fix: Move weaviate imports where needed

cognee/api/v1/search/search.py

@@ -8,8 +8,8 @@ from cognee.modules.search.vector.search_similarity import search_similarity
 from cognee.modules.search.graph.search_categories import search_categories
 from cognee.modules.search.graph.search_neighbour import search_neighbour
 from cognee.modules.search.graph.search_summary import search_summary
-from cognee.shared.data_models import GraphDBType
 from cognee.infrastructure.databases.graph.get_graph_client import get_graph_client
+from cognee.infrastructure import infrastructure_config
 
 class SearchType(Enum):
     ADJACENT = 'ADJACENT'
@@ -42,8 +42,7 @@ async def search(search_type: str, params: Dict[str, Any]) -> List:
 
 
 async def specific_search(query_params: List[SearchParameters]) -> List:
-    graph_client = await get_graph_client(GraphDBType.NETWORKX)
-    await graph_client.load_graph_from_file()
+    graph_client = await get_graph_client(infrastructure_config.get_config()["graph_engine"])
     graph = graph_client.graph
 
     search_functions: Dict[SearchType, Callable] = {
@@ -61,8 +60,7 @@ async def specific_search(query_params: List[SearchParameters]) -> List:
         search_func = search_functions.get(search_param.search_type)
         if search_func:
             # Schedule the coroutine for execution and store the task
-            full_params = {**search_param.params, 'graph': graph}
-            task = search_func(**full_params)
+            task = search_func(**search_param.params, graph = graph)
             search_tasks.append(task)
 
     # Use asyncio.gather to run all scheduled tasks concurrently

cognee/config.py

@@ -73,6 +73,8 @@ class Config:
     connect_documents: bool = False
 
     # Database parameters
+    graph_database_provider: str = os.getenv("GRAPH_DB_PROVIDER", "NETWORKX")
+
     if (
         os.getenv("ENV") == "prod"
         or os.getenv("ENV") == "dev"

cognee/infrastructure/InfrastructureConfig.py

@@ -84,7 +84,7 @@ class InfrastructureConfig():
                     config.weaviate_api_key,
                     embedding_engine = self.embedding_engine
                 )
-            except EnvironmentError:
+            except (EnvironmentError, ModuleNotFoundError):
                 if config.qdrant_url is None and config.qdrant_api_key is None:
                     raise EnvironmentError("Qdrant is not configured!")
 

cognee/infrastructure/databases/graph/get_graph_client.py

@@ -5,7 +5,6 @@ from cognee.shared.data_models import GraphDBType
 from cognee.infrastructure import infrastructure_config
 from .graph_db_interface import GraphDBInterface
 from .networkx.adapter import NetworkXAdapter
-from .neo4j_driver.adapter import Neo4jAdapter
 
 config = Config()
 config.load()
@@ -15,15 +14,18 @@ async def get_graph_client(graph_type: GraphDBType, graph_file_name: str = None)
     """Factory function to get the appropriate graph client based on the graph type."""
     graph_file_path = f"{infrastructure_config.get_config('database_directory_path')}/{graph_file_name if graph_file_name else config.graph_filename}"
 
-    if graph_type == GraphDBType.NETWORKX:
-        graph_client = NetworkXAdapter(filename = graph_file_path)
-        await graph_client.load_graph_from_file()
-        return graph_client
-    elif graph_type == GraphDBType.NEO4J:
-        return Neo4jAdapter(
-            graph_database_url = config.graph_database_url,
-            graph_database_username = config.graph_database_username,
-            graph_database_password = config.graph_database_password
-        )
-    else:
-        raise ValueError("Unsupported graph database type.")
+    if graph_type == GraphDBType.NEO4J:
+        try:
+            from .neo4j_driver.adapter import Neo4jAdapter
+
+            return Neo4jAdapter(
+                graph_database_url = config.graph_database_url,
+                graph_database_username = config.graph_database_username,
+                graph_database_password = config.graph_database_password
+            )
+        except:
+            pass
+            
+    graph_client = NetworkXAdapter(filename = graph_file_path)
+    await graph_client.load_graph_from_file()
+    return graph_client

cognee/infrastructure/databases/vector/weaviate_db/WeaviateAdapter.py

@@ -2,10 +2,6 @@ import asyncio
 from uuid import UUID
 from typing import List, Optional
 from multiprocessing import Pool
-import weaviate
-import weaviate.classes as wvc
-import weaviate.classes.config as wvcc
-from weaviate.classes.data import DataObject
 from ..vector_db_interface import VectorDBInterface
 from ..models.DataPoint import DataPoint
 from ..models.ScoredResult import ScoredResult
@@ -17,6 +13,9 @@ class WeaviateAdapter(VectorDBInterface):
     embedding_engine: EmbeddingEngine = None
 
