Create app.py

app.py

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+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])
+
+if __name__ == "__main__":
+    demo.launch()