新增角色管理、世界观设定、章节管理和AI工具调用功能

- 角色管理：CRUD API + 卡片网格UI，每个角色约200字描述
- 世界观设定：单篇长文编辑器，建议500字以上
- 章节管理：CRUD + 排序 API，左右分栏编辑器，单章5000字上限
- AI工具调用：支持工具审批流程和结构化工具调用
- 小说详情页新增章节、角色、世界观入口按钮

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

backend/app/routers/chat.py

@@ -6,19 +6,78 @@ from fastapi.responses import StreamingResponse
 from sqlmodel import Session, select, func
 
 from ..database import get_session, engine
-from ..models import AIConfig, ChatMessage
+from ..models import AIConfig, ChatMessage, Novel
 from ..schemas import ChatRequest, ChatMessageRead, ChatMessageList
-from ..services.ai_provider import stream_chat
+from ..services.ai_provider import (
+    stream_chat, build_assistant_message, build_tool_results_messages, ToolCall,
+)
+from ..services.tools import get_openai_tools, get_anthropic_tools, execute_tool
 
 router = APIRouter(prefix="/api/chat", tags=["chat"])
 
+# 最大工具调用轮次
+MAX_TOOL_ROUNDS = 8
+
+# 工具名称到中文描述
+TOOL_LABELS: dict[str, str] = {
+    "list_outlines": "查询大纲",
+    "create_outline": "创建大纲",
+    "update_outline": "更新大纲",
+    "delete_outline": "删除大纲",
+    "get_world_setting": "查询世界观",
+    "save_world_setting": "保存世界观",
+}
+
+
+def _build_system_prompt(
+    novel_id: int | None,
+    session: Session,
+    page_context: str | None = None,
+    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'}",
+    ]
+
+    if page_context:
+        parts.append(f"\n用户当前正在查看：{page_context}。")
+
+    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。"
+        )
+
+    return "\n".join(parts)
+
+
+def _get_tools(provider: str) -> list[dict]:
+    if provider == "anthropic":
+        return get_anthropic_tools()
+    return get_openai_tools()
+
+
+def _sse(data: dict) -> str:
+    return f"data: {json.dumps(data, ensure_ascii=False)}\n\n"
+
 
 @router.post("/stream")
 async def chat_stream(
     data: ChatRequest,
     session: Session = Depends(get_session),
 ):
-    """SSE 流式对话端点"""
+    """SSE 流式对话端点，支持 tool calling + 用户审批"""
     config = session.exec(select(AIConfig)).first()
     if not config or not config.api_key:
         return StreamingResponse(
@@ -26,53 +85,120 @@ async def chat_stream(
             media_type="text/event-stream",
         )
 
-    # 保存用户消息
-    user_msg = data.messages[-1] if data.messages else None
-    if user_msg and user_msg.role == "user":
-        db_msg = ChatMessage(
-            novel_id=data.novel_id,
-            role="user",
-            content=user_msg.content,
-        )
-        session.add(db_msg)
-        session.commit()
+    # 保存用户消息（仅首次请求，续传审批时不保存）
+    if not data.pending_tool_calls:
+        user_msg = data.messages[-1] if data.messages else None
+        if user_msg and user_msg.role == "user":
+            db_msg = ChatMessage(
+                novel_id=data.novel_id,
+                role="user",
+                content=user_msg.content,
+            )
+            session.add(db_msg)
+            session.commit()
 
     # 构建消息列表
     messages = [{"role": m.role, "content": m.content} for m in data.messages]
 
-    # 构建上下文摘要（前端展示用）
-    context_preview = [{"role": m["role"], "content": m["content"][:200]} for m in messages]
+    # 构建上下文
+    use_tools = bool(data.novel_id and data.tools_enabled)
+    system_prompt = _build_system_prompt(
+        data.novel_id, session, data.page_context, use_tools
+    )
+    tools = _get_tools(config.provider) if use_tools else None
 
     async def generate():
-        # 先发送上下文预览
-        yield f"data: {json.dumps({'context': context_preview})}\n\n"
+        nonlocal messages
+
+        full_response = data.assistant_text or ""
+        usage_info: dict = {}
 
-        full_response = ""
-        usage_info = {}
         try:
-            async for event in stream_chat(config, messages):
-                if event.text:
-                    full_response += event.text
-                    yield f"data: {json.dumps({'content': event.text})}\n\n"
-                if event.usage:
-                    # 累加usage
-                    for k, v in event.usage.items():
-                        if v:
-                            usage_info[k] = usage_info.get(k, 0) + v
+            # ── 阶段一：如果有待审批的工具调用，先执行它们 ──
+            if data.pending_tool_calls:
+                tool_calls = [
+                    ToolCall(id=tc.id, name=tc.name, arguments=tc.arguments)
+                    for tc in data.pending_tool_calls
+                ]
+
+                # 构建 assistant 消息（含工具调用）
+                assistant_msg = build_assistant_message(
+                    config.provider, data.assistant_text or "", tool_calls
+                )
+                messages.append(assistant_msg)
+
+                # 执行每个工具，发送结果
+                tool_results = []
+                for tc in 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})
+                    yield _sse({"tool_result": {
+                        "name": tc.name,
+                        "label": label,
+                        "result": result,
+                    }})
+
+                # 追加工具结果消息
+                result_msgs = build_tool_results_messages(config.provider, tool_results)
+                messages.extend(result_msgs)
+
+            # ── 阶段二：LLM 循环 ──
+            for _round in range(MAX_TOOL_ROUNDS):
+                round_text = ""
+                round_tool_calls = []
+
+                async for event in stream_chat(config, messages, system_prompt, tools):
+                    if event.text:
+                        round_text += event.text
+                        yield _sse({"content": event.text})
+                    if event.usage:
+                        for k, v in event.usage.items():
+                            if v:
+                                usage_info[k] = usage_info.get(k, 0) + v
+                    if event.tool_calls:
+                        round_tool_calls = event.tool_calls
+
+                # 没有工具调用 → 完成
+                if not round_tool_calls:
+                    full_response += round_text
+                    break
+
+                # 有工具调用 → 暂停，发给前端审批
+                full_response += round_text
+                calls_data = [
+                    {
+                        "id": tc.id,
+                        "name": tc.name,
+                        "label": TOOL_LABELS.get(tc.name, tc.name),
+                        "arguments": tc.arguments,
+                    }
+                    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
+
         except Exception as e:
-            yield f"data: {json.dumps({'error': str(e)})}\n\n"
+            yield _sse({"error": str(e)})
         finally:
-            # 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 f"data: {json.dumps({'done': True, 'usage': usage_info or None})}\n\n"
+            pass
+
+        # 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(
         generate(),
@@ -85,8 +211,8 @@ async def chat_stream(
 
 
 async def _error_stream(message: str):
-    yield f"data: {json.dumps({'error': message})}\n\n"
-    yield f"data: {json.dumps({'done': True})}\n\n"
+    yield _sse({"error": message})
+    yield _sse({"done": True})
 
 
 @router.get("/messages", response_model=ChatMessageList)
@@ -108,7 +234,6 @@ def list_messages(
     items = session.exec(
         query.order_by(ChatMessage.created_at.desc()).limit(limit)
     ).all()
-    # 返回时按时间正序
     items = list(reversed(items))
     return ChatMessageList(
         items=[ChatMessageRead.model_validate(m, from_attributes=True) for m in items],