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import os
import collections as cl
from pathlib import Path
import gradio as gr
from openai import OpenAI
from mylib import (
FileManager,
ChatController,
MessageHandler,
NumericCitations,
)
#
#
#
ChatState = cl.namedtuple('ChatState', 'database, messenger, chat')
#
#
#
def open_ai_vars(prefix='OPENAI_KWARGS_'):
n = len(prefix)
for (k, v) in os.environ.items():
if k.startswith(prefix):
key = k[n:].lower()
yield (key, v)
def load():
client = OpenAI()
database = FileManager(client)
messenger = MessageHandler(client, NumericCitations)
kwargs = dict(open_ai_vars())
instructions = Path('static', 'system-prompt').with_suffix('.txt')
chat = ChatController(client, database, instructions, **kwargs)
return ChatState(database, messenger, chat)
def eject(state):
state.database.cleanup()
state.chat.cleanup()
def upload(data, state):
try:
return state.database(data)
except InterruptedError as err:
raise gr.Error(str(err))
def prompt(message, history, state):
if state.database:
response = state.messenger(state.chat(message))
history.append((
message,
response,
))
else:
gr.Warning('Please upload your documents to begin')
return ( # textbox submit outputs
'', # clear the input text
history, # update the chat output
)
#
#
#
with gr.Blocks() as demo:
state = gr.State(
value=load,
delete_callback=eject,
)
howto = Path('static/howto').with_suffix('.md')
with gr.Row():
with gr.Accordion(label='Instructions', open=False):
gr.Markdown(howto.read_text())
with gr.Row():
with gr.Column():
data = gr.UploadButton(
label='Select and upload your files',
file_count='multiple',
)
repository = gr.Textbox(
label='Files uploaded',
placeholder='Upload your files to begin!',
interactive=False,
)
data.upload(
fn=upload,
inputs=[
data,
state,
],
outputs=repository,
)
with gr.Column(scale=2):
chatbot = gr.Chatbot(
height='70vh',
show_copy_button=True,
)
chatbot.change(scroll_to_output=True)
interaction = gr.Textbox(
label='Ask a question about your documents and press "Enter"',
)
interaction.submit(
fn=prompt,
inputs=[
interaction,
chatbot,
state,
],
outputs=[
interaction,
chatbot,
],
)
if __name__ == '__main__':
auth = tuple(os.getenv(f'GRADIO_{x}') for x in ('USER', 'PASS'))
demo.launch(auth=auth)
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