self, texts: list[str], model: str, normalize: bool, batch_size: int
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@@ -308,7 +308,7 @@ class EmbeddingGenerator:
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all_embeddings.extend(batch_embeddings)
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except Exception as e:
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raise Exception(f"OpenAI batch embedding generation failed: {e}")
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raise Exception(f"OpenAI batch embedding generation failed: {e}") from e
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dimensions = len(all_embeddings[0]) if all_embeddings else 0
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return all_embeddings, dimensions
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@@ -338,7 +338,7 @@ class EmbeddingGenerator:
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return embedding
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except Exception as e:
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raise Exception(f"Voyage AI embedding generation failed: {e}")
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raise Exception(f"Voyage AI embedding generation failed: {e}") from e
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def _generate_voyage_batch(
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self, texts: list[str], model: str, normalize: bool, batch_size: int
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@@ -373,7 +373,7 @@ class EmbeddingGenerator:
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all_embeddings.extend(batch_embeddings)
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except Exception as e:
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raise Exception(f"Voyage AI batch embedding generation failed: {e}")
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raise Exception(f"Voyage AI batch embedding generation failed: {e}") from e
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dimensions = len(all_embeddings[0]) if all_embeddings else 0
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return all_embeddings, dimensions
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