app.py

##############################################
# app.py
##############################################
import os
import json
import gradio as gr
from openai import OpenAI

##############################################################################
# 1. 读取外部文件: furry_species.json & gender_rules.json
##############################################################################
# 假设 furry_species.json 的结构是多级字典: { "AQUATICS ...": { "Cetaceans": [], ...}, ... }
try:
    with open("furry_species.json", "r", encoding="utf-8") as f:
        FURRY_DATA = json.load(f)
except:
    FURRY_DATA = {}

# gender_rules.json: { "male": "...", "female": "...", "intersex": "...", "genderless": "..." }
try:
    with open("gender_rules.json", "r", encoding="utf-8") as f:
        GENDER_RULES = json.load(f)
except:
    GENDER_RULES = {}

##############################################################################
# 2. 构造多级下拉菜单：先选“主分类”，再选“子分类”
##############################################################################
def get_top_categories(furry_data):
    """获取所有顶级分类 (keys)"""
    return sorted(list(furry_data.keys()))

def get_sub_categories(furry_data, top_category):
    """
    根据所选 top_category, 返回二级分类列表
    furry_data[top_category] -> { "Cetaceans": [...], "FishFurs": [...], ... }
    """
    if top_category in furry_data:
        return sorted(list(furry_data[top_category].keys()))
    return []

def get_species_list(furry_data, top_category, sub_category):
    """
    返回最终物种列表
    furry_data[top_category][sub_category] -> list
    """
    if (
        top_category in furry_data
        and sub_category in furry_data[top_category]
    ):
        return sorted(furry_data[top_category][sub_category])
    return []

##############################################################################
# 3. 调用逻辑：GPT 或 DeepSeek
##############################################################################
def generate_tags_and_description(prompt, gender_option, top_cat, sub_cat, species_item, api_mode, api_key):
    """
    1) 构造 tags: gender, base_prompt, furry_species
    2) 读取 gender_rules 并拼入 system prompt
    3) 调用 GPT/DeepSeek
    4) 输出 (tags + 自然语言描述)
    """
    if not api_key:
        return "Error: No API Key provided."
    
    # 性别
    tags = {}
    if gender_option == "Trans_to_Male":
        tags["gender"] = "male"
        rule_text = GENDER_RULES.get("male", "")
    elif gender_option == "Trans_to_Female":
        tags["gender"] = "female"
        rule_text = GENDER_RULES.get("female", "")
    elif gender_option == "Trans_to_Mannequin":
        tags["gender"] = "genderless"
        rule_text = GENDER_RULES.get("genderless", "")
    elif gender_option == "Trans_to_Intersex":
        tags["gender"] = "intersex"
        rule_text = GENDER_RULES.get("intersex", "")
    else:
        # Furry
        tags["gender"] = "furry"
        rule_text = (
            GENDER_RULES.get("male", "") + "\n\n"  # 你可以根据自己的业务需求处理
            + GENDER_RULES.get("female", "") + "\n\n"
            + GENDER_RULES.get("intersex", "") + "\n\n"
            + GENDER_RULES.get("genderless", "")
        )  # 或者只给一个简要 furry rule

        # 选定物种
        final_species = "unknown"
        if top_cat and sub_cat and species_item:
            final_species = f"{top_cat} > {sub_cat} > {species_item}"
        tags["furry_species"] = final_species

    # 原始提示词
    tags["base_prompt"] = prompt

    # BaseURL & 模型
    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

    # 将 tags 拼为字符串
    tags_str = "\n".join([f"{k}: {v}" for k, v in tags.items() if v])

    # system prompt 带上Gender Rules
    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 follow these gender/furry rules:\n\n"
        f"{rule_text}\n\n"
        "When you respond, do not exceed five sentences. Return your final text in English or relevant language.\n"
    )

    # Chat
    try:
        resp = client.chat.completions.create(
            model=model_name,
            messages=[
                {"role": "system", "content": system_prompt},
                {
                    "role": "user",
                    "content": f"Here are the tags:\n{tags_str}\nPlease generate a vivid, imaginative scene description."
                },
            ],
        )
        desc_text = resp.choices[0].message.content.strip()
        # 输出 (tags + desc)
        return f"=== Tags ===\n{tags_str}\n\n=== Description ===\n{desc_text}"

    except Exception as e:
        return f"{api_mode} generation failed. Error: {e}"

def translate_text(content, lang, api_mode, api_key):
    """
    调用 GPT 或 DeepSeek 做翻译
    """
    if not api_key:
        return "Error: No API Key provided."
    if not content.strip():
        return ""

