引入二级大纲功能，新增父子节点关系及子节点排序，同时调整API与UI以支持嵌套大纲管理

2026-03-22 16:53:33 +08:00
parent 20c759150a
commit 098ff4e16d
33 changed files with 2516 additions and 381 deletions
--- a/backend/app/routers/chat.py
+++ b/backend/app/routers/chat.py
@@ -9,7 +9,8 @@ from ..database import get_session, engine
 from ..models import AIConfig, ChatMessage, Novel
 from ..schemas import ChatRequest, ChatMessageRead, ChatMessageList
 from ..services.ai_provider import (
-    stream_chat, build_assistant_message, build_tool_results_messages, ToolCall,
+    stream_chat, simple_completion,
+    build_assistant_message, build_tool_results_messages, ToolCall,
 )
 from ..services.tools import get_openai_tools, get_anthropic_tools, execute_tool

@@ -20,12 +21,23 @@ MAX_TOOL_ROUNDS = 8

 # 工具名称到中文描述
 TOOL_LABELS: dict[str, str] = {
+    "get_novel_info": "查看小说信息",
+    "update_novel_info": "更新小说信息",
    "list_outlines": "查询大纲",
    "create_outline": "创建大纲",
    "update_outline": "更新大纲",
    "delete_outline": "删除大纲",
+    "reorder_outlines": "调整大纲排序",
    "get_world_setting": "查询世界观",
    "save_world_setting": "保存世界观",
+    "list_characters": "查询角色",
+    "create_character": "创建角色",
+    "update_character": "更新角色",
+    "delete_character": "删除角色",
+    "list_chapters": "查询章节",
+    "create_chapter": "创建章节",
+    "update_chapter": "更新章节",
+    "delete_chapter": "删除章节",
 }


@@ -36,28 +48,50 @@ def _build_system_prompt(
    tools_enabled: bool = False,
 ) -> str:
    """根据小说上下文和用户所在页面构建 system prompt"""
-    base = "你是一个专业的小说创作助手。"
-    if not novel_id:
-        return base
-
-    novel = session.get(Novel, novel_id)
-    if not novel:
-        return base
-
    parts = [
-        f"你是一个专业的小说创作助手，当前正在协助创作《{novel.title}》。",
-        f"小说简介：{novel.description or '暂无'}",
+        "你是 Writing Red Dot 写作助手，专注于小说创作领域。",
+        "你擅长：构思情节、塑造角色、打磨文笔、设计世界观、规划大纲结构。",
    ]

+    if novel_id:
+        novel = session.get(Novel, novel_id)
+        if novel:
+            parts.append(f"\n当前小说：《{novel.title}》（ID: {novel.id}）")
+            parts.append(f"小说简介：{novel.description or '暂无'}")
+
    if page_context:
-        parts.append(f"\n用户当前正在查看：{page_context}。")
+        parts.append(f"\n用户当前正在查看：{page_context}。请结合当前页面场景提供针对性建议。")

    if tools_enabled:
        parts.append(
-            "\n你可以使用工具来查看和管理大纲、世界观设定。"
-            "\n当用户要求查看、添加、修改或删除大纲或世界观时，请使用相应的工具。"
-            "\n执行完工具操作后，请向用户简要说明操作结果。"
+            "\n## 你的工具能力\n"
+            "你是一个具备工具调用能力的写作助手。你拥有以下专用工具，没有其他任何工具：\n"
+            "\n### 小说信息\n"
+            "1. get_novel_info — 查看当前小说的标题、简介等基础信息\n"
+            "2. update_novel_info — 修改小说标题或简介\n"
+            "\n### 大纲管理\n"
+            "3. list_outlines — 列出所有大纲节点\n"
+            "4. create_outline — 创建新的大纲节点（需要提供摘要，可选详情和父节点ID）\n"
+            "5. update_outline — 更新指定大纲节点的摘要或详情\n"
+            "6. delete_outline — 删除指定大纲节点\n"
+            "\n### 世界观\n"
+            "7. get_world_setting — 获取世界观设定内容\n"
+            "8. save_world_setting — 保存或更新世界观设定\n"
+            "\n### 角色管理\n"
+            "9. list_characters — 列出所有角色\n"
+            "10. create_character — 创建新角色（需要提供名称，可选描述）\n"
+            "11. update_character — 更新指定角色的名称或描述\n"
+            "12. delete_character — 删除指定角色\n"
+            "\n### 章节管理\n"
+            "13. list_chapters — 列出所有章节\n"
+            "14. create_chapter — 创建新章节（需要提供标题，可选正文）\n"
+            "15. update_chapter — 更新指定章节的标题或正文\n"
+            "16. delete_chapter — 删除指定章节\n"
+            "\n当用户询问你有哪些工具或能力时，请据实回答上述工具。"
+            "\n当用户要求查看或修改小说信息、大纲、世界观、角色或章节时，请主动使用相应工具完成操作，并简要说明结果。"
        )
+        if not novel_id:
+            parts.append("\n注意：工具操作需要关联到具体小说。如果用户需要使用工具，请提示他们先进入某本小说。")

    return "\n".join(parts)

