Update app.py

app.py

@@ -1,42 +1,67 @@
+##############################################
+# app.py
+##############################################
 import os
+import json
 import gradio as gr
 import requests
 
-# 从新版 openai>=1.0.0 库导入
+# 新版 openai>=1.0.0
 from openai import OpenAI
 
 ##############################################################################
-# 1. Furry 物种数据
+# 1. 从外部文件中加载 Furry 物种数据 + Gender 细节文本
 ##############################################################################
-furry_species_map = {
-    "CANIDS (Canines)": ["Dogs", "Wolves", "Foxes", "Jackals"],
-    "FELINES (Cats)": ["HouseCats", "Lions", "Tigers", "Cheetahs"],
-    "CUSTOM (Just An Example)": ["Dragons", "Werewolves", "Kitsune"],
-    # ... 这里你可以替换成更完整的物种分类，或保留最简
-}
-
-def flatten_species(map_dict):
+
+# 读取 Furry 物种分类的 JSON 文件
+# 假设文件名为 furry_species.json，结构示例：
+# {
+#   "CANIDS": ["Dogs", "Wolves", "Foxes"],
+#   "FELINES": ["Lions", "Tigers", "Cheetahs"],
+#   ...
+# }
+try:
+    with open("furry_species.json", "r", encoding="utf-8") as fs_file:
+        furry_map = json.load(fs_file)
+except:
+    furry_map = {}  # 若文件不存在或出错，可给个空dict备用
+
+def flatten_furry_species(map_data):
     """
-    将分门别类的物种字典展开成一个扁平列表，比如:
-    ["CANIDS (Canines) - Dogs", "CANIDS (Canines) - Wolves", ...]
+    将 {分类: [物种列表]} 展开为 ["分类 - 物种"] 形式的扁平列表
     """
     result = []
-    for category, species_list in map_dict.items():
+    for category, species_list in map_data.items():
         for sp in species_list:
             result.append(f"{category} - {sp}")
     return sorted(result)
 
-ALL_FURRY_SPECIES = flatten_species(furry_species_map)
+ALL_FURRY_SPECIES = flatten_furry_species(furry_map)
+
+# 读取 Gender 细节长文本 (记忆库)
+try:
+    with open("gender_details.txt", "r", encoding="utf-8") as gd_file:
+        GENDER_DETAILS_TEXT = gd_file.read()
+except:
+    GENDER_DETAILS_TEXT = (
+        "Gender conversion rules are missing. Please provide gender_details.txt."
+    )
 
 ##############################################################################
-# 2. 核心：调用 GPT 或 DeepSeek 生成描述 & 翻译
+# 2. 核心函数：根据选择调用 GPT 或 DeepSeek
 ##############################################################################
-def generate_transformed_prompt(prompt, gender_option, furry_species, api_mode, api_key):
+
+def generate_description_with_tags(prompt, gender_option, furry_species, api_mode, api_key):
     """
-    1) 构造 tags（包括性别/物种）
-    2) 选择 GPT / DeepSeek 调用
-    3) 返回生成的描述
+    1) 构造 tags（包含 gender/furry/base_prompt）。
+    2) 调用 GPT 或 DeepSeek，带上记忆库信息 (GENDER_DETAILS_TEXT) 作为系统提示。
+    3) 返回 (tags + 自然语言描述) 的输出形式。
     """
+
+    if not api_key:
+        return "Error: No API Key provided."
+
+    # 组装 tags
     tags = {}
     if gender_option == "Trans_to_Male":
         tags["gender"] = "male"
@@ -52,61 +77,65 @@ def generate_transformed_prompt(prompt, gender_option, furry_species, api_mode,
 
     tags["base_prompt"] = prompt
 
-    # 2. 根据选择调用 GPT / DeepSeek
+    # 确定 base_url + model
     if api_mode == "GPT":
-        # GPT
         base_url = None
-        model_name = "gpt-3.5-turbo"  # 你可改成 "gpt-4" 等
+        model_name = "gpt-3.5-turbo"  # or "gpt-4", "gpt-4o", etc.
     else:
         # DeepSeek
         base_url = "https://api.deepseek.com"
         model_name = "deepseek-chat"
 
-    # 创建客户端
-    if not api_key:
-        return "Error: API Key not provided."
-
+    # 创建 OpenAI Client
     client = OpenAI(api_key=api_key)
     if base_url:
         client.base_url = base_url
 
-    # 拼出文字供对话
-    tag_desc = "\n".join([f"{k}: {v}" for k, v in tags.items() if v])
+    # 将tags拼成便于阅读的字符串
+    tags_str = "\n".join([f"{k}: {v}" for k, v in tags.items() if v])
+
+    # 准备对话消息：把 gender_details 放在系统提示中，以便 AI 参考
+    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 obey the following gender transformation & furry rules:\n\n"
+        f"{GENDER_DETAILS_TEXT}\n\n"
+        "After forming your final description, return it in no more than five sentences. Thank you!"
+    )
 
     try:
-        # 发起 chat.completions.create()
         response = client.chat.completions.create(
             model=model_name,
             messages=[
+                {"role": "system", "content": system_prompt},
                 {
-                    "role": "system",
+                    "role": "user",
                     "content": (
-                        "You are a creative assistant that generates detailed and imaginative scene descriptions "
-                        "for AI generation prompts. Focus on the details provided and incorporate them into a "
-                        "cohesive narrative. Use at least three sentences but no more than five sentences."
+                        f"Here are the tags:\n{tags_str}\n"
+                        f"Please generate a vivid, imaginative scene description."
                     ),
                 },
-                {
-                    "role": "user",
-                    "content": f"Here are the tags:\n{tag_desc}\nPlease generate a vivid, imaginative scene description.",
-                },
-            ]
+            ],
         )
-        return response.choices[0].message.content.strip()
+        description = response.choices[0].message.content.strip()
+
+        # 输出形式：(tags + 自然语言描述)
+        output_text = f"=== Tags ===\n{tags_str}\n\n=== Description ===\n{description}"
+        return output_text
+
     except Exception as e:
         return f"{api_mode} generation failed. Error: {e}"
 
-
-def translate_prompt_text(text, target_language, api_mode, api_key):
+def translate_text(text, translate_language, api_mode, api_key):
     """
-    调用 GPT / DeepSeek 做翻译，简化写法：同样只需改 model/base_url
+    仅做一次简单翻译。若不需要翻译可以省去。也可用系统提示让 AI 翻译。
     """
     if not api_key:
-        return "Error: API Key not provided."
-
+        return "Error: No API Key provided."
     if not text.strip():
         return ""
 
+    # GPT vs DeepSeek
     if api_mode == "GPT":
         base_url = None
         model_name = "gpt-3.5-turbo"
@@ -118,8 +147,8 @@ def translate_prompt_text(text, target_language, api_mode, api_key):
     if base_url:
         client.base_url = base_url
 
+    system_prompt = f"You are a professional translator. Translate the following text to {translate_language}:"
     try:
-        system_prompt = f"You are a professional translator. Translate the following text to {target_language}:"
         resp = client.chat.completions.create(
             model=model_name,
             messages=[
@@ -134,24 +163,26 @@ def translate_prompt_text(text, target_language, api_mode, api_key):
 ##############################################################################
 # 3. Gradio 界面
 ##############################################################################
-def build_app():
+def build_interface():
     with gr.Blocks() as demo:
-        gr.Markdown("## Prompt TransTool - GPT/DeepSeek 性别物种转换")
+        gr.Markdown("## Prompt Transformer (GPT / DeepSeek) - (tags + 自然语言描述)")
 
         with gr.Row():
             with gr.Column():
+                # 选择 API
                 api_mode = gr.Radio(
-                    label="选择 API（GPT / DeepSeek）",
+                    label="选择API (GPT or DeepSeek)",
                     choices=["GPT", "DeepSeek"],
                     value="GPT",
                 )
                 api_key = gr.Textbox(
-                    label="API 密钥 (API Key)",
+                    label="API密钥 (API Key)",
                     type="password",
-                    placeholder="请输入 GPT 或 DeepSeek 的 API 密钥"
+                    placeholder="在此输入 GPT / DeepSeek 的API Key"
                 )
+                # 性别 / Furry
                 gender_option = gr.Radio(
-                    label="转换目标 (Gender / Furry)",
+                    label="转换目标",
                     choices=[
                         "Trans_to_Male",
                         "Trans_to_Female",
@@ -161,60 +192,62 @@ def build_app():
                     ],
                     value="Trans_to_Male",
                 )
-                furry_species_box = gr.Dropdown(
-                    label="Furry 物种 (Furry Species)",
+                furry_species = gr.Dropdown(
+                    label="Furry 物种选择",
                     choices=ALL_FURRY_SPECIES,
                     value=None,
                     visible=False
                 )
-                def show_furry_spec(g):
-                    return gr.update(visible=(g == "Trans_to_Furry"))
-                gender_option.change(show_furry_spec, inputs=[gender_option], outputs=[furry_species_box])
+
+                def show_furry_species(choice):
+                    return gr.update(visible=(choice == "Trans_to_Furry"))
+
+                gender_option.change(show_furry_species, inputs=[gender_option], outputs=[furry_species])
 
             with gr.Column():
-                prompt_input = gr.Textbox(
+                user_prompt = gr.Textbox(
                     label="提示词 (Prompt)",
-                    lines=5,
-                    placeholder="示例：一位穿红色连衣裙的少女在花园中..."
+                    lines=4,
+                    placeholder="示例：一位穿着蓝色长裙的少女，坐在海边..."
                 )
-                gen_output = gr.Textbox(
-                    label="转换后 (Transformed Prompt)",
-                    lines=6
+                output_tags_and_desc = gr.Textbox(
+                    label="(tags + 自然语言描述)",
+                    lines=10
                 )
 
-        # 翻译
         with gr.Row():
             translate_language = gr.Dropdown(
                 label="翻译语言 (Translation Language)",
                 choices=["English", "Chinese", "Japanese", "French", "German", "Spanish"],
-                value="English",
+                value="English"
             )
             translate_output = gr.Textbox(
-                label="翻译结果 (Translation Result)",
-                lines=6
+                label="翻译结果",
+                lines=10
             )
 
-        def on_generate(prompt, gender, furry, mode, key, lang):
-            # 1) 生成转换后提示词
-            transformed = generate_transformed_prompt(prompt, gender, furry, mode, key)
-            # 2) 翻译
-            translated = translate_prompt_text(transformed, lang, mode, key)
-            return transformed, translated
+        # 点击生成 -> 同时调用生成描述 & 翻译
+        def on_generate(prompt, gender, f_species, mode, key, lang):
+            # 1. 生成 (tags + 自然语言描述)
+            result_text = generate_description_with_tags(prompt, gender, f_species, mode, key)
+            # 2. 翻译
+            translated = translate_text(result_text, lang, mode, key)
+            return result_text, translated
 
-        prompt_input.submit(
+        user_prompt.submit(
             fn=on_generate,
-            inputs=[prompt_input, gender_option, furry_species_box, api_mode, api_key, translate_language],
-            outputs=[gen_output, translate_output],
+            inputs=[user_prompt, gender_option, furry_species, api_mode, api_key, translate_language],
+            outputs=[output_tags_and_desc, translate_output]
         )
-        btn = gr.Button("生成 / Generate")
-        btn.click(
+        generate_btn = gr.Button("生成 / Generate")
+        generate_btn.click(
             fn=on_generate,
-            inputs=[prompt_input, gender_option, furry_species_box, api_mode, api_key, translate_language],
-            outputs=[gen_output, translate_output],
+            inputs=[user_prompt, gender_option, furry_species, api_mode, api_key, translate_language],
+            outputs=[output_tags_and_desc, translate_output]
         )
 
     return demo
 
 if __name__ == "__main__":
-    demo = build_app()
+    demo = build_interface()
     demo.launch()