rm mutable defaults (#9974)

libs/langchain/langchain/callbacks/mlflow_callback.py

@@ -242,7 +242,7 @@ class MlflowCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
         self,
         name: Optional[str] = "langchainrun-%",
         experiment: Optional[str] = "langchain",
-        tags: Optional[Dict] = {},
+        tags: Optional[Dict] = None,
         tracking_uri: Optional[str] = None,
     ) -> None:
         """Initialize callback handler."""
@@ -254,7 +254,7 @@ class MlflowCallbackHandler(BaseMetadataCallbackHandler, BaseCallbackHandler):
 
         self.name = name
         self.experiment = experiment
-        self.tags = tags
+        self.tags = tags or {}
         self.tracking_uri = tracking_uri
 
         self.temp_dir = tempfile.TemporaryDirectory()

libs/langchain/langchain/callbacks/promptlayer_callback.py

@@ -40,12 +40,12 @@ class PromptLayerCallbackHandler(BaseCallbackHandler):
     def __init__(
         self,
         pl_id_callback: Optional[Callable[..., Any]] = None,
-        pl_tags: Optional[List[str]] = [],
+        pl_tags: Optional[List[str]] = None,
     ) -> None:
         """Initialize the PromptLayerCallbackHandler."""
         _lazy_import_promptlayer()
         self.pl_id_callback = pl_id_callback
-        self.pl_tags = pl_tags
+        self.pl_tags = pl_tags or []
         self.runs: Dict[UUID, Dict[str, Any]] = {}
 
     def on_chat_model_start(

libs/langchain/langchain/document_loaders/async_html.py

@@ -33,7 +33,7 @@ class AsyncHtmlLoader(BaseLoader):
         verify_ssl: Optional[bool] = True,
         proxies: Optional[dict] = None,
         requests_per_second: int = 2,
-        requests_kwargs: Dict[str, Any] = {},
+        requests_kwargs: Optional[Dict[str, Any]] = None,
         raise_for_status: bool = False,
     ):
         """Initialize with a webpage path."""
@@ -67,7 +67,7 @@ class AsyncHtmlLoader(BaseLoader):
             self.session.proxies.update(proxies)
 
         self.requests_per_second = requests_per_second
-        self.requests_kwargs = requests_kwargs
+        self.requests_kwargs = requests_kwargs or {}
         self.raise_for_status = raise_for_status
 
     async def _fetch(

libs/langchain/langchain/graphs/nebula_graph.py

@@ -1,6 +1,6 @@
 import logging
 from string import Template
-from typing import Any, Dict
+from typing import Any, Dict, Optional
 
 logger = logging.getLogger(__name__)
 
@@ -106,11 +106,12 @@ class NebulaGraph:
         """Returns the schema of the NebulaGraph database"""
         return self.schema
 
-    def execute(self, query: str, params: dict = {}, retry: int = 0) -> Any:
+    def execute(self, query: str, params: Optional[dict] = None, retry: int = 0) -> Any:
         """Query NebulaGraph database."""
         from nebula3.Exception import IOErrorException, NoValidSessionException
         from nebula3.fbthrift.transport.TTransport import TTransportException
 
+        params = params or {}
         try:
             result = self.session_pool.execute_parameter(query, params)
             if not result.is_succeeded():

libs/langchain/langchain/llms/symblai_nebula.py

@@ -183,9 +183,10 @@ def make_request(
     instruction: str,
     conversation: str,
     url: str = f"{DEFAULT_NEBULA_SERVICE_URL}{DEFAULT_NEBULA_SERVICE_PATH}",
-    params: Dict = {},
+    params: Optional[Dict] = None,
 ) -> Any:
     """Generate text from the model."""
+    params = params or {}
     headers = {
         "Content-Type": "application/json",
         "ApiKey": f"{self.nebula_api_key}",

libs/langchain/langchain/vectorstores/marqo.py

@@ -372,10 +372,10 @@ class Marqo(VectorStore):
         index_name: str = "",
         url: str = "http://localhost:8882",
         api_key: str = "",
-        add_documents_settings: Optional[Dict[str, Any]] = {},
+        add_documents_settings: Optional[Dict[str, Any]] = None,
         searchable_attributes: Optional[List[str]] = None,
         page_content_builder: Optional[Callable[[Dict[str, str]], str]] = None,
-        index_settings: Optional[Dict[str, Any]] = {},
+        index_settings: Optional[Dict[str, Any]] = None,
         verbose: bool = True,
         **kwargs: Any,
     ) -> Marqo:
@@ -435,7 +435,7 @@ class Marqo(VectorStore):
         client = marqo.Client(url=url, api_key=api_key)
 
