import gradio as gr
from transformers import pipeline, Conversation
# from transformers.pipelines.conversational import Conversation

# def greet(name):
#     return "Hello " + name + "!!"

# iface = gr.Interface(fn=greet, inputs="text", outputs="text")
# iface.launch()

chatbot_model = "facebook/blenderbot-400M-distill"

chatbot = pipeline(model=chatbot_model)

past_user_inputs = []
generated_responses = []

def echo(message, history):
    return message

def chatbot_response(message, chat_history):
    # print(message)
    # return message + "??" # message, chat_history
    # conversation = Conversation(text=message, past_user_inputs=past_user_inputs, generated_responses=generated_responses)
    # conv = Conversation(chat_history)
    # conv = Conversation(text=message)
    # print(chatbot)
    # print("---")
    # conv.add_user_input(message)
    # print(conv)
    # print("---")
    # chat_history.append(message)
    # print(chat_history)
    # print("---")
    conv = chatbot(message)
    generated_text = conv[-1]["generated_text"]
    return generated_text
    # return chat_history
    # generated_text # , chat_history # , chat_history
    # conv.append_response(bot_message)

    # past_user_inputs.append(message)
    # generated_responses.append(bot_message)

    # chat_history.append((message, bot_message))

app = gr.ChatInterface(fn=chatbot_response, examples=["hi", "hola", "merhaba"], title="Chat Bot")
app.launch()