Spaces:
Running
Running
File size: 13,030 Bytes
bef3741 1e6c6f2 9fd65e9 bef3741 64322bd 813f6fc 64322bd 1e6c6f2 813f6fc 1e6c6f2 0550b9b ceffbde 1e6c6f2 813f6fc 1e6c6f2 0550b9b ceffbde 813f6fc ceffbde 813f6fc ceffbde 0550b9b 1e6c6f2 0550b9b ec75df1 0550b9b 1e6c6f2 0550b9b 813f6fc 0550b9b 813f6fc 81a32a1 0550b9b 813f6fc 81a32a1 813f6fc 81a32a1 813f6fc 81a32a1 9fd65e9 813f6fc ec75df1 813f6fc 81a32a1 9fd65e9 81a32a1 9fd65e9 81a32a1 9fd65e9 81a32a1 9fd65e9 81a32a1 9fd65e9 81a32a1 9fd65e9 81a32a1 9fd65e9 813f6fc 81a32a1 0550b9b 1e6c6f2 ec75df1 ceffbde 813f6fc ceffbde bef3741 64322bd bef3741 64322bd 81a32a1 813f6fc 81a32a1 813f6fc 81a32a1 ec75df1 813f6fc ec75df1 64322bd 0550b9b ceffbde 64322bd 1e6c6f2 81a32a1 1e6c6f2 64322bd 813f6fc 64322bd ceffbde 64322bd 9fd65e9 0550b9b 81a32a1 64322bd 1e6c6f2 0550b9b ceffbde 64322bd ceffbde 64322bd bef3741 64322bd bef3741 64322bd ec75df1 813f6fc ec75df1 64322bd ceffbde 64322bd ec75df1 9fd65e9 0550b9b 64322bd ceffbde 0f91f56 ceffbde 64322bd 9fd65e9 64322bd 1e6c6f2 64322bd 9ec2497 64322bd 9ec2497 64322bd 0550b9b 64322bd 813f6fc ec75df1 813f6fc 64322bd 0550b9b 64322bd 9ec2497 64322bd bef3741 0550b9b 64322bd 0550b9b ec75df1 0550b9b ec75df1 0550b9b 64322bd 0550b9b ec75df1 0550b9b 64322bd 0f91f56 64322bd 1e6c6f2 813f6fc ec75df1 0550b9b ec75df1 813f6fc 0550b9b 1e6c6f2 0550b9b 813f6fc 0550b9b 813f6fc 0550b9b 64322bd 1e6c6f2 9ec2497 813f6fc 64322bd ec75df1 9ec2497 1e6c6f2 64322bd 0550b9b 9ec2497 81a32a1 1e6c6f2 64322bd 813f6fc 1e6c6f2 64322bd 0550b9b 813f6fc 0550b9b 813f6fc 81a32a1 9fd65e9 81a32a1 9fd65e9 81a32a1 813f6fc 9fd65e9 ec75df1 05bf4a2 1e6c6f2 64322bd 0550b9b 813f6fc 64322bd 813f6fc 64322bd 0550b9b 813f6fc 64322bd 1e6c6f2 bef3741 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 |
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() |