Merge branch 'dhk-1' into 'master'
Dhk 1 See merge request knowledge-base-bj/deerflow-server!25
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董宏凯 committed
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@@ -32,6 +32,50 @@ ai_writing:
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---
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## 1.5 检索关键词数量
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素材专家的检索词数量由**用户在写作表单中指定**（「检索关键词数量」输入框，
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范围 `1~10`，默认 `6`）。数量越多素材越全面，但检索与排序更耗时。
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- 该参数随 `POST /api/ai-writing/start` 的 `keyword_count` 字段传入，写入 `AIWritingState.keyword_count`。
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- `researcher_node` 用它决定让 LLM 生成多少个检索词、并发检索多少个方向
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（`EXTRACT_KEYWORDS_USER` prompt 按该数量格式化，`search_keywords = keywords[:keyword_count]`）。
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- 非法值（缺省 / 越界 / 非数字）由前后端双重兜底：后端 `_resolve_keyword_count()`
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规整到 `[1, 10]`，越界回退默认 `6`。
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- 补充搜索（`re_search`）时用户额外添加的关键词不会被该上限截断。
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---
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## 1.6 素材总量上限
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素材收集专家最终保留的素材**总条数**由后端配置文件统一控制，并按检索词数**均分**到每个词。
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配置位置：`offline-backend-20260512/backend/config.yaml` 的 `ai_writing` 段：
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```yaml
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ai_writing:
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# 素材总量上限，范围 1~100，非法值回退 20
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max_materials: 20
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```
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均分规则 —— `每个检索词的检索条数 = ⌈ max_materials / 实际检索词数 ⌉`（向上取整）：
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| `max_materials` | 检索词数 | 每词检索条数 |
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|---|---|---|
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| 20 | 1 | 20 |
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| 20 | 2 | 10 |
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| 20 | 3 | 7（共 21，合并后截断到 20） |
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| 20 | 5 | 4 |
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- 各检索词按上表条数检索 → 合并去重 → 最终统一截断到 `max_materials`。
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- 向上取整是为了保证去重后素材数仍能接近上限；去重后实际条数可能略少于上限（不同词命中同一篇），属正常。
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- 与 [1.5](#15-检索关键词数量) 的关系：`keyword_count` 决定**搜几个词**，`max_materials` 决定**总共要多少条**，两者相除得到每词条数。
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- 涉及代码：`researcher.py` 的 `_resolve_max_materials()`（读配置 + 规整）与 `_per_keyword_limit()`（均分计算）。
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> `config.yaml` 支持热加载，改完一般无需重启后端。
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---
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## 2. 内网接口规格
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- **地址**：`http://10.106.57.180:7863/knowledge_base/search_docs_es`
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@@ -176,6 +220,17 @@ INTRANET_SOURCE_URL_BASE + recUuid
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「查看原文」地址前缀写在 `src/core/config/index.ts` 的 `INTRANET_SOURCE_URL_BASE`。
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若内网原文详情页地址有变，只改这一个常量即可。
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### 4.5 检索到的素材全是无关内容
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**现象**：素材卡片内容与写作意图完全不沾边。
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**排查**：检查后端日志里素材专家实际用的检索词。常见原因是模型把关键词提取
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提示词模板里的占位符（如「关键词1」「...」）当成真关键词去检索了。
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`researcher.py` 的 `_clean_keywords()` 已对此做防御：剔除 `关键词\d*` / `keyword\d*` /
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`...` 等占位符，全部被滤掉时回退为写作意图本身。若仍出现，检查
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`researcher_prompts.py` 的 `EXTRACT_KEYWORDS` 提示词是否又引入了易被误抄的示例占位符。
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---
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## 5. 联调上线步骤
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@@ -21,6 +21,8 @@ export async function startWritingSession(req: AIWritingRequest): Promise<string
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target_audience: req.targetAudience,
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word_count_target: req.wordCountTarget,
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model_name: req.modelName ?? '',
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keyword_count: req.keywordCount,
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writing_mode: req.writingMode,
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}),
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});
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if (!resp.ok) throw new Error(`启动失败: ${resp.status}`);
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@@ -105,6 +107,17 @@ function normalizeEvent(parsed: Record<string, unknown>): Partial<ProgressEvent>
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// outline
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if (out.outline) out.outline = normalizeOutline(out.outline);
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// blocked_sections（section_help await_user）
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if (Array.isArray(out.blocked_sections)) {
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out.blockedSections = out.blocked_sections.map((b: unknown) => {
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const o = b as Record<string, unknown>;
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return {
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sectionTitle: o.section_title ?? o.sectionTitle ?? '',
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reason: o.reason ?? '',
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};
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});
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}
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// draft_ready: 后端发 "title"/"markdown"，前端期望 draftTitle/draftMarkdown
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if ('markdown' in out && !out.draftMarkdown) out.draftMarkdown = out.markdown;
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if ('title' in out && !out.draftTitle) out.draftTitle = out.title;
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@@ -202,6 +215,10 @@ export async function resumeWriting(
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user_revision_notes: payload.userRevisionNotes ?? '',
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override_verdict: payload.overrideVerdict ?? false,
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selected_issue_indices: payload.selectedIssueIndices ?? null,
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section_decisions: (payload.sectionDecisions ?? []).map((d) => ({
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section_title: d.sectionTitle,
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decision: d.decision,
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})),
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}),
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});
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if (!resp.ok) throw new Error(`提交干预失败: ${resp.status}`);
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@@ -36,6 +36,8 @@ export function AIWritingForm({ onSubmit, disabled }: AIWritingFormProps) {
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const [articleType, setArticleType] = useState('analysis');
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const [audience, setAudience] = useState('普通读者');
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const [wordCountInput, setWordCountInput] = useState('800');
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const [keywordCountInput, setKeywordCountInput] = useState('6');
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const [strictMode, setStrictMode] = useState(false);
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const [modelName, setModelName] = useState('');
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const [models, setModels] = useState<ModelOption[]>([]);
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@@ -94,15 +96,28 @@ export function AIWritingForm({ onSubmit, disabled }: AIWritingFormProps) {
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}
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}
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// 检索关键词数量限定 1~10，非法值回退默认 6
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function handleKeywordCountBlur() {
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const num = parseInt(keywordCountInput, 10);
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if (isNaN(num)) {
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setKeywordCountInput('6');
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} else {
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setKeywordCountInput(String(Math.max(1, Math.min(10, num))));
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}
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}
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function handleSubmit(e: React.FormEvent) {
