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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()
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