Spaces:
Runtime error
Runtime error
File size: 8,120 Bytes
9aa6aea cd9f1f6 9aa6aea ce50c4e 9aa6aea 862c154 9aa6aea 862c154 9aa6aea 862c154 9aa6aea 505f63b 9aa6aea 862c154 9aa6aea cd9f1f6 9aa6aea |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 |
# -*- coding: utf-8 -*-
# ===================================================
#
# Author : Fan Zhang
# Email : [email protected]
# Institute : Beijing Academy of Artificial Intelligence (BAAI)
# Create On : 2023-12-11 15:35
# Last Modified : 2023-12-20 14:15
# File Name : generation_frontend.py
# Description :
#
# ===================================================
import base64
import json
import io
import time
from PIL import Image
import requests
import gradio as gr
from .constants import EVA_IMAGE_SIZE
from .meta import ConvMeta, Role, DataMeta
from .utils import frontend_logger as logging
CONTROLLER_URL = ""
def submit(
meta,
enable_grd,
left,
top,
right,
bottom,
image,
text,
):
if meta is None:
meta = ConvMeta()
meta.pop_error()
if meta.has_gen:
meta.clear()
if enable_grd:
if text == "" and image is None:
logging.info(f"{meta.log_id}: invalid input: no valid data for grounding input")
gr.Error("text or image must be given if enable grounding generation")
return meta.format_chatbot(), meta, False, 0, 0, EVA_IMAGE_SIZE, EVA_IMAGE_SIZE, None, ""
meta.append(Role.USER, DataMeta.build(text=text, image=image, coordinate=[left, top, right, bottom]))
elif image is not None and text != "":
logging.info(f"{meta.log_id}: invalid input: give text and image simultaneously for single modality input")
gr.Error("Do not submit text and image data at the same time!!!")
return meta.format_chatbot(), meta, False, 0, 0, EVA_IMAGE_SIZE, EVA_IMAGE_SIZE, None, ""
elif image is not None:
meta.append(Role.USER, DataMeta.build(image=image))
elif text != "":
meta.append(Role.USER, DataMeta.build(text=text))
return meta.format_chatbot(), meta, False, 0, 0, EVA_IMAGE_SIZE, EVA_IMAGE_SIZE, None, ""
def clear_history(meta):
if meta is None:
meta = ConvMeta()
meta.clear()
return meta.format_chatbot(), meta
def generate(meta, classifier_free_guidance, steps):
if meta is None:
meta = ConvMeta()
meta.pop_error()
meta.pop()
prompt = meta.format_prompt()
prompt_list, image_list = [], {}
for idx, p in enumerate(prompt):
if isinstance(p, Image.Image):
key = f"[<IMAGE{idx}>]"
prompt_list.append(["IMAGE", key])
buf = io.BytesIO()
p.save(buf, format="PNG")
image_list[key] = (key, io.BytesIO(buf.getvalue()), "image/png")
else:
prompt_list.append(["TEXT", p])
if len(image_list) == 0:
image_list = None
logging.info(f"{meta.log_id}: construct generation reqeust with prompt {prompt_list}")
t0 = time.time()
try:
rsp = requests.post(
CONTROLLER_URL + "/v1/mmg",
files=image_list,
data={
"log_id": meta.log_id,
"prompt": json.dumps(prompt_list),
"classifier_free_guidance": classifier_free_guidance,
"steps": steps,
},
)
except Exception as ex:
rsp = requests.Response()
rsp.status_code = 1099
rsp._content = str(ex).encode()
t1 = time.time()
logging.info(f"{meta.log_id}: get response with status code: {rsp.status_code}, time: {(t1-t0)*1000:.3f}ms")
if rsp.status_code == requests.codes.ok:
content = json.loads(rsp.text)
if content["code"] == 0:
image = Image.open(io.BytesIO(base64.b64decode(content["data"])))
meta.append(Role.ASSISTANT, DataMeta.build(image=image, resize=False))
else:
meta.append(Role.ASSISTANT, DataMeta.build(text=f"GENERATE FAILED: {content['data']}", is_error=True))
else:
meta.append(Role.ASSISTANT, DataMeta.build(text=f"GENERATE FAILED: http failed with code {rsp.status_code}, msg: {rsp.text}", is_error=True))
return meta.format_chatbot(), meta
def build_generation(args):
global CONTROLLER_URL
CONTROLLER_URL = args.controller_url
with gr.Blocks(title="Emu", theme=gr.themes.Default(primary_hue="blue", secondary_hue="blue")) as demo:
state = gr.State()
with gr.Row():
with gr.Column(scale=2):
with gr.Row():
imagebox = gr.Image(type="pil")
with gr.Row():
with gr.Accordion("Grounding Parameters", open=True, visible=True) as grounding_row:
enable_grd = gr.Checkbox(label="Enable")
left = gr.Slider(minimum=0, maximum=EVA_IMAGE_SIZE, value=0, step=1, interactive=True, label="left")
top = gr.Slider(minimum=0, maximum=EVA_IMAGE_SIZE, value=0, step=1, interactive=True, label="top")
right = gr.Slider(minimum=0, maximum=EVA_IMAGE_SIZE, value=EVA_IMAGE_SIZE, step=1, interactive=True, label="right")
bottom = gr.Slider(minimum=0, maximum=EVA_IMAGE_SIZE, value=EVA_IMAGE_SIZE, step=1, interactive=True, label="bottom")
with gr.Row():
with gr.Accordion("Diffusion Parameters", open=True, visible=True) as parameters_row:
cfg = gr.Slider(minimum=1, maximum=30, value=3, step=0.5, interactive=True, label="classifier free guidance")
steps = gr.Slider(minimum=1, maximum=100, value=50, step=1, interactive=True, label="steps")
with gr.Column(scale=6):
chatbot = gr.Chatbot(
elem_id="chatbot",
label="Emu Chatbot",
visible=True,
height=720,
)
with gr.Row():
with gr.Column(scale=8):
textbox = gr.Textbox(
show_label=False,
placeholder="Enter text and add to prompt",
visible=True,
container=False,
)
with gr.Column(scale=1, min_width=60):
add_btn = gr.Button(value="Add")
with gr.Row(visible=True) as button_row:
# upvote_btn = gr.Button(value="👍 Upvote", interactive=False)
# downvote_btn = gr.Button(value="👎 Downvote", interactive=False)
# regenerate_btn = gr.Button(value="🔄 Regenerate", interactive=False)
clear_btn = gr.Button(value="🗑️ Clear History")
generate_btn = gr.Button(value="Generate")
clear_btn.click(clear_history, inputs=state, outputs=[chatbot, state])
textbox.submit(
submit,
inputs=[
state,
enable_grd,
left,
top,
right,
bottom,
imagebox,
textbox,
],
outputs=[
chatbot,
state,
enable_grd,
left,
top,
right,
bottom,
imagebox,
textbox,
],
)
add_btn.click(
submit,
inputs=[
state,
enable_grd,
left,
top,
right,
bottom,
imagebox,
textbox,
],
outputs=[
chatbot,
state,
enable_grd,
left,
top,
right,
bottom,
imagebox,
textbox,
],
)
generate_btn.click(
generate,
inputs=[
state,
cfg,
steps,
],
outputs=[
chatbot,
state,
]
)
return demo
|