Update app.py

app.py

@@ -1,6 +1,3 @@
-##############################################
-# app.py
-##############################################
 import os
 import json
 import gradio as gr
@@ -9,14 +6,12 @@ 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)
@@ -24,83 +19,66 @@ except:
     GENDER_RULES = {}
 
 ##############################################################################
-# 2. 构造多级下拉菜单：先选“主分类”，再选“子分类”
+# 2. 多级菜单构造函数
 ##############################################################################
 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]
-    ):
+    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
+# 3. 核心调用：GPT 或 DeepSeek
 ##############################################################################
-def generate_tags_and_description(prompt, gender_option, top_cat, sub_cat, species_item, api_mode, api_key):
+def generate_transformed_output(
+    prompt,        # 原始 Prompt，如 "1girl, butterfly, solo..."
+    gender_option, # 转换目标
+    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)
+    根据指定的性别/物种等规则，让 GPT/DeepSeek 输出仅两段内容：
+     (转化后tags)
+
+     转化后描述 (3~6句)
+    不展示原始 prompt/base_prompt/gender: ... 等信息。
     """
     if not api_key:
         return "Error: No API Key provided."
-    
-    # 性别
-    tags = {}
+
+    # 根据 gender_option 选对应的 rule
     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"
+        # 你可以综合 male/female/intersex/genderless，也可以有专门 furry 的说明
         rule_text = (
-            GENDER_RULES.get("male", "") + "\n\n"  # 根据自己的需求处理
+            GENDER_RULES.get("male", "") + "\n\n"
             + 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"
+        )
+        # 如果想在规则中附加选定的物种信息：
         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
+            rule_text += f"\nFurry species: {top_cat} > {sub_cat} > {species_item}\n"
 
-    # BaseURL & 模型
+    # 选定 GPT or DeepSeek
     if api_mode == "GPT":
         base_url = None
-        model_name = "gpt-3.5-turbo"
+        model_name = "gpt-3.5-turbo"  # 可改成 "gpt-4"
     else:
         base_url = "https://api.deepseek.com"
         model_name = "deepseek-chat"
@@ -109,40 +87,46 @@ def generate_tags_and_description(prompt, gender_option, top_cat, sub_cat, speci
     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 rules:\n\n"
-        f"{rule_text}\n\n"
-        "When you respond, do not exceed six sentences or less than three sentences. Return your final text in English in the format of (tags \n Nature Language description).\n"
-    )
+    # 构造 System Prompt：要求只输出两段；第一行(转化后tags)，空行，随后3~6句描述
+    # 让它把 prompt 中的 tags 进行「合并、替换、去重、增加」等处理
+    system_prompt = f"""
+You are a creative assistant that modifies the user's base prompt tags 
+to reflect the correct gender/furry transformations, following these rules:
+
+{rule_text}
+
+Steps:
+1) The original prompt tags are: {prompt}
+2) Convert them into NEW combined tags that reflect the requested transformation. 
+   (Remove or replace conflicting tags, unify synonyms, add any essential tags 
+    for {gender_option} or for the selected furry species.)
+3) Output EXACTLY two parts:
+   - First line: the final, consolidated tags in parentheses (e.g. (male, solo, ...)).
+   - Then a blank line.
+   - Then a short imaginative scene description (3 to 6 sentences). 
+4) Do NOT include 'gender:' or 'base_prompt:' or any headings or extra lines. 
+5) Output everything in English.
+6) Do not reference these steps in the final answer.
+""".strip()
 
-    # 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."
-                },
+                {"role": "user", "content": "Generate the final tags and description now."},
             ],
         )
-        desc_text = resp.choices[0].message.content.strip()
-        # 输出 (tags + desc)
-        return f"=== Tags ===\n{tags_str}\n\n=== Description ===\n{desc_text}"
+        # 结果中仅包含 (tags)\n\n(description)
+        result = resp.choices[0].message.content.strip()
+        return result
 
     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
+    对上一步的 (tags)\n\n(description) 做翻译，保持格式
     """
     if not api_key:
         return "Error: No API Key provided."
@@ -160,13 +144,18 @@ def translate_text(content, lang, api_mode, api_key):
     if base_url:
         client.base_url = base_url
 
-    system_prompt = f"You are a translator. Translate the following text to {lang}:"
+    translate_system_prompt = f"""
+You are a translator. Translate the following text to {lang}, 
+preserving the parentheses line and blank lines if present. 
+Do not add extra headings.
+""".strip()
+
     try:
         resp = client.chat.completions.create(
             model=model_name,
             messages=[
-                {"role": "system", "content": system_prompt},
-                {"role": "user",   "content": content},
+                {"role": "system", "content": translate_system_prompt},
+                {"role": "user", "content": content},
             ],
         )
         return resp.choices[0].message.content.strip()
@@ -174,27 +163,30 @@ def translate_text(content, lang, api_mode, api_key):
         return f"{api_mode} translation failed. Error: {e}"
 
