diff --git a/examples/apps/documents_chat.py b/examples/apps/documents_chat.py
index 3b1b2a43..8f7f24a4 100644
--- a/examples/apps/documents_chat.py
+++ b/examples/apps/documents_chat.py
@@ -125,7 +125,7 @@ async def _handle_message(
         if not self._documents_ingested:
             yield self.NO_DOCUMENTS_INGESTED_MESSAGE
         results = await self.document_search.search(message[-1])
-        prompt = RAGPrompt(QueryWithContext(query=message, context=[i.get_text_representation() for i in results]))
+        prompt = RAGPrompt(QueryWithContext(query=message, context=[i.text_representation for i in results]))
         response = await self._llm.generate(prompt)
         yield response.answer
 
diff --git a/examples/document-search/chroma.py b/examples/document-search/chroma.py
index 5524fcd3..bdf27dc5 100644
--- a/examples/document-search/chroma.py
+++ b/examples/document-search/chroma.py
@@ -100,7 +100,7 @@ async def main() -> None:
 
     print()
     print(f"Documents similar to: {query}")
-    print([element.get_text_representation() for element in results])
+    print([element.text_representation for element in results])
 
 
 if __name__ == "__main__":
diff --git a/examples/document-search/chroma_otel.py b/examples/document-search/chroma_otel.py
index 64b5e198..7efd5195 100644
--- a/examples/document-search/chroma_otel.py
+++ b/examples/document-search/chroma_otel.py
@@ -130,7 +130,7 @@ async def main() -> None:
 
     print()
     print(f"Documents similar to: {query}")
-    print([element.get_text_representation() for element in results])
+    print([element.text_representation for element in results])
 
 
 if __name__ == "__main__":
diff --git a/examples/document-search/multimodal.py b/examples/document-search/multimodal.py
index 88dfb571..0e932bd5 100644
--- a/examples/document-search/multimodal.py
+++ b/examples/document-search/multimodal.py
@@ -91,7 +91,7 @@ async def main() -> None:
     print("Results for 'Fluffy teady bear toy':")
     for result in results:
         document = await result.document_meta.fetch()
-        print(f"Type: {result.element_type}, Location: {document.local_path}, Text: {result.get_text_representation()}")
+        print(f"Type: {result.element_type}, Location: {document.local_path}, Text: {result.text_representation}")
 
 
 if __name__ == "__main__":
diff --git a/examples/document-search/qdrant.py b/examples/document-search/qdrant.py
index bc1bfbf7..b1ea998e 100644
--- a/examples/document-search/qdrant.py
+++ b/examples/document-search/qdrant.py
@@ -100,7 +100,7 @@ async def main() -> None:
 
     print()
     print(f"Documents similar to: {query}")
-    print([element.get_text_representation() for element in results])
+    print([element.text_representation for element in results])
 
 
 if __name__ == "__main__":
diff --git a/packages/ragbits-core/src/ragbits/core/vector_stores/__init__.py b/packages/ragbits-core/src/ragbits/core/vector_stores/__init__.py
index 565125e3..7fb02751 100644
--- a/packages/ragbits-core/src/ragbits/core/vector_stores/__init__.py
+++ b/packages/ragbits-core/src/ragbits/core/vector_stores/__init__.py
@@ -1,34 +1,27 @@
 import sys
 
-from ..metadata_stores import get_metadata_store
-from ..utils.config_handling import get_cls_from_config
-from .base import VectorStore, VectorStoreEntry, VectorStoreOptions, WhereQuery
-from .in_memory import InMemoryVectorStore
+from ragbits.core.utils.config_handling import get_cls_from_config
+from ragbits.core.vector_stores.base import VectorStore, VectorStoreEntry, VectorStoreOptions, WhereQuery
+from ragbits.core.vector_stores.in_memory import InMemoryVectorStore
 
-__all__ = ["InMemoryVectorStore", "VectorStore", "VectorStoreEntry", "WhereQuery"]
+__all__ = ["InMemoryVectorStore", "VectorStore", "VectorStoreEntry", "VectorStoreOptions", "WhereQuery"]
 
-module = sys.modules[__name__]
 
-
-def get_vector_store(vector_store_config: dict) -> VectorStore:
+def get_vector_store(config: dict) -> VectorStore:
     """
     Initializes and returns a VectorStore object based on the provided configuration.
 
