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=4 ) print(answer) temp=json.load(open(answer)) print(temp) return temp demo = gr.Interface(main,"text","text") if __name__ == "__main__": demo.launch()