app.py

import gradio as gr
# from langchain.llms import OpenAI
# from langchain.llms.fake import FakeListLLM

# from langchain import PromptTemplate, FewShotPromptTemplate
# from langchain.utilities import TextRequestsWrapper
# import json

# def generate_prompt(embedding_url, extra_prompt, count):

#     output = TextRequestsWrapper().get(embedding_url)
#     result = json.loads(output)

#     example_formatter_template = "标题: {sentence}\n热度: {hot_level}"
#     example_prompt = PromptTemplate(
#         input_variables=["sentence", "hot_level"],
#         template=example_formatter_template,
#     )

#     few_shot_prompt = FewShotPromptTemplate(
#         examples=result["data"],
#         example_prompt=example_prompt,
#         prefix="你是一个短视频方专家，你的职责是为短视频的制作进行选题。\n以下是某视频站点的最新热词\n\n",
#         # The suffix is some text that goes after the examples in the prompt.
#         # Usually, this is where the user input will go
#         suffix="{extra_prompt}\n\n请根据以上内容草拟{count}个吸引人的短视频的标题:",
#         # The input variables are the variables that the overall prompt expects.
#         input_variables=["extra_prompt", "count"],
#         # The example_separator is the string we will use to join the prefix, examples, and suffix together with.
#         example_separator="\n\n",
#     )

#     # We can now generate a prompt using the `format` method.
#     # print(few_shot_prompt.format(count="5"))
#     return few_shot_prompt.format(extra_prompt=extra_prompt, count=count)

# def generate_topics(
#         openai_api_key: str, 
#         embedding_url: str,
#         extra_prompt: str, 
#         count: int, 
#         repeat: int
#     ):
#     if openai_api_key.strip() == "":
#         return "请输入OPENAI API KEY"
    
#     llm = OpenAI(temperature=.7, openai_api_key=openai_api_key)

#     prompt = generate_prompt(embedding_url, extra_prompt, count)
#     print(prompt)
    
#     llm_result = llm.generate([prompt]*repeat)

#     answer = "" if repeat == 1 else f"以下是合并的{str(repeat)}次选题结果：\n\n"
#     for i in range(len(llm_result.generations)):
#         answer += f"{'下一个：' if i > 0 else ''}" + llm_result.generations[i][0].text + "\n\n"
    
#     print(answer)

#     token_usage = llm_result.llm_output["token_usage"]["total_tokens"] if llm_result.llm_output else 0
#     answer += f"##总共消耗Token数：{str(token_usage)}"

#     return answer

with gr.Blocks() as demo:
  gr.HTML("""<div style="text-align: center; max-width: 700px; margin: 0 auto;">
        <div
        style="
            display: inline-flex;
            align-items: center;
            gap: 0.8rem;
            font-size: 1.75rem;
        "
        >
        <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
            Generate Topics & Scripts by LLM
        </h1>
        </div>
    </div>""")  
  
  topics_output = gr.Textbox(label='选题结果')

  #   extra_req = gr.Textbox(label = 'Type in your query args for your douyin retriever api(optional)', placeholder = '')
  # api_spec = gr.Textbox(label = 'Type in your douyin retriever api spec (ref to https://www.klarna.com/us/shopping/public/openai/v0/api-docs/)', placeholder='')
  # api_path = gr.Textbox(label = 'Type in the api path (ref to the spec above, like "/public/openai/v0/products")', placeholder = '')
  embedding_url = gr.Textbox(label = '热门内容获取API的URL')
  # examples = gr.Examples(examples=["https://huggingface.co/spaces/JStudio/Video_Topics_Scripts_LLMGen/raw/main/douyin_1.txt"],
  #                          inputs=[embedding_url])
  extra_prompt = gr.Textbox(label = '追加的一些Prompt(可选)')
  with gr.Row():
    openai_api_key = gr.Textbox(type='password', label="输入你的OpenAI API key")

  with gr.Row():
    count = gr.Slider(
      label="每次生成几个选题", value=5, minimum=0, maximum=10, step=1
    )
    repeat = gr.Slider(
      label="让ChatGPT重试几次", value=1, minimum=0, maximum=10, step=1
    )
    # fakeLLM = gr.CheckboxGroup(choices=["是"], value=[], label="调用FakeLLM")

  btn = gr.Button("生成选题")
  # output = gr.Textbox(label="Topics Generating Output")

  # topic = gr.Textbox(label='需要生成视频脚本的选题')
  # keyword = gr.Textbox(label='内容相关的关键字')
  # btn2 = gr.Button("生成视频创作脚本")
  # output2 = gr.Textbox(label="Scripts")

  #btn.click(generate_topics, [openai_api_key, embedding_url, extra_prompt, count, repeat], [topics_output])
  # btn2.click(chat.generateScripts, [], [chatbot])

demo.launch()