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version3.4
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master-int
| Author | SHA1 | Date | |
|---|---|---|---|
| c1680076fa | |||
| 0fc1a32b73 | |||
| 05376c1428 | |||
| bcbcfdc52c |
@ -70,7 +70,7 @@ MAX_RETRY = 2
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# 模型选择是 (注意: LLM_MODEL是默认选中的模型, 它*必须*被包含在AVAIL_LLM_MODELS列表中 )
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LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
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AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
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AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt35", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss", "newbing", "stack-claude"]
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# P.S. 其他可用的模型还包括 ["gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613", "newbing-free", "jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
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@ -109,10 +109,10 @@ SLACK_CLAUDE_USER_TOKEN = ''
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# 如果需要使用AZURE 详情请见额外文档 docs\use_azure.md
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AZURE_ENDPOINT = "https://你亲手写的api名称.openai.azure.com/"
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AZURE_ENDPOINT = "https://你的api名称.openai.azure.com/"
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AZURE_API_KEY = "填入azure openai api的密钥"
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AZURE_API_VERSION = "2023-05-15" # 一般不修改
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AZURE_ENGINE = "填入你亲手写的部署名" # 读 docs\use_azure.md
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AZURE_API_VERSION = "填入api版本"
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AZURE_ENGINE = "填入ENGINE"
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# 使用Newbing
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@ -353,6 +353,18 @@ def get_crazy_functions():
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except:
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print('Load function plugin failed')
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try:
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from crazy_functions.交互功能函数模板 import 交互功能模板函数
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function_plugins.update({
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"交互功能模板函数": {
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"Color": "stop",
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# "AsButton": False,
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"Function": HotReload(交互功能模板函数)
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}
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})
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except:
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print('Load function plugin failed')
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try:
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from crazy_functions.Latex输出PDF结果 import Latex英文纠错加PDF对比
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function_plugins.update({
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@ -130,11 +130,6 @@ def request_gpt_model_in_new_thread_with_ui_alive(
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yield from update_ui(chatbot=chatbot, history=[]) # 如果最后成功了,则删除报错信息
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return final_result
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def can_multi_process(llm):
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if llm.startswith('gpt-'): return True
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if llm.startswith('api2d-'): return True
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if llm.startswith('azure-'): return True
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return False
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def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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inputs_array, inputs_show_user_array, llm_kwargs,
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@ -180,7 +175,7 @@ def request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency(
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except: max_workers = 8
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if max_workers <= 0: max_workers = 3
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# 屏蔽掉 chatglm的多线程,可能会导致严重卡顿
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if not can_multi_process(llm_kwargs['llm_model']):
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if not (llm_kwargs['llm_model'].startswith('gpt-') or llm_kwargs['llm_model'].startswith('api2d-')):
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max_workers = 1
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executor = ThreadPoolExecutor(max_workers=max_workers)
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63
crazy_functions/交互功能函数模板.py
Normal file
63
crazy_functions/交互功能函数模板.py
Normal file
@ -0,0 +1,63 @@
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from toolbox import CatchException, update_ui
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from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
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@CatchException
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def 交互功能模板函数(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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"""
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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
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llm_kwargs gpt模型参数, 如温度和top_p等, 一般原样传递下去就行
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plugin_kwargs 插件模型的参数, 如温度和top_p等, 一般原样传递下去就行
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chatbot 聊天显示框的句柄,用于显示给用户
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history 聊天历史,前情提要
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system_prompt 给gpt的静默提醒
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web_port 当前软件运行的端口号