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e.preventDefault();
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if (!intent.trim()) return;
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const wordCount = Math.max(100, parseInt(wordCountInput, 10) || 800);
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const keywordCount = Math.max(1, Math.min(10, parseInt(keywordCountInput, 10) || 6));
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onSubmit({
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userIntent: intent.trim(),
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articleType,
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targetAudience: audience.trim() || '普通读者',
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wordCountTarget: wordCount,
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keywordCount,
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writingMode: strictMode ? 'strict' : 'loose',
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modelName: modelName || undefined,
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});
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}
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@@ -158,6 +173,42 @@ export function AIWritingForm({ onSubmit, disabled }: AIWritingFormProps) {
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</div>
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</div>
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<div className="space-y-1.5">
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<label className="text-xs font-medium text-muted-foreground">检索关键词数量（1~10）</label>
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<input
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type="number"
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min={1}
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max={10}
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step={1}
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className={INPUT_CLASS}
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placeholder="6"
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value={keywordCountInput}
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onChange={(e) => setKeywordCountInput(e.target.value)}
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onBlur={handleKeywordCountBlur}
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disabled={disabled}
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/>
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<p className="text-[11px] text-muted-foreground/70">
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素材收集专家用几个关键词检索，越多素材越全面但耗时更长。
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</p>
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</div>
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<div className="flex items-start gap-2 rounded-md border bg-muted/20 px-3 py-2">
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<input
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type="checkbox"
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id="strict-mode"
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checked={strictMode}
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onChange={(e) => setStrictMode(e.target.checked)}
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disabled={disabled}
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className="mt-0.5 size-3.5 shrink-0 accent-primary cursor-pointer"
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/>
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<label htmlFor="strict-mode" className="cursor-pointer select-none">
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<span className="text-xs font-medium text-foreground/80">严格依据素材写作</span>
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<p className="text-[11px] text-muted-foreground/70 mt-0.5 leading-relaxed">
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勾选后作家只依据检索素材写作，素材不足以支撑某章节时会暂停询问你；不勾选则可结合通用知识补充论述。
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</p>
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</label>
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</div>
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<div className="space-y-1.5">
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<label className="text-xs font-medium text-muted-foreground">目标读者</label>
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<input
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@@ -34,6 +34,7 @@ const STATUS_LABEL: Record<string, string> = {
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writing_outline: '作家规划大纲中…',
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awaiting_outline_confirm: '等待确认大纲',
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writing_draft: '作家写作中…',
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awaiting_section_help: '等待处理素材不足的章节',
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awaiting_draft_confirm: '等待确认草稿',
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reviewing: '编辑审核中…',
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awaiting_review_confirm: '等待处理编辑意见',
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@@ -425,6 +426,14 @@ export function AIWritingPanel() {
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<ReqRow label="目标字数">
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<span className="text-muted-foreground">{state.request.wordCountTarget} 字</span>
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</ReqRow>
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<ReqRow label="检索关键词数量">
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<span className="text-muted-foreground">{state.request.keywordCount} 个</span>
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</ReqRow>
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<ReqRow label="写作模式">
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<span className="text-muted-foreground">
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{state.request.writingMode === 'strict' ? '严格依据素材' : '宽松（可结合通用知识）'}
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</span>
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</ReqRow>
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{state.request.modelName && (
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<ReqRow label="写作模型">
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<span className="text-muted-foreground">{state.request.modelName}</span>
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@@ -58,6 +58,37 @@ function SectionThinking({ thinkingText, isDone }: { thinkingText: string; isDon
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);
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}
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/** 章节正文：把 `### 要点` 行渲染成小标题，其余按段落显示（流式纯文本，非完整 markdown 解析） */
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function SectionBody({ text, showCursor }: { text: string; showCursor: boolean }) {
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const lines = text.split('\n');
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return (
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<div className="m-0">
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{lines.map((line, i) => {
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// 严格模式下作家声明素材不足的哨兵行，不展示给用户
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if (line.includes('[[SECTION_BLOCKED]]')) return null;
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const heading = /^[ \t]*#{1,6}[ \t]+/.exec(line);
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if (heading) {
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return (
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<p key={i} className="text-xs font-semibold text-foreground mt-2 mb-1">
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{line.slice(heading[0].length)}
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</p>
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);
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}
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if (!line.trim()) return null; // 跳过空行，避免大段空白
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return (
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<p
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key={i}
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className="text-xs leading-relaxed text-foreground/90 whitespace-pre-wrap m-0 mb-1"
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>
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{line}
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</p>
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);
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})}
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{showCursor && <TypewriterCursor />}
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</div>
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);
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}
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export function DraftStreamingView({ title, sections }: DraftStreamingViewProps) {
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const bottomRef = useRef<HTMLDivElement>(null);
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@@ -91,11 +122,11 @@ export function DraftStreamingView({ title, sections }: DraftStreamingViewProps)
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{/* 该章节的思考过程（可折叠） */}
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<SectionThinking thinkingText={sec.thinkingText} isDone={sec.isDone} />