     Args:
-        vector_store_config: A dictionary containing configuration details for the VectorStore.
+        config: A dictionary containing configuration details for the VectorStore.
 
     Returns:
         An instance of the specified VectorStore class, initialized with the provided config
         (if any) or default arguments.
-    """
-    vector_store_cls = get_cls_from_config(vector_store_config["type"], module)
-    config = vector_store_config.get("config", {})
 
-    if vector_store_config["type"].endswith(("ChromaVectorStore", "QdrantVectorStore")):
-        return vector_store_cls.from_config(config)
-
-    metadata_store_config = vector_store_config.get("metadata_store_config")
-    return vector_store_cls(
-        default_options=VectorStoreOptions(**config.get("default_options", {})),
-        metadata_store=get_metadata_store(metadata_store_config),
-    )
+    Raises:
+        KeyError: If the provided configuration does not contain a valid "type" key.
+        InvalidConfigurationError: If the provided configuration is invalid.
+        NotImplementedError: If the specified VectorStore class cannot be created from the provided configuration.
+    """
+    vector_store_cls = get_cls_from_config(config["type"], sys.modules[__name__])
+    return vector_store_cls.from_config(config.get("config", {}))
diff --git a/packages/ragbits-core/src/ragbits/core/vector_stores/base.py b/packages/ragbits-core/src/ragbits/core/vector_stores/base.py
index 234ca441..9ba342e4 100644
--- a/packages/ragbits-core/src/ragbits/core/vector_stores/base.py
+++ b/packages/ragbits-core/src/ragbits/core/vector_stores/base.py
@@ -13,8 +13,8 @@ class VectorStoreEntry(BaseModel):
     """
 
     id: str
+    key: str
     vector: list[float]
-    content: str
     metadata: dict
 
 
@@ -48,6 +48,22 @@ def __init__(
         self._default_options = default_options or VectorStoreOptions()
         self._metadata_store = metadata_store
 
+    @classmethod
+    def from_config(cls, config: dict) -> "VectorStore":
+        """
+        Creates and returns an instance of the Reranker class from the given configuration.
+
+        Args:
+            config: A dictionary containing the configuration for initializing the Reranker instance.
+
+        Returns:
+            An initialized instance of the Reranker class.
+
+        Raises:
+            NotImplementedError: If the class cannot be created from the provided configuration.
+        """
+        raise NotImplementedError(f"Cannot create class {cls.__name__} from config.")
+
     @abstractmethod
     async def store(self, entries: list[VectorStoreEntry]) -> None:
         """
diff --git a/packages/ragbits-core/src/ragbits/core/vector_stores/chroma.py b/packages/ragbits-core/src/ragbits/core/vector_stores/chroma.py
index bd46549b..e9f55c95 100644
--- a/packages/ragbits-core/src/ragbits/core/vector_stores/chroma.py
+++ b/packages/ragbits-core/src/ragbits/core/vector_stores/chroma.py
@@ -2,7 +2,6 @@
 from typing import Literal
 
 import chromadb
-from chromadb import Collection
 from chromadb.api import ClientAPI
 
 from ragbits.core.audit import traceable
@@ -39,16 +38,7 @@ def __init__(
         self._client = client
         self._index_name = index_name
         self._distance_method = distance_method
-        self._collection = self._get_chroma_collection()
-
-    def _get_chroma_collection(self) -> Collection:
-        """
-        Gets or creates a collection with the given name and metadata.
-
-        Returns:
-            The collection.
-        """
-        return self._client.get_or_create_collection(
+        self._collection = self._client.get_or_create_collection(
             name=self._index_name,
             metadata={"hnsw:space": self._distance_method},
         )
@@ -68,7 +58,7 @@ def from_config(cls, config: dict) -> "ChromaVectorStore":
         return cls(
             client=client_cls(**config["client"].get("config", {})),
             index_name=config["index_name"],
-            distance_method=config.get("distance_method", "l2"),
+            distance_method=config.get("distance_method", "cosine"),
             default_options=VectorStoreOptions(**config.get("default_options", {})),
             metadata_store=get_metadata_store(config.get("metadata_store")),
         )
@@ -81,8 +71,11 @@ async def store(self, entries: list[VectorStoreEntry]) -> None:
         Args:
             entries: The entries to store.
         """
+        if not entries:
+            return
+
         ids = [entry.id for entry in entries]
-        documents = [entry.content for entry in entries]
+        documents = [entry.key for entry in entries]
         embeddings = [entry.vector for entry in entries]
         metadatas = [entry.metadata for entry in entries]
 
