Spaces:
Runtime error
Runtime error
File size: 9,329 Bytes
9aa6aea 6a25365 9aa6aea 6a25365 9aa6aea 862c154 9aa6aea 862c154 9aa6aea 862c154 9aa6aea 505f63b 9aa6aea 862c154 9aa6aea 6a25365 9aa6aea 6a25365 9aa6aea cd9f1f6 9aa6aea cd9f1f6 9aa6aea 0bd8053 9aa6aea 6a25365 9aa6aea 6a25365 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 |
# -*- coding: utf-8 -*-
# ===================================================
#
# Author : Fan Zhang
# Email : zhangfan@baai.ac.cn
# Institute : Beijing Academy of Artificial Intelligence (BAAI)
# Create On : 2023-12-12 18:05
# Last Modified : 2023-12-20 15:59
# File Name : chat_frontend.py
# Description :
#
# ===================================================
import json
import io
import time
from PIL import Image
import requests
import gradio as gr
from .meta import ConvMeta, Role, DataMeta
from .utils import extract_frames
from .utils import frontend_logger as logging
from .constants import LICENSE, TERM_OF_USE
CONTROLLER_URL = ""
def submit(
meta,
image,
video,
text,
num_frames,
):
if meta is None:
meta = ConvMeta()
meta.pop_error()
check_text = (text != "" and text is not None)
check_image = image is not None
check_video = video is not None
if check_text + check_image + check_video != 1:
logging.info(f"{meta.log_id}: invalid input: give multi madality simultaneously for single modality input")
gr.Error("Invalid input number, must give exactly one modality input at a time")
return meta.format_chatbot(), meta, None, None, ""
if check_text:
meta.append(Role.USER, DataMeta.build(text=text))
elif check_image:
meta.append(Role.USER, DataMeta.build(image=image))
elif check_video:
frames = extract_frames(video, num_frames)
meta.append(Role.USER, DataMeta.build(frames=frames))
return meta.format_chatbot(), meta, None, None, ""
def clear_history(meta):
if meta is None:
meta = ConvMeta()
meta.clear()
return meta.format_chatbot(), meta
def generate(
meta,
do_sample,
max_new_tokens,
temperature,
top_k,
top_p,
length_penalty,
num_beams,
repetition_penalty,
):
if meta is None:
meta = ConvMeta()
meta.pop_error()
meta.pop()
prompt = meta.format_chat()
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 chat reqeust with prompt {prompt_list}")
t0 = time.time()
try:
rsp = requests.post(
CONTROLLER_URL + "/v1/mmc",
files=image_list,
data={
"log_id": meta.log_id,
"prompt": json.dumps(prompt_list),
"do_sample": do_sample,
"max_new_tokens": max_new_tokens,
"temperature": temperature,
"top_k": top_k,
"top_p": top_p,
"length_penalty": length_penalty,
"num_beams": num_beams,
"repetition_penalty": repetition_penalty,
},
)
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:
meta.append(Role.ASSISTANT, DataMeta.build(text=content["data"]))
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 push_examples(examples, meta):
if meta is None:
meta = ConvMeta()
meta.clear()
image, prompt = examples
meta.append(Role.USER, DataMeta.build(image=Image.open(image)))
meta.append(Role.USER, DataMeta.build(text=prompt))
return meta.format_chatbot(), meta
def build_chat(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():
videobox = gr.Video()
with gr.Accordion("Parameters", open=True, visible=True) as parameter_row:
do_sample = gr.Checkbox(value=False, label="Do Sample", interactive=True)
max_new_tokens = gr.Slider(minimum=0, maximum=2048, value=512, step=1, interactive=True, label="Max Output Tokens")
temperature = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.05, interactive=True, label="Temperature")
top_k = gr.Slider(minimum=1, maximum=5, value=3, step=1, interactive=True, label="Top K")
top_p = gr.Slider(minimum=0, maximum=1, value=0.9, step=0.05, interactive=True, label="Top P")
length_penalty = gr.Slider(minimum=0, maximum=5, value=2, step=0.1, interactive=True, label="Length Penalty")
num_beams = gr.Slider(minimum=1, maximum=10, value=5, step=1, interactive=True, label="Beam Size")
repetition_penalty = gr.Slider(minimum=1.0, maximum=10.0, value=1.0, step=0.5, interactive=True, label="Repetition Penalty")
num_frames = gr.Number(interactive=True, value=8, maximum=12, label="Num Video Frames")
with gr.Column(scale=6):
chatbot = gr.Chatbot(
elem_id="chatbot",
label="Emu Chatbot",
visible=True,
height=1070,
)
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="π Upvote", interactive=False)
# downvote_btn = gr.Button(value="π Downvote", interactive=False)
# flag_btn = gr.Button(value="β οΈ Flag", interactive=False)
# regenerate_btn = gr.Button(value="π Regenerate", interactive=False)
clear_btn = gr.Button(value="ποΈ Clear History")
generate_btn = gr.Button(value="Generate")
with gr.Row():
examples = gr.Dataset(components=[gr.Image(type="pil", visible=False), gr.Textbox(visible=False)],
label="Examples",
samples=[
["./examples/roadmap.jpg", "Imagine you are a guiding robot.\nHere is a photo I took. Please tell me how to get to the restroom."],
["./examples/shapes.jpeg", "Look at this sequence of three shapes. What shape should come as the fourth shape? Explain your reasoning with detailed descriptions of the first shapes."],
],
)
gr.Markdown(TERM_OF_USE)
gr.Markdown(LICENSE)
clear_btn.click(clear_history, inputs=state, outputs=[chatbot, state])
textbox.submit(
submit,
inputs=[
state,
imagebox,
videobox,
textbox,
num_frames,
],
outputs=[
chatbot,
state,
imagebox,
videobox,
textbox,
],
)
add_btn.click(
submit,
inputs=[
state,
imagebox,
videobox,
textbox,
num_frames,
],
outputs=[
chatbot,
state,
imagebox,
videobox,
textbox,
],
)
generate_btn.click(
generate,
inputs=[
state,
do_sample,
max_new_tokens,
temperature,
top_k,
top_p,
length_penalty,
num_beams,
repetition_penalty,
],
outputs=[
chatbot,
state,
],
)
examples.click(
push_examples,
inputs=[
examples,
state,
],
outputs=[
chatbot,
state,
]
)
return demo
|