    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 translator. Translate the following text to {lang}:"
    try:
        resp = client.chat.completions.create(
            model=model_name,
            messages=[
                {"role": "system", "content": system_prompt},
                {"role": "user",   "content": content},
            ],
        )
        return resp.choices[0].message.content.strip()
    except Exception as e:
        return f"{api_mode} translation failed. Error: {e}"

##############################################################################
# 4. Gradio 界面
##############################################################################
def build_interface():
    with gr.Blocks() as demo:
        gr.Markdown("## Prompt Furry/Gender Transformer (GPT / DeepSeek)")

        with gr.Row():
            with gr.Column():
                api_mode = gr.Radio(
                    label="选择API (GPT or DeepSeek)",
                    choices=["GPT", "DeepSeek"],
                    value="GPT"
                )
                api_key = gr.Textbox(
                    label="API Key",
                    type="password"
                )

                # 性别
                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"
                )

                # 顶级分类
                top_cat_dd = gr.Dropdown(
                    label="Furry: 主分类 (Top Category)",
                    choices=get_top_categories(FURRY_DATA),
                    value=None,
                    visible=False
                )
                # 二级分类
                sub_cat_dd = gr.Dropdown(
                    label="Furry: 子分类 (Sub-Category)",
                    choices=[],
                    value=None,
                    visible=False
                )
                # 物种
                species_dd = gr.Dropdown(
                    label="Furry: 物种 (Species)",
                    choices=[],
                    value=None,
                    visible=False
                )

                # 性别选项变化 -> 显示或隐藏 Furry 下拉
                def show_furry_options(chosen):
                    if chosen == "Trans_to_Furry":
                        return gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
                    else:
                        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)

                gender_option.change(
                    fn=show_furry_options,
                    inputs=[gender_option],
                    outputs=[top_cat_dd, sub_cat_dd, species_dd]
                )

                # 顶级分类 -> 更新子分类
                def on_top_cat_select(selected):
                    subs = get_sub_categories(FURRY_DATA, selected)
                    return gr.update(choices=subs, value=None)

                top_cat_dd.change(
                    fn=on_top_cat_select,
                    inputs=[top_cat_dd],
                    outputs=[sub_cat_dd]
                )

                # 子分类 -> 更新物种
                def on_sub_cat_select(top_c, sub_c):
                    sp = get_species_list(FURRY_DATA, top_c, sub_c)
                    return gr.update(choices=sp, value=None)

                sub_cat_dd.change(
                    fn=on_sub_cat_select,
                    inputs=[top_cat_dd, sub_cat_dd],
                    outputs=[species_dd]
                )

            with gr.Column():
                user_prompt = gr.Textbox(
                    label="提示词 (Prompt)",
                    lines=4
                )
                output_result = gr.Textbox(
                    label="(tags + 自然语言描述)",
                    lines=10
                )

        with gr.Row():
            translate_lang = gr.Dropdown(
                label="翻译语言",
                choices=["English", "Chinese", "Japanese", "French", "German", "Spanish"],
                value="English"
            )
            translate_result = gr.Textbox(
                label="翻译结果",
                lines=10
            )

        ######################################################################
        # 生成
        ######################################################################
        def on_generate(prompt, gender, tc, sc, spc, mode, key, lang):
            # 1) 生成
            tags_desc = generate_tags_and_description(prompt, gender, tc, sc, spc, mode, key)
            # 2) 翻译
            trans_txt = translate_text(tags_desc, lang, mode, key)
            return tags_desc, trans_txt

        user_prompt.submit(
            fn=on_generate,
            inputs=[user_prompt, gender_option, top_cat_dd, sub_cat_dd, species_dd, api_mode, api_key, translate_lang],
            outputs=[output_result, translate_result]
        )

        gen_btn = gr.Button("生成 / Generate")
        gen_btn.click(
            fn=on_generate,
            inputs=[user_prompt, gender_option, top_cat_dd, sub_cat_dd, species_dd, api_mode, api_key, translate_lang],
            outputs=[output_result, translate_result]
        )

    return demo

if __name__ == "__main__":
    demo = build_interface()
    demo.launch()