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"""
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history = [] # 清空历史,以免输入溢出
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chatbot.append(("这是什么功能?", "交互功能函数模板。在执行完成之后, 可以将自身的状态存储到cookie中, 等待用户的再次调用。"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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state = chatbot._cookies.get('plugin_state_0001', None) # 初始化插件状态
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if state is None:
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chatbot._cookies['lock_plugin'] = 'crazy_functions.交互功能函数模板->交互功能模板函数' # 赋予插件锁定 锁定插件回调路径,当下一次用户提交时,会直接转到该函数
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chatbot._cookies['plugin_state_0001'] = 'wait_user_keyword' # 赋予插件状态
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chatbot.append(("第一次调用:", "请输入关键词, 我将为您查找相关壁纸, 建议使用英文单词, 插件锁定中,请直接提交即可。"))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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if state == 'wait_user_keyword':
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chatbot._cookies['lock_plugin'] = None # 解除插件锁定,避免遗忘导致死锁
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chatbot._cookies['plugin_state_0001'] = None # 解除插件状态,避免遗忘导致死锁
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# 解除插件锁定
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chatbot.append((f"获取关键词:{txt}", ""))
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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page_return = get_image_page_by_keyword(txt)
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inputs=inputs_show_user=f"Extract all image urls in this html page, pick the first 5 images and show them with markdown format: \n\n {page_return}"
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gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
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inputs=inputs, inputs_show_user=inputs_show_user,
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llm_kwargs=llm_kwargs, chatbot=chatbot, history=[],
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sys_prompt="When you want to show an image, use markdown format. e.g. . If there are no image url provided, answer 'no image url provided'"
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)
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chatbot[-1] = [chatbot[-1][0], gpt_say]
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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# ---------------------------------------------------------------------------------
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def get_image_page_by_keyword(keyword):
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import requests
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from bs4 import BeautifulSoup
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response = requests.get(f'https://wallhaven.cc/search?q={keyword}', timeout=2)
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res = "image urls: \n"
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for image_element in BeautifulSoup(response.content, 'html.parser').findAll("img"):
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try:
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res += image_element["data-src"]
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res += "\n"
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except:
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pass
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return res
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@ -90,12 +90,11 @@
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到现在为止,申请操作就完成了,需要记下来的有下面几个东西:
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● 密钥(对应AZURE_API_KEY,1或2都可以)
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● 密钥(1或2都可以)
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● 终结点 (对应AZURE_ENDPOINT)
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● 部署名(对应AZURE_ENGINE,不是模型名)
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● 终结点
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● 部署名(不是模型名)
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# 修改 config.py
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@ -103,14 +102,50 @@
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AZURE_ENDPOINT = "填入终结点"
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AZURE_API_KEY = "填入azure openai api的密钥"
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AZURE_API_VERSION = "2023-05-15" # 默认使用 2023-05-15 版本,无需修改
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AZURE_ENGINE = "填入部署名" # 见上图
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AZURE_ENGINE = "填入部署名"
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```
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# API的使用
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接下来就是具体怎么使用API了,还是可以参考官方文档:[快速入门 - 开始通过 Azure OpenAI 服务使用 ChatGPT 和 GPT-4 - Azure OpenAI Service | Microsoft Learn](https://learn.microsoft.com/zh-cn/azure/cognitive-services/openai/chatgpt-quickstart?pivots=programming-language-python)
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和openai自己的api调用有点类似,都需要安装openai库,不同的是调用方式
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```
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import openai
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openai.api_type = "azure" #固定格式,无需修改
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openai.api_base = os.getenv("AZURE_OPENAI_ENDPOINT") #这里填入“终结点”
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openai.api_version = "2023-05-15" #固定格式,无需修改
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openai.api_key = os.getenv("AZURE_OPENAI_KEY") #这里填入“密钥1”或“密钥2”
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response = openai.ChatCompletion.create(
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engine="gpt-35-turbo", #这里填入的不是模型名,是部署名
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messages=[
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{"role": "system", "content": "You are a helpful assistant."},
