fix: formatting and utils

src/backend/langflow/graph/utils.py

@@ -0,0 +1,26 @@
+import base64
+import json
+from typing import Dict
+
+import yaml
+
+
+def load_dict(file_name, file_content, accepted_types) -> Dict:
+    """Load a file from a string."""
+    # Check if the file is accepted
+    if not any(file_name.endswith(suffix) for suffix in accepted_types):
+        raise ValueError(f"File {file_name} is not accepted")
+    # Get the suffix
+    suffix = file_name.split(".")[-1]
+    # file_content == 'data:application/x-yaml;base64,b3BlbmFwaTogIjMuMC4wIg...'
+    data = file_content.split(",")[1]
+    decoded_bytes = base64.b64decode(data)
+
+    # Convert the bytes object to a string
+    decoded_string = decoded_bytes.decode("utf-8")
+    if suffix == "json":
+        # Return the json content
+        return json.loads(decoded_string)
+    elif suffix in ["yaml", "yml"]:
+        # Return the yaml content
+        return yaml.safe_load(decoded_string)

src/backend/langflow/interface/agents/base.py

@@ -1,10 +1,12 @@
-from langchain.agents import loading
-from langflow.custom.customs import get_custom_nodes
-from langflow.interface.base import LangChainTypeCreator
-from langflow.utils.util import build_template_from_class
-from langflow.settings import settings
 from typing import Dict, List
-from langflow.interface.agents.custom import JsonAgent
+
+from langchain.agents import loading
+
+from langflow.custom.customs import get_custom_nodes
+from langflow.interface.agents.custom import CUSTOM_AGENTS
+from langflow.interface.base import LangChainTypeCreator
+from langflow.settings import settings
+from langflow.utils.util import build_template_from_class
 
 
 class AgentCreator(LangChainTypeCreator):
@@ -15,7 +17,8 @@ class AgentCreator(LangChainTypeCreator):
         if self.type_dict is None:
             self.type_dict = loading.AGENT_TO_CLASS
             # Add JsonAgent to the list of agents
-            self.type_dict["JsonAgent"] = JsonAgent
+            for name, agent in CUSTOM_AGENTS.items():
+                self.type_dict[name] = agent
         return self.type_dict
 
     def get_signature(self, name: str) -> Dict | None:

src/backend/langflow/interface/listing.py

@@ -5,6 +5,7 @@ from langflow.interface.memories.base import memory_creator
 from langflow.interface.prompts.base import prompt_creator
 from langflow.interface.toolkits.base import toolkits_creator
 from langflow.interface.tools.base import tool_creator
+from langflow.interface.wrappers.base import wrapper_creator
 
 
 def get_type_dict():
@@ -16,6 +17,7 @@ def get_type_dict():
         "chains": chain_creator.to_list(),
         "memory": memory_creator.to_list(),
         "toolkits": toolkits_creator.to_list(),
+        "wrappers": wrapper_creator.to_list(),
     }
 
 

src/backend/langflow/interface/loading.py

@@ -1,19 +1,16 @@
 import json
 from typing import Any, Dict, Optional
 
+from langchain.agents import ZeroShotAgent
+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.load_tools import (
     _BASE_TOOLS,
     _EXTRA_LLM_TOOLS,
     _EXTRA_OPTIONAL_TOOLS,
     _LLM_TOOLS,
 )
-from langchain.agents import agent as agent_module
-
-
-from langflow.interface.importing.utils import import_by_type
-
-from langchain.agents import ZeroShotAgent
 from langchain.agents.loading import load_agent_from_config
 from langchain.agents.tools import Tool
 from langchain.callbacks.base import BaseCallbackManager
@@ -21,20 +18,29 @@ from langchain.chains.loading import load_chain_from_config
 from langchain.llms.base import BaseLLM
 from langchain.llms.loading import load_llm_from_config
 
+from langflow.interface.agents.custom import CUSTOM_AGENTS
+from langflow.interface.importing.utils import import_by_type
+from langflow.interface.toolkits.base import toolkits_creator
 from langflow.interface.types import get_type_list
 from langflow.utils import payload, util, validate
 
 
 def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
     """Instantiate class from module type and key, and params"""
+    if node_type in CUSTOM_AGENTS:
+        if custom_agent := CUSTOM_AGENTS.get(node_type):
+            return custom_agent.initialize(**params)
+
     class_object = import_by_type(_type=base_type, name=node_type)
+
     if base_type == "agents":
         # We need to initialize it differently
-        allowed_tools = params["allowed_tools"]
-        llm_chain = params["llm_chain"]
-        return load_agent_executor(class_object, allowed_tools, llm_chain)
-    elif base_type == "tools" or node_type != "ZeroShotPrompt":
-        return class_object(**params)
+        return load_agent_executor(class_object, params)
+    elif node_type == "ZeroShotPrompt":
+        if "tools" not in params:
+            params["tools"] = []
+        return ZeroShotAgent.create_prompt(**params)
+
     elif node_type == "PythonFunction":
         # If the node_type is "PythonFunction"
         # we need to get the function from the params
@@ -45,10 +51,14 @@ def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
         if isinstance(function_string, str):
             return validate.eval_function(function_string)
         raise ValueError("Function should be a string")
+    elif base_type == "toolkits":
+        loaded_toolkit = class_object(**params)
+        # Check if node_type has a loader
+        if toolkits_creator.has_create_function(node_type):
+            return load_toolkits_executor(node_type, loaded_toolkit, params)
+        return loaded_toolkit
     else:
-        if "tools" not in params:
-            params["tools"] = []
-        return ZeroShotAgent.create_prompt(**params)
+        return class_object(**params)
 
 
 def load_flow_from_json(path: str):
@@ -122,10 +132,10 @@ def load_agent_executor_from_config(
     )
 
 
-def load_agent_executor(
-    agent_class: type[agent_module.Agent], allowed_tools, llm_chain, **kwargs
-):
+def load_agent_executor(agent_class: type[agent_module.Agent], params, **kwargs):
     """Load agent executor from agent class, tools and chain"""
+    allowed_tools = params["allowed_tools"]
+    llm_chain = params["llm_chain"]
     tool_names = [tool.name for tool in allowed_tools]
     agent = agent_class(allowed_tools=tool_names, llm_chain=llm_chain)
     return AgentExecutor.from_agent_and_tools(
@@ -135,6 +145,14 @@ def load_agent_executor(
     )
 
 
+def load_toolkits_executor(node_type: str, toolkit: BaseToolkit, params: dict):
+    create_function = toolkits_creator.get_create_function(node_type)
+    llm = params.get("llm", None)
+    if llm:
+        return create_function(llm=llm, toolkit=toolkit)
+    return
+
+
 def load_tools_from_config(tool_list: list[dict]) -> list:
     """Load tools based on a config list.
 

src/backend/langflow/interface/types.py

@@ -1,8 +1,8 @@
 from langflow.interface.agents.base import agent_creator
+from langflow.interface.chains.base import chain_creator
 from langflow.interface.llms.base import llm_creator
 from langflow.interface.memories.base import memory_creator
 from langflow.interface.prompts.base import prompt_creator
-from langflow.interface.chains.base import chain_creator
 from langflow.interface.toolkits.base import toolkits_creator
 from langflow.interface.tools.base import tool_creator
 from langflow.interface.wrappers.base import wrapper_creator

tests/conftest.py

@@ -1,4 +1,5 @@
 from pathlib import Path
+
 import pytest
 from fastapi.testclient import TestClient