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added lint

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vasilije 2025-07-09 22:13:49 +02:00
parent 982f0831a4
commit 19c6aaa53d
1 changed files with 41 additions and 41 deletions
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82
cognee/infrastructure/databases/hybrid/falkordb/FalkorDBAdapter.py
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@ -341,47 +341,47 @@ class FalkorDBAdapter(VectorDBInterface, GraphDBInterface):
return collection_name in collections return collection_name in collections
async def create_data_points(self, data_points: list[DataPoint]): # async def create_data_points(self, data_points: list[DataPoint]):
""" # """
Add a list of data points to the graph database via batching. # Add a list of data points to the graph database via batching.
#
Can raise exceptions if there are issues during the database operations. # Can raise exceptions if there are issues during the database operations.
#
Parameters: # Parameters:
----------- # -----------
#
- data_points (list[DataPoint]): A list of DataPoint instances to be inserted into # - data_points (list[DataPoint]): A list of DataPoint instances to be inserted into
the database. # the database.
""" # """
embeddable_values = [] # embeddable_values = []
vector_map = {} # vector_map = {}
#
for data_point in data_points: # for data_point in data_points:
property_names = DataPoint.get_embeddable_property_names(data_point) # property_names = DataPoint.get_embeddable_property_names(data_point)
key = str(data_point.id) # key = str(data_point.id)
vector_map[key] = {} # vector_map[key] = {}
#
for property_name in property_names: # for property_name in property_names:
property_value = getattr(data_point, property_name, None) # property_value = getattr(data_point, property_name, None)
#
if property_value is not None: # if property_value is not None:
vector_map[key][property_name] = len(embeddable_values) # vector_map[key][property_name] = len(embeddable_values)
embeddable_values.append(property_value) # embeddable_values.append(property_value)
else: # else:
vector_map[key][property_name] = None # vector_map[key][property_name] = None
#
vectorized_values = await self.embed_data(embeddable_values) # vectorized_values = await self.embed_data(embeddable_values)
#
for data_point in data_points: # for data_point in data_points:
vectorized_data = [ # vectorized_data = [
vectorized_values[vector_map[str(data_point.id)][property_name]] # vectorized_values[vector_map[str(data_point.id)][property_name]]
if vector_map[str(data_point.id)][property_name] is not None # if vector_map[str(data_point.id)][property_name] is not None
else None # else None
for property_name in DataPoint.get_embeddable_property_names(data_point) # for property_name in DataPoint.get_embeddable_property_names(data_point)
] # ]
#
query, params = await self.create_data_point_query(data_point, vectorized_data) # query, params = await self.create_data_point_query(data_point, vectorized_data)
self.query(query, params) # self.query(query, params)
async def create_vector_index(self, index_name: str, index_property_name: str): async def create_vector_index(self, index_name: str, index_property_name: str):
""" """