         try:
-            client.create_index(index_name, settings_dict=index_settings)
+            client.create_index(index_name, settings_dict=index_settings or {})
             if verbose:
                 print(f"Created {index_name} successfully.")
         except Exception:
@@ -446,7 +446,7 @@ class Marqo(VectorStore):
             client,
             index_name,
             searchable_attributes=searchable_attributes,
-            add_documents_settings=add_documents_settings,
+            add_documents_settings=add_documents_settings or {},
             page_content_builder=page_content_builder,
         )
         instance.add_texts(texts, metadatas)

libs/langchain/langchain/vectorstores/redis/base.py

@@ -991,7 +991,7 @@ class Redis(VectorStore):
         self,
         k: int,
         filter: Optional[RedisFilterExpression] = None,
-        return_fields: List[str] = [],
+        return_fields: Optional[List[str]] = None,
     ) -> "Query":
         try:
             from redis.commands.search.query import Query
@@ -1000,6 +1000,7 @@ class Redis(VectorStore):
                 "Could not import redis python package. "
                 "Please install it with `pip install redis`."
             ) from e
+        return_fields = return_fields or []
         vector_key = self._schema.content_vector_key
         base_query = f"@{vector_key}:[VECTOR_RANGE $distance_threshold $vector]"
 
@@ -1020,7 +1021,7 @@ class Redis(VectorStore):
         self,
         k: int,
         filter: Optional[RedisFilterExpression] = None,
-        return_fields: List[str] = [],
+        return_fields: Optional[List[str]] = None,
     ) -> "Query":
         """Prepare query for vector search.
 
@@ -1038,6 +1039,7 @@ class Redis(VectorStore):
                 "Could not import redis python package. "
                 "Please install it with `pip install redis`."
             ) from e
+        return_fields = return_fields or []
         query_prefix = "*"
         if filter:
             query_prefix = f"{str(filter)}"

libs/langchain/langchain/vectorstores/singlestoredb.py

@@ -345,8 +345,9 @@ class SingleStoreDB(VectorStore):
             def build_where_clause(
                 where_clause_values: List[Any],
                 sub_filter: dict,
-                prefix_args: List[str] = [],
+                prefix_args: Optional[List[str]] = None,
             ) -> None:
+                prefix_args = prefix_args or []
                 for key in sub_filter.keys():
                     if isinstance(sub_filter[key], dict):
                         build_where_clause(

libs/langchain/langchain/vectorstores/vectara.py

@@ -463,7 +463,7 @@ class VectaraRetriever(VectorStoreRetriever):
         self,
         texts: List[str],
         metadatas: Optional[List[dict]] = None,
-        doc_metadata: Optional[dict] = {},
+        doc_metadata: Optional[dict] = None,
     ) -> None:
         """Add text to the Vectara vectorstore.
 
@@ -471,4 +471,4 @@ class VectaraRetriever(VectorStoreRetriever):
             texts (List[str]): The text
             metadatas (List[dict]): Metadata dicts, must line up with existing store
         """
-        self.vectorstore.add_texts(texts, metadatas, doc_metadata)
+        self.vectorstore.add_texts(texts, metadatas, doc_metadata or {})

libs/langchain/langchain/vectorstores/zilliz.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 import logging
-from typing import Any, List, Optional
+from typing import Any, Dict, List, Optional
 
 from langchain.embeddings.base import Embeddings
 from langchain.vectorstores.milvus import Milvus
@@ -140,7 +140,7 @@ class Zilliz(Milvus):
         embedding: Embeddings,
         metadatas: Optional[List[dict]] = None,
         collection_name: str = "LangChainCollection",
-        connection_args: dict[str, Any] = {},
+        connection_args: Optional[Dict[str, Any]] = None,
         consistency_level: str = "Session",
         index_params: Optional[dict] = None,
         search_params: Optional[dict] = None,
@@ -173,7 +173,7 @@ class Zilliz(Milvus):
         vector_db = cls(
             embedding_function=embedding,
             collection_name=collection_name,
-            connection_args=connection_args,
+            connection_args=connection_args or {},
             consistency_level=consistency_level,
             index_params=index_params,
             search_params=search_params,