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{/* 正文内容 */}
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<p className="text-xs leading-relaxed text-foreground/90 whitespace-pre-wrap m-0">
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{sec.text}
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{sec.sectionIndex === activeSectionIdx && !sec.isDone && <TypewriterCursor />}
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</p>
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{/* 正文内容（### 要点行渲染为小标题） */}
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<SectionBody
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text={sec.text}
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showCursor={sec.sectionIndex === activeSectionIdx && !sec.isDone}
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/>
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</div>
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))}
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@@ -2,11 +2,14 @@ import { useRef, useState } from 'react';
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import {
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PauseCircle, CheckCircle2, RotateCcw, Search,
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RefreshCw, PenLine, ArrowRight, ShieldAlert, ClipboardEdit, SendHorizonal,
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Trash2, BookOpen,
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} from 'lucide-react';
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import { Button } from '@/components/ui/button';
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import { cn } from '@/lib/utils';
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import type {
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AIMaterial, AIOutline, ReviewResult, ReviewIssue,
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ProgressEvent, UserInterventionPayload,
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BlockedSection, SectionDecisionKind,
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} from '../../types/ai-writing';
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import { MaterialsCard } from './MaterialsCard';
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import { MaterialsToolbar } from './MaterialsToolbar';
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@@ -56,6 +59,16 @@ export function InterventionCard({
|
||||
);
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}
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|
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if (pausePoint === 'section_help') {
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return (
|
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<SectionHelpCard
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blockedSections={pauseEvent.blockedSections ?? []}
|
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onSubmit={onSubmit}
|
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disabled={disabled}
|
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/>
|
||||
);
|
||||
}
|
||||
|
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if (pausePoint === 'review_confirm') {
|
||||
return (
|
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<ReviewConfirmCard
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@@ -239,7 +252,12 @@ function OutlineConfirmCard({ outline: initialOutline, onSubmit, disabled }: Out
|
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const text = feedback.trim();
|
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if (!text) return;
|
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setSubmitting(true);
|
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await onSubmit({ action: 're_outline', outlineFeedback: text });
|
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// 带上卡片里的当前大纲，让 AI 在此基础上按要求增删/调整，而非从零重生成
|
||||
await onSubmit({
|
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action: 're_outline',
|
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outlineFeedback: text,
|
||||
editedOutline: editedOutline ?? undefined,
|
||||
});
|
||||
setSubmitting(false);
|
||||
}
|
||||
|
||||
@@ -547,3 +565,99 @@ function ReviewConfirmCard({ reviewResult, revisionCount, onSubmit, disabled }:
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
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// ── 素材不足求助 ──────────────────────────────────────────────────────────────
|
||||
|
||||
interface SectionHelpCardProps {
|
||||
blockedSections: BlockedSection[];
|
||||
onSubmit: (payload: UserInterventionPayload) => void;
|
||||
disabled?: boolean;
|
||||
}
|
||||
|
||||
const DECISION_OPTIONS: { value: SectionDecisionKind; label: string; icon: typeof Search }[] = [
|
||||
{ value: 'supplement', label: '补充检索素材', icon: Search },
|
||||
{ value: 'loose', label: '按通用知识续写', icon: BookOpen },
|
||||
{ value: 'delete', label: '删除该章节', icon: Trash2 },
|
||||
];
|
||||
|
||||
function SectionHelpCard({ blockedSections, onSubmit, disabled }: SectionHelpCardProps) {
|
||||
const [decisions, setDecisions] = useState<Record<string, SectionDecisionKind>>(
|
||||
() => Object.fromEntries(blockedSections.map((b) => [b.sectionTitle, 'supplement'])),
|
||||
);
|
||||
const [submitting, setSubmitting] = useState(false);
|
||||
|
||||
const hasSupplement = Object.values(decisions).some((d) => d === 'supplement');
|
||||
|
||||
async function handleSubmit() {
|
||||
setSubmitting(true);
|
||||
await onSubmit({
|
||||
action: 'section_help',
|
||||
sectionDecisions: blockedSections.map((b) => ({
|
||||
sectionTitle: b.sectionTitle,
|
||||
decision: decisions[b.sectionTitle] ?? 'supplement',
|
||||
})),
|
||||
});
|
||||
setSubmitting(false);
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="rounded-md border border-amber-200 bg-amber-50/50 dark:border-amber-900/40 dark:bg-amber-950/20 space-y-3 p-3">
|
||||
<div className="flex items-start gap-2">
|
||||
<ShieldAlert className="size-4 text-amber-500 shrink-0 mt-0.5" />
|
||||
<div>
|
||||
<p className="text-xs font-medium">部分章节素材不足，需要你决定</p>
|
||||
<p className="text-xs text-muted-foreground mt-0.5">
|
||||
严格依据素材模式下，以下 {blockedSections.length} 个章节缺少足够素材支撑写作。请为每个章节选择处理方式。
|
||||
</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div className="space-y-2">
|
||||
{blockedSections.map((b) => (
|
||||
<div key={b.sectionTitle} className="rounded-md border bg-background p-2.5 space-y-2">
|
||||
<div>
|
||||
<p className="text-xs font-medium">{b.sectionTitle}</p>
|
||||
<p className="text-[11px] text-muted-foreground mt-0.5">{b.reason}</p>
|
||||
</div>
|
||||
<div className="flex gap-1">
|
||||
{DECISION_OPTIONS.map((opt) => {
|
||||
const active = (decisions[b.sectionTitle] ?? 'supplement') === opt.value;
|
||||
const Icon = opt.icon;
|
||||
return (
|
||||
<button
|
||||
key={opt.value}
|
||||
type="button"
|
||||
disabled={disabled || submitting}
|
||||
onClick={() => setDecisions((p) => ({ ...p, [b.sectionTitle]: opt.value }))}
|
||||
className={cn(
|
||||
'flex-1 flex items-center justify-center gap-1 rounded px-1.5 py-1 text-[11px] border transition-colors',
|
||||
active
|
||||
? 'border-primary bg-primary/10 text-primary font-medium'
|
||||
: 'border-input text-muted-foreground hover:bg-muted/50',
|
||||
)}
|
||||
>
|
||||
<Icon className="size-3 shrink-0" />
|
||||
{opt.label}
|
||||
</button>
|
||||
);
|
||||
})}
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
|
||||
{hasSupplement && (
|
||||
<p className="text-[11px] text-amber-600 dark:text-amber-400">
|
||||
含「补充检索素材」的章节将触发重新检索并重新规划大纲，本轮其它选择不生效。
|
||||
</p>
|
||||
)}
|
||||
|
||||
<Button
|
||||
type="button" size="sm" className="w-full h-8 text-xs gap-1.5"
|
||||
onClick={handleSubmit} disabled={disabled || submitting}
|
||||
>
|
||||
<CheckCircle2 className="size-3.5" />提交并继续
|
||||
</Button>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -0,0 +1,192 @@
|
||||
import { useCallback, useEffect, useMemo, useState } from "react";
|
||||
import type { Editor } from "@tiptap/react";
|
||||
import { PanelLeftClose, PanelLeftOpen } from "lucide-react";
|
||||
|
||||
import { cn } from "@/lib/utils";
|
||||
import { useDocumentOutline } from "../../hooks/useDocumentOutline";
|
||||
import type { OutlineHeading } from "../../hooks/useDocumentOutline";
|
||||
|
||||
interface DraftOutlineSidebarProps {
|
||||
/** Tiptap 编辑器实例，用于提取标题并解析标题 DOM */
|
||||
editor: Editor | null;
|
||||
/** 文档滚动容器，点击目录项 / scroll-spy 时在其内部滚动与定位 */
|
||||
scrollEl: HTMLElement | null;
|
||||
}
|
||||
|
||||
/** 点击跳转时标题距容器顶部预留的间距（px） */
|
||||
const SCROLL_TOP_OFFSET = 16;
|
||||
|
||||
/** scroll-spy：标题顶部进入此阈值内即视为「当前章节」（px） */
|
||||
const ACTIVE_THRESHOLD = 80;
|
||||
|
||||
/**
|
||||
* 目录项的展示层级：
|
||||
* - 文档 H1 = 文章标题，单独作顶部标题块（不进列表）
|
||||
* - 文档 H2 = 章节名称 → 列表一级项
|
||||
* - 文档 H3 = 要点 → 列表二级项
|
||||
*/
|
||||
function displayLevel(h: OutlineHeading): 1 | 2 {
|
||||
return h.level >= 3 ? 2 : 1;
|
||||
}
|
||||
|
||||
/**
|
||||
* 草稿文档左侧目录栏（仿豆包 / Word 目录窗格）：
|
||||
* 顶部独立标题块 + 章节/要点两级列表，支持点击平滑跳转、滚动高亮、折叠。
|
||||
*/
|
||||
export function DraftOutlineSidebar({ editor, scrollEl }: DraftOutlineSidebarProps) {
|
||||
const headings = useDocumentOutline(editor);
|
||||
const [activeId, setActiveId] = useState<string | null>(null);
|
||||
const [collapsed, setCollapsed] = useState(false);
|
||||
|
||||
// 第一个 H1 作为文章标题，其余标题进目录列表
|
||||
const { titleHeading, items } = useMemo(() => {
|
||||
const titleIdx = headings.findIndex((h) => h.level === 1);
|
||||
return {
|
||||
titleHeading: titleIdx >= 0 ? headings[titleIdx] : null,
|
||||
items: headings.filter((_, i) => i !== titleIdx),
|
||||
};
|
||||
}, [headings]);
