gpt-academic / crazy_functions /图片生成.py
qingxu98's picture
version 3.6
17d0a32
from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicState
def gen_image(llm_kwargs, prompt, resolution="1024x1024", model="dall-e-2", quality=None):
import requests, json, time, os
from request_llms.bridge_all import model_info
proxies = get_conf('proxies')
# Set up OpenAI API key and model
api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
# 'https://api.openai.com/v1/chat/completions'
img_endpoint = chat_endpoint.replace('chat/completions','images/generations')
# # Generate the image
url = img_endpoint
headers = {
'Authorization': f"Bearer {api_key}",
'Content-Type': 'application/json'
}
data = {
'prompt': prompt,
'n': 1,
'size': resolution,
'model': model,
'response_format': 'url'
}
if quality is not None: data.update({'quality': quality})
response = requests.post(url, headers=headers, json=data, proxies=proxies)
print(response.content)
try:
image_url = json.loads(response.content.decode('utf8'))['data'][0]['url']
except:
raise RuntimeError(response.content.decode())
# 文件保存到本地
r = requests.get(image_url, proxies=proxies)
file_path = f'{get_log_folder()}/image_gen/'
os.makedirs(file_path, exist_ok=True)
file_name = 'Image' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.png'
with open(file_path+file_name, 'wb+') as f: f.write(r.content)
return image_url, file_path+file_name
def edit_image(llm_kwargs, prompt, image_path, resolution="1024x1024", model="dall-e-2"):
import requests, json, time, os
from request_llms.bridge_all import model_info
proxies = get_conf('proxies')
api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
# 'https://api.openai.com/v1/chat/completions'
img_endpoint = chat_endpoint.replace('chat/completions','images/edits')
# # Generate the image
url = img_endpoint
headers = {
'Authorization': f"Bearer {api_key}",
'Content-Type': 'application/json'
}
data = {
'image': open(image_path, 'rb'),
'prompt': prompt,
'n': 1,
'size': resolution,
'model': model,
'response_format': 'url'
}
response = requests.post(url, headers=headers, json=data, proxies=proxies)
print(response.content)
try:
image_url = json.loads(response.content.decode('utf8'))['data'][0]['url']
except:
raise RuntimeError(response.content.decode())
# 文件保存到本地
r = requests.get(image_url, proxies=proxies)
file_path = f'{get_log_folder()}/image_gen/'
os.makedirs(file_path, exist_ok=True)
file_name = 'Image' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.png'
with open(file_path+file_name, 'wb+') as f: f.write(r.content)
return image_url, file_path+file_name
@CatchException
def 图片生成_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
"""
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
llm_kwargs gpt模型参数,如温度和top_p等,一般原样传递下去就行
plugin_kwargs 插件模型的参数,暂时没有用武之地
chatbot 聊天显示框的句柄,用于显示给用户
history 聊天历史,前情提要
system_prompt 给gpt的静默提醒
web_port 当前软件运行的端口号
"""
history = [] # 清空历史,以免输入溢出
chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*或者api2d-*。如果中文Prompt效果不理想, 请尝试英文Prompt。正在处理中 ....."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 由于请求gpt需要一段时间,我们先及时地做一次界面更新
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
resolution = plugin_kwargs.get("advanced_arg", '1024x1024')
image_url, image_path = gen_image(llm_kwargs, prompt, resolution)
chatbot.append([prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
@CatchException
def 图片生成_DALLE3(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
history = [] # 清空历史,以免输入溢出
chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*或者api2d-*。如果中文Prompt效果不理想, 请尝试英文Prompt。正在处理中 ....."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 由于请求gpt需要一段时间,我们先及时地做一次界面更新
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
resolution = plugin_kwargs.get("advanced_arg", '1024x1024').lower()
if resolution.endswith('-hd'):
resolution = resolution.replace('-hd', '')
quality = 'hd'
else:
quality = 'standard'
image_url, image_path = gen_image(llm_kwargs, prompt, resolution, model="dall-e-3", quality=quality)
chatbot.append([prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
class ImageEditState(GptAcademicState):
# 尚未完成
def get_image_file(self, x):
import os, glob
if len(x) == 0: return False, None
if not os.path.exists(x): return False, None
if x.endswith('.png'): return True, x
file_manifest = [f for f in glob.glob(f'{x}/**/*.png', recursive=True)]
confirm = (len(file_manifest) >= 1 and file_manifest[0].endswith('.png') and os.path.exists(file_manifest[0]))
file = None if not confirm else file_manifest[0]
return confirm, file
def get_resolution(self, x):
return (x in ['256x256', '512x512', '1024x1024']), x
def get_prompt(self, x):
confirm = (len(x)>=5) and (not self.get_resolution(x)[0]) and (not self.get_image_file(x)[0])
return confirm, x
def reset(self):
self.req = [
{'value':None, 'description': '请先上传图像(必须是.png格式), 然后再次点击本插件', 'verify_fn': self.get_image_file},
{'value':None, 'description': '请输入分辨率,可选:256x256, 512x512 或 1024x1024', 'verify_fn': self.get_resolution},
{'value':None, 'description': '请输入修改需求,建议您使用英文提示词', 'verify_fn': self.get_prompt},
]
self.info = ""
def feed(self, prompt, chatbot):
for r in self.req:
if r['value'] is None:
confirm, res = r['verify_fn'](prompt)
if confirm:
r['value'] = res
self.set_state(chatbot, 'dummy_key', 'dummy_value')
break
return self
def next_req(self):
for r in self.req:
if r['value'] is None:
return r['description']
return "已经收集到所有信息"
def already_obtained_all_materials(self):
return all([x['value'] is not None for x in self.req])
@CatchException
def 图片修改_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
# 尚未完成
history = [] # 清空历史
state = ImageEditState.get_state(chatbot, ImageEditState)
state = state.feed(prompt, chatbot)
if not state.already_obtained_all_materials():
chatbot.append(["图片修改(先上传图片,再输入修改需求,最后输入分辨率)", state.next_req()])
yield from update_ui(chatbot=chatbot, history=history)
return
image_path = state.req[0]
resolution = state.req[1]
prompt = state.req[2]
chatbot.append(["图片修改, 执行中", f"图片:`{image_path}`<br/>分辨率:`{resolution}`<br/>修改需求:`{prompt}`"])
yield from update_ui(chatbot=chatbot, history=history)
image_url, image_path = edit_image(llm_kwargs, prompt, image_path, resolution)
chatbot.append([state.prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新