@@ -130,12 +123,12 @@ async def retrieve(self, vector: list[float], options: VectorStoreOptions | None
         return [
             VectorStoreEntry(
                 id=id,
-                content=document,
+                key=document,
                 vector=list(embeddings),
                 metadata=metadata,  # type: ignore
             )
-            for batch in zip(ids, metadatas, embeddings, distances, documents, strict=False)
-            for id, metadata, embeddings, distance, document in zip(*batch, strict=False)
+            for batch in zip(ids, metadatas, embeddings, distances, documents, strict=True)
+            for id, metadata, embeddings, distance, document in zip(*batch, strict=True)
             if options.max_distance is None or distance <= options.max_distance
         ]
 
@@ -180,9 +173,9 @@ async def list(
         return [
             VectorStoreEntry(
                 id=id,
-                content=document,
+                key=document,
                 vector=list(embedding),
                 metadata=metadata,  # type: ignore
             )
-            for id, metadata, embedding, document in zip(ids, metadatas, embeddings, documents, strict=False)
+            for id, metadata, embedding, document in zip(ids, metadatas, embeddings, documents, strict=True)
         ]
diff --git a/packages/ragbits-core/src/ragbits/core/vector_stores/in_memory.py b/packages/ragbits-core/src/ragbits/core/vector_stores/in_memory.py
index d1a1c27e..28f69608 100644
--- a/packages/ragbits-core/src/ragbits/core/vector_stores/in_memory.py
+++ b/packages/ragbits-core/src/ragbits/core/vector_stores/in_memory.py
@@ -3,6 +3,7 @@
 import numpy as np
 
 from ragbits.core.audit import traceable
+from ragbits.core.metadata_stores import get_metadata_store
 from ragbits.core.metadata_stores.base import MetadataStore
 from ragbits.core.vector_stores.base import VectorStore, VectorStoreEntry, VectorStoreOptions, WhereQuery
 
@@ -27,6 +28,22 @@ def __init__(
         super().__init__(default_options=default_options, metadata_store=metadata_store)
         self._storage: dict[str, VectorStoreEntry] = {}
 
+    @classmethod
+    def from_config(cls, config: dict) -> "InMemoryVectorStore":
+        """
+        Creates and returns an instance of the InMemoryVectorStore class from the given configuration.
+
+        Args:
+            config: A dictionary containing the configuration for initializing the InMemoryVectorStore instance.
+
+        Returns:
+            An initialized instance of the InMemoryVectorStore class.
+        """
+        return cls(
+            default_options=VectorStoreOptions(**config.get("default_options", {})),
+            metadata_store=get_metadata_store(config.get("metadata_store")),
+        )
+
     @traceable
     async def store(self, entries: list[VectorStoreEntry]) -> None:
         """
diff --git a/packages/ragbits-core/src/ragbits/core/vector_stores/qdrant.py b/packages/ragbits-core/src/ragbits/core/vector_stores/qdrant.py
index 6dcb3c03..d5bfeb4f 100644
--- a/packages/ragbits-core/src/ragbits/core/vector_stores/qdrant.py
+++ b/packages/ragbits-core/src/ragbits/core/vector_stores/qdrant.py
@@ -70,6 +70,9 @@ async def store(self, entries: list[VectorStoreEntry]) -> None:
         Raises:
             QdrantException: If upload to collection fails.
         """
+        if not entries:
+            return
+
         if not await self._client.collection_exists(self._index_name):
             await self._client.create_collection(
                 collection_name=self._index_name,
@@ -78,16 +81,16 @@ async def store(self, entries: list[VectorStoreEntry]) -> None:
 
