############################################## # app.py ############################################## import os import json import gradio as gr import requests # 新版 openai>=1.0.0 from openai import OpenAI ############################################################################## # 1. 从外部文件中加载 Furry 物种数据 + Gender 细节文本 ############################################################################## # 读取 Furry 物种分类的 JSON 文件 # 假设文件名为 furry_species.json，结构示例： # { # "CANIDS": ["Dogs", "Wolves", "Foxes"], # "FELINES": ["Lions", "Tigers", "Cheetahs"], # ... # } try: with open("furry_species.json", "r", encoding="utf-8") as fs_file: furry_map = json.load(fs_file) except: furry_map = {} # 若文件不存在或出错，可给个空dict备用 def flatten_furry_species(map_data): """ 将 {分类: [物种列表]} 展开为 ["分类 - 物种"] 形式的扁平列表 """ result = [] for category, species_list in map_data.items(): for sp in species_list: result.append(f"{category} - {sp}") return sorted(result) ALL_FURRY_SPECIES = flatten_furry_species(furry_map) # 读取 Gender 细节长文本 (记忆库) try: with open("gender_details.txt", "r", encoding="utf-8") as gd_file: GENDER_DETAILS_TEXT = gd_file.read() except: GENDER_DETAILS_TEXT = ( "Gender conversion rules are missing. Please provide gender_details.txt." ) ############################################################################## # 2. 核心函数：根据选择调用 GPT 或 DeepSeek ############################################################################## def generate_description_with_tags(prompt, gender_option, furry_species, api_mode, api_key): """ 1) 构造 tags（包含 gender/furry/base_prompt）。 2) 调用 GPT 或 DeepSeek，带上记忆库信息 (GENDER_DETAILS_TEXT) 作为系统提示。 3) 返回 (tags + 自然语言描述) 的输出形式。 """ if not api_key: return "Error: No API Key provided." # 组装 tags tags = {} 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" tags["base_prompt"] = prompt # 确定 base_url + model if api_mode == "GPT": base_url = None model_name = "gpt-3.5-turbo" # or "gpt-4", "gpt-4o", etc. else: # DeepSeek base_url = "https://api.deepseek.com" model_name = "deepseek-chat" # 创建 OpenAI Client client = OpenAI(api_key=api_key) if base_url: client.base_url = base_url # 将tags拼成便于阅读的字符串 tags_str = "\n".join([f"{k}: {v}" for k, v in tags.items() if v]) # 准备对话消息：把 gender_details 放在系统提示中，以便 AI 参考 system_prompt = ( "You are a creative assistant that generates detailed and imaginative scene descriptions " "for AI generation prompts. Focus on the details provided, incorporate them into a cohesive narrative, " "and obey the following gender transformation & furry rules:\n\n" f"{GENDER_DETAILS_TEXT}\n\n" "After forming your final description, return it in no more than five sentences. Thank you!" ) try: response = client.chat.completions.create( model=model_name, messages=[ {"role": "system", "content": system_prompt}, { "role": "user", "content": ( f"Here are the tags:\n{tags_str}\n" f"Please generate a vivid, imaginative scene description." ), }, ], ) description = response.choices[0].message.content.strip() # 输出形式：(tags + 自然语言描述) output_text = f"=== Tags ===\n{tags_str}\n\n=== Description ===\n{description}" return output_text except Exception as e: return f"{api_mode} generation failed. Error: {e}" def translate_text(text, translate_language, api_mode, api_key): """ 仅做一次简单翻译。若不需要翻译可以省去。也可用系统提示让 AI 翻译。 """ if not api_key: return "Error: No API Key provided." if not text.strip(): return "" # GPT vs DeepSeek if api_mode == "GPT": base_url = None model_name = "gpt-3.5-turbo" else: base_url = "https://api.deepseek.com" model_name = "deepseek-chat" client = OpenAI(api_key=api_key) if base_url: client.base_url = base_url system_prompt = f"You are a professional translator. Translate the following text to {translate_language}:" try: resp = client.chat.completions.create( model=model_name, messages=[ {"role": "system", "content": system_prompt}, {"role": "user", "content": text}, ] ) return resp.choices[0].message.content.strip() except Exception as e: return f"{api_mode} translation failed. Error: {e}" ############################################################################## # 3. Gradio 界面 ############################################################################## def build_interface(): with gr.Blocks() as demo: gr.Markdown("## Prompt Transformer (GPT / DeepSeek) - (tags + 自然语言描述)") with gr.Row(): with gr.Column(): # 选择 API api_mode = gr.Radio( label="选择API (GPT or DeepSeek)", choices=["GPT", "DeepSeek"], value="GPT", ) api_key = gr.Textbox( label="API密钥 (API Key)", type="password", placeholder="在此输入 GPT / DeepSeek 的API Key" ) # 性别 / Furry gender_option = gr.Radio( label="转换目标", choices=[ "Trans_to_Male", "Trans_to_Female", "Trans_to_Mannequin", "Trans_to_Intersex", "Trans_to_Furry", ], value="Trans_to_Male", ) furry_species = gr.Dropdown( label="Furry 物种选择", choices=ALL_FURRY_SPECIES, value=None, visible=False ) def show_furry_species(choice): return gr.update(visible=(choice == "Trans_to_Furry")) gender_option.change(show_furry_species, inputs=[gender_option], outputs=[furry_species]) with gr.Column(): user_prompt = gr.Textbox( label="提示词 (Prompt)", lines=4, placeholder="示例：一位穿着蓝色长裙的少女，坐在海边..." ) output_tags_and_desc = gr.Textbox( label="(tags + 自然语言描述)", lines=10 ) with gr.Row(): translate_language = gr.Dropdown( label="翻译语言 (Translation Language)", choices=["English", "Chinese", "Japanese", "French", "German", "Spanish"], value="English" ) translate_output = gr.Textbox( label="翻译结果", lines=10 ) # 点击生成 -> 同时调用生成描述 & 翻译 def on_generate(prompt, gender, f_species, mode, key, lang): # 1. 生成 (tags + 自然语言描述) result_text = generate_description_with_tags(prompt, gender, f_species, mode, key) # 2. 翻译 translated = translate_text(result_text, lang, mode, key) return result_text, translated user_prompt.submit( fn=on_generate, inputs=[user_prompt, gender_option, furry_species, api_mode, api_key, translate_language], outputs=[output_tags_and_desc, translate_output] ) generate_btn = gr.Button("生成 / Generate") generate_btn.click( fn=on_generate, inputs=[user_prompt, gender_option, furry_species, api_mode, api_key, translate_language], outputs=[output_tags_and_desc, translate_output] ) return demo if __name__ == "__main__": demo = build_interface() demo.launch()