chore: add dynamic vector adapter integration

cognee/infrastructure/databases/hybrid/falkordb/FalkorDBAdapter.py

@@ -24,13 +24,13 @@ class IndexSchema(DataPoint):
 class FalkorDBAdapter(VectorDBInterface, GraphDBInterface):
     def __init__(
         self,
-        database_url: str,
+        url: str,
-        database_port: int,
+        port: int,
         embedding_engine=EmbeddingEngine,
     ):
         self.driver = FalkorDB(
-            host=database_url,
+            host=url,
-            port=database_port,
+            port=port,
         )
         self.embedding_engine = embedding_engine
         self.graph_name = "cognee_graph"

cognee/infrastructure/databases/vector/__init__.py

@@ -3,3 +3,4 @@ from .models.CollectionConfig import CollectionConfig
 from .vector_db_interface import VectorDBInterface
 from .config import get_vectordb_config
 from .get_vector_engine import get_vector_engine
+from .use_vector_adapter import use_vector_adapter

cognee/infrastructure/databases/vector/create_vector_engine copy.py

@@ -0,0 +1,108 @@
+from .embeddings import get_embedding_engine
+
+from functools import lru_cache
+
+
+@lru_cache
+def create_vector_engine(
+    vector_db_url: str,
+    vector_db_port: str,
+    vector_db_key: str,
+    vector_db_provider: str,
+):
+    embedding_engine = get_embedding_engine()
+
+    if vector_db_provider == "weaviate":
+        from .weaviate_db import WeaviateAdapter
+
+        if not (vector_db_url and vector_db_key):
+            raise EnvironmentError("Missing requred Weaviate credentials!")
+
+        return WeaviateAdapter(vector_db_url, vector_db_key, embedding_engine=embedding_engine)
+
+    elif vector_db_provider == "qdrant":
+        if not (vector_db_url and vector_db_key):
+            raise EnvironmentError("Missing requred Qdrant credentials!")
+
+        from .qdrant.QDrantAdapter import QDrantAdapter
+
+        return QDrantAdapter(
+            url=vector_db_url,
+            api_key=vector_db_key,
+            embedding_engine=embedding_engine,
+        )
+
+    elif vector_db_provider == "milvus":
+        from .milvus.MilvusAdapter import MilvusAdapter
+
+        if not vector_db_url:
+            raise EnvironmentError("Missing required Milvus credentials!")
+
+        return MilvusAdapter(
+            url=vector_db_url,
+            api_key=vector_db_key,
+            embedding_engine=embedding_engine,
+        )
+
+    elif vector_db_provider == "pgvector":
+        from cognee.infrastructure.databases.relational import get_relational_config
+
+        # Get configuration for postgres database
+        relational_config = get_relational_config()
+        db_username = relational_config.db_username
+        db_password = relational_config.db_password
+        db_host = relational_config.db_host
+        db_port = relational_config.db_port
+        db_name = relational_config.db_name
+
+        if not (db_host and db_port and db_name and db_username and db_password):
+            raise EnvironmentError("Missing requred pgvector credentials!")
+
+        connection_string: str = (
+            f"postgresql+asyncpg://{db_username}:{db_password}@{db_host}:{db_port}/{db_name}"
+        )
+
+        from .pgvector.PGVectorAdapter import PGVectorAdapter
+
+        return PGVectorAdapter(
+            connection_string,
+            vector_db_key,
+            embedding_engine,
+        )
+
+    elif vector_db_provider == "falkordb":
+        if not (vector_db_url and vector_db_port):
+            raise EnvironmentError("Missing requred FalkorDB credentials!")
+
+        from ..hybrid.falkordb.FalkorDBAdapter import FalkorDBAdapter
+
+        return FalkorDBAdapter(
+            url=vector_db_url,
+            port=vector_db_port,
+            embedding_engine=embedding_engine,
+        )
+
+    elif vector_db_provider == "chromadb":
+        try:
+            import chromadb
+        except ImportError:
+            raise ImportError(
+                "ChromaDB is not installed. Please install it with 'pip install chromadb'"
+            )
+
+        from .chromadb.ChromaDBAdapter import ChromaDBAdapter
+
+        return ChromaDBAdapter(
+            url=vector_db_url,
+            api_key=vector_db_key,
+            embedding_engine=embedding_engine,
+        )
+
+    else:
+        from .lancedb.LanceDBAdapter import LanceDBAdapter
+
+        return LanceDBAdapter(
+            url=vector_db_url,
+            api_key=vector_db_key,
+            embedding_engine=embedding_engine,
+        )

cognee/infrastructure/databases/vector/create_vector_engine.py

@@ -1,4 +1,5 @@
 from .embeddings import get_embedding_engine
+from .supported_adapters import supported_adapters
 
 from functools import lru_cache
 
@@ -12,97 +13,6 @@ def create_vector_engine(
 ):
     embedding_engine = get_embedding_engine()
 