@@ -72,6 +106,23 @@ def _sse(data: dict) -> str:
    return f"data: {json.dumps(data, ensure_ascii=False)}\n\n"


+def _save_assistant_message(novel_id: int | None, full_response: str, tool_call_logs: list[str]):
+    """保存 AI 回复到 DB（含工具调用摘要）。在 finally 中调用，确保断连也能保存。"""
+    save_content = full_response
+    if tool_call_logs:
+        tool_summary = "\n".join(tool_call_logs)
+        save_content = f"[以下操作已执行]\n{tool_summary}\n\n{full_response}"
+    if save_content.strip():
+        with Session(engine) as s:
+            ai_msg = ChatMessage(
+                novel_id=novel_id,
+                role="assistant",
+                content=save_content,
+            )
+            s.add(ai_msg)
+            s.commit()
+
+
@router.post("/stream")
 async def chat_stream(
    data: ChatRequest,
@@ -101,7 +152,7 @@ async def chat_stream(
    messages = [{"role": m.role, "content": m.content} for m in data.messages]

    # 构建上下文
-    use_tools = bool(data.novel_id and data.tools_enabled)
+    use_tools = bool(data.tools_enabled)
    system_prompt = _build_system_prompt(
        data.novel_id, session, data.page_context, use_tools
    )
@@ -112,6 +163,8 @@ async def chat_stream(

        full_response = data.assistant_text or ""
        usage_info: dict = {}
+        # 记录本次对话中的工具调用摘要（用于保存到 DB）
+        tool_call_logs: list[str] = []

        try:
            # ── 阶段一：如果有待审批的工具调用，先执行它们 ──
@@ -133,6 +186,7 @@ async def chat_stream(
                    label = TOOL_LABELS.get(tc.name, tc.name)
                    result = execute_tool(tc.name, tc.arguments, data.novel_id)
                    tool_results.append({"id": tc.id, "result": result})
+                    tool_call_logs.append(f"[工具调用: {label}] 参数: {json.dumps(tc.arguments, ensure_ascii=False)} → 结果: {result}")
                    yield _sse({"tool_result": {
                        "name": tc.name,
                        "label": label,
@@ -164,7 +218,7 @@ async def chat_stream(
                    full_response += round_text
                    break

-                # 有工具调用 → 暂停，发给前端审批
+                # 有工具调用
                full_response += round_text
                calls_data = [
                    {
@@ -175,29 +229,48 @@ async def chat_stream(
                    }
                    for tc in round_tool_calls
                ]
-                yield _sse({
-                    "tool_calls_pending": calls_data,
-                    "assistant_text": full_response,
-                })
-                # 标记为待审批，前端需要续传
-                yield _sse({"done": True, "pending": True, "usage": usage_info or None})
-                return  # 暂停，不保存到 DB
+
+                if data.auto_approve_tools:
+                    # 自动执行模式：直接执行工具，不暂停
+                    yield _sse({"tool_calls_auto": calls_data})
+
+                    assistant_msg = build_assistant_message(
+                        config.provider, full_response, round_tool_calls
+                    )
+                    messages.append(assistant_msg)
+
+                    tool_results = []
+                    for tc in round_tool_calls:
+                        label = TOOL_LABELS.get(tc.name, tc.name)
+                        result = execute_tool(tc.name, tc.arguments, data.novel_id)
+                        tool_results.append({"id": tc.id, "result": result})
+                        tool_call_logs.append(f"[工具调用: {label}] 参数: {json.dumps(tc.arguments, ensure_ascii=False)} → 结果: {result}")
+                        yield _sse({"tool_result": {
+                            "name": tc.name,
+                            "label": label,
+                            "result": result,
+                        }})
+
+                    result_msgs = build_tool_results_messages(config.provider, tool_results)
+                    messages.extend(result_msgs)
+                    # 继续循环，让 LLM 基于工具结果生成回复
+                    continue
+                else:
+                    # 审批模式：暂停，发给前端审批
+                    yield _sse({
+                        "tool_calls_pending": calls_data,
+                        "assistant_text": full_response,
+                    })
+                    yield _sse({"done": True, "pending": True, "usage": usage_info or None})
+                    return  # 暂停，不保存到 DB

