Spaces:
Runtime error
Runtime error
File size: 5,153 Bytes
8ec41f0 |
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 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 |
import os
import re
import pickle
import base64
import requests
import argparse
import numpy as np
import gradio as gr
from functools import partial
from PIL import Image
SERVER_URL = os.getenv('SERVER_URL')
def get_images(state):
history = ''
for i in range(len(state)):
for j in range(len(state[i])):
history += state[i][j] + '\n'
for image_path in re.findall('image/[0-9,a-z]+\.png', history):
if os.path.exists(image_path):
continue
data = {'method': 'get_image', 'args': [image_path], 'kwargs': {}}
data = base64.b64encode(pickle.dumps(data)).decode('utf-8')
response = requests.post(SERVER_URL, json=data)
image = pickle.loads(base64.b64decode(response.json().encode('utf-8')))
image.save(image_path)
def bot_request(method, *args, **kwargs):
data = {'method': method, 'args': args, 'kwargs': kwargs}
data = base64.b64encode(pickle.dumps(data)).decode('utf-8')
response = requests.post(SERVER_URL, json=data)
response = pickle.loads(base64.b64decode(response.json().encode('utf-8')))
if response is not None:
state = response[0]
get_images(state)
return response
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--temperature', type=float, default=0.0, help='temperature for the llm model')
parser.add_argument('--max_new_tokens', type=int, default=128, help='max number of new tokens to generate')
parser.add_argument('--top_p', type=float, default=1.0, help='top_p for the llm model')
parser.add_argument('--top_k', type=int, default=40, help='top_k for the llm model')
parser.add_argument('--num_beams', type=int, default=4, help='num_beams for the llm model')
parser.add_argument('--keep_last_n_paragraphs', type=int, default=1, help='keep last n paragraphs in the memory')
args = parser.parse_args()
examples = [
['images/example-1.jpg', 'What is unusual about this image?'],
['images/example-2.jpg', 'Make the image look like a cartoon.'],
['images/example-3.jpg', 'Segment the tie in the image.'],
['images/example-4.jpg', 'Generate a man watching a sea based on the pose of the woman.'],
['images/example-5.jpg', 'Replace the dog with a cat.'],
]
if not os.path.exists('image'):
os.makedirs('image')
with gr.Blocks() as demo:
with gr.Row():
with gr.Column(scale=0.3):
with gr.Row():
image = gr.Image(type="pil", label="input image")
with gr.Row():
txt = gr.Textbox(lines=7, show_label=False, elem_id="textbox",
placeholder="Enter text and press submit, or upload an image").style(container=False)
with gr.Row():
submit = gr.Button("Submit")
with gr.Row():
clear = gr.Button("Clear")
with gr.Row():
keep_last_n_paragraphs = gr.Slider(
minimum=0,
maximum=3,
value=args.keep_last_n_paragraphs,
step=1,
interactive=True,
label="Remember Last N Paragraphs")
max_new_token = gr.Slider(
minimum=128,
maximum=1024,
value=args.max_new_tokens,
step=64,
interactive=True,
label="Max New Tokens")
temperature = gr.Slider(
minimum=0.0,
maximum=1.0,
value=args.temperature,
step=0.1,
interactive=True,
label="Temperature")
top_p = gr.Slider(
minimum=0.0,
maximum=1.0,
value=args.top_p,
step=0.1,
interactive=True,
label="Top P")
with gr.Column(scale=0.7):
chatbot = gr.Chatbot(elem_id="chatbot", label="🦙 GPT4Tools").style(height=690)
state = gr.State([])
txt.submit(partial(bot_request, 'run_text'), [txt, state], [chatbot, state])
txt.submit(lambda: "", None, txt)
image.upload(lambda: "", None, txt)
submit.click(partial(bot_request, 'run_image'), [image, state, txt], [chatbot, state, txt]).then(
partial(bot_request, 'run_text'), [txt, state, temperature, top_p, max_new_token, keep_last_n_paragraphs], [chatbot, state, txt]).then(
lambda: None, None, image)
clear.click(partial(bot_request, 'clear'))
clear.click(lambda: [], None, chatbot)
clear.click(lambda: [], None, state)
with gr.Row():
gr.Examples(
examples=examples,
inputs=[image, txt],
)
demo.launch()
|