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import os
import json
import re
import gradio as gr
from openai import OpenAI
##############################################################################
# 1. 读取外部文件
##############################################################################
try:
with open("furry_species.json", "r", encoding="utf-8") as ff:
FURRY_DATA = json.load(ff)
except:
FURRY_DATA = {}
try:
with open("gender_rules.json", "r", encoding="utf-8") as gf:
GENDER_RULES = json.load(gf)
except:
GENDER_RULES = {}
try:
with open("transform_rules.json", "r", encoding="utf-8") as tf:
TRANSFORM_DICT = json.load(tf)
except:
TRANSFORM_DICT = {}
##############################################################################
# 2. 多级菜单函数
##############################################################################
def get_top_categories(furry_data):
return sorted(list(furry_data.keys()))
def get_sub_categories(furry_data, top_category):
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):
if top_category in furry_data and sub_category in furry_data[top_category]:
return sorted(furry_data[top_category][sub_category])
return []
##############################################################################
# 3. 合并规则文本
##############################################################################
def merge_transform_rules_into_prompt(rules_json):
"""
将 transform_rules.json 中的相关字段转为统一文本,
供 system_prompt 里参考。
"""
if not rules_json:
return "(No transform rules loaded)"
gt = rules_json.get("gender_transform", {})
sp = rules_json.get("shared_preferences", {})
td = rules_json.get("table_details", {})
text_parts = []
text_parts.append("==== GENDER TRANSFORM RULES ====")
text_parts.append(str(gt))
text_parts.append("==== SHARED PREFERENCES ====")
text_parts.append(str(sp))
text_parts.append("==== TABLE DETAILS (PRO ACTIONS) ====")
text_parts.append(str(td))
return "\n".join(text_parts)
RULES_TEXT_FULL = merge_transform_rules_into_prompt(TRANSFORM_DICT)
##############################################################################
# 4. 强制替换:根据 override_conflicting_descriptors
##############################################################################
# 前端选项 -> transform_rules.json 里的 override_conflicting_descriptors key
transform_map = {
"Trans_to_Male": "female_to_male",
"Trans_to_Female": "male_to_female",
"Trans_to_Mannequin": "any_to_genderless",
"Trans_to_Intersex": "any_to_intersex",
"Trans_to_Furry": "trans_to_furry"
}
def forced_replace(prompt, direction):
"""
读取 transform_rules.json["override_conflicting_descriptors"][direction] 的键值,
用正则整词替换 prompt 中出现的 old->new。
"""
if not TRANSFORM_DICT:
return prompt
override_section = TRANSFORM_DICT.get("override_conflicting_descriptors", {})
replacements = override_section.get(direction, {})
if not replacements:
return prompt # 该方向没有映射表,直接返回
for old, new in replacements.items():
# (?i)不分大小写, \b表示单词边界
pattern = r"(?i)\b" + re.escape(old) + r"\b"
prompt = re.sub(pattern, new, prompt)
return prompt
##############################################################################
# 5. 核心 GPT/DeepSeek 调用
##############################################################################
def generate_transformed_output(prompt, gender_option, top_cat, sub_cat, species_item, api_mode, api_key):
"""
最终在 GPT/DeepSeek 中生成 (tags)\n\n(description)。
"""
if not api_key:
return "Error: No API Key provided."
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
# 如果用户选 Furry, 记录一下当前选到的物种路径
if gender_option == "Trans_to_Furry":
furry_path = f"{top_cat} > {sub_cat} > {species_item}" if (top_cat and sub_cat and species_item) else "unknown"
extra_line = f"\nFurry chosen: {furry_path}\n"
else:
extra_line = ""
# 根据 user 选择加载 gender_rules.json 里的东西
gender_specific_rule = ""
if gender_option == "Trans_to_Male":
gender_specific_rule = GENDER_RULES.get("male", "")
elif gender_option == "Trans_to_Female":
gender_specific_rule = GENDER_RULES.get("female", "")
elif gender_option == "Trans_to_Mannequin":
gender_specific_rule = GENDER_RULES.get("genderless", "")
elif gender_option == "Trans_to_Intersex":
gender_specific_rule = GENDER_RULES.get("intersex", "")
# 组装 System Prompt
system_prompt = f"""
You are a creative assistant that transforms the user's base prompt
to reflect correct gender/furry transformations. Follow these references:
1) Detailed Transform Rules (transform_rules.json):
{RULES_TEXT_FULL}
2) Additional short gender rules (gender_rules.json):
{gender_specific_rule}
{extra_line}
Instructions:
- Original prompt tags: {prompt}
- Convert them into NEW combined tags, removing or replacing conflicting ones.
