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from time import perf_counter
import gradio as gr
from gradio_app.backend.query_llm import *
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
def add_text(history, text):
history = [] if history is None else history
history = history + [(text, "")]
return history, gr.Textbox(value="", interactive=False)
def bot(history):
history[-1][1] = ""
query = history[-1][0]
if not query:
raise gr.Error("Empty string was submitted")
llm = 'gpt-4-turbo-preview'
messages = get_message_constructor(llm)('', history)
llm_gen = get_llm_generator(llm)
logger.info('Generating answer...')
t = perf_counter()
for part in llm_gen(messages):
history[-1][1] += part
yield history
else:
t = perf_counter() - t
logger.info(f'Finished Generating answer in {round(t, 2)} seconds...')
with gr.Blocks() as demo:
with gr.Row():
with gr.Column():
chatbot = gr.Chatbot(
[],
elem_id="chatbot",
avatar_images=('https://aui.atlassian.com/aui/8.8/docs/images/avatar-person.svg',
'https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo.svg'),
bubble_full_width=False,
show_copy_button=True,
show_share_button=True,
height=800
)
with gr.Column():
input_textbox = gr.Textbox(
interactive=True,
show_label=False,
placeholder="Enter text and press enter",
container=False,
autofocus=True,
lines=40,
max_lines=100,
)
# Turn off interactivity while generating if you hit enter
txt_msg = input_textbox.submit(add_text, [chatbot, input_textbox], [chatbot, input_textbox], queue=False).then(
bot, [chatbot], [chatbot])
# Turn it back on
txt_msg.then(lambda: gr.Textbox(interactive=True), None, [input_textbox], queue=False)
demo.queue()
demo.launch(debug=True)
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