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{"role": "user", "content": "Does Azure OpenAI support customer managed keys?"},
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{"role": "assistant", "content": "Yes, customer managed keys are supported by Azure OpenAI."},
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{"role": "user", "content": "Do other Azure Cognitive Services support this too?"}
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]
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)
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print(response)
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print(response['choices'][0]['message']['content'])
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```
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需要注意的是:
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1. engine那里填入的是部署名,不是模型名
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2. 通过openai库获得的这个 response 和通过 request 库访问 url 获得的 response 不同,不需要 decode,已经是解析好的 json 了,直接根据键值读取即可。
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更细节的使用方法,详见官方API文档。
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# 关于费用
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Azure OpenAI API 还是需要一些费用的(免费订阅只有1个月有效期)
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Azure OpenAI API 还是需要一些费用的(免费订阅只有1个月有效期),费用如下:
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具体可以可以看这个网址 :[Azure OpenAI 服务 - 定价| Microsoft Azure](https://azure.microsoft.com/zh-cn/pricing/details/cognitive-services/openai-service/?cdn=disable)
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25
main.py
25
main.py
@ -45,10 +45,10 @@ def main():
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proxy_info = check_proxy(proxies)
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gr_L1 = lambda: gr.Row().style()
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gr_L2 = lambda scale: gr.Column(scale=scale)
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gr_L2 = lambda scale, elem_id: gr.Column(scale=scale, elem_id=elem_id)
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if LAYOUT == "TOP-DOWN":
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gr_L1 = lambda: DummyWith()
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gr_L2 = lambda scale: gr.Row()
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gr_L2 = lambda scale, elem_id: gr.Row()
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CHATBOT_HEIGHT /= 2
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cancel_handles = []
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@ -56,12 +56,12 @@ def main():
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gr.HTML(title_html)
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cookies = gr.State({'api_key': API_KEY, 'llm_model': LLM_MODEL})
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with gr_L1():
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with gr_L2(scale=2):
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chatbot = gr.Chatbot(label=f"当前模型:{LLM_MODEL}")
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chatbot.style(height=CHATBOT_HEIGHT)
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with gr_L2(scale=2, elem_id="gpt-chat"):
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chatbot = gr.Chatbot(label=f"当前模型:{LLM_MODEL}", elem_id="gpt-chatbot")
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if LAYOUT == "TOP-DOWN": chatbot.style(height=CHATBOT_HEIGHT)
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history = gr.State([])
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with gr_L2(scale=1):
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with gr.Accordion("输入区", open=True) as area_input_primary:
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with gr_L2(scale=1, elem_id="gpt-panel"):
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with gr.Accordion("输入区", open=True, elem_id="input-panel") as area_input_primary:
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with gr.Row():
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txt = gr.Textbox(show_label=False, placeholder="Input question here.").style(container=False)
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with gr.Row():
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@ -71,14 +71,14 @@ def main():
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stopBtn = gr.Button("停止", variant="secondary"); stopBtn.style(size="sm")
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clearBtn = gr.Button("清除", variant="secondary", visible=False); clearBtn.style(size="sm")
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with gr.Row():
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status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}")
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with gr.Accordion("基础功能区", open=True) as area_basic_fn:
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status = gr.Markdown(f"Tip: 按Enter提交, 按Shift+Enter换行。当前模型: {LLM_MODEL} \n {proxy_info}", elem_id="state-panel")
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with gr.Accordion("基础功能区", open=True, elem_id="basic-panel") as area_basic_fn:
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with gr.Row():
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for k in functional:
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if ("Visible" in functional[k]) and (not functional[k]["Visible"]): continue
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variant = functional[k]["Color"] if "Color" in functional[k] else "secondary"
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functional[k]["Button"] = gr.Button(k, variant=variant)
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with gr.Accordion("函数插件区", open=True) as area_crazy_fn:
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with gr.Accordion("函数插件区", open=True, elem_id="plugin-panel") as area_crazy_fn:
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with gr.Row():
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gr.Markdown("注意:以下“红颜色”标识的函数插件需从输入区读取路径作为参数.")
