refactor: Change raw SQL queries to SQLalchemy ORM for PGVectorAdapter

Changed raw SQL quries to use SQLalchemy ORM for PGVectorAdapter

Refactor #COG-170

cognee/infrastructure/databases/vector/pgvector/PGVectorAdapter.py

@@ -1,13 +1,13 @@
-from typing import List, Optional, get_type_hints, Any, Dict
-from sqlalchemy import text, select
-from sqlalchemy import JSON, Column, Table
+from typing import List, Optional, get_type_hints
+from sqlalchemy import JSON, Column, Table, select, delete
+
 from ..models.ScoredResult import ScoredResult
 import asyncio
 
 from ..vector_db_interface import VectorDBInterface, DataPoint
 from sqlalchemy.orm import Mapped, mapped_column
 from ..embeddings.EmbeddingEngine import EmbeddingEngine
-from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine, async_sessionmaker
+from sqlalchemy.ext.asyncio import create_async_engine, async_sessionmaker
 from pgvector.sqlalchemy import Vector
 
 from ...relational.sqlalchemy.SqlAlchemyAdapter import SQLAlchemyAdapter
@@ -49,17 +49,13 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
 
     async def has_collection(self, collection_name: str) -> bool:
         async with self.engine.begin() as connection:
-            # TODO: Switch to using ORM instead of raw query
-            result = await connection.execute(
-                text(
-                    "SELECT table_name FROM information_schema.tables WHERE table_schema = 'public';"
-                )
-            )
-            tables = result.fetchall()
-            for table in tables:
-                if collection_name == table[0]:
-                    return True
-            return False
+            # Load the schema information into the MetaData object
+            await connection.run_sync(Base.metadata.reflect)
+
+            if collection_name in Base.metadata.tables:
+                return True
+            else:
+                return False
 
     async def create_collection(self, collection_name: str, payload_schema=None):
         data_point_types = get_type_hints(DataPoint)
@@ -133,30 +129,32 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
             session.add_all(pgvector_data_points)
             await session.commit()
 
+    async def get_table(self, collection_name: str) -> Table:
+        """
+        Dynamically loads a table using the given collection name
+        with an async engine.
+        """
+        async with self.engine.begin() as connection:
+            await connection.run_sync(Base.metadata.reflect)  # Reflect the metadata
+            if collection_name in Base.metadata.tables:
+                return Base.metadata.tables[collection_name]
+            else:
+                raise ValueError(f"Table '{collection_name}' not found.")
+
     async def retrieve(self, collection_name: str, data_point_ids: List[str]):
-        async with AsyncSession(self.engine) as session:
-            try:
-                # Construct the SQL query
-                # TODO: Switch to using ORM instead of raw query
-                if len(data_point_ids) == 1:
-                    query = text(f"SELECT * FROM {collection_name} WHERE id = :id")
-                    result = await session.execute(query, {"id": data_point_ids[0]})
-                else:
-                    query = text(
-                        f"SELECT * FROM {collection_name} WHERE id = ANY(:ids)"
-                    )
-                    result = await session.execute(query, {"ids": data_point_ids})
+        async with self.get_async_session() as session:
+            # Get PGVectorDataPoint Table from database
+            PGVectorDataPoint = await self.get_table(collection_name)
 
-                # Fetch all rows
-                rows = result.fetchall()
+            results = await session.execute(
+                select(PGVectorDataPoint).where(PGVectorDataPoint.c.id.in_(data_point_ids))
+            )
+            results = results.all()
 
-                return [
-                    ScoredResult(id=row["id"], payload=row["payload"], score=0)
-                    for row in rows
-                ]
-            except Exception as e:
-                print(f"Error retrieving data: {e}")
-                return []
+            return [
+                ScoredResult(id=result.id, payload=result.payload, score=0)
+                for result in results
+            ]
 
     async def search(
         self,
@@ -175,10 +173,10 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
         # Use async session to connect to the database
         async with self.get_async_session() as session:
             try:
-                PGVectorDataPoint = Table(
-                    collection_name, Base.metadata, autoload_with=self.engine
-                )
+                # Get PGVectorDataPoint Table from database
+                PGVectorDataPoint = await self.get_table(collection_name)
 
+                # Find closest vectors to query_vector
                 closest_items = await session.execute(
                     select(
                         PGVectorDataPoint,
@@ -230,7 +228,14 @@ class PGVectorAdapter(SQLAlchemyAdapter, VectorDBInterface):
         )
 
     async def delete_data_points(self, collection_name: str, data_point_ids: list[str]):
-        pass
+        async with self.get_async_session() as session:
+            # Get PGVectorDataPoint Table from database
+            PGVectorDataPoint = await self.get_table(collection_name)
+            results = await session.execute(
+                delete(PGVectorDataPoint).where(PGVectorDataPoint.c.id.in_(data_point_ids))
+            )
+            await session.commit()
+            return results
 
     async def prune(self):
         # Clean up the database if it was set up as temporary