fix: Fix chunk naive llm classifier #173
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Fixed chunk naive llm classifier uuid issue, added fix for deletion of data points for LanceDB Fix #COG-472
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Actionable comments posted: 2
🧹 Outside diff range and nitpick comments (1)
cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py (1)
167-170: Consider performance optimization for large delete operations.For large-scale deletions, consider implementing batch processing to avoid potential memory issues or timeout problems.
Consider these improvements:
- Add a batch size parameter with a reasonable default (e.g., 1000)
- Process deletions in chunks when dealing with a large number of IDs
- Add logging for tracking deletion progress
Would you like me to provide an implementation example with batch processing?
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📒 Files selected for processing (2)
cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py(1 hunks)cognee/tasks/chunk_naive_llm_classifier/chunk_naive_llm_classifier.py(1 hunks)
🔇 Additional comments (2)
cognee/tasks/chunk_naive_llm_classifier/chunk_naive_llm_classifier.py (1)
41-41: LGTM! The UUID conversion fix looks correct.
The change properly converts UUID objects to strings before passing them to vector_engine.retrieve, which should resolve the UUID type compatibility issue with LanceDB.
Let's verify if similar UUID-to-string conversions are needed elsewhere in the codebase:
✅ Verification successful
Let me gather more information about the UUID handling in vector engine interfaces and implementations.
UUID handling is consistent across vector engine implementations
After analyzing the codebase, I can confirm that:
- The vector engine interface and all implementations (LanceDB, Weaviate, QDrant, PGVector) consistently expect string IDs in their
retrievemethod signatures. - The UUID-to-string conversion in the review is part of a broader pattern where UUIDs are consistently converted to strings before vector storage operations.
- The fix aligns with existing UUID handling patterns in the codebase, where UUIDs are converted to strings when used as identifiers in both vector and graph operations.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for direct UUID usage with vector engine operations
rg -l "uuid" | xargs rg "vector.*retrieve|retrieve.*vector" -B 5 -A 5
# Look for UUID type hints in vector engine interfaces
ast-grep --pattern 'class $_(VectorEngine|DataPoint|$$$):
$$$
def retrieve($$$):
$$$'
Length of output: 3203
Script:
#!/bin/bash
# Check vector engine interface and implementations for UUID handling
ast-grep --pattern 'class VectorEngine:
$$$'
# Look for retrieve method signatures in vector engine implementations
ast-grep --pattern 'async def retrieve(
$$$
):
$$$'
# Search for UUID type hints or conversions in vector-related files
rg -l "vector" | xargs rg "UUID|uuid" -B 2 -A 2
Length of output: 23026
cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py (1)
167-170: Verify the impact on UUID handling.
Since this PR aims to fix a UUID problem, let's verify that the changes properly handle UUID strings in both single and multiple deletion cases.
Let's check the codebase for UUID handling patterns:
✅ Verification successful
Let me analyze the UUID handling patterns in the codebase to verify if the changes properly handle UUID strings in both single and multiple deletion cases.
From the search results, I can see:
- The codebase has a custom UUID type implementation in
cognee/infrastructure/databases/relational/data_types/UUID.pythat handles various UUID formats and conversions. - In the vector database models (
DataPointandScoredResult), IDs are stored as strings. - The LanceDBAdapter's schema shows
idfield usingdata_point_types["id"]type.
Let me check the specific data point type definitions and any UUID-to-string conversions in the LanceDB adapter:
Based on the analysis of the codebase, I can now provide a conclusive response about the UUID handling in the LanceDB deletion operations.
UUID handling is properly implemented in the deletion operations
The implementation is correct because:
- The
DataPointmodel usesid: strtype, confirming that IDs are stored as strings in the vector database - The LanceDB adapter inherits this string-based ID type through
data_point_types["id"] - The deletion queries using string formatting (
'id = '{data_point_ids[0]}'andid IN {tuple(data_point_ids)}) are appropriate for string-based IDs
The PR's changes maintain consistency with the existing string-based ID handling in both single and multiple deletion cases, making it compatible with UUID strings.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check UUID handling patterns in the codebase
# Look for UUID-related imports and type hints
echo "Checking UUID imports and type hints:"
rg -l "import uuid|from uuid|UUID"
# Look for UUID usage patterns
echo -e "\nChecking UUID usage patterns:"
rg "UUID\(|uuid\." -A 3
# Look for ID field type declarations
echo -e "\nChecking ID field type declarations:"
ast-grep --pattern 'id: $_'
Length of output: 9023
Script:
#!/bin/bash
# Check data point type definitions and UUID conversions in LanceDB adapter
echo "Checking LanceDB adapter implementation:"
rg -A 10 "data_point_types\s*=" cognee/infrastructure/databases/vector/lancedb/LanceDBAdapter.py
echo -e "\nChecking UUID to string conversions:"
rg "str\(.*UUID.*\)|UUID.*str" cognee/infrastructure/databases/vector/lancedb/
echo -e "\nChecking DataPoint model usage:"
rg -A 5 "class DataPoint" cognee/infrastructure/databases/vector/models/DataPoint.py
Length of output: 1119
| @@ -39,7 +38,7 @@ class Keyword(BaseModel): | |||
| if await vector_engine.has_collection(collection_name): | |||
| existing_data_points = await vector_engine.retrieve( | |||
| collection_name, | |||
| list(set(classification_data_points)), | |||
| [str(classification_data) for classification_data in list(set(classification_data_points))], | |||
There was a problem hiding this comment.
🛠️ Refactor suggestion
Consider centralizing UUID-to-string conversion logic.
To improve maintainability and ensure consistent UUID handling, consider extracting the conversion logic into a utility function:
def ensure_string_id(id_value: str | uuid.UUID) -> str:
"""Ensure ID is in string format for database operations."""
return str(id_value) if isinstance(id_value, uuid.UUID) else id_valueThis could be used throughout the code:
-[str(classification_data) for classification_data in list(set(classification_data_points))]
+[ensure_string_id(classification_data) for classification_data in list(set(classification_data_points))]| if len(data_point_ids) == 1: | ||
| results = await collection.delete(f"id = '{data_point_ids[0]}'") | ||
| else: | ||
| results = await collection.delete(f"id IN {tuple(data_point_ids)}") |
There was a problem hiding this comment.
Fix potential SQL injection vulnerability and add input validation.
The current implementation has several issues that need to be addressed:
- Using string interpolation for SQL queries is unsafe and could lead to SQL injection. While LanceDB might have internal protections, it's better to use parameterized queries when available.
- There's no validation for empty
data_point_idslist. - The tuple conversion for multiple IDs might fail if
data_point_idscontains only one item.
Consider applying these improvements:
async def delete_data_points(self, collection_name: str, data_point_ids: list[str]):
connection = await self.get_connection()
collection = await connection.open_table(collection_name)
+ if not data_point_ids:
+ return None
if len(data_point_ids) == 1:
- results = await collection.delete(f"id = '{data_point_ids[0]}'")
+ results = await collection.delete("id = ?", [data_point_ids[0]])
else:
- results = await collection.delete(f"id IN {tuple(data_point_ids)}")
+ placeholders = ','.join(['?' for _ in data_point_ids])
+ results = await collection.delete(f"id IN ({placeholders})", data_point_ids)
return resultsNote: If LanceDB doesn't support parameterized queries, please verify their documentation for the recommended way to safely handle user input in queries.
Committable suggestion was skipped due to low confidence.
Fixed chunk naive llm classifier uuid issue, added fix for deletion of data points for LanceDB
Fix #COG-472
Summary by CodeRabbit
New Features
Bug Fixes
Refactor