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with gr.Row():
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@ -100,7 +100,7 @@ def main():
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with gr.Row():
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with gr.Accordion("点击展开“文件上传区”。上传本地文件可供红色函数插件调用。", open=False) as area_file_up:
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file_upload = gr.Files(label="任何文件, 但推荐上传压缩文件(zip, tar)", file_count="multiple")
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with gr.Accordion("更换模型 & SysPrompt & 交互界面布局", open=(LAYOUT == "TOP-DOWN")):
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with gr.Accordion("更换模型 & SysPrompt & 交互界面布局", open=(LAYOUT == "TOP-DOWN"), elem_id="interact-panel"):
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system_prompt = gr.Textbox(show_label=True, placeholder=f"System Prompt", label="System prompt", value=initial_prompt)
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top_p = gr.Slider(minimum=-0, maximum=1.0, value=1.0, step=0.01,interactive=True, label="Top-p (nucleus sampling)",)
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temperature = gr.Slider(minimum=-0, maximum=2.0, value=1.0, step=0.01, interactive=True, label="Temperature",)
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@ -109,7 +109,7 @@ def main():
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md_dropdown = gr.Dropdown(AVAIL_LLM_MODELS, value=LLM_MODEL, label="更换LLM模型/请求源").style(container=False)
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gr.Markdown(description)
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with gr.Accordion("备选输入区", open=True, visible=False) as area_input_secondary:
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with gr.Accordion("备选输入区", open=True, visible=False, elem_id="input-panel2") as area_input_secondary:
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with gr.Row():
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txt2 = gr.Textbox(show_label=False, placeholder="Input question here.", label="输入区2").style(container=False)
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with gr.Row():
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@ -185,6 +185,7 @@ def main():
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# 终止按钮的回调函数注册
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stopBtn.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
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stopBtn2.click(fn=None, inputs=None, outputs=None, cancels=cancel_handles)
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demo.load(lambda: 0, inputs=None, outputs=None, _js='()=>{ChatBotHeight();}')
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# gradio的inbrowser触发不太稳定,回滚代码到原始的浏览器打开函数
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def auto_opentab_delay():
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@ -121,7 +121,7 @@ model_info = {
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},
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||||
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# azure openai
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"azure-gpt-3.5":{
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"azure-gpt35":{
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"fn_with_ui": azure_ui,
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"fn_without_ui": azure_noui,
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"endpoint": get_conf("AZURE_ENDPOINT"),
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@ -14,8 +14,7 @@ import traceback
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import importlib
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import openai
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import time
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import requests
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import json
