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#!/usr/bin/env python | |
import gradio as gr | |
import os | |
import json | |
import requests | |
import time | |
from concurrent.futures import ThreadPoolExecutor | |
from utils import is_chinese, process_image_without_resize, parse_response, templates_agent_cogagent, template_grounding_cogvlm, postprocess_text | |
DESCRIPTION = '''<h2 style='text-align: center'> <a href="https://github.com/THUDM/CogVLM"> CogVLM & CogAgent Chat Demo</a> </h2>''' | |
NOTES = 'This app is adapted from <a href="https://github.com/THUDM/CogVLM">https://github.com/THUDM/CogVLM</a>. It would be recommended to check out the repo if you want to see the detail of our model.\n\n该demo仅作为测试使用,不支持批量请求。如有大批量需求,欢迎联系[智谱AI](mailto:business@zhipuai.cn)。\n\n请注意CoogVLM-17B目前仅支持英文。' | |
MAINTENANCE_NOTICE1 = 'Hint 1: If the app report "Something went wrong, connection error out", please turn off your proxy and retry.<br>Hint 2: If you upload a large size of image like 10MB, it may take some time to upload and process. Please be patient and wait.' | |
GROUNDING_NOTICE = 'Hint: When you check "Grounding", please use the <a href="https://github.com/THUDM/CogVLM/blob/main/utils/utils/template.py#L344">corresponding prompt</a> or the examples below.' | |
AGENT_NOTICE = 'Hint: When you check "CogAgent", please use the <a href="https://github.com/THUDM/CogVLM/blob/main/utils/utils/template.py#L761C1-L761C17">corresponding prompt</a> or the examples below.' | |
default_chatbox = [("", "Hi, What do you want to know about this image?")] | |
URL = os.environ.get("URL") | |
def make_request(URL, headers, data): | |
response = requests.request("POST", URL, headers=headers, data=data, timeout=(60, 100)) | |
return response.json() | |
def post( | |
input_text, | |
temperature, | |
top_p, | |
top_k, | |
image_prompt, | |
result_previous, | |
hidden_image, | |
grounding, | |
cogagent, | |
grounding_template, | |
agent_template | |
): | |
result_text = [(ele[0], ele[1]) for ele in result_previous] | |
for i in range(len(result_text)-1, -1, -1): | |
if result_text[i][0] == "" or result_text[i][0] == None: | |
del result_text[i] | |
print(f"history {result_text}") | |
is_zh = is_chinese(input_text) | |
if image_prompt is None: | |
print("Image empty") | |
if is_zh: | |
result_text.append((input_text, '图片为空!请上传图片并重试。')) | |
else: | |
result_text.append((input_text, 'Image empty! Please upload a image and retry.')) | |
return input_text, result_text, hidden_image | |
elif input_text == "": | |
print("Text empty") | |
result_text.append((input_text, 'Text empty! Please enter text and retry.')) | |
return "", result_text, hidden_image | |
headers = { | |
"Content-Type": "application/json; charset=UTF-8", | |
"User-Agent": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.87 Safari/537.36", | |
} | |
if image_prompt: | |
pil_img, encoded_img, image_hash, image_path_grounding = process_image_without_resize(image_prompt) | |
print(f"image_hash:{image_hash}, hidden_image_hash:{hidden_image}") | |
if hidden_image is not None and image_hash != hidden_image: | |
print("image has been update") | |
result_text = [] | |
hidden_image = image_hash | |
else: | |
encoded_img = None | |
model_use = "vlm_chat" | |
if not cogagent and grounding: | |
model_use = "vlm_grounding" | |
if grounding_template: | |
input_text = postprocess_text(grounding_template, input_text) | |
elif cogagent: | |
model_use = "agent_chat" | |
if agent_template is not None and agent_template != "do not use template": | |
input_text = postprocess_text(agent_template, input_text) | |
prompt = input_text | |
if grounding: | |
prompt += "(with grounding)" | |
print(f'request {model_use} model... with prompt {prompt}, grounding_template {grounding_template}, agent_template {agent_template}') | |
data = json.dumps({ | |
'model_use': model_use, | |
'is_grounding': grounding, | |
'text': prompt, | |
'history': result_text, | |
'image': encoded_img, | |
'temperature': temperature, | |
'top_p': top_p, | |
'top_k': top_k, | |
'do_sample': True, | |
