Refactor code to extract class name from custom code

- Updatethe `get_function_custom` function to use the `validate.extract_class_name` function to extract class name from the `code` parameter.
- Modify `instantiate_tool` function to update the `class_object` with the return value of `get_function_custom` and call the `build` method on the instantiated object with the remaining params.
- Add a new function `extract_class_name` in the `validate` module to extract class name from the `code` parameter.

src/backend/langflow/interface/importing/utils.py

@@ -165,26 +165,6 @@ def get_function(code):
 
 
 def get_function_custom(code):
-    function_name = "build"
-    class_name = "MyPythonClass"
-
-    code = """
-from langchain.llms import OpenAI
-from langchain.chains import ConversationChain
-from langchain.memory import ConversationBufferMemory
-
-
-class MyPythonClass:
-    def my_conversation(self):
-        llm = OpenAI(temperature=0)
-        return ConversationChain(
-            llm=llm, verbose=True, memory=ConversationBufferMemory()
-        )
-
-    def build(self, my_custom_input: str) -> ConversationChain:
-        conversation = self.my_conversation()
-        
-        return conversation
-    """
+    class_name = validate.extract_class_name(code)
 
     return validate.create_class(code, class_name)

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

@@ -178,8 +178,8 @@ def instantiate_tool(node_type, class_object, params):
         params["func"] = get_function(params.get("code"))
         return class_object(**params)
     elif node_type == "CustomComponent":
-        params["func"] = get_function_custom(params.get("code"))
-        return class_object(**params)
+        class_object = get_function_custom(params.pop("code"))
+        return class_object().build(**params)
     # For backward compatibility
     elif node_type == "PythonFunction":
         function_string = params["code"]

src/backend/langflow/interface/tools/custom.py

@@ -84,6 +84,7 @@ class CustomComponent(BaseModel):
     function_entrypoint_name = "build"
     return_type_valid_list = [
         "ConversationChain",
+        "BaseLLM",
         "Tool"
     ]
     class_template = {

src/backend/langflow/utils/constants.py

@@ -57,7 +57,10 @@ from langchain.memory import ConversationBufferMemory
 
 class MyPythonClass:
     def my_conversation(self):
-        llm = OpenAI(temperature=0)
+        llm = OpenAI(
+            openai_api_key='',
+            temperature=0
+        )
         return ConversationChain(
             llm=llm, verbose=True, memory=ConversationBufferMemory()
         )

src/backend/langflow/utils/validate.py

@@ -230,3 +230,11 @@ def extract_function_name(code):
         if isinstance(node, ast.FunctionDef):
             return node.name
     raise ValueError("No function definition found in the code string")
+
+
+def extract_class_name(code):
+    module = ast.parse(code)
+    for node in module.body:
+        if isinstance(node, ast.ClassDef):
+            return node.name
+    raise ValueError("No class definition found in the code string")