Added a few fixes and refactored the base app

level_3/vectordb/basevectordb.py

@@ -40,34 +40,28 @@ import json
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY", "")
 marvin.settings.openai.api_key = os.environ.get("OPENAI_API_KEY")
 
-LTM_MEMORY_ID_DEFAULT = "00000"
-ST_MEMORY_ID_DEFAULT = "0000"
-BUFFER_ID_DEFAULT = "0000"
-
-
 class VectorDBFactory:
+    def __init__(self):
+        self.db_map = {
+            "pinecone": PineconeVectorDB,
+            "weaviate": WeaviateVectorDB,
+            # Add more database types and their corresponding classes here
+        }
+
     def create_vector_db(
         self,
         user_id: str,
         index_name: str,
         memory_id: str,
-        ltm_memory_id: str = LTM_MEMORY_ID_DEFAULT,
-        st_memory_id: str = ST_MEMORY_ID_DEFAULT,
-        buffer_id: str = BUFFER_ID_DEFAULT,
-        db_type: str = "pinecone",
+        db_type: str = "weaviate",
         namespace: str = None,
-        embeddings = None,
+        embeddings=None,
     ):
-        db_map = {"pinecone": PineconeVectorDB, "weaviate": WeaviateVectorDB}
-
-        if db_type in db_map:
-            return db_map[db_type](
+        if db_type in self.db_map:
+            return self.db_map[db_type](
                 user_id,
                 index_name,
                 memory_id,
-                ltm_memory_id,
-                st_memory_id,
-                buffer_id,
                 namespace,
                 embeddings
             )
@@ -101,8 +95,61 @@ class BaseMemory:
         )
 
     def init_client(self, embeddings, namespace: str):
+        return self.vector_db.init_client(embeddings, namespace)
 
-        return self.vector_db.init_weaviate_client(embeddings, namespace)
+
+# class VectorDBFactory:
+#     def create_vector_db(
+#         self,
+#         user_id: str,
+#         index_name: str,
+#         memory_id: str,
+#         db_type: str = "pinecone",
+#         namespace: str = None,
+#         embeddings = None,
+#     ):
+#         db_map = {"pinecone": PineconeVectorDB, "weaviate": WeaviateVectorDB}
+#
+#         if db_type in db_map:
+#             return db_map[db_type](
+#                 user_id,
+#                 index_name,
+#                 memory_id,
+#                 namespace,
+#                 embeddings
+#             )
+#
+#         raise ValueError(f"Unsupported database type: {db_type}")
+#
+# class BaseMemory:
+#     def __init__(
+#         self,
+#         user_id: str,
+#         memory_id: Optional[str],
+#         index_name: Optional[str],
+#         db_type: str,
+#         namespace: str,
+#         embeddings: Optional[None],
+#     ):
+#         self.user_id = user_id
+#         self.memory_id = memory_id
+#         self.index_name = index_name
+#         self.namespace = namespace
+#         self.embeddings = embeddings
+#         self.db_type = db_type
+#         factory = VectorDBFactory()
+#         self.vector_db = factory.create_vector_db(
+#             self.user_id,
+#             self.index_name,
+#             self.memory_id,
+#             db_type=self.db_type,
+#             namespace=self.namespace,
+#             embeddings=self.embeddings
+#         )
+#
+#     def init_client(self, embeddings, namespace: str):
+#
+#         return self.vector_db.init_weaviate_client(embeddings, namespace)
 
     def create_field(self, field_type, **kwargs):
         field_mapping = {

level_3/vectordb/vectordb.py

@@ -32,9 +32,6 @@ class VectorDB:
         user_id: str,
         index_name: str,
         memory_id: str,
-        ltm_memory_id: str = LTM_MEMORY_ID_DEFAULT,
-        st_memory_id: str = ST_MEMORY_ID_DEFAULT,
-        buffer_id: str = BUFFER_ID_DEFAULT,
         namespace: str = None,
         embeddings = None,
     ):
@@ -42,9 +39,6 @@ class VectorDB:
         self.index_name = index_name
         self.namespace = namespace
         self.memory_id = memory_id
-        self.ltm_memory_id = ltm_memory_id
-        self.st_memory_id = st_memory_id
-        self.buffer_id = buffer_id
         self.embeddings = embeddings
 
 class PineconeVectorDB(VectorDB):
@@ -81,7 +75,7 @@ class WeaviateVectorDB(VectorDB):
             embedding=embeddings,
             create_schema_if_missing=True,
         )
-        return retriever  # If this is part of the initialization, call it here.
+        return retriever
 
     def init_weaviate_client(self, namespace: str):
         # Weaviate client initialization logic
@@ -295,9 +289,6 @@ class WeaviateVectorDB(VectorDB):
             data_object={
                 # "text": observation,
                 "user_id": str(self.user_id),
-                "memory_id": str(self.memory_id),
-                "ltm_memory_id": str(self.ltm_memory_id),
-                "st_memory_id": str(self.st_memory_id),
                 "buffer_id": str(self.buffer_id),
                 "version": params.get("version", None) or "",
                 "agreement_id": params.get("agreement_id", None) or "",