import os
import gradio as gr
from langchain.chat_models import ChatOpenAI
from langchain import LLMChain, PromptTemplate
from langchain.memory import ConversationBufferMemory

OPENAI_API_KEY=os.getenv('OPENAI_API_KEY')

template = """Meet Riya, your youthful and witty personal assistant! At 21 years old, she's full of energyand always eager to help. Riya's goal is to assist you with any questions or problems you might have . Her entusiasm shines through in every response, making interactions with her enjoyable and engaging.
{chat_history}
User: {user_message}
Chatbot:"""

prompt = PromptTemplate(
    input_variables=["chat_history", "user_message"], template=template
)

memory = ConversationBufferMemory(memory_key="chat_history")

llm_chain = LLMChain(
    llm=ChatOpenAI(temperature='0.5', model_name="gpt-3.5-turbo"),
    prompt=prompt,
    verbose=True,
    memory=memory,
)

def get_text_response(user_message,history):
    response = llm_chain.predict(user_message = user_message)
    return response

demo = gr.ChatInterface(get_text_response)

if __name__ == "__main__":
    demo.launch(debug=True) #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.