 ##############################################################################
-# 4. Gradio 界面
+# 4. Gradio 前端
 ##############################################################################
 def build_interface():
     with gr.Blocks() as demo:
-        gr.Markdown("## Prompt Transformer 提示词性别物种转换器 (GPT/DeepSeek)")
+        gr.Markdown("## Prompt Transformer - 不显示原Prompt与gender/base_prompt，只输出新tags和描述 (GPT/DeepSeek)")
 
         with gr.Row():
             with gr.Column():
+                # 选择 GPT/DeepSeek
                 api_mode = gr.Radio(
-                    label="Choose which API you would like to use -- 选择API (GPT or DeepSeek)",
+                    label="Choose API (GPT or DeepSeek)",
                     choices=["GPT", "DeepSeek"],
                     value="GPT"
                 )
+                # 输入 API Key
                 api_key = gr.Textbox(
                     label="API Key",
-                    type="password"
+                    type="password",
+                    placeholder="Enter your GPT or DeepSeek Key here"
                 )
 
-                # 性别
+                # 性别/Furry
                 gender_option = gr.Radio(
-                    label="转换目标",
+                    label="Gender / Furry Conversion",
                     choices=[
                         "Trans_to_Male",
                         "Trans_to_Female",
@@ -205,109 +197,113 @@ def build_interface():
                     value="Trans_to_Male"
                 )
 
-                # 顶级分类
+                # 若选 Furry -> 多级菜单
                 top_cat_dd = gr.Dropdown(
-                    label="Furry: 主分类 (Top Category)",
+                    label="Furry: 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)",
+                    label="Furry: Sub Category",
                     choices=[],
                     value=None,
                     visible=False
                 )
-                # 物种
                 species_dd = gr.Dropdown(
-                    label="Furry: 物种 (Species)",
+                    label="Furry: Species",
                     choices=[],
                     value=None,
                     visible=False
                 )
 
-                # 性别选项变化 -> 显示或隐藏 Furry 下拉
+                # 当性别选项切到 Furry 时，显示下拉，否则隐藏
                 def show_furry_options(chosen):
                     if chosen == "Trans_to_Furry":
-                        return gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
+                        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)
-
+                        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
+                # 主分类 -> 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
+                # 子分类 -> 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]
                 )
 
+            # 输入 prompt & 输出
             with gr.Column():
                 user_prompt = gr.Textbox(
-                    label="提示词 (Prompt)",
-                    lines=4
+                    label="原始 Prompt (Base Tags)",
+                    lines=5,
+                    placeholder="e.g. 1girl, butterfly, solo, flower..."
                 )
-                output_result = gr.Textbox(
-                    label="(tags + Descriptions (自然语言描述))",
+                final_output = gr.Textbox(
+                    label="(转化后Tags)\n\n(转化后描述)",
                     lines=10
                 )
 
+        # 翻译
         with gr.Row():
             translate_lang = gr.Dropdown(
-                label="翻译语言 Language Translation",
+                label="翻译语言",
                 choices=["English", "Chinese", "Japanese", "French", "German", "Spanish"],
                 value="English"
             )
-            translate_result = gr.Textbox(
-                label="翻译结果",
+            translated_result = gr.Textbox(
+                label="翻译后的结果",
                 lines=10
             )
 
         ######################################################################
-        # 生成
+        # 事件
         ######################################################################
-        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)
+        def on_generate(prompt, gender, tc, sc, sp, mode, key, lang):
+            # 1) 生成新的 (tags) + 描述
+            merged = generate_transformed_output(prompt, gender, tc, sc, sp, mode, key)
             # 2) 翻译
-            trans_txt = translate_text(tags_desc, lang, mode, key)
-            return tags_desc, trans_txt
+            trans = translate_text(merged, lang, mode, key)
+            return merged, trans
 
+        # 回车提交
         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]
+            outputs=[final_output, translated_result]
         )
-
-        gen_btn = gr.Button("生成 / Generate")
-        gen_btn.click(
+        # 点击按钮
+        btn = gr.Button("生成 / Generate")
+        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]
+            outputs=[final_output, translated_result]
         )
 
     return demo
 
+
 if __name__ == "__main__":
     demo = build_interface()
     demo.launch()