Spaces:
Runtime error
Runtime error
File size: 1,267 Bytes
f745223 e8fb838 1ffd977 13a089e e8fb838 f745223 cbcb343 f745223 d8a82cd 52c453e f745223 13a089e 1ffd977 3988351 13a089e 1ffd977 f57923a 1ffd977 0635d16 13a089e 0635d16 13a089e 0635d16 1ffd977 2334dc1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 |
import os
import torch
import gradio as gr
from strings import TITLE, ABSTRACT
from gen import get_pretrained_models, get_output, setup_model_parallel
os.environ["RANK"] = "0"
os.environ["WORLD_SIZE"] = "1"
os.environ["MASTER_ADDR"] = "127.0.0.1"
os.environ["MASTER_PORT"] = "50505"
local_rank, world_size = setup_model_parallel()
generator = get_pretrained_models("7B", "tokenizer", local_rank, world_size)
history = []
def chat(user_input):
bot_response = get_output(generator, user_input)[0]
history.append({
"role": "user",
"content": user_input
})
history.append({
"role": "system",
"content": bot_response
})
response = ""
for word in bot_response.split(" "):
response += word + " "
yield [(user_input, response)]
with gr.Blocks(css = """#col_container {width: 700px; margin-left: auto; margin-right: auto;}
#chatbot {height: 400px; overflow: auto;}""") as demo:
gr.Markdown(f"## {TITLE}\n\n\n\n{ABSTRACT}")
with gr.Column(elem_id='col_container'):
chatbot = gr.Chatbot(elem_id='chatbot')
textbox = gr.Textbox(placeholder="Enter a prompt")
textbox.submit(chat, textbox, chatbot)
demo.queue(api_open=False).launch() |