|
||||
|
||||
const scrollToHeading = useCallback(
|
||||
(pos: number, id: string) => {
|
||||
if (!editor || !scrollEl) return;
|
||||
const dom = editor.view.nodeDOM(pos) as HTMLElement | null;
|
||||
if (!dom) return;
|
||||
const elTop = dom.getBoundingClientRect().top;
|
||||
const containerTop = scrollEl.getBoundingClientRect().top;
|
||||
const target = scrollEl.scrollTop + (elTop - containerTop) - SCROLL_TOP_OFFSET;
|
||||
scrollEl.scrollTo({ top: Math.max(0, target), behavior: "smooth" });
|
||||
setActiveId(id);
|
||||
},
|
||||
[editor, scrollEl],
|
||||
);
|
||||
|
||||
// scroll-spy：随文档滚动高亮当前章节（rAF 节流）
|
||||
useEffect(() => {
|
||||
if (!editor || !scrollEl || headings.length === 0) return;
|
||||
|
||||
let raf = 0;
|
||||
const recompute = () => {
|
||||
raf = 0;
|
||||
const containerTop = scrollEl.getBoundingClientRect().top;
|
||||
let current = headings[0].id;
|
||||
for (const h of headings) {
|
||||
const dom = editor.view.nodeDOM(h.pos) as HTMLElement | null;
|
||||
if (!dom) continue;
|
||||
const relTop = dom.getBoundingClientRect().top - containerTop;
|
||||
// 标题在阈值内或之上 → 当前章节；首个落在阈值下方时其余皆下方，停止
|
||||
if (relTop <= ACTIVE_THRESHOLD) {
|
||||
current = h.id;
|
||||
} else {
|
||||
break;
|
||||
}
|
||||
}
|
||||
setActiveId(current);
|
||||
};
|
||||
|
||||
const onScroll = () => {
|
||||
if (raf) return;
|
||||
raf = requestAnimationFrame(recompute);
|
||||
};
|
||||
|
||||
recompute();
|
||||
scrollEl.addEventListener("scroll", onScroll, { passive: true });
|
||||
return () => {
|
||||
if (raf) cancelAnimationFrame(raf);
|
||||
scrollEl.removeEventListener("scroll", onScroll);
|
||||
};
|
||||
}, [editor, scrollEl, headings]);
|
||||
|
||||
// 没有可导航的章节时不渲染目录栏
|
||||
if (items.length === 0) return null;
|
||||
|
||||
// 折叠态：仅留一条窄轨 + 展开按钮
|
||||
if (collapsed) {
|
||||
return (
|
||||
<div className="w-9 shrink-0 border-r bg-muted/10 flex flex-col items-center pt-2">
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => setCollapsed(false)}
|
||||
title="展开目录"
|
||||
className="size-6 flex items-center justify-center rounded text-muted-foreground hover:text-foreground hover:bg-muted/60 transition-colors"
|
||||
>
|
||||
<PanelLeftOpen className="size-4" />
|
||||
</button>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
|
||||
return (
|
||||
<div className="w-60 shrink-0 border-r bg-muted/10 flex flex-col overflow-hidden">
|
||||
{/* 头部：目录标签 + 折叠按钮 */}
|
||||
<div className="h-9 flex items-center justify-between pl-3 pr-1.5 shrink-0">
|
||||
<span className="text-[11px] font-medium tracking-wide text-muted-foreground/80">目录</span>
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => setCollapsed(true)}
|
||||
title="收起目录"
|
||||
className="size-6 flex items-center justify-center rounded text-muted-foreground hover:text-foreground hover:bg-muted/60 transition-colors"
|
||||
>
|
||||
<PanelLeftClose className="size-3.5" />
|
||||
</button>
|
||||
</div>
|
||||
|
||||
{/* 文章标题块 */}
|
||||
{titleHeading && (
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => scrollToHeading(titleHeading.pos, titleHeading.id)}
|
||||
title={titleHeading.text}
|
||||
className={cn(
|
||||
"shrink-0 w-full text-left px-3 pb-2.5 pt-0.5 border-b transition-colors",
|
||||
"text-[13px] font-semibold leading-snug line-clamp-2",
|
||||
activeId === titleHeading.id
|
||||
? "text-primary"
|
||||
: "text-foreground hover:text-primary",
|
||||
)}
|
||||
>
|
||||
{titleHeading.text}
|
||||
</button>
|
||||
)}
|
||||
|
||||
{/* 章节 / 要点列表 */}
|
||||
<nav className="flex-1 overflow-y-auto py-1.5">
|
||||
{items.map((h) => {
|
||||
const lvl = displayLevel(h);
|
||||
const isActive = h.id === activeId;
|
||||
return (
|
||||
<button
|
||||
key={h.id}
|
||||
type="button"
|
||||
onClick={() => scrollToHeading(h.pos, h.id)}
|
||||
title={h.text}
|
||||
className={cn(
|
||||
"group flex items-center w-full text-left py-1.5 pr-2 border-l-2 transition-colors",
|
||||
lvl === 1 ? "pl-3 text-xs" : "pl-6 text-[11px]",
|
||||
isActive
|
||||
? "border-primary bg-primary/[0.07] text-primary font-medium"
|
||||
: cn(
|
||||
"border-transparent hover:bg-muted/50",
|
||||
lvl === 1
|
||||
? "text-foreground/85 font-medium hover:text-foreground"
|
||||
: "text-muted-foreground hover:text-foreground",
|
||||
),
|
||||
)}
|
||||
>
|
||||
{/* 二级（要点）项前的小圆点 */}
|
||||
{lvl === 2 && (
|
||||
<span
|
||||
className={cn(
|
||||
"shrink-0 size-1 rounded-full mr-1.5",
|
||||
isActive ? "bg-primary" : "bg-muted-foreground/40",
|
||||
)}
|
||||
/>
|
||||
)}
|
||||
<span className="truncate">{h.text}</span>
|
||||
</button>
|
||||
);
|
||||
})}
|
||||
</nav>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -13,6 +13,7 @@ import { WritingBubbleMenu } from "./WritingBubbleMenu";
|
||||
import { WritingParagraphMenu } from "./WritingParagraphMenu";
|
||||
import { WritingAiMenu } from "./WritingAiMenu";
|
||||
import { WritingRewritePreview } from "./WritingRewritePreview";
|
||||
import { DraftOutlineSidebar } from "./DraftOutlineSidebar";
|
||||
import { useCanvasGraphContext } from "../../contexts/CanvasGraphContext";
|
||||
import { useCanvasUIContext } from "../../contexts/CanvasUIContext";
|
||||
import { applyReplace, applyInsert } from "../../utils/apply-rewrite";
|
||||
@@ -45,6 +46,9 @@ export function TextArtifactRenderer({ content, isStreaming }: TextArtifactRende
|
||||
const [showScrollBtn, setShowScrollBtn] = useState(false);
|
||||
const autoScrollRef = useRef(true);
|
||||
|
||||
// 编辑模式文档滚动容器：用 state 而非 ref，使目录栏在容器挂载后能拿到它
|
||||
const [docScrollEl, setDocScrollEl] = useState<HTMLDivElement | null>(null);
|
||||
|
||||
// ── AI rewrite flow state ──────────────────────────────────────────────
|
||||
const [phase, setPhase] = useState<FlowPhase>("idle");
|
||||
const [panelPos, setPanelPos] = useState<PanelPos>({ x: 0, y: 0 });
|
||||
@@ -271,15 +275,21 @@ export function TextArtifactRenderer({ content, isStreaming }: TextArtifactRende
|
||||
<div className="h-full flex flex-col overflow-hidden">
|
||||
<WritingToolbar editor={editor} />
|
||||
|
||||
<div className="flex-1 overflow-y-auto">
|
||||
<div className="max-w-2xl mx-auto px-10 pt-10">
|
||||
{editor && (
|
||||
<>
|
||||
<WritingBubbleMenu editor={editor} onAiRewrite={openAiMenu} />
|
||||
<WritingParagraphMenu editor={editor} onAiRewrite={openAiMenu} />
|
||||
</>
|
||||
)}
|
||||
<TiptapEditor editor={editor} className="tiptap-writing-editor" />
|
||||
<div className="flex-1 flex min-h-0 overflow-hidden">
|
||||
{/* 左侧目录栏（仿豆包）：文档标题层级导航 */}
|
||||
<DraftOutlineSidebar editor={editor} scrollEl={docScrollEl} />
|
||||
|
||||
{/* 文档滚动区 */}
|
||||
<div ref={setDocScrollEl} className="flex-1 overflow-y-auto">
|
||||
<div className="max-w-2xl mx-auto px-10 pt-10">
|
||||
{editor && (
|
||||
<>
|
||||
<WritingBubbleMenu editor={editor} onAiRewrite={openAiMenu} />
|
||||
<WritingParagraphMenu editor={editor} onAiRewrite={openAiMenu} />
|
||||
</>
|
||||
)}
|
||||
<TiptapEditor editor={editor} className="tiptap-writing-editor" />
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
|
||||
@@ -354,6 +354,11 @@ export function useAIWriting() {
|
||||
else nextStatus = 'revising'; // user_revise
|
||||
} else if (pausePoint === 'review_confirm') {
|
||||
nextStatus = payload.action === 'force_finalize' ? 'done' : 'revising'; // accept_review
|
||||
} else if (pausePoint === 'section_help') {
|
||||
// 含「补充检索」→ 回检索；否则（删章节 / 通用知识续写）→ 直接回写作
|
||||
nextStatus = payload.sectionDecisions?.some((d) => d.decision === 'supplement')
|
||||
? 'researching'
|
||||
: 'writing_draft';
|
||||
}
|
||||
|
||||
try {
|
||||
|
||||
@@ -0,0 +1,72 @@
|
||||
import { useEffect, useState } from "react";
|
||||
import type { Editor } from "@tiptap/react";
|
||||
|
||||
/** 文档目录中的一个标题项 */
|
||||
export interface OutlineHeading {
|
||||
/** React key + scroll-spy 标识，按 ProseMirror 位置生成 */
|
||||
id: string;
|
||||
/** 标题层级，仅保留 1~3 */
|
||||
level: 1 | 2 | 3;
|
||||
/** 标题纯文本 */
|
||||
text: string;
|
||||
/** 标题节点在 ProseMirror 文档中的位置，用于解析 DOM 元素 */
|
||||
pos: number;
|
||||
}
|
||||
|
||||
/** 仅纳入目录的最大标题层级（H1~H3） */
|
||||
const MAX_LEVEL = 3;
|
||||
/** 内容变化后重建目录的防抖间隔（ms） */
|
||||
const DEBOUNCE_MS = 200;
|
||||
|
||||
/**
|
||||
* 从 Tiptap 编辑器实时提取 H1~H3 标题，构成文档目录。
|
||||
*
|
||||
* 首次挂载立即构建一次；之后监听 `editor.on('update')`，按 DEBOUNCE_MS 防抖重建，
|
||||
* 避免逐字输入时频繁全量遍历。
|
||||
*/
|
||||
export function useDocumentOutline(editor: Editor | null): OutlineHeading[] {
|
||||
const [headings, setHeadings] = useState<OutlineHeading[]>([]);
|
||||
|
||||
useEffect(() => {
|
||||
if (!editor) {
|
||||
setHeadings([]);
|
||||
return;
|
||||
}
|
||||
|
||||
const compute = () => {
|
||||
const out: OutlineHeading[] = [];
|
||||
editor.state.doc.descendants((node, pos) => {
|
||||
if (node.type.name !== "heading") return true;
|
||||
const level = node.attrs.level as number;
|
||||
if (level >= 1 && level <= MAX_LEVEL) {
|
||||
out.push({
|
||||
id: `heading-${pos}`,
|
||||
level: level as 1 | 2 | 3,
|
||||
text: node.textContent.trim() || "(无标题)",
|
||||
pos,
|
||||
});
|
||||
}
|
||||
return true;
|
||||
});
|
||||
setHeadings(out);
|
||||
};
|
||||
|
||||
// 首次立即构建
|
||||
compute();
|
||||
|
||||
// 内容变化时防抖重建
|
||||
let timer: ReturnType<typeof setTimeout> | undefined;
|
||||
const onUpdate = () => {
|
||||
clearTimeout(timer);
|
||||
timer = setTimeout(compute, DEBOUNCE_MS);
|
||||
};
|
||||
editor.on("update", onUpdate);
|
||||
|
||||
return () => {
|
||||
clearTimeout(timer);
|
||||
editor.off("update", onUpdate);
|
||||
};
|
||||
}, [editor]);
|
||||
|
||||
return headings;
|
||||
}
|
||||
@@ -25,6 +25,22 @@ export interface AIOutline {
|
||||
sections: OutlineSection[];
|
||||
}
|
||||
|
||||
