from gradio_client import Client
from hugchat import hugchat
from hugchat.login import Login
import json
import gradio as gr

chat_client = Client("https://huggingfaceh4-falcon-chat.hf.space/")


retrieval = Client("https://slycat-southampton-similarity.hf.space/")

n_conv = 0
## Instruction: You are an AI language model and must return truthful responses as per the information below\n ##Input: Information: Your name is IITIGPT. You are a helpful and truthful chatbot. You can help answer any questions about the IIT Indore campus."
init_prompt =""
info="Information: \n"
q_prompt="\n ##Instruction: Please  provide an appropriate response to the following: \n"


def change_conv():
    # Create a new conversation
    id = chatbot.new_conversation()
    chatbot.change_conversation(id)
    chatbot.chat(init_prompt)
    chatbot.cookies = {}
    
def main(question):
    global n_conv
    # if(n_conv > 3):
    #     n_conv = 0
    #     change_conv(chatbot)
    information = retrieval.predict(question, api_name = "/predict")
    answer=chat_client.predict(
				"Howdy!",
        "new.json",   
        "You are an AI language model and must return truthful responses as per the information below\n ##Input: Information: Your name is Southampton GPT. You are a helpful and truthful chatbot. You can help answer any questions about the Southampton University." +information+question,	# str  in 'Type an input and press Enter' Textbox component
        0.8,
        0.9,
				fn_index=3
)
    n_conv+=1
    print(answer)
    temp=json.load(open(answer))
    print(temp)
    
    return temp


demo = gr.Interface(main,"text","text")

if __name__ == "__main__":
    demo.launch()