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Update app.py
Browse files
app.py
CHANGED
@@ -1,166 +1,3 @@
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# import gradio as gr
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# import json, os
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# import urllib.request
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# # Replace 'YOUR_API_KEY' with your actual YouTube Data API key
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# API_KEY = os.getenv('api_key')
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# def get_youtube_id(youtube_url):
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# if 'youtube.com' in youtube_url:
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# video_id = youtube_url.split('v=')[-1]
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# elif 'youtu.be' in youtube_url:
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# video_id = youtube_url.split('/')[-1].split('?')[0]
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# return video_id
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# def check_cc_license(youtube_url):
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# # Extract video ID from the URL
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# video_id = get_youtube_id(youtube_url)
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# # YouTube Data API URL to get video details
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# api_url = f'https://www.googleapis.com/youtube/v3/videos?id={video_id}&part=status&key={API_KEY}'
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# try:
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# # Fetch video details
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# response = urllib.request.urlopen(api_url)
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# data = json.load(response)
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# # Check the license status
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# for item in data['items']:
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# if item['status']['license'] == 'creativeCommon':
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# return f"Yes."
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# else:
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# return f"No."
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# except Exception as e:
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# return f"An error occurred: {str(e)}"
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# # Gradio interface
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# interface = gr.Interface(
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# fn=check_cc_license,
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# inputs=gr.Textbox(label="YouTube Video URL"),
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# outputs=gr.Textbox(label="Creative Commons license?")
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# )
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# if __name__ == "__main__":
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# interface.launch()
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# import gradio as gr
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# import asyncio
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# import os
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# from openai import AsyncOpenAI
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# # 从您的模块中导入必要的函数
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# from utils.generate_distractors import prepare_q_inputs, construct_prompt_textonly, generate_distractors
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# from utils.api_utils import generate_from_openai_chat_completion
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# # 修改generate_distractors函数,使其成为异步函数
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# # 假设generate_distractors函数定义在您的模块中,我们需要修改它
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# # 如果无法修改原始模块,请在此处重新定义
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# async def generate_distractors_async(model_name: str,
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# queries: list,
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# n: int=1,
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# max_tokens: int=4096):
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# assert model_name in ["gpt-4o-mini", "gpt-4-turbo", "gpt-4o", "gpt-4o-2024-08-06"], "Invalid model name"
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# client = AsyncOpenAI(api_key=os.environ.get("OPENAI_API_KEY"), base_url="https://yanlp.zeabur.app/v1")
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# messages = prepare_q_inputs(queries)
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# # 直接等待协程而不是使用asyncio.run()
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# responses = await generate_from_openai_chat_completion(
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# client,
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# messages=messages,
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# engine_name=model_name,
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# n=n,
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# max_tokens=max_tokens,
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# requests_per_minute=30,
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# json_format=True
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# )
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# for query, response in zip(queries, responses):
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# new_options = response
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# if new_options and "distractors" in new_options:
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# query["option_5"] = new_options["distractors"].get("E", "")
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# query["option_6"] = new_options["distractors"].get("F", "")
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# query["option_7"] = new_options["distractors"].get("G", "")
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# query["distractor_analysis"] = new_options["distractors"].get("analysis_of_distractors", "")
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# else:
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# query["option_5"] = ""
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# query["option_6"] = ""
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# query["option_7"] = ""
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# query["distractor_analysis"] = ""
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# return queries
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# # 定义异步处理函数
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# async def generate_distractors_gradio(question, option1, option2, option3, option4, answer, answer_analysis):
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# query = {
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# 'question': question,
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# 'option_1': option1,
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# 'option_2': option2,
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# 'option_3': option3,
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# 'option_4': option4,
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# 'answer': answer,
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# 'answer_analysis': answer_analysis
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# }
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# queries = [query] # 因为函数期望的是一个列表
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# # 调用异步生成干扰项的函数
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# results = await generate_distractors_async(
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# model_name="gpt-4o-mini",
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# queries=queries,
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# n=1,
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# max_tokens=4096
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# )
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# # 提取结果
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# result = results[0]
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# new_options = {
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# 'E': result.get('option_5', ''),
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# 'F': result.get('option_6', ''),
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# 'G': result.get('option_7', '')
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# }
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# distractor_analysis = result.get('distractor_analysis', '')
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# # 返回新的干扰项和分析
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# return new_options, distractor_analysis
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# # 创建Gradio界面
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# with gr.Blocks() as demo:
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# gr.Markdown("# 多项选择题干扰项生成器")
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# with gr.Row():
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# question_input = gr.Textbox(label="问题", lines=2)
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# with gr.Row():
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# option1_input = gr.Textbox(label="选项A")
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# option2_input = gr.Textbox(label="选项B")
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# with gr.Row():
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# option3_input = gr.Textbox(label="选项C")
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# option4_input = gr.Textbox(label="选项D")
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# with gr.Row():
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# answer_input = gr.Textbox(label="正确答案")
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# with gr.Row():
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# answer_analysis_input = gr.Textbox(label="答案解析", lines=3)
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# with gr.Row():
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# generate_button = gr.Button("生成干扰项")
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# with gr.Row():
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# output_options = gr.JSON(label="生成的干扰选项")
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# with gr.Row():
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# output_analysis = gr.Textbox(label="干扰项解析", lines=5)