// ── 素材不足求助 ──────────────────────────────────────────────────────────────
|
||||
|
||||
/** 严格模式下素材不足、待用户决策的章节 */
|
||||
export interface BlockedSection {
|
||||
sectionTitle: string;
|
||||
reason: string;
|
||||
}
|
||||
|
||||
/** 单个被阻塞章节的处理决策 */
|
||||
export type SectionDecisionKind = 'supplement' | 'delete' | 'loose';
|
||||
|
||||
export interface SectionDecision {
|
||||
sectionTitle: string;
|
||||
decision: SectionDecisionKind;
|
||||
}
|
||||
|
||||
// ── 编辑审核 ──────────────────────────────────────────────────────────────────
|
||||
|
||||
export interface ReviewIssue {
|
||||
@@ -54,6 +70,7 @@ export type WritingStatus =
|
||||
| 'writing_outline'
|
||||
| 'awaiting_outline_confirm'
|
||||
| 'writing_draft'
|
||||
| 'awaiting_section_help'
|
||||
| 'awaiting_draft_confirm'
|
||||
| 'reviewing'
|
||||
| 'awaiting_review_confirm'
|
||||
@@ -109,8 +126,10 @@ export interface ProgressEvent {
|
||||
// review_ready
|
||||
reviewResult?: ReviewResult;
|
||||
// await_user
|
||||
pausePoint?: 'material_confirm' | 'outline_confirm' | 'draft_confirm' | 'review_confirm';
|
||||
pausePoint?: 'material_confirm' | 'outline_confirm' | 'draft_confirm' | 'review_confirm' | 'section_help';
|
||||
pauseContext?: Record<string, unknown>;
|
||||
// section_help：素材不足、待用户决策的章节
|
||||
blockedSections?: BlockedSection[];
|
||||
}
|
||||
|
||||
// ── 用户干预提交体 ────────────────────────────────────────────────────────────
|
||||
@@ -125,6 +144,8 @@ export interface UserInterventionPayload {
|
||||
overrideVerdict?: boolean;
|
||||
// 用户勾选的审核意见索引（基于 reviewResult.revisionNotes），未传则默认全选
|
||||
selectedIssueIndices?: number[];
|
||||
// section_help：每个被阻塞章节的处理决策
|
||||
sectionDecisions?: SectionDecision[];
|
||||
}
|
||||
|
||||
// ── 写作请求 ──────────────────────────────────────────────────────────────────
|
||||
@@ -135,6 +156,10 @@ export interface AIWritingRequest {
|
||||
targetAudience: string;
|
||||
wordCountTarget: number;
|
||||
modelName?: string;
|
||||
/** 素材检索关键词数量（1~10，默认 6） */
|
||||
keywordCount: number;
|
||||
/** 写作模式：strict=严格依据素材 / loose=可结合通用知识（默认 loose） */
|
||||
writingMode: 'strict' | 'loose';
|
||||
}
|
||||
|
||||
// ── 流式审核条目 ──────────────────────────────────────────────────────────────
|
||||
@@ -173,7 +198,7 @@ export interface StreamingDraftSection {
|
||||
// ── 已完成干预记录 ────────────────────────────────────────────────────────────
|
||||
|
||||
export interface CompletedIntervention {
|
||||
pausePoint: 'material_confirm' | 'outline_confirm' | 'draft_confirm' | 'review_confirm';
|
||||
pausePoint: 'material_confirm' | 'outline_confirm' | 'draft_confirm' | 'review_confirm' | 'section_help';
|
||||
action: string;
|
||||
// material_confirm
|
||||
materials?: AIMaterial[];
|
||||
|
||||
@@ -40,6 +40,10 @@ class StartWritingRequest(BaseModel):
|
||||
target_audience: str = "普通读者"
|
||||
word_count_target: int = 800
|
||||
model_name: str = ""
|
||||
# 素材检索关键词数量：用户指定用几个关键词检索（1~10，默认 6）
|
||||
keyword_count: int = 6
|
||||
# 写作模式：strict=严格依据素材 / loose=可结合通用知识（默认 loose）
|
||||
writing_mode: str = "loose"
|
||||
|
||||
|
||||
class StartWritingResponse(BaseModel):
|
||||
@@ -57,6 +61,9 @@ class ResumeRequest(BaseModel):
|
||||
user_revision_notes: str = ""
|
||||
override_verdict: bool = False
|
||||
selected_issue_indices: Optional[list[int]] = None
|
||||
# 素材不足求助点：每个被阻塞章节的处理决策
|
||||
# [{"sectionTitle": "...", "decision": "supplement|delete|loose"}]
|
||||
section_decisions: list[dict] = Field(default_factory=list)
|
||||
|
||||
|
||||
class RenameSessionRequest(BaseModel):
|
||||
@@ -230,6 +237,10 @@ async def start_writing(body: StartWritingRequest, request: Request):
|
||||
"article_type": body.article_type,
|
||||
"target_audience": body.target_audience,
|
||||
"word_count_target": body.word_count_target,
|
||||
# 规整到 [1, 10]，非法值回退默认 6
|
||||
"keyword_count": max(1, min(10, body.keyword_count)),
|
||||
# 写作模式，非法值回退 loose
|
||||
"writing_mode": body.writing_mode if body.writing_mode in ("strict", "loose") else "loose",
|
||||
"revision_count": 0,
|
||||
"max_revisions": 3,
|
||||
"status": "researching",
|
||||
@@ -421,6 +432,7 @@ async def resume_writing(session_id: str, body: ResumeRequest, request: Request)
|
||||
"userRevisionNotes": body.user_revision_notes,
|
||||
"overrideVerdict": body.override_verdict,
|
||||
"selectedIssueIndices": body.selected_issue_indices,
|
||||
"sectionDecisions": body.section_decisions,
|
||||
}
|
||||
|
||||
# Record this intervention for session history
|
||||
|
||||
+123
-8
@@ -61,6 +61,26 @@ def _normalize_outline(outline: dict) -> dict:
|
||||
return {"title": outline.get("title", ""), "sections": sections}
|
||||
|
||||
|
||||
def _check_outline_material_support(outline: dict) -> str:
|
||||
"""轻量启发式：统计未关联任何素材的章节，返回预警文案（空串=无需预警）。
|
||||
|
||||
仅做提示、不拦截流程；真正的素材不足会在写作节点被检出并触发求助暂停。
|
||||
"""
|
||||
sections = (outline or {}).get("sections", [])
|
||||
weak = [
|
||||
(s.get("section_title") or s.get("sectionTitle") or "")
|
||||
for s in sections
|
||||
if not (s.get("material_ids") or s.get("materialIds"))
|
||||
]
|
||||
weak = [t for t in weak if t]
|
||||
if not weak:
|
||||
return ""
|
||||
return (
|
||||
f"有 {len(weak)} 个章节未关联检索素材（{('、'.join(weak))}）。"
|
||||
"严格依据素材模式下，这些章节在写作时可能因素材不足而暂停向你求助。"
|
||||
)
|
||||
|
||||
|
||||
async def pause_outline_confirm(state: AIWritingState) -> dict:
|
||||
"""PAUSE-2：大纲确认"""
|
||||
user_input: dict = interrupt({
|
||||
@@ -74,20 +94,34 @@ async def pause_outline_confirm(state: AIWritingState) -> dict:
|
||||
if action == "confirm":
|
||||
raw_outline = user_input.get("editedOutline") or state["current_outline"]
|
||||
edited = _normalize_outline(raw_outline) if raw_outline else state["current_outline"]
|
||||
events: list[dict] = [{"type": "resumed", "agent_name": "系统", "message": "用户已确认大纲，开始写作"}]
|
||||
# 阶段四：严格模式下对大纲做轻量素材充分性预警（仅提示，不拦截流程）
|
||||
if state.get("writing_mode") == "strict":
|
||||
warning = _check_outline_material_support(edited)
|
||||
if warning:
|
||||
events.append({
|
||||
"type": "notice", "agent_name": "系统",
|
||||
"title": "素材充分性提示", "detail": warning,
|
||||
})
|
||||
return {
|
||||
"current_outline": edited,
|
||||
"last_user_intervention": user_input,
|
||||
"status": "writing_draft",
|
||||
"progress_events": [{"type": "resumed", "agent_name": "系统", "message": "用户已确认大纲，开始写作"}],
|
||||
"progress_events": events,
|
||||
}
|
||||
|
||||
# re_outline
|
||||
feedback = user_input.get("outlineFeedback", "")
|
||||
return {
|
||||
updates: dict = {
|
||||
"last_user_intervention": {**user_input, "_feedback": feedback},
|
||||
"status": "writing_outline",
|
||||
"progress_events": [{"type": "resumed", "agent_name": "系统", "message": f"重新规划大纲（{feedback[:30]}）"}],
|
||||
}
|
||||
# 用户在卡片里手动改过大纲 → 以手动版作为本次重规划的编辑基准
|
||||
raw_edited = user_input.get("editedOutline")
|
||||
if raw_edited:
|
||||
updates["current_outline"] = _normalize_outline(raw_edited)
|
||||
return updates
|
||||
|
||||
|
||||
async def pause_draft_confirm(state: AIWritingState) -> dict:
|
||||
@@ -127,6 +161,65 @@ async def pause_draft_confirm(state: AIWritingState) -> dict:
|
||||
}
|
||||
|
||||
|
||||
async def pause_section_help(state: AIWritingState) -> dict:
|
||||
"""素材不足求助点：严格模式下作家发现章节缺素材，让用户逐章决定如何处理。
|
||||
|
||||
用户对每个被阻塞章节选择：
|
||||
- supplement：补充检索素材（整体回到检索流程重走）
|
||||
- delete：删除该章节
|
||||
- loose：按通用知识续写该章节
|
||||
"""
|
||||
blocked = state.get("blocked_sections") or []
|
||||
user_input: dict = interrupt({
|
||||
"pause_point": "section_help",
|
||||
"message": "部分章节缺少足够素材支撑写作，请决定如何处理。",
|
||||
"blocked_sections": blocked,
|
||||
})
|
||||
|
||||
# sectionDecisions: [{"sectionTitle": "...", "decision": "supplement|delete|loose"}]
|
||||
by_title: dict = {}
|
||||
for d in user_input.get("sectionDecisions") or []:
|
||||
title = d.get("sectionTitle") or d.get("section_title")
|
||||
if title:
|
||||
by_title[title] = d.get("decision", "loose")
|
||||
|
||||
# 任一章节选「补充检索」→ 整体回到检索，重走「检索 → 素材确认 → 大纲 → 写作」
|
||||
supplement_reasons = [
|
||||
b["reason"] for b in blocked if by_title.get(b["section_title"]) == "supplement"
|
||||
]
|
||||
if supplement_reasons:
|
||||
return {
|
||||
# supplement_search：补充检索（保留已有素材、追加新素材），完成后直接回写作、不重排大纲
|
||||
"last_user_intervention": {**user_input, "action": "supplement_search", "_extra_keywords": supplement_reasons},
|
||||
"status": "researching",
|
||||
"blocked_sections": None,
|
||||
"progress_events": [{"type": "resumed", "agent_name": "系统", "message": "补充检索素材中…"}],
|
||||
}
|
||||
|
||||
# 否则：删除标记章节、记录「通用知识续写」章节，直接回写作
|
||||
outline = state.get("current_outline") or {"title": "", "sections": []}
|
||||
kept, loose_titles = [], []
|
||||
for s in outline.get("sections", []):
|
||||
title = s.get("section_title") or s.get("sectionTitle", "")
|
||||
decision = by_title.get(title)
|
||||
if decision == "delete":
|
||||
continue
|
||||
if decision == "loose":
|
||||
loose_titles.append(title)
|
||||
kept.append(s)
|
||||
# 防御：用户把所有章节都删了 → 保留原大纲并全部按通用知识写，避免空文章
|
||||
if not kept:
|
||||
kept = outline.get("sections", [])
|
||||
loose_titles = [s.get("section_title") or s.get("sectionTitle", "") for s in kept]
|
||||
return {
|
||||
"current_outline": {**outline, "sections": kept},
|
||||
"last_user_intervention": {**user_input, "_loose_sections": loose_titles},
|
||||
"status": "writing_draft",
|
||||
"blocked_sections": None,
|
||||
"progress_events": [{"type": "resumed", "agent_name": "系统", "message": "已按你的选择继续写作…"}],
|
||||
}
|
||||
|
||||
|
||||
async def pause_review_confirm(state: AIWritingState) -> dict:
|
||||
"""PAUSE-4：编辑打回确认"""
|
||||
user_input: dict = interrupt({
|
||||
@@ -156,6 +249,11 @@ async def pause_review_confirm(state: AIWritingState) -> dict:
|
||||
|
||||
# ── 条件路由 ──────────────────────────────────────────────────────────────────
|
