import os import gradio as gr import openai ############################################################################## # 1. GPT 或 DeepSeek 调用示例函数 ############################################################################## def generate_natural_language_description_gpt(tags, api_key, base_url=None, model="gpt-4"): """ 使用 OpenAI GPT 生成自然语言描述的示例函数。 """ if not api_key: return "Error: GPT API Key not provided." # 设置 API openai.api_key = api_key if base_url: openai.api_base = base_url # 将 dict 转成可读字符串 tag_descriptions = "\n".join([ f"{key}: {', '.join(value) if isinstance(value, list) else value}" for key, value in tags.items() if value ]) try: response = openai.ChatCompletion.create( model=model, messages=[ { "role": "system", "content": ( "You are a creative assistant that generates detailed and imaginative scene descriptions " "for AI generation prompts. Focus on the details provided and incorporate them into a " "cohesive narrative. Use at least three sentences but no more than five sentences." ), }, { "role": "user", "content": f"Here are the tags and details:\n{tag_descriptions}\nPlease generate a vivid, imaginative scene description.", }, ] ) return response.choices[0].message.content.strip() except Exception as e: return f"GPT generation failed. Error: {e}" def generate_natural_language_description_deepseek(tags, api_key, base_url=None): """ 使用 DeepSeek API 生成自然语言描述的示例函数。 这里留作你在实际部署时，替换为真正的 DeepSeek API 调用逻辑。 """ if not api_key: return "Error: DeepSeek API Key not provided." # 伪代码示例（请用真实 DeepSeek 调用替换此处） # ---------------------------------- # import requests # response = requests.post( # url=base_url or "https://api.deepseek.com/xxx", # headers={"Authorization": f"Bearer {api_key}"}, # json={"tags": tags} # ) # if response.status_code == 200: # return response.json().get("description", "No description returned.") # else: # return f"DeepSeek generation failed: {response.text}" # ---------------------------------- # 目前只是一个占位返回： return "[DeepSeek: 此处应返回真实API结果]" ############################################################################## # 2. 翻译示例函数（使用 GPT 或 DeepSeek） ############################################################################## def translate_text_with_gpt(text, target_language, api_key, base_url=None, model="gpt-4"): """ 使用 GPT 来进行翻译的简单示例。 """ if not api_key: return "Error: GPT Translation Key not provided." openai.api_key = api_key if base_url: openai.api_base = base_url try: system_prompt = f"You are a professional translator. Translate the following text to {target_language}:" response = openai.ChatCompletion.create( model=model, messages=[ {"role": "system", "content": system_prompt}, {"role": "user", "content": text}, ] ) return response.choices[0].message.content.strip() except Exception as e: return f"GPT translation failed. Error: {e}" def translate_text_with_deepseek(text, target_language, api_key, base_url=None): """ 使用 DeepSeek 来进行翻译的简单示例（仍需你在此处写入实际逻辑）。 """ if not api_key: return "Error: DeepSeek Translation Key not provided." # 伪代码示例（请用真实 DeepSeek 翻译调用替换） # ---------------------------------- # import requests # response = requests.post( # url=base_url or "https://api.deepseek.com/translate", # headers={"Authorization": f"Bearer {api_key}"}, # json={"text": text, "target_language": target_language} # ) # if response.status_code == 200: # return response.json().get("translated_text", "No translation returned.") # else: # return f"DeepSeek translation failed: {response.text}" # ---------------------------------- return "[DeepSeek: 此处应返回翻译API的真实结果]" ############################################################################## # 3. 根据用户选择进行提示词转换并调用 GPT/DeepSeek 生成描述 ############################################################################## def transform_prompt(prompt, gender_option, furry_species, api_mode, api_key): """ 性别/物种转换的简单示例逻辑，然后调用相应 API。 """ tags = {} # 根据选择设置性别或物种标签 if gender_option == "Trans_to_Male": tags["gender"] = "male" elif gender_option == "Trans_to_Female": tags["gender"] = "female" elif gender_option == "Trans_to_Mannequin": tags["gender"] = "genderless" elif gender_option == "Trans_to_Intersex": tags["gender"] = "intersex" elif gender_option == "Trans_to_Furry": tags["gender"] = "furry" tags["furry_species"] = furry_species or "unknown" # 原始提示词 tags["base_prompt"] = prompt # 根据选择的 API 调用对应的函数 if api_mode == "GPT": scene_description = generate_natural_language_description_gpt(tags, api_key) else: # DeepSeek scene_description = generate_natural_language_description_deepseek(tags, api_key) return scene_description ############################################################################## # 4. 调用翻译函数 ############################################################################## def do_translation(scene_desc, translate_language, api_mode, api_key): """ 根据选择的 API（GPT/DeepSeek）进行翻译。 """ if not scene_desc.strip(): return "" if api_mode == "GPT": return translate_text_with_gpt(scene_desc, translate_language, api_key) else: return translate_text_with_deepseek(scene_desc, translate_language, api_key) ############################################################################## # 5. 搭建 Gradio 界面 ############################################################################## def build_interface(): with gr.Blocks() as demo: gr.Markdown("## Prompts_TransTool-提示词一键性别物种转换器") with gr.Row(): with gr.Column(): # 选择调用哪个 API api_mode = gr.Radio( label="选择 API 服务 (Choose API Service)", choices=["GPT", "DeepSeek"], value="GPT" ) # 输入 API Key api_key = gr.Textbox( label="API 密钥 (API Key)", type="password", placeholder="请输入你的 GPT 或 DeepSeek API 密钥" ) # 性别 / Furry 选择 gender_option = gr.Radio( label="性别 / Furry 选项 (Gender / Furry)", choices=[ "Trans_to_Male", "Trans_to_Female", "Trans_to_Mannequin", "Trans_to_Intersex", "Trans_to_Furry" ], value="Trans_to_Male", ) # 选择 Furry 物种 furry_species = gr.Dropdown( label="Furry 物种 (Furry Species)", choices=["Wolf", "Fox", "Tiger", "Lion"], value=None, visible=False # 初始不可见 ) # 当性别选项切换时，如果选择 Furry，就显示物种下拉，否则隐藏 def show_furry_species(gender): return gr.update(visible=(gender == "Trans_to_Furry")) gender_option.change( show_furry_species, inputs=[gender_option], outputs=[furry_species] ) with gr.Column(): # 输入 prompt user_prompt = gr.Textbox( label="提示词 (Prompt)", lines=5, placeholder=( "Please Enter your prompt words. \n" "在此输入你的提示词，例如：一位穿着红色连衣裙的少女，坐在落日余晖下的草地上..." ) ) # 输出场景描述 generated_output = gr.Textbox( label="转换后的提示词 (Generated Trans-Description)", lines=7 ) # 翻译区域 with gr.Row(): translate_language = gr.Dropdown( label="翻译语言 (Translation Language)", # 可自行添加更多语言选项 choices=["English", "Chinese", "Japanese", "French", "German", "Dutch", "Arabic", "Russian", "Persian", "Italian"], value="English", ) translated_text = gr.Textbox( label="翻译结果 (Translated Result)", lines=7 ) ###################################################################### # 事件绑定 ###################################################################### # 生成函数：一次性返回「转换结果」和「翻译结果」 def on_generate(prompt, gender, furry, mode, key, lang): # 1) 先做性别/物种转换，拿到“转换后”提示词 trans_desc = transform_prompt(prompt, gender, furry, mode, key) # 2) 立刻翻译 trans_result = do_translation(trans_desc, lang, mode, key) # 返回两项 return trans_desc, trans_result # 当用户在 prompt 输入后按回车时，触发生成场景描述 + 翻译 user_prompt.submit( fn=on_generate, inputs=[user_prompt, gender_option, furry_species, api_mode, api_key, translate_language], outputs=[generated_output, translated_text], ) # 点击按钮也触发同样的逻辑 generate_button = gr.Button("生成 / Generate") generate_button.click( fn=on_generate, inputs=[user_prompt, gender_option, furry_species, api_mode, api_key, translate_language], outputs=[generated_output, translated_text], ) # 当用户切换翻译语言时，如果已经有转换后的内容，则再次翻译 def on_translate(scene_desc, lang, mode, key): return do_translation(scene_desc, lang, mode, key) translate_language.change( fn=on_translate, inputs=[generated_output, translate_language, api_mode, api_key], outputs=[translated_text] ) return demo # 在 Spaces 启动 if __name__ == "__main__": demo = build_interface() demo.launch()