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# # 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
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# generate_button.click(
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# fn=generate_distractors_gradio,
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# inputs=[question_input, option1_input, option2_input, option3_input, option4_input, answer_input, answer_analysis_input],
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# outputs=[output_options, output_analysis]
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# )
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# # 运行Gradio应用
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# demo.launch()
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import gradio as gr
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import asyncio
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import os
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# 请确保在环境变量中设置了您的YouTube Data API密钥
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API_KEY = "AIzaSyDyPpkFRUpUuSMQbhxwTFxCBLK5qTHU-ms"
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os.environ["OPENAI_API_KEY"] = "sk-h8rybT55JORrT40y2397A06c8f2444F8Ad49407fE85eBf76"
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def get_youtube_id(youtube_url):
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if 'youtube.com' in youtube_url:
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# 从您的模块中导入必要的函数
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from utils.generate_distractors import prepare_q_inputs, construct_prompt_textonly, generate_distractors
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from utils.api_utils import generate_from_openai_chat_completion
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# 修改generate_distractors函数,使其成为异步函数
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# 假设generate_distractors函数定义在您的模块中,我们需要修改它
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# 如果无法修改原始模块,请在此处重新定义
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async def generate_distractors_async(model_name: str,
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queries: list,
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# 定义异步处理函数
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async def generate_distractors_gradio(question, option1, option2, option3, option4, answer, answer_analysis):
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query = {
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'question': question,
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'option_1': option1,
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# 调用异步生成干扰项的函数
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results = await generate_distractors_async(
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model_name="gpt-4o
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queries=queries,
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n=1,
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max_tokens=4096
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'F': result.get('option_6', ''),
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'G': result.get('option_7', '')
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}
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distractor_analysis = result.get('distractor_analysis', '')
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# 返回新的干扰项和分析
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return
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with gr.Blocks() as demo:
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gr.Markdown("# CC检查器和干扰项生成器")
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with gr.Row():
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option1_input = gr.Textbox(label="选项A")
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option2_input = gr.Textbox(label="选项B")
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with gr.Row():
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option3_input = gr.Textbox(label="选项C")
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option4_input = gr.Textbox(label="选项D
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with gr.Row():
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answer_input = gr.Textbox(label="正确答案(A/B/C/D)")
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with gr.Row():
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answer_analysis_input = gr.Textbox(label="答案解析", lines=3)
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generate_button = gr.Button("生成干扰项")
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output_options = gr.
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output_analysis = gr.Textbox(label="干扰项解析", lines=5)
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generate_button.click(
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fn=generate_distractors_gradio,
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# 运行Gradio应用
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demo.launch()
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import gradio as gr
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import asyncio
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import os
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# 请确保在环境变量中设置了您的YouTube Data API密钥
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API_KEY = "AIzaSyDyPpkFRUpUuSMQbhxwTFxCBLK5qTHU-ms"
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def get_youtube_id(youtube_url):
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if 'youtube.com' in youtube_url:
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# 从您的模块中导入必要的函数
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from utils.generate_distractors import prepare_q_inputs, construct_prompt_textonly, generate_distractors
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from utils.api_utils import generate_from_openai_chat_completion
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async def generate_distractors_async(model_name: str,
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queries: list,
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# 定义异步处理函数
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async def generate_distractors_gradio(question, option1, option2, option3, option4, answer, answer_analysis):
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is_valid, message = validate_inputs(question, option1, option2, option3, option4, answer, answer_analysis)
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if not is_valid:
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return {"error": message}, "" # Output error message
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query = {
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'question': question,
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'option_1': option1,
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# 调用异步生成干扰项的函数
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results = await generate_distractors_async(
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model_name="gpt-4o",
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queries=queries,
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n=1,
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max_tokens=4096
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'F': result.get('option_6', ''),
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'G': result.get('option_7', '')
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}
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new_option_str = f"E: {new_options['E']}\nF:{new_options['F']}\nG:{new_options['G']}"
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distractor_analysis = result.get('distractor_analysis', '')
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# 返回新的干扰项和分析
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return new_option_str, distractor_analysis
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def validate_inputs(question, option1, option2, option3, option4, answer, analysis):
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if not question:
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return False, "问题不能为空"
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if not option1:
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return False, "选项A不能为空"
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if not option2:
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return False, "选项B不能为空"
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if not option3:
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return False, "选项C不能为空"
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if not option4:
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return False, "选项D不能为空"
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if not answer:
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return False, "正确答案不能为空"
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if not analysis:
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return False, "答案解析不能为空"
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return True, ""
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with gr.Blocks() as demo:
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gr.Markdown("# CC检查器和干扰项生成器")
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with gr.Row():
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option1_input = gr.Textbox(label="选项A")
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option2_input = gr.Textbox(label="选项B")
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option3_input = gr.Textbox(label="选项C")
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option4_input = gr.Textbox(label="选项D")
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with gr.Row():
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answer_input = gr.Textbox(label="正确答案(A/B/C/D)")
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with gr.Row():
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answer_analysis_input = gr.Textbox(label="答案解析", lines=3)
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generate_button = gr.Button("生成干扰项")
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output_options = gr.Textbox(label="生成的干扰选项")
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output_analysis = gr.Textbox(label="干扰项解析", lines=5)
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generate_button.click(
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fn=generate_distractors_gradio,
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# 运行Gradio应用
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demo.launch()
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