Spaces:
Sleeping
Sleeping
File size: 12,107 Bytes
e9ce3e8 abd44d6 e9ce3e8 abd44d6 e9ce3e8 abd44d6 e9ce3e8 088861c abd44d6 c1d41a3 e9ce3e8 c1d41a3 e9ce3e8 c1d41a3 abd44d6 e9ce3e8 c1d41a3 e9ce3e8 abd44d6 e9ce3e8 abd44d6 e9ce3e8 abd44d6 e9ce3e8 abd44d6 e9ce3e8 abd44d6 e9ce3e8 abd44d6 e9ce3e8 c32abaf e9ce3e8 7d472a0 e9ce3e8 799ae41 e9ce3e8 abd44d6 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 |
# import gradio as gr
# import json, os
# import urllib.request
# # Replace 'YOUR_API_KEY' with your actual YouTube Data API key
# API_KEY = os.getenv('api_key')
# def get_youtube_id(youtube_url):
# if 'youtube.com' in youtube_url:
# video_id = youtube_url.split('v=')[-1]
# elif 'youtu.be' in youtube_url:
# video_id = youtube_url.split('/')[-1].split('?')[0]
# return video_id
# def check_cc_license(youtube_url):
# # Extract video ID from the URL
# video_id = get_youtube_id(youtube_url)
# # YouTube Data API URL to get video details
# api_url = f'https://www.googleapis.com/youtube/v3/videos?id={video_id}&part=status&key={API_KEY}'
# try:
# # Fetch video details
# response = urllib.request.urlopen(api_url)
# data = json.load(response)
# # Check the license status
# for item in data['items']:
# if item['status']['license'] == 'creativeCommon':
# return f"Yes."
# else:
# return f"No."
# except Exception as e:
# return f"An error occurred: {str(e)}"
# # Gradio interface
# interface = gr.Interface(
# fn=check_cc_license,
# inputs=gr.Textbox(label="YouTube Video URL"),
# outputs=gr.Textbox(label="Creative Commons license?")
# )
# if __name__ == "__main__":
# interface.launch()
# import gradio as gr
# import asyncio
# import os
# from openai import AsyncOpenAI
# # 从您的模块中导入必要的函数
# from utils.generate_distractors import prepare_q_inputs, construct_prompt_textonly, generate_distractors
# from utils.api_utils import generate_from_openai_chat_completion
# # 修改generate_distractors函数,使其成为异步函数
# # 假设generate_distractors函数定义在您的模块中,我们需要修改它
# # 如果无法修改原始模块,请在此处重新定义
# async def generate_distractors_async(model_name: str,
# queries: list,
# n: int=1,
# max_tokens: int=4096):
# assert model_name in ["gpt-4o-mini", "gpt-4-turbo", "gpt-4o", "gpt-4o-2024-08-06"], "Invalid model name"
# client = AsyncOpenAI(api_key=os.environ.get("OPENAI_API_KEY"), base_url="https://yanlp.zeabur.app/v1")
# messages = prepare_q_inputs(queries)
# # 直接等待协程而不是使用asyncio.run()
# responses = await generate_from_openai_chat_completion(
# client,
# messages=messages,
# engine_name=model_name,
# n=n,
# max_tokens=max_tokens,
# requests_per_minute=30,
# json_format=True
# )
# for query, response in zip(queries, responses):
# new_options = response
# if new_options and "distractors" in new_options:
# query["option_5"] = new_options["distractors"].get("E", "")
# query["option_6"] = new_options["distractors"].get("F", "")
# query["option_7"] = new_options["distractors"].get("G", "")
# query["distractor_analysis"] = new_options["distractors"].get("analysis_of_distractors", "")
# else:
# query["option_5"] = ""