- Only output two parts:
1) One line of final tags in parentheses, e.g. (male, short hair, dynamic pose, ...)
2) A blank line.
3) Then 3~6 sentences of imaginative scene description in English.
- No extra lines, no headings, no 'gender:' or 'base_prompt:'.
- End of instructions.
""".strip()
try:
resp = client.chat.completions.create(
model=model_name,
messages=[
{"role": "system", "content": system_prompt},
{"role": "user", "content": "Generate final tags and description now."}
],
)
return resp.choices[0].message.content.strip()
except Exception as e:
return f"{api_mode} generation failed. Error: {e}"
##############################################################################
# 6. 翻译函数
##############################################################################
def translate_text(content, lang, api_mode, api_key):
"""
后期翻译, 不更改上方生成逻辑.
"""
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
translate_system_prompt = f"""
You are a translator. Translate the following text to {lang},
keeping parentheses line and blank line if present.
No extra headings.
""".strip()
try:
resp = client.chat.completions.create(
model=model_name,
messages=[
{"role": "system", "content": translate_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}"
##############################################################################
# 7. Gradio 界面
##############################################################################
def build_interface():
with gr.Blocks() as demo:
gr.Markdown("## Prompt Trans-Tool - 提示词物种性别转换器")
with gr.Row():
with gr.Column():
api_mode = gr.Radio(
label="Select API 选择API厂商 (GPT/DeepSeek)",
choices=["GPT", "DeepSeek"],
value="GPT"
)
api_key = gr.Textbox(
label="API Key",
type="password",
placeholder="Input your GPT or DeepSeek Key"
)
gender_option = gr.Radio(
label="Trans-Option 选择转换目标",
choices=[
"Trans_to_Male",
"Trans_to_Female",
"Trans_to_Mannequin",
"Trans_to_Intersex",
"Trans_to_Furry"
],
value="Trans_to_Male"
)
top_cat_dd = gr.Dropdown(
label="Furry: Top Category",
choices=get_top_categories(FURRY_DATA),
value=None,
visible=False
)
sub_cat_dd = gr.Dropdown(
label="Furry: Sub Category",
choices=[],
value=None,
visible=False
)
species_dd = gr.Dropdown(
label="Furry: Species",
choices=[],
value=None,
visible=False
)
def show_furry_options(opt):
if opt == "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]
)
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]
)
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="Original Prompt 原始提示词 (e.g. 1girl, butterfly, solo, ...)",
lines=5
)
final_output = gr.Textbox(
label="Transformed Output 翻译结果 (tags + description)",
lines=10
)
with gr.Row():
translate_lang = gr.Dropdown(
label="Translate to Language 翻译语言",
choices=[
"English", "Chinese", "Japanese", "French", "German",
"Italian", "Spanish", "Russian", "Dutch", "Persian", "Arabic", "Thai"
],
value="English"
)
translated_text = gr.Textbox(
label="Translated Result",
lines=10
)
######################################################################
# 生成
######################################################################
def on_generate(prompt, gender, tc, sc, spc, mode, key, lang):
# 1) 找到 override_conflicting_descriptors 的方向
direction = transform_map.get(gender, None)
if direction:
# 先做强制替换
prompt = forced_replace(prompt, direction)
# 2) 再执行原先逻辑
merged = generate_transformed_output(prompt, gender, tc, sc, spc, mode, key)
# 3) 翻译
trans = translate_text(merged, lang, mode, key)
return merged, trans
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=[final_output, translated_text]
)
gen_btn = gr.Button("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=[final_output, translated_text]
)
return demo
if __name__ == "__main__":
demo = build_interface()
demo.launch()