        except Exception as e:
            yield _sse({"error": str(e)})
        finally:
-            pass
+            # 无论连接是否断开，都保存已有的回复和工具调用到 DB
+            # 这确保刷新页面后 loadHistory 能恢复正确状态
+            _save_assistant_message(data.novel_id, full_response, tool_call_logs)

-        # 正常完成：保存 AI 回复
-        if full_response:
-            with Session(engine) as s:
-                ai_msg = ChatMessage(
-                    novel_id=data.novel_id,
-                    role="assistant",
-                    content=full_response,
-                )
-                s.add(ai_msg)
-                s.commit()
        yield _sse({"done": True, "usage": usage_info or None})

    return StreamingResponse(
@@ -255,3 +328,84 @@ def clear_messages(
    for msg in messages:
        session.delete(msg)
    session.commit()
+
+
+# 保留最近对话轮次数（每轮 = 1 user + 1 assistant）
+KEEP_RECENT_ROUNDS = 2
+
+
+@router.post("/compress")
+async def compress_context(
+    novel_id: int | None = Query(default=None),
+    session: Session = Depends(get_session),
+):
+    """压缩对话上下文：用 LLM 总结旧消息，仅保留最近几轮对话。"""
+    config = session.exec(select(AIConfig)).first()
+    if not config or not config.api_key:
+        return {"error": "请先配置AI服务"}
+
+    # 查询所有消息（按时间正序）
+    query = select(ChatMessage)
+    if novel_id is not None:
+        query = query.where(ChatMessage.novel_id == novel_id)
+    else:
+        query = query.where(ChatMessage.novel_id.is_(None))  # type: ignore
+    all_msgs = list(session.exec(query.order_by(ChatMessage.created_at)).all())
+
+    if len(all_msgs) <= KEEP_RECENT_ROUNDS * 2:
+        return {"compressed": False, "reason": "消息太少，无需压缩"}
+
+    # 分割：旧消息（需要压缩）+ 最近消息（保留原文）
+    keep_count = KEEP_RECENT_ROUNDS * 2
+    old_msgs = all_msgs[:-keep_count]
+    recent_msgs = all_msgs[-keep_count:]
+
+    # 检查第一条旧消息是否已是摘要（避免重复压缩无效内容）
+    # 构建需要总结的对话文本
+    conversation_text = ""
+    for msg in old_msgs:
+        role_label = "用户" if msg.role == "user" else "AI助手"
+        content = msg.content
+        # 如果是已压缩的摘要，标注出来
+        if content.startswith("[对话摘要]"):
+            conversation_text += f"[之前的摘要]{content[5:]}\n\n"
+        else:
+            conversation_text += f"{role_label}: {content}\n\n"
+
+    # 调用 LLM 生成摘要
+    summary_prompt = (
+        "你是一个对话摘要助手。请将以下对话历史压缩为简洁的摘要，保留关键信息：\n"
+        "1. 用户提出的核心需求和决策\n"
+        "2. AI 执行的重要操作及结果（如创建/修改了哪些大纲、角色、章节等）\n"
+        "3. 达成的共识和待办事项\n\n"
+        "只输出摘要内容，不要加前缀或解释。用简洁的条目列表形式。"
+    )
+    summary_messages = [
+        {"role": "user", "content": f"请压缩以下对话历史：\n\n{conversation_text}"}
+    ]
+
+    try:
+        summary = await simple_completion(config, summary_messages, summary_prompt)
+    except Exception as e:
+        return {"error": f"摘要生成失败: {str(e)}"}
+
+    # 删除旧消息
+    for msg in old_msgs:
+        session.delete(msg)
+
+    # 插入摘要消息（时间设为最早保留消息之前）
+    summary_msg = ChatMessage(
+        novel_id=novel_id,
+        role="assistant",
+        content=f"[对话摘要]\n{summary}",
+        created_at=recent_msgs[0].created_at,
+    )
+    session.add(summary_msg)
+    session.commit()
+
+    return {
+        "compressed": True,
+        "removed_count": len(old_msgs),
+        "kept_count": len(recent_msgs),
+        "summary_length": len(summary),
+    }