# query["option_6"] = ""
# query["option_7"] = ""
# query["distractor_analysis"] = ""
# return queries
# # 定义异步处理函数
# async def generate_distractors_gradio(question, option1, option2, option3, option4, answer, answer_analysis):
# query = {
# 'question': question,
# 'option_1': option1,
# 'option_2': option2,
# 'option_3': option3,
# 'option_4': option4,
# 'answer': answer,
# 'answer_analysis': answer_analysis
# }
# queries = [query] # 因为函数期望的是一个列表
# # 调用异步生成干扰项的函数
# results = await generate_distractors_async(
# model_name="gpt-4o-mini",
# queries=queries,
# n=1,
# max_tokens=4096
# )
# # 提取结果
# result = results[0]
# new_options = {
# 'E': result.get('option_5', ''),
# 'F': result.get('option_6', ''),
# 'G': result.get('option_7', '')
# }
# distractor_analysis = result.get('distractor_analysis', '')
# # 返回新的干扰项和分析
# return new_options, distractor_analysis
# # 创建Gradio界面
# with gr.Blocks() as demo:
# gr.Markdown("# 多项选择题干扰项生成器")
# with gr.Row():
# question_input = gr.Textbox(label="问题", lines=2)
# with gr.Row():
# option1_input = gr.Textbox(label="选项A")
# option2_input = gr.Textbox(label="选项B")
# with gr.Row():
# option3_input = gr.Textbox(label="选项C")
# option4_input = gr.Textbox(label="选项D")
# with gr.Row():
# answer_input = gr.Textbox(label="正确答案")
# with gr.Row():
# answer_analysis_input = gr.Textbox(label="答案解析", lines=3)
# with gr.Row():
# generate_button = gr.Button("生成干扰项")
# with gr.Row():
# output_options = gr.JSON(label="生成的干扰选项")
# with gr.Row():
# output_analysis = gr.Textbox(label="干扰项解析", lines=5)
# # 定义按钮点击事件,注意这里不需要修改,Gradio会自动处理异步函数
# generate_button.click(
# fn=generate_distractors_gradio,
# inputs=[question_input, option1_input, option2_input, option3_input, option4_input, answer_input, answer_analysis_input],
# outputs=[output_options, output_analysis]
# )
# # 运行Gradio应用
# demo.launch()
import gradio as gr
import asyncio
import os
import json
import urllib.request
from openai import AsyncOpenAI
# 第一个功能:检查YouTube视频是否具有Creative Commons许可证
# 请确保在环境变量中设置了您的YouTube Data API密钥
API_KEY = "AIzaSyDyPpkFRUpUuSMQbhxwTFxCBLK5qTHU-ms"
os.environ["OPENAI_API_KEY"] = "sk-h8rybT55JORrT40y2397A06c8f2444F8Ad49407fE85eBf76"
def get_youtube_id(youtube_url):
if 'youtube.com' in youtube_url:
video_id = youtube_url.split('v=')[-1]
video_id = video_id.split('&')[0] # 移除可能的额外参数
elif 'youtu.be' in youtube_url:
video_id = youtube_url.split('/')[-1].split('?')[0]
else:
video_id = ''
return video_id
def check_cc_license(youtube_url):
# 从URL中提取视频ID
video_id = get_youtube_id(youtube_url)
if not video_id:
return "Invalid YouTube URL."
# YouTube Data API URL,用于获取视频详情
api_url = f'https://www.googleapis.com/youtube/v3/videos?id={video_id}&part=status&key={API_KEY}'
try:
# 获取视频详情
response = urllib.request.urlopen(api_url)
data = json.load(response)
# 检查许可证状态
if 'items' in data and len(data['items']) > 0:
item = data['items'][0]
if item['status']['license'] == 'creativeCommon':
return "Yes."
else:
return "No."
else:
return "Video not found."
