Spaces:
Runtime error
Runtime error
# -*- 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 : 2024-01-04 09:42 | |
# 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 CHAT_ROUTER, TERM_OF_USE, CHAT_GUIDANCE, RECOMMEND | |
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") | |
meta.append(Role.ASSISTANT, DataMeta.build(text=f"Generate Failed: Invalid input number, must give exactly one modality input at a time", is_error=True)) | |
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() | |
if len(meta) == 0: | |
meta.append(Role.ASSISTANT, DataMeta.build(text=f"Generate Failed: Please enter a valid input", is_error=True)) | |
return meta.format_chatbot(), meta | |
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() | |
gr.Markdown(CHAT_ROUTER) | |
gr.Markdown(CHAT_GUIDANCE) | |
gr.Markdown(RECOMMEND) | |
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/squirrel.jpeg", "What is funny about this image?"], | |
["./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) | |
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 | |