diff --git a/pyproject.toml b/pyproject.toml
index 031a4137..f7301660 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,6 +23,7 @@ classifiers = [
 
 [tool.poetry.dependencies]
 python = "^3.8.1"
+revChatGPT = "*"
 transformers = "*"
 openai = "*"
 langchain = "*"
diff --git a/requirements.txt b/requirements.txt
index c92b868c..8581892a 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,5 +1,6 @@
 # faiss-gpu
 transformers
+revChatGPT
 pandas
 langchain
 nest_asyncio
diff --git a/swarms/models/revgpt.py b/swarms/models/revgpt.py
index 1233f2fd..67f1b1dd 100644
--- a/swarms/models/revgpt.py
+++ b/swarms/models/revgpt.py
@@ -1,24 +1,29 @@
 import os
 import revChatGPT
-from revChatGPT.V1 import Chatbot as RevChatGPTV1
+from revChatGPT.V1 import Chatbot as RevChatGPTV1, time
 from revChatGPT.V3 import Chatbot as RevChatGPTV3
 
+from abc import ABC, abstractmethod
+from revChatGPT.V1 import Chatbot
+
 class RevChatGPTModel:
-    def __init__(self, access_token=None, api_key=None, **kwargs):
+    def __init__(self, access_token=None, **kwargs):
+        super().__init__()
         self.config = kwargs
         if access_token:
-            self.chatbot = RevChatGPTV1(config={"access_token": access_token})
-        elif api_key:
-            self.chatbot = RevChatGPTV3(api_key=api_key)
+            self.chatbot = Chatbot(config={"access_token": access_token})
         else:
-            raise ValueError("Either access_token or api_key must be provided.")
+            raise ValueError("access_token must be provided.")
 
     def run(self, task: str) -> str:
-        response = ""
+        self.start_time = time.time()
+        prev_text = ""
         for data in self.chatbot.ask(task):
-            response = data["message"]
-        return response
+            message = data["message"][len(prev_text):]
+            prev_text = data["message"]
+        self.end_time = time.time()
+        return prev_text
 
     def generate_summary(self, text: str) -> str:
-        # Implement summary generation using RevChatGPT
+        # Implement this method based on your requirements
         pass