Update app.py

app.py

@@ -46,28 +46,23 @@ def get_species_list(furry_data, top_category, sub_category):
 ##############################################################################
 def merge_transform_rules_into_prompt(rules_json):
     """
-    将 transform_rules.json 中的相关字段转为统一文本，便于放到 system_prompt。
-    你也可以分段加入。
+    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)"
     
-    # 1) 读取 gender_transform
     gt = rules_json.get("gender_transform", {})
-    # 注意：这里不一定要用 male_tag_rules, replacements 等字段，
-    # 仅做一个演示将 gt 转成文本
-    text_parts = []
+    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))  # 直接转为字符串或更有条理地拼写
+    text_parts.append(str(gt))
 
-    # 2) shared_preferences
-    sp = rules_json.get("shared_preferences", {})
     text_parts.append("==== SHARED PREFERENCES ====")
     text_parts.append(str(sp))
 
-    # 3) table_details
-    td = rules_json.get("table_details", {})
     text_parts.append("==== TABLE DETAILS (PRO ACTIONS) ====")
     text_parts.append(str(td))
 
@@ -76,33 +71,33 @@ def merge_transform_rules_into_prompt(rules_json):
 RULES_TEXT_FULL = merge_transform_rules_into_prompt(TRANSFORM_DICT)
 
 ##############################################################################
-# 4. 强制替换逻辑
+# 4. 强制替换：根据 override_conflicting_descriptors
 ##############################################################################
 
-# 建立一个映射：用户在前端选 "Trans_to_Male" -> 我们用 transform_rules.json["override_conflicting_descriptors"]["female_to_male"] 等
+# 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",  # 也可在这里加:  if we want forced replacement for "she->anthro_female" etc.
+    "Trans_to_Furry": "trans_to_furry"
 }
 
 def forced_replace(prompt, direction):
     """
-    根据 TRANSFORM_DICT["override_conflicting_descriptors"] 下的映射，
-    对 prompt 中的词做强制替换。
+    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。
     """
-    # direction 是 "female_to_male" / "male_to_female" / ...
+    if not TRANSFORM_DICT:
+        return prompt
+
     override_section = TRANSFORM_DICT.get("override_conflicting_descriptors", {})
     replacements = override_section.get(direction, {})
     if not replacements:
-        # 该方向没有映射，直接返回
-        return prompt
+        return prompt  # 该方向没有映射表，直接返回
 
-    # 逐条用正则整词替换
     for old, new in replacements.items():
-        # \b 表示单词边界，(?i) 表示不区分大小写
+        # (?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
@@ -112,8 +107,7 @@ def forced_replace(prompt, direction):
 ##############################################################################
 def generate_transformed_output(prompt, gender_option, top_cat, sub_cat, species_item, api_mode, api_key):
     """
-    读取 transform_rules.json / GENDER_RULES / FurryData:
-    只输出两段：(tags)\n\n(description)
+    最终在 GPT/DeepSeek 中生成 (tags)\n\n(description)。
     """
     if not api_key:
         return "Error: No API Key provided."
@@ -129,14 +123,14 @@ def generate_transformed_output(prompt, gender_option, top_cat, sub_cat, species
     if base_url:
         client.base_url = base_url
 
-    # 如果选 Furry:
+    # 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 gender_option，取对应 GENDER_RULES
+    # 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", "")
@@ -147,6 +141,7 @@ def generate_transformed_output(prompt, gender_option, top_cat, sub_cat, species
     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:
@@ -174,11 +169,10 @@ Instructions:
             model=model_name,
             messages=[
                 {"role": "system", "content": system_prompt},
-                {"role": "user",  "content": "Generate final tags and description now."}
+                {"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}"
 
@@ -186,6 +180,9 @@ Instructions:
 # 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():
@@ -320,8 +317,10 @@ def build_interface():
         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"],
+                choices=[
+                    "English", "Chinese", "Japanese", "French", "German", 
+                    "Italian", "Spanish", "Russian", "Dutch", "Persian", "Arabic", "Thai"
+                ],
                 value="English"
             )
             translated_text = gr.Textbox(
@@ -333,15 +332,14 @@ def build_interface():
         # 生成
         ######################################################################
         def on_generate(prompt, gender, tc, sc, spc, mode, key, lang):
-            # 1) 先根据 "gender" 选项判断要执行哪种 forced_replace
+            # 1) 找到 override_conflicting_descriptors 的方向
             direction = transform_map.get(gender, None)
             if direction:
-                # 在提交给 GPT 之前，对 prompt 做强制替换
+                # 先做强制替换
                 prompt = forced_replace(prompt, direction)
 
-            # 2) 再调用原先的 generate_transformed_output
+            # 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