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修复embedding失误导入成llm的问题

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This commit is contained in:
YILING0013
2025-02-16 23:10:32 +08:00
parent ba10e6dd66
commit f5691f268f
4 changed files with 143 additions and 26 deletions
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novel_generator/chapter.py
+70 -15
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@@ -1,4 +1,4 @@
#novel_generator/chapter.py
# novel_generator/chapter.py
# -*- coding: utf-8 -*-
"""
章节草稿生成及获取历史章节文本、短期摘要等
@@ -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。
- 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。
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。
"""
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
embedding_adapter = create_llm_adapter(
interface_format=embedding_interface_format,
base_url=embedding_url,
model_name=embedding_model_name,
api_key=embedding_api_key,
temperature=temperature,
max_tokens=max_tokens,
timeout=timeout
from embedding_adapters import create_embedding_adapter # 避免循环依赖
embedding_adapter = create_embedding_adapter(
embedding_interface_format,
embedding_api_key,
embedding_url,
embedding_model_name
)
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 -8
View File
@@ -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(
interface_format=embedding_interface_format,
base_url=embedding_url,
model_name=embedding_model_name,
api_key=embedding_api_key,
temperature=temperature,
max_tokens=max_tokens,
timeout=timeout
embedding_adapter=create_embedding_adapter(
embedding_interface_format,
embedding_api_key,
embedding_url,
embedding_model_name
),
new_chapter=chapter_text,
filepath=filepath
novel_generator/knowledge.py
+1 -1
View File
@@ -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
+66 -2
View File
@@ -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...")
draft_text = generate_chapter_draft(
self.safe_log(f"生成第{chap_num}章草稿：准备生成请求提示词...")
# 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))