||||
|
||||
def after_researcher(state: AIWritingState) -> str:
|
||||
"""检索完成后：补充检索（素材不足求助）直接回写作，否则去素材确认。"""
|
||||
return "writer_draft" if state.get("status") == "writing_draft" else "pause_material"
|
||||
|
||||
|
||||
def after_material_pause(state: AIWritingState) -> str:
|
||||
return "researcher" if state["status"] == "researching" else "writer_outline"
|
||||
|
||||
@@ -164,6 +262,16 @@ def after_outline_pause(state: AIWritingState) -> str:
|
||||
return "writer_outline" if state["status"] == "writing_outline" else "writer_draft"
|
||||
|
||||
|
||||
def after_writer_draft(state: AIWritingState) -> str:
|
||||
"""写作完成后：素材不足则去求助暂停点，否则去草稿确认。"""
|
||||
return "pause_section_help" if state["status"] == "awaiting_section_help" else "pause_draft"
|
||||
|
||||
|
||||
def after_section_help_pause(state: AIWritingState) -> str:
|
||||
"""求助暂停点之后：补充检索回 researcher，否则回写作。"""
|
||||
return "researcher" if state["status"] == "researching" else "writer_draft"
|
||||
|
||||
|
||||
def after_draft_pause(state: AIWritingState) -> str:
|
||||
status = state["status"]
|
||||
if status == "done":
|
||||
@@ -198,14 +306,16 @@ def build_ai_writing_graph():
|
||||
g.add_node("pause_material", pause_material_confirm)
|
||||
g.add_node("writer_outline", writer_outline_node)
|
||||
g.add_node("pause_outline", pause_outline_confirm)
|
||||
g.add_node("writer_draft", writer_draft_node)
|
||||
g.add_node("pause_draft", pause_draft_confirm)
|
||||
g.add_node("editor", editor_node)
|
||||
g.add_node("pause_review", pause_review_confirm)
|
||||
g.add_node("writer_draft", writer_draft_node)
|
||||
g.add_node("pause_section_help", pause_section_help)
|
||||
g.add_node("pause_draft", pause_draft_confirm)
|
||||
g.add_node("editor", editor_node)
|
||||
g.add_node("pause_review", pause_review_confirm)
|
||||
|
||||
g.set_entry_point("intent_parser")
|
||||
g.add_edge("intent_parser", "researcher")
|
||||
g.add_edge("researcher", "pause_material")
|
||||
g.add_conditional_edges("researcher", after_researcher,
|
||||
{"pause_material": "pause_material", "writer_draft": "writer_draft"})
|
||||
|
||||
g.add_conditional_edges("pause_material", after_material_pause,
|
||||
{"researcher": "researcher", "writer_outline": "writer_outline"})
|
||||
@@ -214,7 +324,12 @@ def build_ai_writing_graph():
|
||||
g.add_conditional_edges("pause_outline", after_outline_pause,
|
||||
{"writer_outline": "writer_outline", "writer_draft": "writer_draft"})
|
||||
|
||||
g.add_edge("writer_draft", "pause_draft")
|
||||
g.add_conditional_edges("writer_draft", after_writer_draft,
|
||||
{"pause_section_help": "pause_section_help", "pause_draft": "pause_draft"})
|
||||
|
||||
g.add_conditional_edges("pause_section_help", after_section_help_pause,
|
||||
{"researcher": "researcher", "writer_draft": "writer_draft"})
|
||||
|
||||
g.add_conditional_edges("pause_draft", after_draft_pause,
|
||||
{"end": END, "writer_draft": "writer_draft", "editor": "editor"})
|
||||
|
||||
|
||||
+82
-9
@@ -3,6 +3,7 @@ from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
import re
|
||||
import uuid
|
||||
from typing import List
|
||||
|
||||
@@ -18,7 +19,62 @@ from ._utils import llm_json
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_MAX_MATERIALS = 12
|
||||
# 素材总量上限边界：config.yaml 的 ai_writing.max_materials，非法值回退默认 20
|
||||
_DEFAULT_MAX_MATERIALS = 20
|
||||
_MIN_MAX_MATERIALS = 1
|
||||
_MAX_MAX_MATERIALS = 100
|
||||
|
||||
# 素材检索关键词数量边界：用户可指定 1~10 个，非法值回退默认 6
|
||||
_DEFAULT_KEYWORD_COUNT = 6
|
||||
_MAX_KEYWORD_COUNT = 10
|
||||
|
||||
|
||||
def _resolve_keyword_count(raw: object) -> int:
|
||||
"""把用户传入的检索关键词数量规整到 [1, _MAX_KEYWORD_COUNT]，非法值回退默认 6。"""
|
||||
try:
|
||||
n = int(raw) # type: ignore[arg-type]
|
||||
except (TypeError, ValueError):
|
||||
return _DEFAULT_KEYWORD_COUNT
|
||||
return max(1, min(_MAX_KEYWORD_COUNT, n))
|
||||
|
||||
|
||||
def _resolve_max_materials(raw: object) -> int:
|
||||
"""把 config.yaml 配置的素材总量上限规整到 [1, 100]，非法值回退默认 20。"""
|
||||
try:
|
||||
n = int(raw) # type: ignore[arg-type]
|
||||
except (TypeError, ValueError):
|
||||
return _DEFAULT_MAX_MATERIALS
|
||||
return max(_MIN_MAX_MATERIALS, min(_MAX_MAX_MATERIALS, n))
|
||||
|
||||
|
||||
# 占位/示意性关键词（模型误抄提示词模板时产生），检索前剔除
|
||||
_PLACEHOLDER_KEYWORD_RE = re.compile(r"^(关键词\d*|keyword\d*|kw\d*|\.+|…+)$", re.IGNORECASE)
|
||||
|
||||
|
||||
def _clean_keywords(raw: object, fallback: str) -> list[str]:
|
||||
"""清洗 LLM 产出的关键词：去空白、丢弃占位符（如「关键词1」「...」）、去重。
|
||||
|
||||
全部被滤掉时回退为写作意图本身，避免拿占位词检索出一堆无关素材。
|
||||
"""
|
||||
cleaned: list[str] = []
|
||||
for kw in raw if isinstance(raw, list) else []:
|
||||
s = str(kw).strip()
|
||||
if not s or _PLACEHOLDER_KEYWORD_RE.match(s):
|
||||
continue
|
||||
cleaned.append(s)
|
||||
deduped = list(dict.fromkeys(cleaned))
|
||||
return deduped or [fallback]
|
||||
|
||||
|
||||
def _per_keyword_limit(max_materials: int, total_keywords: int) -> int:
|
||||
"""把素材总量上限均分到每个检索词上的检索条数（向上取整）。
|
||||
|
||||
向上取整保证合并去重后素材数仍能接近总量上限；最终会再统一截断到上限。
|
||||
total_keywords <= 0 时回退为总量上限本身。
|
||||
"""
|
||||
if total_keywords <= 0:
|
||||
return max_materials
|
||||
return (max_materials + total_keywords - 1) // total_keywords
|
||||
|
||||
|
||||
def _notice(title: str, detail: str, raw: str = "") -> dict:
|
||||
@@ -41,6 +97,12 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
|
||||
intervention = state.get("last_user_intervention") or {}
|
||||
extra_keywords: list[str] = intervention.get("_extra_keywords") or intervention.get("extra_keywords") or []
|
||||
|
||||
# 素材不足求助点触发的「补充检索」：保留原大纲，检索完直接回写作、不走素材确认/大纲
|
||||
is_supplement = intervention.get("action") == "supplement_search"
|
||||
|
||||
# 用户指定的检索关键词数量（1~10），决定生成多少个检索词、检索多少个方向
|
||||
keyword_count = _resolve_keyword_count(state.get("keyword_count"))
|
||||
|
||||
# SSE 实时进度推送（与 outline/draft 节点共用 sse_queue 机制）
|
||||
cfg = config.get("configurable", {})
|
||||
sse_queue = cfg.get("sse_queue")
|
||||
@@ -51,6 +113,8 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
|
||||
ai_writing_config = cfg.get("ai_writing_config", {}) or {}
|
||||
keyword_model: str | None = ai_writing_config.get("keyword_model") or None
|
||||
rank_model: str | None = ai_writing_config.get("rank_model") or None
|
||||
# 素材总量上限（config.yaml: ai_writing.max_materials），按检索词数均分到每个词
|
||||
max_materials = _resolve_max_materials(ai_writing_config.get("max_materials"))
|
||||
|
||||
async def _emit(message: str) -> None:
|
||||
if sse_queue is None:
|
||||
@@ -68,20 +132,28 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
|
||||
user_intent=intent,
|
||||
article_type=article_type,
|
||||
target_audience=target_audience,
|
||||
keyword_count=keyword_count,
|
||||
),
|
||||
fallback={"keywords": [intent]},
|
||||
config=config,
|
||||
model_name=keyword_model,
|
||||
)
|
||||
keywords: list[str] = kw_result.get("keywords", [intent])
|
||||
# 清洗关键词：剔除占位符 / 空值，全空时回退写作意图
|
||||
keywords: list[str] = _clean_keywords(kw_result.get("keywords"), intent)
|
||||
if extra_keywords:
|
||||
keywords = list(dict.fromkeys(keywords + extra_keywords))
|
||||
|
||||
# Step 2: 并发搜索
|
||||
provider = get_search_provider(ai_writing_config)
|
||||
|
||||
search_keywords = keywords[:6]
|
||||
# 按用户指定的关键词数量截断；补充搜索时不截断用户额外添加的关键词
|
||||
search_limit = keyword_count
|
||||
if extra_keywords:
|
||||
search_limit = max(search_limit, len(keywords))
|
||||
search_keywords = keywords[:search_limit]
|
||||
total = len(search_keywords)
|
||||
# 每个检索词分到的检索条数 = 总量上限 / 检索词数（向上取整）
|
||||
per_keyword = _per_keyword_limit(max_materials, total)
|
||||
await _emit(f"检索词已生成，开始检索 {total} 个方向…")
|
||||
|
||||
# 并发搜索，但每完成一个就推送进度（计数在单线程 asyncio 下无需加锁）
|
||||
@@ -90,7 +162,7 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
|
||||
async def _search_one(kw: str) -> list[SearchResult]:
|
||||
nonlocal completed
|
||||
try:
|
||||
return await provider.search(kw, max_results=3)
|
||||
return await provider.search(kw, max_results=per_keyword)
|
||||
finally:
|
||||
completed += 1
|
||||
if completed < total:
|
||||
@@ -138,7 +210,7 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
|
||||
# Step 3: 相关度排序（如素材较多，让 LLM 排序）
|
||||
await _emit("检索完成，正在筛选排序素材…")
|
||||
rank_error = ""
|
||||
if len(raw_materials) > _MAX_MATERIALS:
|
||||
if len(raw_materials) > max_materials:
|
||||
materials_list = "\n".join(
|
||||
f"- ID: {m['id']} 标题: {m['title']} 摘要: {m['content'][:100]}"
|
||||
for m in raw_materials
|
||||
@@ -146,7 +218,7 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
|
||||
rank_result = await llm_json(
|
||||
RANK_MATERIALS_SYSTEM,
|
||||
RANK_MATERIALS_USER.format(user_intent=intent, materials_list=materials_list),
|
||||
fallback={"ranked_ids": [m["id"] for m in raw_materials[:_MAX_MATERIALS]], "summary": f"共搜索到{len(raw_materials)}条素材"},
|
||||
fallback={"ranked_ids": [m["id"] for m in raw_materials[:max_materials]], "summary": f"共搜索到{len(raw_materials)}条素材"},
|
||||
config=config,
|
||||
model_name=rank_model,
|
||||
)
|
||||
@@ -159,10 +231,10 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
|
||||
for m in raw_materials:
|
||||
if m["id"] not in sorted_ids_set:
|
||||
sorted_materials.append(m)
|
||||
materials = sorted_materials[:_MAX_MATERIALS]
|
||||
materials = sorted_materials[:max_materials]
|
||||
summary = rank_result.get("summary", f"共搜索到{len(raw_materials)}条素材，精选{len(materials)}条")
|
||||
else:
|
||||
materials = sorted(raw_materials, key=lambda m: m.get("relevance_score", 0), reverse=True)[:_MAX_MATERIALS]
|
||||
materials = sorted(raw_materials, key=lambda m: m.get("relevance_score", 0), reverse=True)[:max_materials]
|
||||
summary = f"共搜索到{len(raw_materials)}条素材，精选{len(materials)}条"
|
||||
|
||||
# 空结果兜底：未检索到任何素材时给出明确文案，前端据此弹出「无数据继续」选项
|
||||