     def __init__(self, url: str, api_key: str, embedding_engine: EmbeddingEngine):
+        import weaviate
+        import weaviate.classes as wvc
+      
         self.embedding_engine = embedding_engine
 
         self.client = weaviate.connect_to_wcs(
@@ -32,6 +31,8 @@ class WeaviateAdapter(VectorDBInterface):
         return await self.embedding_engine.embed_text(data)
 
     async def create_collection(self, collection_name: str):
+        import weaviate.classes.config as wvcc
+
         event_loop = asyncio.get_event_loop()
 
         def sync_create_collection():
@@ -57,6 +58,8 @@ class WeaviateAdapter(VectorDBInterface):
         return self.client.collections.get(collection_name)
 
     async def create_data_points(self, collection_name: str, data_points: List[DataPoint]):
+        from weaviate.classes.data import DataObject
+
         data_vectors = await self.embed_data(
             list(map(lambda data_point: data_point.get_embeddable_data(), data_points)))
 
@@ -95,6 +98,8 @@ class WeaviateAdapter(VectorDBInterface):
             limit: int = None,
             with_vector: bool = False
     ):
+        import weaviate.classes as wvc
+
         if query_text is None and query_vector is None:
             raise ValueError("One of query_text or query_vector must be provided!")
 

cognee/modules/search/graph/search_adjacent.py

@@ -3,9 +3,8 @@
 
 from typing import Union, Dict
 import networkx as nx
-from neo4j import AsyncSession
 from cognee.shared.data_models import GraphDBType
-async def search_adjacent(graph: Union[nx.Graph, AsyncSession], query: str, infrastructure_config: Dict, other_param: dict = None) -> Dict[str, str]:
+async def search_adjacent(graph: Union[nx.Graph, any], query: str, infrastructure_config: Dict, other_param: dict = None) -> Dict[str, str]:
     """
     Find the neighbours of a given node in the graph and return their descriptions.
     Supports both NetworkX graphs and Neo4j graph databases based on the configuration.

cognee/modules/search/graph/search_categories.py

@@ -2,11 +2,10 @@ from typing import Union, Dict
 
 """ Search categories in the graph and return their summary attributes. """
 
-from neo4j import AsyncSession
 from cognee.shared.data_models import GraphDBType
 import networkx as nx
 
-async def search_categories(graph: Union[nx.Graph, AsyncSession], query_label: str, infrastructure_config: Dict):
+async def search_categories(graph: Union[nx.Graph, any], query_label: str, infrastructure_config: Dict):
     """
     Filter nodes in the graph that contain the specified label and return their summary attributes.
     This function supports both NetworkX graphs and Neo4j graph databases.

cognee/modules/search/graph/search_neighbour.py

@@ -1,13 +1,11 @@
 """ Fetches the context of a given node in the graph"""
 from typing import Union, Dict
 
-from neo4j import AsyncSession
-
 from cognee.infrastructure.databases.graph.get_graph_client import get_graph_client
 import networkx as nx
 from cognee.shared.data_models import GraphDBType
 
-async def search_neighbour(graph: Union[nx.Graph, AsyncSession], id: str, infrastructure_config: Dict,
+async def search_neighbour(graph: Union[nx.Graph, any], id: str, infrastructure_config: Dict,
                            other_param: dict = None):
     """
     Search for nodes that share the same 'layer_uuid' as the specified node and return their descriptions.

cognee/modules/search/graph/search_summary.py

@@ -3,10 +3,9 @@
 
 from typing import Union, Dict
 import networkx as nx
-from neo4j import AsyncSession
 from cognee.shared.data_models import GraphDBType
 
-async def search_summary(graph: Union[nx.Graph, AsyncSession], query: str, infrastructure_config: Dict, other_param: str = None) -> Dict[str, str]:
+async def search_summary(graph: Union[nx.Graph, any], query: str, infrastructure_config: Dict, other_param: str = None) -> Dict[str, str]:
     """
     Filter nodes based on a condition (such as containing 'SUMMARY' in their identifiers) and return their summary attributes.
     Supports both NetworkX graphs and Neo4j graph databases based on the configuration.

cognee/modules/search/vector/search_similarity.py

@@ -3,7 +3,7 @@ from cognee.infrastructure import infrastructure_config
 from cognee.infrastructure.databases.graph.get_graph_client import get_graph_client
 
 
-async def search_similarity(query: str):
+async def search_similarity(query: str, graph):
     graph_db_type = infrastructure_config.get_config()["graph_engine"]
 
     graph_client = await get_graph_client(graph_db_type)
@@ -35,7 +35,7 @@ async def search_similarity(query: str):
 
     for graph_node_data in graph_nodes:
         graph_node = await graph_client.extract_node(graph_node_data["node_id"])
-        
+
         if "chunk_collection" not in graph_node and "chunk_id" not in graph_node:
             continue