Update app.py

app.py

@@ -292,6 +292,57 @@
 # if __name__ == "__main__":
 #     demo.launch()
 
+# import os
+# import subprocess
+# import gradio as gr
+
+# # Install necessary packages
+# subprocess.check_call(["pip", "install", "-U", "langchain-openai", "gradio", "langchain-community"])
+
+# from langchain_openai import ChatOpenAI
+# from langchain.prompts import PromptTemplate
+# from langchain.memory import ConversationBufferMemory
+# from langchain.chains import Runnable, RunnableSequence
+
+# # Set OpenAI API Key
+# OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
+
+# # Define the template for the chatbot's response
+# template = """You are a helpful assistant to answer all user queries.
+# {chat_history}
+# User: {user_message}
+# Chatbot:"""
+
+# # Define the prompt template
+# prompt = PromptTemplate(
+#     input_variables=["chat_history", "user_message"], 
+#     template=template
+# )
+
+# # Initialize conversation memory
+# memory = ConversationBufferMemory(memory_key="chat_history")
+
+# # Define the runnable sequence
+# chatbot_runnable = RunnableSequence(prompt | ChatOpenAI(temperature=0.5, model="gpt-3.5-turbo"))
+
+# # Function to get chatbot response
+# def get_text_response(user_message, history=None):
+#     # Ensure history is a list
+#     if history is None:
+#         history = []
+
+#     # Prepare the conversation history
+#     chat_history = history + [f"User: {user_message}"]
+#     response = chatbot_runnable.invoke({"chat_history": "\n".join(chat_history), "user_message": user_message})
+    
+#     return response
+
+# # Create a Gradio chat interface
+# demo = gr.Interface(fn=get_text_response, inputs=["text", "state"], outputs="text")
+
+# if __name__ == "__main__":
+#     demo.launch()
+
 import os
 import subprocess
 import gradio as gr
@@ -302,7 +353,6 @@ subprocess.check_call(["pip", "install", "-U", "langchain-openai", "gradio", "la
 from langchain_openai import ChatOpenAI
 from langchain.prompts import PromptTemplate
 from langchain.memory import ConversationBufferMemory
-from langchain.chains import Runnable, RunnableSequence
 
 # Set OpenAI API Key
 OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
@@ -322,9 +372,6 @@ prompt = PromptTemplate(
 # Initialize conversation memory
 memory = ConversationBufferMemory(memory_key="chat_history")
 
-# Define the runnable sequence
-chatbot_runnable = RunnableSequence(prompt | ChatOpenAI(temperature=0.5, model="gpt-3.5-turbo"))
-
 # Function to get chatbot response
 def get_text_response(user_message, history=None):
     # Ensure history is a list
@@ -333,9 +380,10 @@ def get_text_response(user_message, history=None):
 
     # Prepare the conversation history
     chat_history = history + [f"User: {user_message}"]
-    response = chatbot_runnable.invoke({"chat_history": "\n".join(chat_history), "user_message": user_message})
+    llm = ChatOpenAI(temperature=0.5, model="gpt-3.5-turbo")
+    response = llm({"chat_history": "\n".join(chat_history), "user_message": user_message})
     
-    return response
+    return response['choices'][0]['message']['content']
 
 # Create a Gradio chat interface
 demo = gr.Interface(fn=get_text_response, inputs=["text", "state"], outputs="text")
@@ -348,3 +396,4 @@ if __name__ == "__main__":
 
 
 
+