@@ -189,7 +261,8 @@ async def researcher_node(state: AIWritingState, config: RunnableConfig) -> dict
|
||||
|
||||
return {
|
||||
"material_package": pkg,
|
||||
"status": "awaiting_material_confirm",
|
||||
# 补充检索：直接回写作（沿用原大纲）；常规检索：进入素材确认暂停点
|
||||
"status": "writing_draft" if is_supplement else "awaiting_material_confirm",
|
||||
"progress_events": [
|
||||
{"type": "step_start", "agent_name": "素材收集专家", "message": f"搜索关键词：{', '.join(keywords[:3])}"},
|
||||
*notices,
|
||||
|
||||
+87
-3
@@ -3,16 +3,53 @@ from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import logging
|
||||
import re
|
||||
|
||||
from langchain_core.messages import HumanMessage, SystemMessage
|
||||
from langchain_core.runnables import RunnableConfig
|
||||
|
||||
from ..state import AIWritingState, DraftArticle
|
||||
from ..prompts.writer_prompts import DRAFT_SECTION_SYSTEM, DRAFT_SECTION_USER, DRAFT_EXPAND_USER
|
||||
from ..prompts.writer_prompts import (
|
||||
DRAFT_SECTION_SYSTEM, DRAFT_SECTION_USER, DRAFT_EXPAND_USER,
|
||||
WRITER_MODE_LOOSE, WRITER_MODE_STRICT, SECTION_BLOCKED_MARKER,
|
||||
)
|
||||
from ._utils import get_model, _content_to_text, count_words, ThinkTagParser
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# 章节正文里的 Markdown 标题行（允许前导空白）
|
||||
_HEADING_PREFIX_RE = re.compile(r"^[ \t]*#{1,6}[ \t]+", re.MULTILINE)
|
||||
|
||||
|
||||
def _normalize_section_headings(text: str) -> str:
|
||||
"""把章节正文里所有 Markdown 标题行统一压成三级标题（###）。
|
||||
|
||||
作家被要求只用 ### 作为「要点」小标题；模型偶尔误用 #/##/#### 时在此纠正，
|
||||
保证文档标题层级符合「文章 # → 章节 ## → 要点 ###」，
|
||||
前端目录栏据此才能把要点正确识别为二级标题。
|
||||
"""
|
||||
return _HEADING_PREFIX_RE.sub("### ", text)
|
||||
|
||||
|
||||
# 疑似「拒绝 / 元话语」的强特征短语：模型把对用户说的话当成正文输出时出现，
|
||||
# 这些短语几乎不可能出现在正常文章里，用作安全网识别。
|
||||
_REFUSAL_MARKERS = (
|
||||
"我无法完成", "无法完成此任务", "无法完成该任务", "无法完成这个任务",
|
||||
"无法完成本次", "无法写出符合", "无法撰写这篇", "无法基于现有素材",
|
||||
"无法基于当前素材", "无法基于提供的素材",
|
||||
)
|
||||
|
||||
|
||||
def _looks_like_refusal(text: str) -> bool:
|
||||
"""判断一段章节产出是否疑似「拒绝 / 元话语」而非真正的文章正文。
|
||||
|
||||
模型遇到素材与意图不匹配时，可能把「我无法完成此任务」之类对用户说的话
|
||||
当成正文输出。这里用强特征短语做启发式识别（安全网，非强校验）。
|
||||
"""
|
||||
if not text or not text.strip():
|
||||
return False
|
||||
return any(marker in text for marker in _REFUSAL_MARKERS)
|
||||
|
||||
|
||||
def _get_section_materials(material_ids: list[str], pkg: dict) -> str:
|
||||
mat_map = {m["id"]: m for m in pkg.get("materials", [])}
|
||||
@@ -39,6 +76,10 @@ async def writer_draft_node(state: AIWritingState, config: RunnableConfig) -> di
|
||||
intervention = state.get("last_user_intervention") or {}
|
||||
revision_count = state.get("revision_count", 0)
|
||||
|
||||
# 写作模式；用户在「素材不足求助」里选「按通用知识续写」的章节强制走宽松
|
||||
writing_mode = state.get("writing_mode", "loose")
|
||||
loose_titles: set[str] = set(intervention.get("_loose_sections") or [])
|
||||
|
||||
# SSE 流式推送所需
|
||||
cfg = config.get("configurable", {})
|
||||
sse_queue: asyncio.Queue | None = cfg.get("sse_queue")
|
||||
@@ -89,6 +130,7 @@ async def writer_draft_node(state: AIWritingState, config: RunnableConfig) -> di
|
||||
section_titles: list[str] = []
|
||||
section_bufs: list[str] = [] # 各章节正文（不含 ## 标题），供扩写兜底逐节替换
|
||||
section_errors: list[str] = [] # 分节写作的模型异常，供完成后非致命提示
|
||||
blocked_sections: list[dict] = [] # 严格模式下素材不足、无法写作的章节
|
||||
|
||||
for i, section in enumerate(sections):
|
||||
sec_title = _section_title(i, section)
|
||||
@@ -104,6 +146,10 @@ async def writer_draft_node(state: AIWritingState, config: RunnableConfig) -> di
|
||||
for j, s in enumerate(sections)
|
||||
)
|
||||
|
||||
# 本章节是否走严格模式（全局严格 且 未被用户标记为「通用知识续写」）
|
||||
section_is_strict = writing_mode == "strict" and sec_title not in loose_titles
|
||||
mode_section = WRITER_MODE_STRICT if section_is_strict else WRITER_MODE_LOOSE
|
||||
|
||||
user_msg = DRAFT_SECTION_USER.format(
|
||||
article_title=article_title,
|
||||
outline_context=outline_context,
|
||||
@@ -111,6 +157,7 @@ async def writer_draft_node(state: AIWritingState, config: RunnableConfig) -> di
|
||||
key_points=key_points_str,
|
||||
section_materials=section_materials,
|
||||
revision_section=revision_notes,
|
||||
mode_section=mode_section,
|
||||
target_words=words_per_section,
|
||||
)
|
||||
|
||||
@@ -147,8 +194,27 @@ async def writer_draft_node(state: AIWritingState, config: RunnableConfig) -> di
|
||||
"is_section_done": True,
|
||||
}))
|
||||
|
||||
cleaned_buf = section_buf.strip()
|
||||
blocked_reason = ""
|
||||
# 严格模式：作家用哨兵声明素材不足，或仍输出了拒绝话术 → 标记为待求助章节
|
||||
if section_is_strict and SECTION_BLOCKED_MARKER in cleaned_buf:
|
||||
blocked_reason = (
|
||||
cleaned_buf.split(SECTION_BLOCKED_MARKER, 1)[1].strip()[:120]
|
||||
or "素材不足以支撑本章节写作"
|
||||
)
|
||||
elif _looks_like_refusal(cleaned_buf):
|
||||
if section_is_strict:
|
||||
blocked_reason = "素材不足以支撑本章节写作"
|
||||
else:
|
||||
# 宽松模式：模型仍拒绝，安全网占位，不打断流程
|
||||
logger.warning("draft section [%s] looks like a refusal, replaced with placeholder", sec_title)
|
||||
section_errors.append(f"「{sec_title}」生成内容疑似拒绝/无关，已占位")
|
||||
cleaned_buf = "（本节内容生成异常，建议重新生成或补充相关素材）"
|
||||
if blocked_reason:
|
||||
blocked_sections.append({"section_title": sec_title, "reason": blocked_reason})
|
||||
cleaned_buf = f"（本节素材不足：{blocked_reason}）"
|
||||
section_titles.append(sec_title)
|
||||
section_bufs.append(section_buf.strip())
|
||||
section_bufs.append(cleaned_buf)
|
||||
|
||||
except Exception as e:
|
||||
logger.error("draft section [%s] failed: %s", sec_title, e, exc_info=True)
|
||||
@@ -156,8 +222,26 @@ async def writer_draft_node(state: AIWritingState, config: RunnableConfig) -> di
|
||||
section_bufs.append("（内容生成失败，请重试）")
|
||||
section_errors.append(f"「{sec_title}」{type(e).__name__}: {e}")
|
||||
|
||||
# 严格模式下有章节无法基于素材写作 → 暂停求助用户，不产出半成品草稿
|
||||
if blocked_sections:
|
||||
return {
|
||||
"blocked_sections": blocked_sections,
|
||||
"status": "awaiting_section_help",
|
||||
"progress_events": [
|
||||
{"type": "step_start", "agent_name": "作家", "message": f"开始写作（第{revision_count+1}稿）"},
|
||||
{
|
||||
"type": "notice", "agent_name": "作家", "title": "素材不足",
|
||||
"detail": f"有 {len(blocked_sections)} 个章节缺少足够素材支撑写作，需要你决定如何处理。",
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
def _assemble() -> str:
|
||||
body = "\n\n".join(f"## {t}\n\n{b}" for t, b in zip(section_titles, section_bufs))
|
||||
# 章节正文里的标题统一归一到 ###（要点小标题），章节标题用 ##，文章标题用 #
|
||||
body = "\n\n".join(
|
||||
f"## {t}\n\n{_normalize_section_headings(b)}"
|
||||
for t, b in zip(section_titles, section_bufs)
|
||||
)
|
||||
return f"# {article_title}\n\n{body}"
|
||||
|
||||
full_markdown = _assemble()
|
||||
|
||||
+48
-22
@@ -2,13 +2,16 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
|
||||
from langchain_core.messages import HumanMessage, SystemMessage
|
||||
from langchain_core.runnables import RunnableConfig
|
||||
|
||||
from ..state import AIWritingState, Outline, OutlineSection
|
||||
from ..prompts.writer_prompts import OUTLINE_SYSTEM, OUTLINE_USER
|
||||
from ..prompts.writer_prompts import (
|
||||
OUTLINE_SYSTEM, OUTLINE_USER, OUTLINE_REVISE_SYSTEM, OUTLINE_REVISE_USER,
|
||||
)
|
||||
from ._utils import get_model, parse_json, _content_to_text, ThinkTagParser
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -42,20 +45,39 @@ async def writer_outline_node(state: AIWritingState, config: RunnableConfig) ->
|
||||
pkg = state.get("material_package") or {"keywords": [], "materials": [], "summary": ""}
|
||||
intervention = state.get("last_user_intervention") or {}
|
||||
|
||||
feedback_section = ""
|
||||
if intervention.get("action") == "re_outline" and intervention.get("_feedback"):
|
||||
feedback_section = f"\n重新规划要求：{intervention['_feedback']}"
|
||||
feedback = ""
|
||||
if intervention.get("action") == "re_outline":
|
||||
feedback = intervention.get("_feedback") or intervention.get("outline_feedback") or ""
|
||||
elif intervention.get("outline_feedback"):
|
||||
feedback_section = f"\n重新规划要求：{intervention['outline_feedback']}"
|
||||
feedback = intervention.get("outline_feedback") or ""
|
||||
|
||||
user_prompt = OUTLINE_USER.format(
|
||||
user_intent=state["user_intent"],
|
||||
article_type=state.get("article_type", "analysis"),
|
||||
target_audience=state.get("target_audience", "普通读者"),
|
||||
word_count_target=state.get("word_count_target", 800),
|
||||
materials_summary=_materials_summary(pkg),
|
||||
feedback_section=feedback_section,
|
||||
)
|
||||
# 重新规划且已有大纲 → 走「编辑模式」：把当前大纲喂给模型，按用户要求调整，
|
||||
# 而非从零重生成（否则「加一节/删一节」这类指令没有可编辑的基准）。
|
||||
current_outline = state.get("current_outline")
|
||||
is_revise = bool(feedback) and bool(current_outline)
|
||||
|
||||
if is_revise:
|
||||
system_prompt = OUTLINE_REVISE_SYSTEM
|
||||
user_prompt = OUTLINE_REVISE_USER.format(
|
||||
user_intent=state["user_intent"],
|
||||
article_type=state.get("article_type", "analysis"),
|
||||
target_audience=state.get("target_audience", "普通读者"),
|
||||
word_count_target=state.get("word_count_target", 800),
|
||||
current_outline=json.dumps(current_outline, ensure_ascii=False, indent=2),
|
||||
feedback=feedback,
|
||||
materials_summary=_materials_summary(pkg),
|
||||
)
|
||||
else:
|
||||
system_prompt = OUTLINE_SYSTEM
|
||||
feedback_section = f"\n重新规划要求：{feedback}" if feedback else ""
|
||||
user_prompt = OUTLINE_USER.format(
|
||||
user_intent=state["user_intent"],
|
||||
article_type=state.get("article_type", "analysis"),
|
||||
target_audience=state.get("target_audience", "普通读者"),
|
||||
word_count_target=state.get("word_count_target", 800),
|
||||
materials_summary=_materials_summary(pkg),
|
||||
feedback_section=feedback_section,
|
||||
)
|
||||
|
||||
# SSE 流式推送
|
||||
cfg = config.get("configurable", {})
|
||||
@@ -70,7 +92,7 @@ async def writer_outline_node(state: AIWritingState, config: RunnableConfig) ->