'max_new_tokens': 2048 | |
}) | |
try: | |
with ThreadPoolExecutor(max_workers=1) as executor: | |
future = executor.submit(make_request, URL, headers, data) | |
# time.sleep(15) | |
response = future.result() # Blocks until the request is complete | |
# response = requests.request("POST", URL, headers=headers, data=data, timeout=(60, 100)).json() | |
except Exception as e: | |
print("error message", e) | |
if is_zh: | |
result_text.append((input_text, '超时!请稍等几分钟再重试。')) | |
else: | |
result_text.append((input_text, 'Timeout! Please wait a few minutes and retry.')) | |
return "", result_text, hidden_image | |
print('request done...') | |
# response = {'result':input_text} | |
answer = str(response['result']) | |
if grounding: | |
parse_response(pil_img, answer, image_path_grounding) | |
new_answer = answer.replace(input_text, "") | |
result_text.append((input_text, new_answer)) | |
result_text.append((None, (image_path_grounding,))) | |
else: | |
result_text.append((input_text, answer)) | |
print(result_text) | |
print('finished') | |
return "", result_text, hidden_image | |
def clear_fn(value): | |
return "", default_chatbox, None | |
def clear_fn2(value): | |
return default_chatbox | |
def main(): | |
gr.close_all() | |
examples = [] | |
with open("./examples/example_inputs.jsonl") as f: | |
for line in f: | |
data = json.loads(line) | |
examples.append(data) | |
with gr.Blocks(css='style.css') as demo: | |
gr.Markdown(DESCRIPTION) | |
gr.Markdown(NOTES) | |
with gr.Row(): | |
with gr.Column(scale=4.5): | |
with gr.Group(): | |
input_text = gr.Textbox(label='Input Text', placeholder='Please enter text prompt below and press ENTER.') | |
with gr.Row(): | |
run_button = gr.Button('Generate') | |
clear_button = gr.Button('Clear') | |
image_prompt = gr.Image(type="filepath", label="Image Prompt", value=None) | |
with gr.Row(): | |
grounding = gr.Checkbox(label="Grounding") | |
cogagent = gr.Checkbox(label="CogAgent") | |
with gr.Row(): | |
# grounding_notice = gr.Markdown(GROUNDING_NOTICE) | |
grounding_template = gr.Dropdown(choices=template_grounding_cogvlm, label="Grounding Template", value=template_grounding_cogvlm[0]) | |
# agent_notice = gr.Markdown(AGENT_NOTICE) | |
agent_template = gr.Dropdown(choices=templates_agent_cogagent, label="Agent Template", value=templates_agent_cogagent[0]) | |
with gr.Row(): | |
temperature = gr.Slider(maximum=1, value=0.9, minimum=0, label='Temperature') | |
top_p = gr.Slider(maximum=1, value=0.8, minimum=0, label='Top P') | |
top_k = gr.Slider(maximum=50, value=5, minimum=1, step=1, label='Top K') | |
with gr.Column(scale=5.5): | |
result_text = gr.components.Chatbot(label='Multi-round conversation History', value=[("", "Hi, What do you want to know about this image?")], height=550) | |
hidden_image_hash = gr.Textbox(visible=False) | |
gr_examples = gr.Examples(examples=[[example["text"], example["image"], example["grounding"], example["cogagent"]] for example in examples], | |
inputs=[input_text, image_prompt, grounding, cogagent], | |
label="Example Inputs (Click to insert an examplet into the input box)", | |
examples_per_page=6) | |
gr.Markdown(MAINTENANCE_NOTICE1) | |
print(gr.__version__) | |
run_button.click(fn=post,inputs=[input_text, temperature, top_p, top_k, image_prompt, result_text, hidden_image_hash, grounding, cogagent, grounding_template, agent_template], | |
outputs=[input_text, result_text, hidden_image_hash]) | |
input_text.submit(fn=post,inputs=[input_text, temperature, top_p, top_k, image_prompt, result_text, hidden_image_hash, grounding, cogagent, grounding_template, agent_template], | |
outputs=[input_text, result_text, hidden_image_hash]) | |
clear_button.click(fn=clear_fn, inputs=clear_button, outputs=[input_text, result_text, image_prompt]) | |
image_prompt.upload(fn=clear_fn2, inputs=clear_button, outputs=[result_text]) | |
image_prompt.clear(fn=clear_fn2, inputs=clear_button, outputs=[result_text]) | |
print(gr.__version__) | |
demo.queue(concurrency_count=10) | |
demo.launch(server_port=7862) | |
if __name__ == '__main__': | |
main() |