         ids = [entry.id for entry in entries]
         embeddings = [entry.vector for entry in entries]
-        payloads = [{"__document": entry.content} for entry in entries]
+        payloads = [{"document": entry.key} for entry in entries]
         metadatas = [entry.metadata for entry in entries]
 
         metadatas = (
-            [{"__metadata": json.dumps(metadata, default=str)} for metadata in metadatas]
+            [{"metadata": json.dumps(metadata, default=str)} for metadata in metadatas]
             if self._metadata_store is None
             else await self._metadata_store.store(ids, metadatas)  # type: ignore
         )
         if metadatas is not None:
-            payloads = [{**payload, **metadata} for (payload, metadata) in zip(payloads, metadatas, strict=False)]
+            payloads = [{**payload, **metadata} for (payload, metadata) in zip(payloads, metadatas, strict=True)]
 
         self._client.upload_collection(
             collection_name=self._index_name,
@@ -126,9 +129,9 @@ async def retrieve(self, vector: list[float], options: VectorStoreOptions | None
 
         ids = [point.id for point in results.points]
         vectors = [point.vector for point in results.points]
-        documents = [point.payload["__document"] for point in results.points]  # type: ignore
+        documents = [point.payload["document"] for point in results.points]  # type: ignore
         metadatas = (
-            [json.loads(point.payload["__metadata"]) for point in results.points]  # type: ignore
+            [json.loads(point.payload["metadata"]) for point in results.points]  # type: ignore
             if self._metadata_store is None
             else await self._metadata_store.get(ids)  # type: ignore
         )
@@ -136,7 +139,7 @@ async def retrieve(self, vector: list[float], options: VectorStoreOptions | None
         return [
             VectorStoreEntry(
                 id=str(id),
-                content=document,
+                key=document,
                 vector=vector,  # type: ignore
                 metadata=metadata,
             )
@@ -176,9 +179,9 @@ async def list(  # type: ignore
 
         ids = [point.id for point in results.points]
         vectors = [point.vector for point in results.points]
-        documents = [point.payload["__document"] for point in results.points]  # type: ignore
+        documents = [point.payload["document"] for point in results.points]  # type: ignore
         metadatas = (
-            [json.loads(point.payload["__metadata"]) for point in results.points]  # type: ignore
+            [json.loads(point.payload["metadata"]) for point in results.points]  # type: ignore
             if self._metadata_store is None
             else await self._metadata_store.get(ids)  # type: ignore
         )
@@ -186,7 +189,7 @@ async def list(  # type: ignore
         return [
             VectorStoreEntry(
                 id=str(id),
-                content=document,
+                key=document,
                 vector=vector,  # type: ignore
                 metadata=metadata,
             )
diff --git a/packages/ragbits-core/tests/unit/vector_stores/test_chroma.py b/packages/ragbits-core/tests/unit/vector_stores/test_chroma.py
index b3d038ec..ee48f804 100644
--- a/packages/ragbits-core/tests/unit/vector_stores/test_chroma.py
+++ b/packages/ragbits-core/tests/unit/vector_stores/test_chroma.py
@@ -14,16 +14,11 @@ def mock_chromadb_store() -> ChromaVectorStore:
     )
 
 
-async def test_get_chroma_collection(mock_chromadb_store: ChromaVectorStore) -> None:
-    _ = mock_chromadb_store._get_chroma_collection()
-    assert mock_chromadb_store._client.get_or_create_collection.call_count == 2  # type: ignore
-
-
 async def test_store(mock_chromadb_store: ChromaVectorStore) -> None:
     data = [
         VectorStoreEntry(
             id="test_key",
-            content="test content",
+            key="test content",
             vector=[0.1, 0.2, 0.3],
             metadata={
                 "content": "test content",
@@ -70,8 +65,7 @@ async def test_retrieve(
     mock_chromadb_store: ChromaVectorStore, max_distance: float | None, results: list[dict]
 ) -> None:
     vector = [0.1, 0.2, 0.3]
-    mock_collection = mock_chromadb_store._get_chroma_collection()
-    mock_collection.query.return_value = {  # type: ignore
+    mock_chromadb_store._collection.query.return_value = {  # type: ignore
         "metadatas": [
             [
                 {
@@ -98,12 +92,11 @@ async def test_retrieve(
         assert entry.metadata["document"]["title"] == result["title"]
         assert entry.vector == result["vector"]
         assert entry.id == f"test_id_{results.index(result) + 1}"
-        assert entry.content == result["content"]
+        assert entry.key == result["content"]
 