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||||
|
||||
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||||
# 读取config.py文件中关于AZURE OPENAI API的信息
|
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from toolbox import get_conf, update_ui, clip_history, trimmed_format_exc
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@ -44,6 +43,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
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chatbot 为WebUI中显示的对话列表,修改它,然后yeild出去,可以直接修改对话界面内容
|
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additional_fn代表点击的哪个按钮,按钮见functional.py
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"""
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print(llm_kwargs["llm_model"])
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||||
|
||||
if additional_fn is not None:
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import core_functional
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@ -57,6 +57,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
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chatbot.append((inputs, ""))
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yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
|
||||
|
||||
|
||||
payload = generate_azure_payload(inputs, llm_kwargs, history, system_prompt, stream)
|
||||
|
||||
history.append(inputs); history.append("")
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||||
@ -64,21 +65,19 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
|
||||
retry = 0
|
||||
while True:
|
||||
try:
|
||||
|
||||
openai.api_type = "azure"
|
||||
openai.api_version = AZURE_API_VERSION
|
||||
openai.api_base = AZURE_ENDPOINT
|
||||
openai.api_key = AZURE_API_KEY
|
||||
response = openai.ChatCompletion.create(timeout=TIMEOUT_SECONDS, **payload);break
|
||||
except openai.error.AuthenticationError:
|
||||
tb_str = '```\n' + trimmed_format_exc() + '```'
|
||||
chatbot[-1] = [chatbot[-1][0], tb_str]
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg="openai返回错误") # 刷新界面
|
||||
return
|
||||
|
||||
except:
|
||||
retry += 1
|
||||
traceback.print_exc()
|
||||
chatbot[-1] = ((chatbot[-1][0], "获取response失败,重试中。。。"))
|
||||
retry_msg = f",正在重试 ({retry}/{MAX_RETRY}) ……" if MAX_RETRY > 0 else ""
|
||||
yield from update_ui(chatbot=chatbot, history=history, msg="请求超时"+retry_msg) # 刷新界面
|
||||
if retry > MAX_RETRY: raise TimeoutError
|
||||
if MAX_RETRY!=0: print(f'请求超时,正在重试 ({retry}/{MAX_RETRY}) ……')
|
||||
|
||||
gpt_replying_buffer = ""
|
||||
is_head_of_the_stream = True
|
||||
@ -142,18 +141,21 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
|
||||
payload = generate_azure_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=True)
|
||||
retry = 0
|
||||
while True:
|
||||
|
||||
try:
|
||||
openai.api_type = "azure"
|
||||
openai.api_version = AZURE_API_VERSION
|
||||
openai.api_base = AZURE_ENDPOINT
|
||||
openai.api_key = AZURE_API_KEY
|
||||
response = openai.ChatCompletion.create(timeout=TIMEOUT_SECONDS, **payload);break
|
||||
|
||||
except:
|
||||
retry += 1
|
||||
traceback.print_exc()
|
||||
if retry > MAX_RETRY: raise TimeoutError
|
||||
if MAX_RETRY!=0: print(f'请求超时,正在重试 ({retry}/{MAX_RETRY}) ……')
|
||||
|
||||
|
||||
stream_response = response
|
||||
result = ''
|
||||
while True:
|
||||
@ -162,14 +164,19 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
|
||||
break
|
||||
except:
|
||||
chunk = next(stream_response) # 失败了,重试一次?再失败就没办法了。
|
||||
if len(chunk)==0: continue
|
||||
|
||||
json_data = json.loads(str(chunk))['choices'][0]
|
||||
delta = json_data["delta"]
|
||||
if len(delta) == 0:
|
||||
break
|
||||
if "role" in delta:
|
||||
continue
|
||||
if len(chunk)==0: continue
|
||||
if not chunk.startswith('data:'):
|
||||
error_msg = get_full_error(chunk, stream_response)
|
||||
if "reduce the length" in error_msg:
|
||||
raise ConnectionAbortedError("AZURE OPENAI API拒绝了请求:" + error_msg)
|
||||
else:
|
||||
