langchain[patch]: Rollback multiple keys in Qdrant (#14390)

This reverts commit 38813d7. This is a
temporary fix, as I don't see a clear way on how to use multiple keys
with `Qdrant.from_texts`.

Context: #14378

libs/langchain/langchain/vectorstores/qdrant.py

@@ -82,17 +82,17 @@ class Qdrant(VectorStore):
             qdrant = Qdrant(client, collection_name, embedding_function)
     """
 
-    CONTENT_KEY = ["page_content"]
-    METADATA_KEY = ["metadata"]
+    CONTENT_KEY = "page_content"
+    METADATA_KEY = "metadata"
     VECTOR_NAME = None
 
     def __init__(
         self,
         client: Any,
         collection_name: str,
         embeddings: Optional[Embeddings] = None,
-        content_payload_key: Union[list, str] = CONTENT_KEY,
-        metadata_payload_key: Union[list, str] = METADATA_KEY,
+        content_payload_key: str = CONTENT_KEY,
+        metadata_payload_key: str = METADATA_KEY,
         distance_strategy: str = "COSINE",
         vector_name: Optional[str] = VECTOR_NAME,
         embedding_function: Optional[Callable] = None,  # deprecated
@@ -112,12 +112,6 @@ def __init__(
                 f"got {type(client)}"
             )
 
-        if isinstance(content_payload_key, str):  # Ensuring Backward compatibility
-            content_payload_key = [content_payload_key]
-
-        if isinstance(metadata_payload_key, str):  # Ensuring Backward compatibility
-            metadata_payload_key = [metadata_payload_key]
-
         if embeddings is None and embedding_function is None:
             raise ValueError(
                 "`embeddings` value can't be None. Pass `Embeddings` instance."
@@ -133,14 +127,8 @@ def __init__(
         self._embeddings_function = embedding_function
         self.client: qdrant_client.QdrantClient = client
         self.collection_name = collection_name
-        self.content_payload_key = (
-            content_payload_key if content_payload_key is not None else self.CONTENT_KEY
-        )
-        self.metadata_payload_key = (
-            metadata_payload_key
-            if metadata_payload_key is not None
-            else self.METADATA_KEY
-        )
+        self.content_payload_key = content_payload_key or self.CONTENT_KEY
+        self.metadata_payload_key = metadata_payload_key or self.METADATA_KEY
         self.vector_name = vector_name or self.VECTOR_NAME
 
         if embedding_function is not None:
@@ -1190,8 +1178,8 @@ def from_texts(
         path: Optional[str] = None,
         collection_name: Optional[str] = None,
         distance_func: str = "Cosine",
-        content_payload_key: List[str] = CONTENT_KEY,
-        metadata_payload_key: List[str] = METADATA_KEY,
+        content_payload_key: str = CONTENT_KEY,
+        metadata_payload_key: str = METADATA_KEY,
         vector_name: Optional[str] = VECTOR_NAME,
         batch_size: int = 64,
         shard_number: Optional[int] = None,
@@ -1366,8 +1354,8 @@ async def afrom_texts(
         path: Optional[str] = None,
         collection_name: Optional[str] = None,
         distance_func: str = "Cosine",
-        content_payload_key: List[str] = CONTENT_KEY,
-        metadata_payload_key: List[str] = METADATA_KEY,
+        content_payload_key: str = CONTENT_KEY,
+        metadata_payload_key: str = METADATA_KEY,
         vector_name: Optional[str] = VECTOR_NAME,
         batch_size: int = 64,
         shard_number: Optional[int] = None,
@@ -1539,8 +1527,8 @@ def construct_instance(
         path: Optional[str] = None,
         collection_name: Optional[str] = None,
         distance_func: str = "Cosine",
-        content_payload_key: List[str] = CONTENT_KEY,
-        metadata_payload_key: List[str] = METADATA_KEY,
+        content_payload_key: str = CONTENT_KEY,
+        metadata_payload_key: str = METADATA_KEY,
         vector_name: Optional[str] = VECTOR_NAME,
         shard_number: Optional[int] = None,
         replication_factor: Optional[int] = None,
@@ -1703,8 +1691,8 @@ async def aconstruct_instance(
         path: Optional[str] = None,
         collection_name: Optional[str] = None,
         distance_func: str = "Cosine",
-        content_payload_key: List[str] = CONTENT_KEY,
-        metadata_payload_key: List[str] = METADATA_KEY,
+        content_payload_key: str = CONTENT_KEY,
+        metadata_payload_key: str = METADATA_KEY,
         vector_name: Optional[str] = VECTOR_NAME,
         shard_number: Optional[int] = None,
         replication_factor: Optional[int] = None,
@@ -1900,11 +1888,11 @@ def _similarity_search_with_relevance_scores(
 
     @classmethod
     def _build_payloads(
-        cls: Type[Qdrant],
+        cls,
         texts: Iterable[str],
         metadatas: Optional[List[dict]],
-        content_payload_key: list[str],
-        metadata_payload_key: list[str],
+        content_payload_key: str,
+        metadata_payload_key: str,
     ) -> List[dict]:
         payloads = []
         for i, text in enumerate(texts):
@@ -1925,67 +1913,29 @@ def _build_payloads(
 
     @classmethod
     def _document_from_scored_point(
-        cls: Type[Qdrant],
+        cls,
         scored_point: Any,
-        content_payload_key: list[str],
-        metadata_payload_key: list[str],
+        content_payload_key: str,
+        metadata_payload_key: str,
     ) -> Document:
-        payload = scored_point.payload
-        return Qdrant._document_from_payload(
-            payload=payload,
-            content_payload_key=content_payload_key,
-            metadata_payload_key=metadata_payload_key,
+        return Document(
+            page_content=scored_point.payload.get(content_payload_key),
+            metadata=scored_point.payload.get(metadata_payload_key) or {},
         )
 
     @classmethod
     def _document_from_scored_point_grpc(
-        cls: Type[Qdrant],
+        cls,
         scored_point: Any,
-        content_payload_key: list[str],
-        metadata_payload_key: list[str],
+        content_payload_key: str,
+        metadata_payload_key: str,
     ) -> Document:
         from qdrant_client.conversions.conversion import grpc_to_payload
 
         payload = grpc_to_payload(scored_point.payload)
-        return Qdrant._document_from_payload(
-            payload=payload,
-            content_payload_key=content_payload_key,
-            metadata_payload_key=metadata_payload_key,
-        )
-
-    @classmethod
-    def _document_from_payload(
-        cls: Type[Qdrant],
-        payload: Any,
-        content_payload_key: list[str],
-        metadata_payload_key: list[str],
-    ) -> Document:
-        if len(content_payload_key) == 1:
-            content = payload.get(
-                content_payload_key
-            )  # Ensuring backward compatibility
-        elif len(content_payload_key) > 1:
-            content = {
-                content_key: payload.get(content_key)
-                for content_key in content_payload_key
-            }
-            content = str(content)  # Ensuring str type output
-        else:
-            content = ""
-        if len(metadata_payload_key) == 1:
-            metadata = payload.get(
-                metadata_payload_key
-            )  # Ensuring backward compatibility
-        elif len(metadata_payload_key) > 1:
-            metadata = {
-                metadata_key: payload.get(metadata_key)
-                for metadata_key in metadata_payload_key
-            }
-        else:
-            metadata = {}
         return Document(
-            page_content=content,
-            metadata=metadata,
+            page_content=payload[content_payload_key],
+            metadata=payload.get(metadata_payload_key) or {},
         )
 
     def _build_condition(self, key: str, value: Any) -> List[rest.FieldCondition]: