修复embedding失误导入成llm的问题

novel_generator/chapter.py

@@ -68,7 +68,7 @@ def summarize_recent_chapters(
         short_summary = response_text
     return (short_summary, next_chapter_keywords)
 
-def generate_chapter_draft(
+def build_chapter_prompt(
     api_key: str,
     base_url: str,
     model_name: str,
@@ -91,10 +91,7 @@ def generate_chapter_draft(
     timeout: int = 600
 ) -> str:
     """
-    根据 novel_number 判断是否为第一章。
+    构造当前章节的请求提示词，不调用 LLM，仅返回构造好的提示词字符串。
-    - 若是第一章，则使用 first_chapter_draft_prompt
-    - 否则使用 next_chapter_draft_prompt
-    最终将生成文本存入 chapters/chapter_{novel_number}.txt。
     """
     arch_file = os.path.join(filepath, "Novel_architecture.txt")
     novel_architecture_text = read_file(arch_file)
@@ -155,15 +152,12 @@ def generate_chapter_draft(
                 else:
                     previous_chapter_excerpt = text_block
                 break
-        from llm_adapters import create_llm_adapter  # 避免循环依赖
+        from embedding_adapters import create_embedding_adapter  # 避免循环依赖
-        embedding_adapter = create_llm_adapter(
+        embedding_adapter = create_embedding_adapter(
-            interface_format=embedding_interface_format,
+            embedding_interface_format,
-            base_url=embedding_url,
+            embedding_api_key,
-            model_name=embedding_model_name,
+            embedding_url,
-            api_key=embedding_api_key,
+            embedding_model_name
-            temperature=temperature,
-            max_tokens=max_tokens,
-            timeout=timeout
         )
         retrieval_query = short_summary + " " + next_chapter_keywords
         relevant_context = get_relevant_context_from_vector_store(
@@ -195,6 +189,67 @@ def generate_chapter_draft(
             context_excerpt=relevant_context,
             previous_chapter_excerpt=previous_chapter_excerpt
         )
+    return prompt_text
+
+def generate_chapter_draft(
+    api_key: str,
+    base_url: str,
+    model_name: str,
+    filepath: str,
+    novel_number: int,
+    word_number: int,
+    temperature: float,
+    user_guidance: str,
+    characters_involved: str,
+    key_items: str,
+    scene_location: str,
+    time_constraint: str,
+    embedding_api_key: str,
+    embedding_url: str,
+    embedding_interface_format: str,
+    embedding_model_name: str,
+    embedding_retrieval_k: int = 2,
+    interface_format: str = "openai",
+    max_tokens: int = 2048,
+    timeout: int = 600,
+    custom_prompt_text: str = None  # 新增参数，若不为 None，则使用用户编辑后的提示词
+) -> str:
+    """
+    根据 novel_number 判断是否为第一章。
+    - 若是第一章，则使用 first_chapter_draft_prompt
+    - 否则使用 next_chapter_draft_prompt
+    若 custom_prompt_text 提供，则以此作为提示词进行生成。
+    最终将生成文本存入 chapters/chapter_{novel_number}.txt。
+    """
+    # 构造提示词：若用户提供了编辑后的提示词，则使用之；否则构造默认提示词
+    if custom_prompt_text is None:
+        prompt_text = build_chapter_prompt(
+            api_key=api_key,
+            base_url=base_url,
+            model_name=model_name,
+            filepath=filepath,
+            novel_number=novel_number,
+            word_number=word_number,
+            temperature=temperature,
+            user_guidance=user_guidance,
+            characters_involved=characters_involved,
+            key_items=key_items,
+            scene_location=scene_location,
+            time_constraint=time_constraint,
+            embedding_api_key=embedding_api_key,
+            embedding_url=embedding_url,
+            embedding_interface_format=embedding_interface_format,
+            embedding_model_name=embedding_model_name,
+            embedding_retrieval_k=embedding_retrieval_k,
+            interface_format=interface_format,
+            max_tokens=max_tokens,
+            timeout=timeout
+        )
+    else:
+        prompt_text = custom_prompt_text
+
+    chapters_dir = os.path.join(filepath, "chapters")
+    os.makedirs(chapters_dir, exist_ok=True)
 
     llm_adapter = create_llm_adapter(
         interface_format=interface_format,

novel_generator/finalization.py

@@ -6,6 +6,7 @@
 import os
 import logging
 from llm_adapters import create_llm_adapter
+from embedding_adapters import create_embedding_adapter
 from prompt_definitions import summary_prompt, update_character_state_prompt
 from novel_generator.common import invoke_with_cleaning
 from utils import read_file, clear_file_content, save_string_to_txt
@@ -75,14 +76,11 @@ def finalize_chapter(
     save_string_to_txt(new_char_state, character_state_file)
 
     update_vector_store(
-        embedding_adapter=create_llm_adapter(
+        embedding_adapter=create_embedding_adapter(
-            interface_format=embedding_interface_format,
+            embedding_interface_format,
-            base_url=embedding_url,
+            embedding_api_key,
-            model_name=embedding_model_name,
+            embedding_url,
-            api_key=embedding_api_key,
+            embedding_model_name
-            temperature=temperature,
-            max_tokens=max_tokens,
-            timeout=timeout
         ),
         new_chapter=chapter_text,
         filepath=filepath

novel_generator/knowledge.py

@@ -68,7 +68,7 @@ def import_knowledge_file(
         logging.warning("知识库文件内容为空。")
         return
     paragraphs = advanced_split_content(content)
-    from llm_adapters import create_embedding_adapter
+    from embedding_adapters import create_embedding_adapter
     embedding_adapter = create_embedding_adapter(
         embedding_interface_format,
         embedding_api_key,

ui/generation_handlers.py

@@ -131,8 +131,11 @@ def generate_chapter_draft_ui(self):
             embedding_model_name = self.embedding_model_name_var.get().strip()
             embedding_k = self.safe_get_int(self.embedding_retrieval_k_var, 4)
 
-            self.safe_log(f"开始生成第{chap_num}章草稿...")
+            self.safe_log(f"生成第{chap_num}章草稿：准备生成请求提示词...")
-            draft_text = generate_chapter_draft(
+
+            # 调用新添加的 build_chapter_prompt 函数构造初始提示词
+            from novel_generator.chapter import build_chapter_prompt
+            prompt_text = build_chapter_prompt(
                 api_key=api_key,
                 base_url=base_url,
                 model_name=model_name,
@@ -154,6 +157,67 @@ def generate_chapter_draft_ui(self):
                 max_tokens=max_tokens,
                 timeout=timeout_val
             )
+
+            # 弹出可编辑提示词对话框，等待用户确认或取消
+            result = {"prompt": None}
+            event = threading.Event()
+
+            def create_dialog():
+                dialog = ctk.CTkToplevel(self.master)
+                dialog.title("当前章节请求提示词（可编辑）")
+                dialog.geometry("600x400")
+                text_box = ctk.CTkTextbox(dialog, wrap="word", font=("Microsoft YaHei", 12))
+                text_box.pack(fill="both", expand=True, padx=10, pady=10)
+                text_box.insert("0.0", prompt_text)
+                button_frame = ctk.CTkFrame(dialog)
+                button_frame.pack(pady=10)
+                def on_confirm():
+                    result["prompt"] = text_box.get("1.0", "end").strip()
+                    dialog.destroy()
+                    event.set()
+                def on_cancel():
+                    result["prompt"] = None
+                    dialog.destroy()
+                    event.set()
+                btn_confirm = ctk.CTkButton(button_frame, text="确认使用", font=("Microsoft YaHei", 12), command=on_confirm)
+                btn_confirm.pack(side="left", padx=10)
+                btn_cancel = ctk.CTkButton(button_frame, text="取消请求", font=("Microsoft YaHei", 12), command=on_cancel)
+                btn_cancel.pack(side="left", padx=10)
+                # 若用户直接关闭弹窗，则调用 on_cancel 处理
+                dialog.protocol("WM_DELETE_WINDOW", on_cancel)
+                dialog.grab_set()
+            self.master.after(0, create_dialog)
+            event.wait()  # 等待用户操作完成
+            edited_prompt = result["prompt"]
+            if edited_prompt is None:
+                self.safe_log("❌ 用户取消了草稿生成请求。")
+                return
+
+            self.safe_log("开始生成章节草稿...")
+            from novel_generator.chapter import generate_chapter_draft
+            draft_text = generate_chapter_draft(
+                api_key=api_key,
+                base_url=base_url,
+                model_name=model_name,
+                filepath=filepath,
+                novel_number=chap_num,
+                word_number=word_number,
+                temperature=temperature,
+                user_guidance=user_guidance,
+                characters_involved=char_inv,
+                key_items=key_items,
+                scene_location=scene_loc,
+                time_constraint=time_constr,
+                embedding_api_key=embedding_api_key,
+                embedding_url=embedding_url,
+                embedding_interface_format=embedding_interface_format,
+                embedding_model_name=embedding_model_name,
+                embedding_retrieval_k=embedding_k,
+                interface_format=interface_format,
+                max_tokens=max_tokens,
+                timeout=timeout_val,
+                custom_prompt_text=edited_prompt  # 使用用户编辑后的提示词
+            )
             if draft_text:
                 self.safe_log(f"✅ 第{chap_num}章草稿生成完成。请在左侧查看或编辑。")
                 self.master.after(0, lambda: self.show_chapter_in_textbox(draft_text))