raise RuntimeError("AZURE OPENAI API拒绝了请求:" + error_msg)
|
||||
if ('data: [DONE]' in chunk): break
|
||||
|
||||
delta = chunk["delta"]
|
||||
if len(delta) == 0: break
|
||||
if "role" in delta: continue
|
||||
if "content" in delta:
|
||||
result += delta["content"]
|
||||
if not console_slience: print(delta["content"], end='')
|
||||
@ -177,14 +184,11 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
|
||||
# 观测窗,把已经获取的数据显示出去
|
||||
if len(observe_window) >= 1: observe_window[0] += delta["content"]
|
||||
# 看门狗,如果超过期限没有喂狗,则终止
|
||||
if len(observe_window) >= 2000:
|
||||
if len(observe_window) >= 2:
|
||||
if (time.time()-observe_window[1]) > watch_dog_patience:
|
||||
raise RuntimeError("用户取消了程序。")
|
||||
else:
|
||||
raise RuntimeError("意外Json结构:"+delta)
|
||||
if json_data['finish_reason'] == 'content_filter':
|
||||
raise RuntimeError("由于提问含不合规内容被Azure过滤。")
|
||||
if json_data['finish_reason'] == 'length':
|
||||
else: raise RuntimeError("意外Json结构:"+delta)
|
||||
if chunk['finish_reason'] == 'length':
|
||||
raise ConnectionAbortedError("正常结束,但显示Token不足,导致输出不完整,请削减单次输入的文本量。")
|
||||
return result
|
||||
|
||||
|
||||
57
theme.py
57
theme.py
@ -1,6 +1,6 @@
|
||||
import gradio as gr
|
||||
from toolbox import get_conf
|
||||
CODE_HIGHLIGHT, ADD_WAIFU = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU')
|
||||
CODE_HIGHLIGHT, ADD_WAIFU, LAYOUT = get_conf('CODE_HIGHLIGHT', 'ADD_WAIFU', 'LAYOUT')
|
||||
# gradio可用颜色列表
|
||||
# gr.themes.utils.colors.slate (石板色)
|
||||
# gr.themes.utils.colors.gray (灰色)
|
||||
@ -82,9 +82,62 @@ def adjust_theme():
|
||||
button_cancel_text_color_dark="white",
|
||||
)
|
||||
|
||||
# Layout = "LEFT-RIGHT"
|
||||
js = """
|
||||
<script>
|
||||
function ChatBotHeight() {
|
||||
function update_height(){
|
||||
var { panel_height_target, chatbot_height, chatbot } = get_elements();
|
||||
if (panel_height_target!=chatbot_height)
|
||||
{
|
||||
var pixelString = panel_height_target.toString() + 'px';
|
||||
chatbot.style.maxHeight = pixelString; chatbot.style.height = pixelString;
|
||||
}
|
||||
}
|
||||
|
||||
function update_height_slow(){
|
||||
var { panel_height_target, chatbot_height, chatbot } = get_elements();
|
||||
if (panel_height_target!=chatbot_height)
|
||||
{
|
||||
new_panel_height = (panel_height_target - chatbot_height)*0.5 + chatbot_height;
|
||||
if (Math.abs(new_panel_height - panel_height_target) < 10){
|
||||
new_panel_height = panel_height_target;
|
||||
}
|
||||
console.log(chatbot_height, panel_height_target, new_panel_height);
|
||||
var pixelString = new_panel_height.toString() + 'px';
|
||||
chatbot.style.maxHeight = pixelString; chatbot.style.height = pixelString;
|
||||
}
|
||||
}
|
||||
|
||||
update_height();
|
||||
setInterval(function() {
|
||||
update_height_slow()
|
||||
}, 50); // 每100毫秒执行一次
|
||||
}
|
||||
|
||||
function get_elements() {
|
||||
const chatbot = document.querySelector('#gpt-chatbot > div.wrap.svelte-18telvq');
|
||||
const panel1 = document.querySelector('#input-panel');
|
||||
const panel2 = document.querySelector('#basic-panel');
|
||||
const panel3 = document.querySelector('#plugin-panel');
|
||||
const panel4 = document.querySelector('#interact-panel');
|
||||
const panel5 = document.querySelector('#input-panel2');
|
||||
const panel_active = document.querySelector('#state-panel');
|
||||
var panel_height_target = (20-panel_active.offsetHeight) + panel1.offsetHeight + panel2.offsetHeight + panel3.offsetHeight + panel4.offsetHeight + panel5.offsetHeight + 21;
|
||||
var panel_height_target = parseInt(panel_height_target);
|
||||
var chatbot_height = chatbot.style.height;
|
||||
var chatbot_height = parseInt(chatbot_height);
|
||||
return { panel_height_target, chatbot_height, chatbot };
|
||||
}
|
||||
</script>
|
||||
"""
|
||||
|
||||
if LAYOUT=="TOP-DOWN":
|
||||
js = ""
|
||||
|
||||
# 添加一个萌萌的看板娘
|
||||
if ADD_WAIFU:
|
||||
js = """
|
||||
js += """
|
||||
<script src="file=docs/waifu_plugin/jquery.min.js"></script>