-    if vector_db_provider == "weaviate":
+    vector_db_adapter = supported_adapters.get(vector_db_provider, None)
-        from .weaviate_db import WeaviateAdapter
 
-        if not (vector_db_url and vector_db_key):
+    return vector_db_adapter(url=vector_db_url, api_key=vector_db_key, embedding_engine=embedding_engine)
-            raise EnvironmentError("Missing requred Weaviate credentials!")
-
-        return WeaviateAdapter(vector_db_url, vector_db_key, embedding_engine=embedding_engine)
-
-    elif vector_db_provider == "qdrant":
-        if not (vector_db_url and vector_db_key):
-            raise EnvironmentError("Missing requred Qdrant credentials!")
-
-        from .qdrant.QDrantAdapter import QDrantAdapter
-
-        return QDrantAdapter(
-            url=vector_db_url,
-            api_key=vector_db_key,
-            embedding_engine=embedding_engine,
-        )
-
-    elif vector_db_provider == "milvus":
-        from .milvus.MilvusAdapter import MilvusAdapter
-
-        if not vector_db_url:
-            raise EnvironmentError("Missing required Milvus credentials!")
-
-        return MilvusAdapter(
-            url=vector_db_url,
-            api_key=vector_db_key,
-            embedding_engine=embedding_engine,
-        )
-
-    elif vector_db_provider == "pgvector":
-        from cognee.infrastructure.databases.relational import get_relational_config
-
-        # Get configuration for postgres database
-        relational_config = get_relational_config()
-        db_username = relational_config.db_username
-        db_password = relational_config.db_password
-        db_host = relational_config.db_host
-        db_port = relational_config.db_port
-        db_name = relational_config.db_name
-
-        if not (db_host and db_port and db_name and db_username and db_password):
-            raise EnvironmentError("Missing requred pgvector credentials!")
-
-        connection_string: str = (
-            f"postgresql+asyncpg://{db_username}:{db_password}@{db_host}:{db_port}/{db_name}"
-        )
-
-        from .pgvector.PGVectorAdapter import PGVectorAdapter
-
-        return PGVectorAdapter(
-            connection_string,
-            vector_db_key,
-            embedding_engine,
-        )
-
-    elif vector_db_provider == "falkordb":
-        if not (vector_db_url and vector_db_port):
-            raise EnvironmentError("Missing requred FalkorDB credentials!")
-
-        from ..hybrid.falkordb.FalkorDBAdapter import FalkorDBAdapter
-
-        return FalkorDBAdapter(
-            database_url=vector_db_url,
-            database_port=vector_db_port,
-            embedding_engine=embedding_engine,
-        )
-
-    elif vector_db_provider == "chromadb":
-        try:
-            import chromadb
-        except ImportError:
-            raise ImportError(
-                "ChromaDB is not installed. Please install it with 'pip install chromadb'"
-            )
-
-        from .chromadb.ChromaDBAdapter import ChromaDBAdapter
-
-        return ChromaDBAdapter(
-            url=vector_db_url,
-            api_key=vector_db_key,
-            embedding_engine=embedding_engine,
-        )
-
-    else:
-        from .lancedb.LanceDBAdapter import LanceDBAdapter
-
-        return LanceDBAdapter(
-            url=vector_db_url,
-            api_key=vector_db_key,
-            embedding_engine=embedding_engine,
-        )

cognee/infrastructure/databases/vector/exceptions/__init__.py

@@ -1 +1 @@
-from .exceptions import CollectionNotFoundError
+from .exceptions import *

cognee/infrastructure/databases/vector/exceptions/exceptions.py

@@ -12,3 +12,15 @@ class CollectionNotFoundError(CriticalError):
         log_level="DEBUG",
     ):
         super().__init__(message, name, status_code, log, log_level)
+
+
+class VectorEngineInitializationError(CriticalError):
+    def __init__(
+        self,
+        message,
+        name: str = "VectorEngineInitializationError",
+        status_code: int = status.HTTP_422_UNPROCESSABLE_ENTITY,
+        log=True,
+        log_level="ERROR",
+    ):
+        super().__init__(message, name, status_code, log, log_level)

cognee/infrastructure/databases/vector/supported_adapters.py

@@ -0,0 +1,6 @@
+from .lancedb.LanceDBAdapter import LanceDBAdapter
+
+
+supported_adapters = {
+    "lancedb": LanceDBAdapter,
+}

cognee/infrastructure/databases/vector/use_vector_adapter.py

@@ -0,0 +1,6 @@
+from .vector_db_interface import VectorDBInterface
+from .supported_adapters import supported_adapters
+
+
+def use_vector_adapter(vector_adapter_name: str, vector_adapter: VectorDBInterface):
+    supported_adapters[vector_adapter_name] = vector_adapter