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import gradio as gr
import pandas as pd
from functools import partial
def save_chatbot_dialogue(chat_tutor, save_type):
formatted_convo = pd.DataFrame(chat_tutor.conversation_memory, columns=['user', 'chatbot'])
output_fname = f'tutoring_conversation.{save_type}'
if save_type == 'csv':
formatted_convo.to_csv(output_fname, index=False)
elif save_type == 'json':
formatted_convo.to_json(output_fname, orient='records')
elif save_type == 'txt':
temp = formatted_convo.apply(lambda x: 'User: {0}\nAI: {1}'.format(x[0], x[1]), axis=1)
temp = '\n\n'.join(temp.tolist())
with open(output_fname, 'w') as f:
f.write(temp)
else:
gr.update(value=None, visible=False)
return gr.update(value=output_fname, visible=True)
save_json = partial(save_chatbot_dialogue, save_type='json')
save_txt = partial(save_chatbot_dialogue, save_type='txt')
# history is a list of list
# [[user_input_str, bot_response_str], ...]
class BasicTutor:
# create basic initialization function
def __init__(self):
self.conversation_memory = []
self.flattened_conversation = ''
def add_user_message(self, user_message):
self.conversation_memory.append([user_message, None])
self.flattened_conversation = self.flattened_conversation + '\n\n' + 'User: ' + user_message
def get_tutor_reply(self, user_message):
# get tutor message
tutor_message = "You said: " + user_message
# add tutor message to conversation memory
self.conversation_memory[-1][1] = tutor_message
self.flattened_conversation = self.flattened_conversation + '\nAI: ' + tutor_message
def forget_conversation(self):
self.conversation_memory = []
self.flattened_conversation = ''
### Chatbot Functions ###
def add_user_message(user_message, chat_tutor):
"""Display user message and update chat history to include it."""
chat_tutor.add_user_message(user_message)
return chat_tutor.conversation_memory, chat_tutor
def get_tutor_reply(user_message, chat_tutor):
chat_tutor.get_tutor_reply(user_message)
return gr.update(value="", interactive=True), chat_tutor.conversation_memory, chat_tutor
with gr.Blocks() as demo:
#initialize tutor (with state)
study_tutor = gr.State(BasicTutor())
# Chatbot interface
gr.Markdown("""
## Chat with the Model
Description here
""")
with gr.Row(equal_height=True):
with gr.Column(scale=2):
chatbot = gr.Chatbot()
with gr.Row():
user_chat_input = gr.Textbox(label="User input", scale=9)
user_chat_submit = gr.Button("Ask/answer model", scale=1)
user_chat_submit.click(add_user_message,
[user_chat_input, study_tutor],
[chatbot, study_tutor], queue=False).then(
get_tutor_reply, [user_chat_input, study_tutor], [user_chat_input, chatbot, study_tutor], queue=True)
with gr.Blocks():
gr.Markdown("""
## Export Your Chat History
Export your chat history as a .json, .txt, or .csv file
""")
with gr.Row():
export_dialogue_button_json = gr.Button("JSON")
export_dialogue_button_txt = gr.Button("TXT")
file_download = gr.Files(label="Download here",
file_types=['.txt', '.json'], type="file", visible=False)
export_dialogue_button_json.click(save_json, study_tutor, file_download, show_progress=True)
export_dialogue_button_txt.click(save_txt, study_tutor, file_download, show_progress=True)
demo.queue()
demo.launch() |