🔨 refactor(loading.py): add type hints to function parameters and return types

This commit adds type hints to the function parameters and return types in the loading.py file. This improves the readability and maintainability of the codebase by making it easier to understand the expected types of the parameters and return values of the functions.

src/backend/langflow/interface/initialize/loading.py

@@ -1,5 +1,5 @@
 import json
-from typing import Any, Callable, Dict, Sequence
+from typing import Any, Callable, Dict, Sequence, Type
 
 from langchain.agents import ZeroShotAgent
 from langchain.agents import agent as agent_module
@@ -16,6 +16,12 @@ from langflow.interface.toolkits.base import toolkits_creator
 from langflow.interface.chains.base import chain_creator
 from langflow.interface.utils import load_file_into_dict
 from langflow.utils import validate
+from langchain.text_splitter import TextSplitter
+from langchain.chains.base import Chain
+from langchain.vectorstores.base import VectorStore
+from langchain.document_loaders.base import BaseLoader
+from langchain.embeddings.base import Embeddings
+from langchain.prompts.base import BasePromptTemplate
 
 
 def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
@@ -76,7 +82,7 @@ def instantiate_based_on_type(class_object, base_type, node_type, params):
         return class_object(**params)
 
 
-def instantiate_chains(node_type, class_object, params):
+def instantiate_chains(node_type, class_object: Type[Chain], params: Dict):
     if "retriever" in params and hasattr(params["retriever"], "as_retriever"):
         params["retriever"] = params["retriever"].as_retriever()
     if node_type in chain_creator.from_method_nodes:
@@ -88,11 +94,11 @@ def instantiate_chains(node_type, class_object, params):
     return class_object(**params)
 
 
-def instantiate_agent(class_object, params):
+def instantiate_agent(class_object: Type[Chain], params: Dict):
     return load_agent_executor(class_object, params)
 
 
-def instantiate_prompt(node_type, class_object, params):
+def instantiate_prompt(node_type, class_object: Type[BasePromptTemplate], params: Dict):
     if node_type == "ZeroShotPrompt":
         if "tools" not in params:
             params["tools"] = []
@@ -100,7 +106,7 @@ def instantiate_prompt(node_type, class_object, params):
     return class_object(**params)
 
 
-def instantiate_tool(node_type, class_object, params):
+def instantiate_tool(node_type, class_object: Type[BaseTool], params: Dict):
     if node_type == "JsonSpec":
         params["dict_"] = load_file_into_dict(params.pop("path"))
         return class_object(**params)
@@ -118,7 +124,7 @@ def instantiate_tool(node_type, class_object, params):
     return class_object(**params)
 
 
-def instantiate_toolkit(node_type, class_object, params):
+def instantiate_toolkit(node_type, class_object: Type[BaseToolkit], params: Dict):
     loaded_toolkit = class_object(**params)
     # Commenting this out for now to use toolkits as normal tools
     # if toolkits_creator.has_create_function(node_type):
@@ -128,7 +134,7 @@ def instantiate_toolkit(node_type, class_object, params):
     return loaded_toolkit
 
 
-def instantiate_embedding(class_object, params):
+def instantiate_embedding(class_object: Type[Embeddings], params: Dict):
     params.pop("model", None)
     params.pop("headers", None)
     try:
@@ -142,7 +148,7 @@ def instantiate_embedding(class_object, params):
         return class_object(**params)
 
 
-def instantiate_vectorstore(class_object, params):
+def instantiate_vectorstore(class_object: Type[VectorStore], params: Dict):
     search_kwargs = params.pop("search_kwargs", {})
     if initializer := vecstore_initializer.get(class_object.__name__):
         vecstore = initializer(class_object, params)
@@ -158,7 +164,7 @@ def instantiate_vectorstore(class_object, params):
     return vecstore
 
 
-def instantiate_documentloader(class_object, params):
+def instantiate_documentloader(class_object: Type[BaseLoader], params: Dict):
     if "file_filter" in params:
         # file_filter will be a string but we need a function
         # that will be used to filter the files using file_filter
@@ -187,7 +193,7 @@ def instantiate_documentloader(class_object, params):
     return docs
 
 
-def instantiate_textsplitter(class_object, params):
+def instantiate_textsplitter(class_object: Type[TextSplitter], params: Dict):
     try:
         documents = params.pop("documents")
     except KeyError as e:
@@ -195,11 +201,17 @@ def instantiate_textsplitter(class_object, params):
             "The source you provided did not load correctly or was empty."
             "Try changing the chunk_size of the Text Splitter."
         ) from e
-    text_splitter = class_object(**params)
+    if "separator_type" in params and params["separator_type"] == "Text":
+        text_splitter = class_object(**params)
+    else:
+        params["language"] = params.pop("separator_type", None)
+        params.pop("separators", None)
+        text_splitter = class_object.from_language(**params)
+
     return text_splitter.split_documents(documents)
 
 
-def instantiate_utility(node_type, class_object, params):
+def instantiate_utility(node_type, class_object, params: Dict):
     if node_type == "SQLDatabase":
         return class_object.from_uri(params.pop("uri"))
     return class_object(**params)