 
 async def test_list(mock_chromadb_store: ChromaVectorStore) -> None:
-    mock_collection = mock_chromadb_store._get_chroma_collection()
-    mock_collection.get.return_value = {  # type: ignore
+    mock_chromadb_store._collection.get.return_value = {  # type: ignore
         "metadatas": [
             {
                 "__metadata": '{"content": "test content", "document": {"title": "test title", "source":'
@@ -125,10 +118,10 @@ async def test_list(mock_chromadb_store: ChromaVectorStore) -> None:
     assert entries[0].metadata["content"] == "test content"
     assert entries[0].metadata["document"]["title"] == "test title"
     assert entries[0].vector == [0.12, 0.25, 0.29]
-    assert entries[0].content == "test content 1"
+    assert entries[0].key == "test content 1"
     assert entries[0].id == "test_id_1"
     assert entries[1].metadata["content"] == "test content 2"
     assert entries[1].metadata["document"]["title"] == "test title 2"
     assert entries[1].vector == [0.13, 0.26, 0.30]
-    assert entries[1].content == "test content2"
+    assert entries[1].key == "test content2"
     assert entries[1].id == "test_id_2"
diff --git a/packages/ragbits-core/tests/unit/vector_stores/test_in_memory.py b/packages/ragbits-core/tests/unit/vector_stores/test_in_memory.py
index d47e19a2..0de1f29d 100644
--- a/packages/ragbits-core/tests/unit/vector_stores/test_in_memory.py
+++ b/packages/ragbits-core/tests/unit/vector_stores/test_in_memory.py
@@ -1,6 +1,7 @@
 from pathlib import Path
 
 import pytest
+from pydantic import computed_field
 
 from ragbits.core.vector_stores.base import VectorStoreOptions
 from ragbits.core.vector_stores.in_memory import InMemoryVectorStore
@@ -20,12 +21,14 @@ class AnimalElement(Element):
     type: str
     age: int
 
-    def get_text_representation(self) -> str:
+    @computed_field  # type: ignore[prop-decorator]
+    @property
+    def text_representation(self) -> str:
         """
         Get the text representation of the element.
 
         Returns:
-            The key.
+            The text representation.
         """
         return self.name
 
