🔧 chore(llm.py): add function to initialize VertexAI credentials

🔧 chore(loading.py): call initialize_vertexai function when node_type is "VertexAI"
The `llm.py` file now includes a new function `initialize_vertexai` that initializes the VertexAI credentials if a `credentials` parameter is provided. This allows for the usage of VertexAI credentials in the application. In `loading.py`, the `initialize_vertexai` function is called when the `node_type` is "VertexAI", ensuring that the VertexAI credentials are properly initialized for that specific node type.

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

@@ -0,0 +1,9 @@
+def initialize_vertexai(class_object, params):
+    if credentials_path := params.get("credentials"):
+        from google.oauth2 import service_account
+
+        credentials_object = service_account.Credentials.from_service_account_file(
+            filename=credentials_path
+        )
+        params["credentials"] = credentials_object
+    return class_object(**params)

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

@@ -6,6 +6,7 @@ from langchain.agents import agent as agent_module
 from langchain.agents.agent import AgentExecutor
 from langchain.agents.agent_toolkits.base import BaseToolkit
 from langchain.agents.tools import BaseTool
+from langflow.interface.initialize.llm import initialize_vertexai
 
 from langflow.interface.initialize.vector_store import vecstore_initializer
 
@@ -89,6 +90,8 @@ def instantiate_llm(node_type, class_object, params: Dict):
     # if "openai_api_base" in params and "jina" in params["openai_api_base"]:
     # False if condition is True
     ChatConfig.streaming = "jina" not in params.get("openai_api_base", "")
+    if node_type == "VertexAI":
+        return initialize_vertexai(class_object=class_object, params=params)
 
     return class_object(**params)