|
||||
<script src="file=docs/waifu_plugin/jquery-ui.min.js"></script>
|
||||
<script src="file=docs/waifu_plugin/autoload.js"></script>
|
||||
|
||||
35
toolbox.py
35
toolbox.py
@ -4,6 +4,7 @@ import time
|
||||
import inspect
|
||||
import re
|
||||
import os
|
||||
import gradio
|
||||
from latex2mathml.converter import convert as tex2mathml
|
||||
from functools import wraps, lru_cache
|
||||
pj = os.path.join
|
||||
@ -35,17 +36,19 @@ class ChatBotWithCookies(list):
|
||||
def get_cookies(self):
|
||||
return self._cookies
|
||||
|
||||
black_list = ['127.0.0.1']
|
||||
|
||||
def ArgsGeneralWrapper(f):
|
||||
"""
|
||||
装饰器函数,用于重组输入参数,改变输入参数的顺序与结构。
|
||||
"""
|
||||
def decorated(cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg, *args):
|
||||
def decorated(request: gradio.Request, cookies, max_length, llm_model, txt, txt2, top_p, temperature, chatbot, history, system_prompt, plugin_advanced_arg, *args):
|
||||
txt_passon = txt
|
||||
if txt == "" and txt2 != "": txt_passon = txt2
|
||||
# 引入一个有cookie的chatbot
|
||||
cookies.update({
|
||||
'top_p':top_p,
|
||||
'llm_model': llm_model,
|
||||
'temperature':temperature,
|
||||
})
|
||||
llm_kwargs = {
|
||||
@ -54,13 +57,25 @@ def ArgsGeneralWrapper(f):
|
||||
'top_p':top_p,
|
||||
'max_length': max_length,
|
||||
'temperature':temperature,
|
||||
'client_ip': request.client.host,
|
||||
}
|
||||
plugin_kwargs = {
|
||||
"advanced_arg": plugin_advanced_arg,
|
||||
}
|
||||
chatbot_with_cookie = ChatBotWithCookies(cookies)
|
||||
chatbot_with_cookie.write_list(chatbot)
|
||||
if llm_kwargs['client_ip'] in black_list:
|
||||
chatbot_with_cookie.append(['IP已封禁, 当前IP黑名单' + str(black_list), 'IP已封禁:' + llm_kwargs['client_ip']])
|
||||
yield from update_ui(chatbot_with_cookie, history, msg='IP已封禁')
|
||||
return # 结束
|
||||
if cookies.get('lock_plugin', None) is None:
|
||||
# 正常状态
|
||||
yield from f(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
else:
|
||||
# 处理个别特殊插件的锁定状态
|
||||
module, fn_name = cookies['lock_plugin'].split('->')
|
||||
f_hot_reload = getattr(importlib.import_module(module, fn_name), fn_name)
|
||||
yield from f_hot_reload(txt_passon, llm_kwargs, plugin_kwargs, chatbot_with_cookie, history, system_prompt, *args)
|
||||
return decorated
|
||||
|
||||
|
||||
@ -68,8 +83,22 @@ def update_ui(chatbot, history, msg='正常', **kwargs): # 刷新界面
|
||||
"""
|
||||
刷新用户界面
|
||||
"""
|
||||
assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时,可用clear将其清空,然后用for+append循环重新赋值。"
|
||||
yield chatbot.get_cookies(), chatbot, history, msg
|
||||
assert isinstance(chatbot, ChatBotWithCookies), "在传递chatbot的过程中不要将其丢弃。必要时, 可用clear将其清空, 然后用for+append循环重新赋值。"
|
||||
|
||||
cookies = chatbot.get_cookies()
|
||||
|
||||
# 解决插件锁定时的界面显示问题
|
||||
if cookies.get('lock_plugin', None):
|
||||
label = cookies.get('llm_model', "") + " | " + "正在锁定插件" + cookies.get('lock_plugin', None)
|
||||
chatbot_gr = gradio.update(value=chatbot, label=label)
|
||||
if cookies.get('label', "") != label: cookies['label'] = label # 记住当前的label
|
||||
elif cookies.get('label', None):
|
||||
chatbot_gr = gradio.update(value=chatbot, label=cookies.get('llm_model', ""))
|
||||
cookies['label'] = None # 清空label
|
||||
else:
|
||||
chatbot_gr = chatbot
|
||||
|
||||
yield cookies, chatbot_gr, history, msg
|
||||
|
||||
def update_ui_lastest_msg(lastmsg, chatbot, history, delay=1): # 刷新界面
|
||||
"""
|
||||
|
||||
4
version
4
version
@ -1,5 +1,5 @@
|
||||
{
|
||||
"version": 3.43,
|
||||
"version": 3.42,
|
||||
"show_feature": true,
|
||||
"new_feature": "修复Azure接口的BUG <-> 完善多语言模块 <-> 完善本地Latex矫错和翻译功能 <-> 增加gpt-3.5-16k的支持 <-> 新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件"
|
||||
"new_feature": "完善本地Latex矫错和翻译功能 <-> 增加gpt-3.5-16k的支持 <-> 新增最强Arxiv论文翻译插件 <-> 修复gradio复制按钮BUG <-> 修复PDF翻译的BUG, 新增HTML中英双栏对照 <-> 添加了OpenAI图片生成插件 <-> 添加了OpenAI音频转文本总结插件 <-> 通过Slack添加对Claude的支持"
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user