except Exception as e:
return f"An error occurred: {str(e)}"
# 第二个功能:为多项选择题生成干扰项
# 从您的模块中导入必要的函数
from utils.generate_distractors import prepare_q_inputs, construct_prompt_textonly, generate_distractors
from utils.api_utils import generate_from_openai_chat_completion
# 修改generate_distractors函数,使其成为异步函数
# 假设generate_distractors函数定义在您的模块中,我们需要修改它
# 如果无法修改原始模块,请在此处重新定义
async def generate_distractors_async(model_name: str,
queries: list,
n: int=1,
max_tokens: int=4096):
assert model_name in ["gpt-4o-mini", "gpt-4-turbo", "gpt-4o", "gpt-4o-2024-08-06"], "Invalid model name"
client = AsyncOpenAI(api_key=os.environ.get("OPENAI_API_KEY"), base_url="https://yanlp.zeabur.app/v1")
messages = prepare_q_inputs(queries)
# 直接等待协程而不是使用asyncio.run()
responses = await generate_from_openai_chat_completion(
client,
messages=messages,
engine_name=model_name,
n=n,
max_tokens=max_tokens,
requests_per_minute=30,
json_format=True
)
for query, response in zip(queries, responses):
new_options = response
if new_options and "distractors" in new_options:
query["option_5"] = new_options["distractors"].get("E", "")
query["option_6"] = new_options["distractors"].get("F", "")
query["option_7"] = new_options["distractors"].get("G", "")
query["distractor_analysis"] = new_options["distractors"].get("analysis_of_distractors", "")
else:
query["option_5"] = ""
query["option_6"] = ""
query["option_7"] = ""
query["distractor_analysis"] = ""
return queries
# 定义异步处理函数
async def generate_distractors_gradio(question, option1, option2, option3, option4, answer, answer_analysis):
query = {
'question': question,
'option_1': option1,
'option_2': option2,
'option_3': option3,
'option_4': option4,
'answer': answer,
'answer_analysis': answer_analysis
}
queries = [query] # 因为函数期望的是一个列表
# 调用异步生成干扰项的函数
results = await generate_distractors_async(
model_name="gpt-4o-mini",
queries=queries,
n=1,
max_tokens=4096
)
# 提取结果
result = results[0]
new_options = {
'E': result.get('option_5', ''),
'F': result.get('option_6', ''),
'G': result.get('option_7', '')
}
distractor_analysis = result.get('distractor_analysis', '')
# 返回新的干扰项和分析
return new_options, distractor_analysis
with gr.Blocks() as demo:
gr.Markdown("# CC检查器和干扰项生成器")
with gr.Tabs():
with gr.TabItem("YouTube Creative Commons检查器"):
gr.Markdown("## 检查YouTube视频是否具有Creative Commons许可证")
youtube_url_input = gr.Textbox(label="YouTube视频URL")
cc_license_output = gr.Textbox(label="是否为Creative Commons许可证?")
check_button = gr.Button("检查许可证")
check_button.click(
fn=check_cc_license,
inputs=youtube_url_input,
outputs=cc_license_output
)
with gr.TabItem("多项选择题干扰项生成器"):
gr.Markdown("## 为多项选择题生成干扰项")
with gr.Row():
question_input = gr.Textbox(label="问题", lines=2)
with gr.Row():
option1_input = gr.Textbox(label="选项A")
option2_input = gr.Textbox(label="选项B")
with gr.Row():
option3_input = gr.Textbox(label="选项C")
option4_input = gr.Textbox(label="选项D(可以输入也可以不输入)")
with gr.Row():
answer_input = gr.Textbox(label="正确答案(A/B/C/D)")
with gr.Row():
answer_analysis_input = gr.Textbox(label="答案解析", lines=3)
generate_button = gr.Button("生成干扰项")
output_options = gr.JSON(label="生成的干扰选项")
output_analysis = gr.Textbox(label="干扰项解析", lines=5)
generate_button.click(
fn=generate_distractors_gradio,
inputs=[question_input, option1_input, option2_input, option3_input, option4_input, answer_input, answer_analysis_input],
outputs=[output_options, output_analysis]
)
# 运行Gradio应用
demo.launch()
|