diff --git a/packages/ragbits-core/tests/unit/vector_stores/test_qdrant.py b/packages/ragbits-core/tests/unit/vector_stores/test_qdrant.py
index 72685b89..345f8aed 100644
--- a/packages/ragbits-core/tests/unit/vector_stores/test_qdrant.py
+++ b/packages/ragbits-core/tests/unit/vector_stores/test_qdrant.py
@@ -19,7 +19,7 @@ async def test_store(mock_qdrant_store: QdrantVectorStore) -> None:
     data = [
         VectorStoreEntry(
             id="1c7d6b27-4ef1-537c-ad7c-676edb8bc8a8",
-            content="test_key",
+            key="test_key",
             vector=[0.1, 0.2, 0.3],
             metadata={
                 "content": "test content",
@@ -42,8 +42,8 @@ async def test_store(mock_qdrant_store: QdrantVectorStore) -> None:
         vectors=[[0.1, 0.2, 0.3]],
         payload=[
             {
-                "__document": "test_key",
-                "__metadata": '{"content": "test content", '
+                "document": "test_key",
+                "metadata": '{"content": "test content", '
                 '"document": {"title": "test title", "source": {"path": "/test/path"}, "document_type": "test_type"}}',
             }
         ],
@@ -61,8 +61,8 @@ async def test_retrieve(mock_qdrant_store: QdrantVectorStore) -> None:
                 vector=[0.12, 0.25, 0.29],
                 score=0.9,
                 payload={
-                    "__document": "test_key 1",
-                    "__metadata": '{"content": "test content 1",'
+                    "document": "test_key 1",
+                    "metadata": '{"content": "test content 1",'
                     '"document": {"title": "test title 1", '
                     '"source": {"path": "/test/path-1"}, "document_type": "txt"}}',
                 },
@@ -73,8 +73,8 @@ async def test_retrieve(mock_qdrant_store: QdrantVectorStore) -> None:
                 vector=[0.13, 0.26, 0.30],
                 score=0.9,
                 payload={
-                    "__document": "test_key 2",
-                    "__metadata": '{"content": "test content 2", '
+                    "document": "test_key 2",
+                    "metadata": '{"content": "test content 2", '
                     '"document": {"title": "test title 2", '
                     '"source": {"path": "/test/path-2"}, "document_type": "txt"}}',
                 },
@@ -105,8 +105,8 @@ async def test_list(mock_qdrant_store: QdrantVectorStore) -> None:
                 vector=[0.12, 0.25, 0.29],
                 score=0.9,
                 payload={
-                    "__document": "test_key 1",
-                    "__metadata": '{"content": "test content 1",'
+                    "document": "test_key 1",
+                    "metadata": '{"content": "test content 1",'
                     '"document": {"title": "test title 1", '
                     '"source": {"path": "/test/path-1"}, "document_type": "txt"}}',
                 },
@@ -117,8 +117,8 @@ async def test_list(mock_qdrant_store: QdrantVectorStore) -> None:
                 vector=[0.13, 0.26, 0.30],
                 score=0.9,
                 payload={
-                    "__document": "test_key 2",
-                    "__metadata": '{"content": "test content 2", '
+                    "document": "test_key 2",
+                    "metadata": '{"content": "test content 2", '
                     '"document": {"title": "test title 2", '
                     '"source": {"path": "/test/path-2"}, "document_type": "txt"}}',
                 },
diff --git a/packages/ragbits-document-search/src/ragbits/document_search/_main.py b/packages/ragbits-document-search/src/ragbits/document_search/_main.py
index 521ea0ff..daa56dc0 100644
--- a/packages/ragbits-document-search/src/ragbits/document_search/_main.py
+++ b/packages/ragbits-document-search/src/ragbits/document_search/_main.py
@@ -170,7 +170,7 @@ async def insert_elements(self, elements: list[Element]) -> None:
         Args:
             elements: The list of Elements to insert.
         """
-        vectors = await self.embedder.embed_text([element.get_text_for_embedding() for element in elements])
+        vectors = await self.embedder.embed_text([element.key for element in elements])
 
         image_elements = [element for element in elements if isinstance(element, ImageElement)]
         entries = [element.to_vector_db_entry(vector) for element, vector in zip(elements, vectors, strict=False)]
diff --git a/packages/ragbits-document-search/src/ragbits/document_search/documents/element.py b/packages/ragbits-document-search/src/ragbits/document_search/documents/element.py
index 893d7d3c..63bf82bd 100644
--- a/packages/ragbits-document-search/src/ragbits/document_search/documents/element.py
+++ b/packages/ragbits-document-search/src/ragbits/document_search/documents/element.py
@@ -42,24 +42,27 @@ def id(self) -> str:
         id_components = [
             self.document_meta.id,
             self.element_type,
-            self.get_text_for_embedding(),
-            self.get_text_representation(),
+            self.key,
+            self.text_representation,
             str(self.location),
         ]
-
         return str(uuid.uuid5(uuid.NAMESPACE_OID, ";".join(id_components)))
 
-    def get_text_for_embedding(self) -> str:
+    @computed_field  # type: ignore[prop-decorator]
+    @property
+    def key(self) -> str:
         """
-        Get the text representation of the element for embedding.
+        Get the representation of the element for embedding.
 
         Returns:
-            The text representation for embedding.
+            The representation for embedding.
         """
-        return self.get_text_representation()
+        return self.text_representation
 
+    @computed_field  # type: ignore[prop-decorator]
+    @property
     @abstractmethod
-    def get_text_representation(self) -> str:
+    def text_representation(self) -> str:
         """
         Get the text representation of the element.
 
