diff --git a/src/backend/base/langflow/components/models/OpenAIModel.py b/src/backend/base/langflow/components/models/OpenAIModel.py
index 329b0357f..c5592c2c4 100644
--- a/src/backend/base/langflow/components/models/OpenAIModel.py
+++ b/src/backend/base/langflow/components/models/OpenAIModel.py
@@ -6,7 +6,8 @@ from pydantic.v1 import SecretStr
 from langflow.base.constants import STREAM_INFO_TEXT
 from langflow.base.models.model import LCModelComponent
 from langflow.base.models.openai_constants import MODEL_NAMES
-from langflow.field_typing import NestedDict, Text
+from langflow.field_typing import BaseLanguageModel, Text
+from langflow.template import Input, Output
 
 
 class OpenAIModelComponent(LCModelComponent):
@@ -14,80 +15,64 @@ class OpenAIModelComponent(LCModelComponent):
     description = "Generates text using OpenAI LLMs."
     icon = "OpenAI"
 
-    field_order = [
-        "max_tokens",
-        "model_kwargs",
-        "model_name",
-        "openai_api_base",
-        "openai_api_key",
-        "temperature",
-        "input_value",
-        "system_message",
-        "stream",
+    inputs = [
+        Input(name="input_value", type=str, display_name="Input", input_types=["Text", "Record", "Prompt"]),
+        Input(
+            name="max_tokens",
+            type=Optional[int],
+            display_name="Max Tokens",
+            advanced=True,
+            info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
+        ),
+        Input(name="model_kwargs", type=dict, display_name="Model Kwargs", advanced=True),
+        Input(name="model_name", type=str, display_name="Model Name", advanced=False, options=MODEL_NAMES),
+        Input(
+            name="openai_api_base",
+            type=Optional[str],
+            display_name="OpenAI API Base",
+            advanced=True,
+            info="The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
+        ),
+        Input(
+            name="openai_api_key",
+            type=str,
+            display_name="OpenAI API Key",
+            info="The OpenAI API Key to use for the OpenAI model.",
+            advanced=False,
+            password=True,
+        ),
+        Input(name="temperature", type=float, display_name="Temperature", advanced=False, default=0.1),
+        Input(name="stream", type=bool, display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
+        Input(
+            name="system_message",
+            type=Optional[str],
+            display_name="System Message",
+            info="System message to pass to the model.",
+            advanced=True,
+        ),
+    ]
+    outputs = [
+        Output(display_name="Text", name="text_output", method="text_response"),
+        Output(display_name="Language Model", name="model_output", method="model_response"),
     ]
 
-    def build_config(self):
-        return {
-            "input_value": {"display_name": "Input", "input_types": ["Text", "Record", "Prompt"]},
-            "max_tokens": {
-                "display_name": "Max Tokens",
-                "advanced": True,
-                "info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
-            },
-            "model_kwargs": {
-                "display_name": "Model Kwargs",
-                "advanced": True,
-            },
-            "model_name": {
-                "display_name": "Model Name",
-                "advanced": False,
-                "options": MODEL_NAMES,
-            },
-            "openai_api_base": {
-                "display_name": "OpenAI API Base",
-                "advanced": True,
-                "info": (
-                    "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\n"
-                    "You can change this to use other APIs like JinaChat, LocalAI and Prem."
-                ),
-            },
-            "openai_api_key": {
-                "display_name": "OpenAI API Key",
-                "info": "The OpenAI API Key to use for the OpenAI model.",
-                "advanced": False,
-                "password": True,
-            },
-            "temperature": {
-                "display_name": "Temperature",
-                "advanced": False,
-                "value": 0.1,
-            },
-            "stream": {
-                "display_name": "Stream",
-                "info": STREAM_INFO_TEXT,
-                "advanced": True,
-            },
-            "system_message": {
-                "display_name": "System Message",
-                "info": "System message to pass to the model.",
-                "advanced": True,
-            },
-        }
+    def text_response(self) -> Text:
+        input_value = self.input_value
+        stream = self.stream
+        system_message = self.system_message
+        output = self.model_response()
+        result = self.get_chat_result(output, stream, input_value, system_message)
+        self.status = result
+        return result
+
+    def model_response(self) -> BaseLanguageModel:
+        openai_api_key = self.openai_api_key
+        temperature = self.temperature
+        model_name = self.model_name
+        max_tokens = self.max_tokens
+        model_kwargs = self.model_kwargs
+        openai_api_base = self.openai_api_base or "https://api.openai.com/v1"
 
-    def build(
-        self,
-        input_value: Text,
-        openai_api_key: str,
-        temperature: float = 0.1,
-        model_name: str = "gpt-3.5-turbo",
-        max_tokens: Optional[int] = 256,
-        model_kwargs: NestedDict = {},
-        openai_api_base: Optional[str] = None,
-        stream: bool = False,
-        system_message: Optional[str] = None,
-    ) -> Text:
-        if not openai_api_base:
-            openai_api_base = "https://api.openai.com/v1"
         if openai_api_key:
             api_key = SecretStr(openai_api_key)
         else:
@@ -101,5 +86,4 @@ class OpenAIModelComponent(LCModelComponent):
             api_key=api_key,
             temperature=temperature,
         )
-
-        return self.get_chat_result(output, stream, input_value, system_message)
+        return output