|
||||
# 留在 try 外会硬崩溃；放进来则统一走下方的 status:error 兜底。
|
||||
model = get_model(config)
|
||||
async for chunk in model.astream([
|
||||
SystemMessage(content=OUTLINE_SYSTEM),
|
||||
SystemMessage(content=system_prompt),
|
||||
HumanMessage(content=user_prompt),
|
||||
]):
|
||||
delta = _content_to_text(chunk.content)
|
||||
@@ -98,14 +120,18 @@ async def writer_outline_node(state: AIWritingState, config: RunnableConfig) ->
|
||||
}],
|
||||
}
|
||||
|
||||
fallback = {
|
||||
"title": "未命名文章",
|
||||
"sections": [
|
||||
{"section_title": "引言", "key_points": ["背景介绍"], "material_ids": []},
|
||||
{"section_title": "正文", "key_points": ["核心内容"], "material_ids": []},
|
||||
{"section_title": "结论", "key_points": ["总结"], "material_ids": []},
|
||||
],
|
||||
}
|
||||
# 编辑模式解析失败时回退为「当前大纲」，避免把用户已有大纲弄丢
|
||||
if is_revise:
|
||||
fallback = current_outline
|
||||
else:
|
||||
fallback = {
|
||||
"title": "未命名文章",
|
||||
"sections": [
|
||||
{"section_title": "引言", "key_points": ["背景介绍"], "material_ids": []},
|
||||
{"section_title": "正文", "key_points": ["核心内容"], "material_ids": []},
|
||||
{"section_title": "结论", "key_points": ["总结"], "material_ids": []},
|
||||
],
|
||||
}
|
||||
result = parse_json(full_text, fallback)
|
||||
|
||||
outline = _parse_outline(result)
|
||||
|
||||
+15
-4
@@ -1,9 +1,13 @@
|
||||
# 注：两个 USER 提示词末尾的 `/no_think` 是 Qwen3 系列的"软开关"，
|
||||
# 收到当轮即跳过思考过程；对其它大模型只是一行普通文本、无副作用。
|
||||
# 中文「严禁思考」强令块对所有模型生效，保留不动。
|
||||
|
||||
EXTRACT_KEYWORDS_SYSTEM = """你是一名专业情报研究员（素材收集专家）。
|
||||
你的目标：为写作任务提取搜索关键词。
|
||||
你的工作背景：你在一家权威媒体机构任职，熟悉各类信息源的可信度评估。
|
||||
|
||||
你只能做以下事情：
|
||||
1. 从写作意图中提取 3-6 个搜索关键词
|
||||
1. 从写作意图中按要求的数量提取搜索关键词
|
||||
你不能写文章，不能评价内容好坏，只做关键词提取。
|
||||
|
||||
【严禁思考】
|
||||
@@ -25,8 +29,13 @@ EXTRACT_KEYWORDS_USER = """写作意图：{user_intent}
|
||||
文章类型：{article_type}
|
||||
目标读者：{target_audience}
|
||||
|
||||
请提取 3-6 个搜索关键词，用于搜集相关素材。只输出 JSON：
|
||||
{{"keywords": ["关键词1", "关键词2"]}}"""
|
||||
请提取 {keyword_count} 个搜索关键词，用于搜集相关素材。
|
||||
关键词数量必须为 {keyword_count} 个，不多不少。
|
||||
关键词必须是依据上述写作意图提炼的真实检索词，不要照抄下方 JSON 模板里的占位符。
|
||||
只输出 JSON（下方 ... 是占位示意，不是真实关键词）：
|
||||
{{"keywords": ["...", "..."]}}
|
||||
|
||||
/no_think"""
|
||||
|
||||
RANK_MATERIALS_SYSTEM = """你是一名专业情报研究员（素材收集专家）。
|
||||
你的目标：对搜索结果按相关度排序和筛选。
|
||||
@@ -56,4 +65,6 @@ RANK_MATERIALS_USER = """写作意图：{user_intent}
|
||||
{materials_list}
|
||||
|
||||
请选出最相关的素材ID（最多8条），按相关度从高到低排序。只输出 JSON：
|
||||
{{"ranked_ids": ["id1", "id2"], "summary": "共搜索到X条素材，精选Y条"}}"""
|
||||
{{"ranked_ids": ["id1", "id2"], "summary": "共搜索到X条素材，精选Y条"}}
|
||||
|
||||
/no_think"""
|
||||
+103
-12
@@ -5,7 +5,17 @@ OUTLINE_SYSTEM = """你是一名专业内容创作者（作家）。
|
||||
你只能做以下事情：
|
||||
1. 分析素材，提取核心观点
|
||||
2. 规划文章章节结构和每节要点
|
||||
你不能写正文，只写大纲。
|
||||
你不能写正文，只写大纲。大纲须紧扣写作意图，并尽量覆盖可用素材中的核心信息。
|
||||
|
||||
【严禁思考与表态】（最高优先级）
|
||||
- 禁止输出任何思考、分析、规划过程，禁止 <think></think> 标签及其中内容。
|
||||
- 禁止输出任何对用户说的话或对任务的评价（如"素材不足""无法规划大纲"）；无论素材是否充分，都必须直接产出大纲 JSON。
|
||||
- 收到输入后立即、直接输出最终 JSON，不得有任何前置内容。
|
||||
|
||||
【要点（key_points）的特殊要求】
|
||||
- 每个要点都会作为文章里的一个二级小标题呈现，所以要点必须写成"标题式短语"。
|
||||
- 用简洁的名词性短语，控制在 15 字以内，不要写成完整句子，不要带句末标点。
|
||||
- 每个章节规划 2-4 个要点，不要过多，避免文章被切得过碎。
|
||||
|
||||
【输出要求】
|
||||
- 只输出一个 JSON 对象，不要任何解释文字，不要 markdown 代码块。
|
||||
@@ -17,9 +27,9 @@ OUTLINE_SYSTEM = """你是一名专业内容创作者（作家）。
|
||||
{
|
||||
"title": "新能源汽车出口为何高速增长",
|
||||
"sections": [
|
||||
{"section_title": "引言：出口数据创新高", "key_points": ["今年出口量同比增长", "在全球市场的排名变化"], "material_ids": ["m001"]},
|
||||
{"section_title": "引言：出口数据创新高", "key_points": ["出口量同比增幅", "全球市场排名变化"], "material_ids": ["m001"]},
|
||||
{"section_title": "增长背后的三大动因", "key_points": ["产业链成本优势", "海外政策利好", "产品竞争力提升"], "material_ids": ["m002", "m003"]},
|
||||
{"section_title": "结论与展望", "key_points": ["未来增长面临的挑战", "行业趋势判断"], "material_ids": ["m004"]}
|
||||
{"section_title": "结论与展望", "key_points": ["未来增长挑战", "行业趋势判断"], "material_ids": ["m004"]}
|
||||
]
|
||||
}"""
|
||||
|
||||
@@ -33,21 +43,98 @@ OUTLINE_USER = """写作意图：{user_intent}
|
||||
|
||||
请规划文章大纲（3-5个章节），只输出 JSON 格式。"""
|
||||
|
||||
# ── 重新规划（基于现有大纲的编辑）─────────────────────────────────────────────
|
||||
|
||||
OUTLINE_REVISE_SYSTEM = """你是一名专业内容创作者（作家）。
|
||||
你的目标：根据用户的修改要求，调整一份【已有的文章大纲】。
|
||||
你的工作背景：你有十年内容创作经验，擅长精准理解修改意图并落实到大纲结构上。
|
||||
|
||||
你只能做以下事情：
|
||||
1. 在「当前大纲」基础上，按「用户修改要求」做调整
|
||||
你不能写正文，只输出调整后的大纲。
|
||||
|
||||
【修改原则】（最高优先级）
|
||||
- 准确识别并落实用户意图，常见操作：新增章节、删除章节、合并章节、拆分章节、调整章节顺序、修改章节标题、调整章节要点。
|
||||
- 只改用户明确提到的部分：用户没要求改动的章节，必须原样保留（标题、要点、material_ids 全部不变）。
|
||||
- 新增章节时：紧扣写作意图补充合理章节，并尽量关联可用素材的 material_ids。
|
||||
- 章节数量完全由用户要求决定，没有上下限——用户要加就加、要减就减。
|
||||
|
||||
【严禁思考与表态】（最高优先级）
|
||||
- 禁止输出任何思考、分析、规划过程，禁止 <think></think> 标签及其中内容。
|
||||
- 禁止输出任何对用户说的话；收到输入后立即、直接输出最终 JSON。
|
||||
|
||||
【要点（key_points）的特殊要求】
|
||||
- 每个要点会作为文章里的二级小标题呈现，写成简洁名词性短语，15 字以内，不带句末标点。
|
||||
- 每个章节 2-4 个要点。
|
||||
|
||||
【输出要求】
|
||||
- 只输出一个调整后的【完整】大纲 JSON 对象，不要解释文字，不要 markdown 代码块。
|
||||
- 必须使用英文双引号 "。
|
||||
- material_ids 中的 ID 必须来自给定素材，没有合适素材时填 []。
|
||||
- 结构与「当前大纲」一致：
|
||||
{"title": "...", "sections": [{"section_title": "...", "key_points": ["..."], "material_ids": ["..."]}]}"""
|
||||
|
||||
OUTLINE_REVISE_USER = """写作意图：{user_intent}
|
||||
文章类型：{article_type}
|
||||
目标读者：{target_audience}
|
||||
目标字数：{word_count_target}字
|
||||
|
||||
当前大纲（JSON）：
|
||||
{current_outline}
|
||||
|
||||
用户修改要求：{feedback}
|
||||
|
||||
可用素材摘要：
|
||||
{materials_summary}
|
||||
|
||||
请在「当前大纲」基础上落实上述「用户修改要求」，未提到的章节保持原样，输出调整后的完整大纲 JSON。"""
|
||||
|
||||
DRAFT_SECTION_SYSTEM = """你是一名专业内容创作者（作家）。
|
||||
你的目标：根据大纲和素材，写出一段高质量的文章内容。
|
||||
你的目标：根据大纲和素材，写出一段结构清晰、高质量的文章内容。
|
||||
你的工作背景：你有十年内容创作经验，文字流畅，善于用事实说话。
|
||||
|
||||
你只能做以下事情：
|
||||
1. 根据给定的章节要点和素材写这一段内容
|
||||
2. 观点必须来自素材，不编造数据
|
||||
2. 优先采用素材中的事实与数据；素材不足时可结合你的通用知识与常识补充论述，但须紧扣写作意图与章节主题，不要脱离主题杜撰具体的数字、人名、机构名与日期
|
||||
你不能修改大纲，不能写其他章节，只写当前这一段。
|
||||
|
||||
【严禁思考与表态】（最高优先级）
|
||||
- 禁止输出任何思考、分析、规划过程，禁止"让我想想""首先""我需要""根据写作要求"之类的过渡语。
|
||||
- 禁止输出 <think></think> 标签及其中的任何内容。
|
||||
- 禁止输出任何对用户说的话或对任务本身的评价，例如"我无法完成此任务""您提供的素材无法支撑写作""建议您提供……素材""素材与意图不匹配"等——这类话绝不允许出现在文章里。
|
||||
- 无论素材是否充分，你都必须直接产出文章正文本身；收到输入后立即开始写正文（含 ### 小标题），不要有任何前置说明。
|
||||
|
||||
【结构要求】
|
||||
- 把本章节的每一个「章节要点」写成一个二级小标题，用 Markdown 三级标题语法：### 要点
|
||||
- 每个 ### 小标题下面紧跟该要点的论述正文，正文连贯成段。
|
||||
- 即使章节只有一个要点，也要为它写出对应的 ### 小标题。
|
||||
- 小标题文字简洁，直接沿用给定的要点措辞，不要加序号、不要加标点。
|
||||
- 只能使用 ### 这一级标题；绝不要输出 # 或 ##（文章标题、章节标题由系统统一添加）。
|
||||
|
||||
【输出要求】
|
||||
- 直接返回这一段的正文文字，不要 JSON，不要章节标题，不要解释。
|
||||
- 直接返回这一段的内容（含 ### 小标题与正文），不要 JSON，不要解释。
|
||||
- 不要写"以下是正文""本段内容如下"之类的开场白。
|
||||
- 段落要连贯成文，不要罗列要点。
|
||||
- 紧扣本章节主题，不要写「文章整体结构」中其他章节负责的内容，避免重复。
|
||||
- 充分展开每个要点：每个要点至少用 2-3 句话论述，结合素材中的事实与数据说理，写满要求的篇幅。"""
|
||||
- 充分展开每个要点：每个要点至少用 2-3 句话论述，尽量结合素材中的事实与数据说理，写满要求的篇幅。"""
|
||||
|
||||
# ── 写作模式说明：注入 DRAFT_SECTION_USER 的 {mode_section} ───────────────────
|
||||
|
||||
# 章节无法基于素材写作时，作家在严格模式下输出的哨兵标记
|
||||
SECTION_BLOCKED_MARKER = "[[SECTION_BLOCKED]]"
|
||||
|
||||
WRITER_MODE_LOOSE = """
|
||||
【写作模式：宽松】
|
||||
素材充分时优先采用素材；素材不足时可结合你的通用知识与常识补充论述，
|
||||
但必须紧扣写作意图与本章节主题，不要脱离主题杜撰具体数字、人名、机构名。"""
|
||||
|
||||
WRITER_MODE_STRICT = """
|
||||
【写作模式：严格依据素材】
|
||||
本章节论述必须严格基于上方「相关素材」，不得使用素材之外的知识，不得杜撰任何事实与数据。
|
||||
如果上方素材确实不足以支撑本章节的写作，不要勉强拼凑、不要写无关内容，
|
||||
此时只输出一行：{marker} 一句话说明缺什么素材（例：{marker} 缺少关于XX的具体数据与案例），
|
||||
此外不要输出任何内容。只要素材能支撑哪怕部分要点，就正常写作，不要输出该标记。""".format(
|
||||
marker=SECTION_BLOCKED_MARKER
|
||||
)
|
||||
|
||||
DRAFT_SECTION_USER = """文章标题：{article_title}
|
||||
文章整体结构：
|
||||
@@ -58,8 +145,9 @@ DRAFT_SECTION_USER = """文章标题：{article_title}
|
||||
|
||||
相关素材：
|
||||
{section_materials}
|
||||
{revision_section}
|
||||
请写出「{section_title}」这一章节的正文内容，不少于 {target_words} 字，论述充分、内容充实。"""
|
||||
{revision_section}{mode_section}
|
||||
请写出「{section_title}」这一章节的内容，不少于 {target_words} 字。
|
||||
把上述每个章节要点写成一个 ### 二级小标题，并在标题下展开论述，论述充分、内容充实。"""
|
||||
|
||||
DRAFT_EXPAND_USER = """文章标题：{article_title}
|
||||
当前章节：{section_title}
|
||||
@@ -71,5 +159,8 @@ DRAFT_EXPAND_USER = """文章标题：{article_title}
|
||||
这一章节已有内容如下：
|
||||
{existing_text}
|
||||
|
||||
以上内容篇幅不足。请在保留原意和事实的基础上重写并扩充这一章节，使正文不少于 {target_words} 字。
|
||||
要求：补充更多来自素材的事实、数据与分析，论述更充分、更具体；直接返回扩充后的完整章节正文，不要章节标题、不要解释。"""
|
||||
以上内容篇幅不足。请在保留原意、事实和 ### 二级小标题结构的基础上重写并扩充这一章节，使内容不少于 {target_words} 字。
|
||||
要求：
|
||||
- 补充更多来自素材的事实、数据与分析，论述更充分、更具体。
|
||||
- 保留并沿用原有的 ### 小标题（每个章节要点对应一个），只用 ### 这一级标题，不要输出 # 或 ##。
|
||||
- 直接返回扩充后的完整章节内容（含 ### 小标题），不要解释。"""
|
||||
+14
-1
@@ -73,17 +73,27 @@ class UserInterventionPayload(TypedDict):
|
||||
WritingStatus = Literal[
|
||||
"researching", "awaiting_material_confirm",
|
||||
"writing_outline", "awaiting_outline_confirm",
|
||||
"writing_draft", "awaiting_draft_confirm",
|
||||
"writing_draft", "awaiting_section_help", "awaiting_draft_confirm",
|
||||
"reviewing", "awaiting_review_confirm",
|
||||
"revising", "done", "error",
|
||||
]
|
||||
|
||||
|
||||
class BlockedSection(TypedDict):
|
||||
"""严格模式下素材不足、无法写作的章节。"""
|
||||
section_title: str
|
||||
reason: str
|
||||
|
||||
class AIWritingState(TypedDict):
|
||||
# 写作配置
|
||||
user_intent: str
|
||||
article_type: str
|
||||
target_audience: str
|
||||
word_count_target: int
|
||||
# 素材检索关键词数量（用户指定，1~10，默认 6）
|
||||
keyword_count: int
|
||||
# 写作模式：strict=严格依据素材 / loose=可结合通用知识（默认 loose）
|
||||
writing_mode: str
|
||||
|
||||
# Agent A 输出
|
||||
material_package: Optional[MaterialPackage]
|
||||
@@ -99,6 +109,9 @@ class AIWritingState(TypedDict):
|
||||
# 用户干预数据（每个干预点会覆盖）
|
||||
last_user_intervention: Optional[UserInterventionPayload]
|
||||
|
||||
# 严格模式下素材不足、待用户决策的章节（写作节点产出，求助暂停点消费）
|
||||
blocked_sections: Optional[List[BlockedSection]]
|
||||
|
||||
# 流程控制
|
||||
revision_count: int
|
||||
max_revisions: int
|
||||
|
||||
Reference in new issue
Block a user