@@ -68,12 +71,10 @@ def get_text_representation(self) -> str:
         """
 
     @classmethod
-    def __pydantic_init_subclass__(cls, **kwargs: Any) -> None:  # pylint: disable=unused-argument #noqa: ANN401
+    def __pydantic_init_subclass__(cls, **kwargs: Any) -> None:  # noqa: ANN401
         element_type_default = cls.model_fields["element_type"].default
-
         if element_type_default is None:
             raise ValueError("Element type must be defined")
-
         Element._elements_registry[element_type_default] = cls
 
     @classmethod
@@ -87,11 +88,9 @@ def from_vector_db_entry(cls, db_entry: VectorStoreEntry) -> "Element":
         Returns:
             The element.
         """
-        meta = db_entry.metadata
-        element_type = meta["element_type"]
+        element_type = db_entry.metadata["element_type"]
         element_cls = Element._elements_registry[element_type]
-
-        return element_cls(**meta)
+        return element_cls(**db_entry.metadata)
 
     def to_vector_db_entry(self, vector: list[float]) -> VectorStoreEntry:
         """
@@ -105,9 +104,9 @@ def to_vector_db_entry(self, vector: list[float]) -> VectorStoreEntry:
         """
         return VectorStoreEntry(
             id=self.id,
+            key=self.key,
             vector=vector,
-            content=self.get_text_for_embedding(),
-            metadata=self.model_dump(),
+            metadata=self.model_dump(exclude={"id", "key"}),
         )
 
 
@@ -119,7 +118,9 @@ class TextElement(Element):
     element_type: str = "text"
     content: str
 
-    def get_text_representation(self) -> str:
+    @computed_field  # type: ignore[prop-decorator]
+    @property
+    def text_representation(self) -> str:
         """
         Get the text representation of the element.
 
@@ -139,7 +140,9 @@ class ImageElement(Element):
     ocr_extracted_text: str
     image_bytes: bytes
 
-    def get_text_representation(self) -> str:
+    @computed_field  # type: ignore[prop-decorator]
+    @property
+    def text_representation(self) -> str:
         """
         Get the text representation of the element.
 
diff --git a/packages/ragbits-document-search/src/ragbits/document_search/retrieval/rerankers/litellm.py b/packages/ragbits-document-search/src/ragbits/document_search/retrieval/rerankers/litellm.py
index c83906ce..a27e982f 100644
--- a/packages/ragbits-document-search/src/ragbits/document_search/retrieval/rerankers/litellm.py
+++ b/packages/ragbits-document-search/src/ragbits/document_search/retrieval/rerankers/litellm.py
@@ -58,7 +58,7 @@ async def rerank(
             The reranked elements.
         """
         options = self._default_options if options is None else options
-        documents = [element.get_text_representation() for element in elements]
+        documents = [element.text_representation for element in elements]
 
         response = await litellm.arerank(
             model=self.model,
diff --git a/packages/ragbits-document-search/tests/unit/test_elements.py b/packages/ragbits-document-search/tests/unit/test_elements.py
index 7f98307c..f4b1fa78 100644
--- a/packages/ragbits-document-search/tests/unit/test_elements.py
+++ b/packages/ragbits-document-search/tests/unit/test_elements.py
@@ -1,20 +1,24 @@
+from pydantic import computed_field
+
 from ragbits.core.vector_stores.base import VectorStoreEntry
 from ragbits.document_search.documents.document import DocumentType
 from ragbits.document_search.documents.element import Element
 
 
-def test_resolving_element_type():
+def test_resolving_element_type() -> None:
     class MyElement(Element):
         element_type: str = "custom_element"
         foo: str
 
-        def get_text_representation(self) -> str:
+        @computed_field  # type: ignore[prop-decorator]
+        @property
+        def text_representation(self) -> str:
             return self.foo + self.foo
 
     element = Element.from_vector_db_entry(
         db_entry=VectorStoreEntry(
             id="test id",
-            content="test content",
+            key="test content",
             vector=[0.1, 0.2],
             metadata={
                 "element_type": "custom_element",
@@ -29,7 +33,7 @@ def get_text_representation(self) -> str:
 
     assert isinstance(element, MyElement)
     assert element.foo == "bar"
-    assert element.get_text_for_embedding() == "barbar"
-    assert element.get_text_representation() == "barbar"
+    assert element.key == "barbar"
+    assert element.text_representation == "barbar"
     assert element.document_meta.document_type == DocumentType.TXT
     assert element.document_meta.source.source_type == "local_file_source"