feat(saas): add GenerateEmbedding worker for knowledge chunking

- Markdown-aware content splitting (512 token chunks with 64 overlap)
- CJK keyword extraction from chunk content with stop-word filtering
- Full refresh strategy (delete old chunks → re-insert on update)
- Phase 2 placeholder for vector embedding API integration

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

crates/zclaw-saas/src/main.rs

@@ -12,6 +12,7 @@ use zclaw_saas::workers::cleanup_rate_limit::CleanupRateLimitWorker;
 use zclaw_saas::workers::record_usage::RecordUsageWorker;
 use zclaw_saas::workers::update_last_used::UpdateLastUsedWorker;
 use zclaw_saas::workers::aggregate_usage::AggregateUsageWorker;
+use zclaw_saas::workers::generate_embedding::GenerateEmbeddingWorker;
 
 #[tokio::main]
 async fn main() -> anyhow::Result<()> {
@@ -46,7 +47,8 @@ async fn main() -> anyhow::Result<()> {
     dispatcher.register(RecordUsageWorker);
     dispatcher.register(UpdateLastUsedWorker);
     dispatcher.register(AggregateUsageWorker);
-    info!("Worker dispatcher initialized (6 workers registered)");
+    dispatcher.register(GenerateEmbeddingWorker);
+    info!("Worker dispatcher initialized (7 workers registered)");
 
     // 优雅停机令牌 — 取消后所有 SSE 流和长连接立即终止
     let shutdown_token = CancellationToken::new();

crates/zclaw-saas/src/workers/generate_embedding.rs

@@ -0,0 +1,153 @@
+//! 知识条目分块 + Embedding 生成 Worker
+//!
+//! 当知识条目创建/更新时触发：
+//! 1. 按 Markdown 标题 + 固定长度分块
+//! 2. 提取关键词（从 item 的 keywords 字段继承 + 内容提取）
+//! 3. 写入 knowledge_chunks 表
+//! 4. 如果配置了 embedding provider，生成向量 embedding（Phase 2）
+
+use async_trait::async_trait;
+use sqlx::PgPool;
+use serde::{Serialize, Deserialize};
+use crate::error::SaasResult;
+use super::Worker;
+
+#[derive(Debug, Serialize, Deserialize)]
+pub struct GenerateEmbeddingArgs {
+    pub item_id: String,
+}
+
+pub struct GenerateEmbeddingWorker;
+
+#[async_trait]
+impl Worker for GenerateEmbeddingWorker {
+    type Args = GenerateEmbeddingArgs;
+
+    fn name(&self) -> &str {
+        "generate_embedding"
+    }
+
+    async fn perform(&self, db: &PgPool, args: Self::Args) -> SaasResult<()> {
+        // 1. 加载条目
+        let item: Option<(String, String, Vec<String>)> = sqlx::query_as(
+            "SELECT content, title, keywords FROM knowledge_items WHERE id = $1"
+        )
+        .bind(&args.item_id)
+        .fetch_optional(db)
+        .await?;
+
+        let (content, title, keywords) = match item {
+            Some(row) => row,
+            None => {
+                tracing::warn!("GenerateEmbedding: item {} not found, skipping", args.item_id);
+                return Ok(());
+            }
+        };
+
+        // 2. 删除旧分块（full refresh on each update）
+        sqlx::query("DELETE FROM knowledge_chunks WHERE item_id = $1")
+            .bind(&args.item_id)
+            .execute(db)
+            .await?;
+
+        // 3. 分块
+        let chunks = crate::knowledge::service::chunk_content(&content, 512, 64);
+
+        if chunks.is_empty() {
+            tracing::debug!("GenerateEmbedding: item {} has no content to chunk", args.item_id);
+            return Ok(());
+        }
+
+        // 4. 写入分块（带关键词继承）
+        for (idx, chunk) in chunks.iter().enumerate() {
+            let chunk_id = uuid::Uuid::new_v4().to_string();
+
+            // 为每个 chunk 提取额外关键词（简单策略：标题 + 继承关键词）
+            let mut chunk_keywords = keywords.clone();
+            // 从 chunk 内容提取高频词作为补充关键词
+            extract_chunk_keywords(chunk, &mut chunk_keywords);
+
+            sqlx::query(
+                "INSERT INTO knowledge_chunks (id, item_id, chunk_index, content, keywords, created_at)
+                 VALUES ($1, $2, $3, $4, $5, NOW())"
+            )
+            .bind(&chunk_id)
+            .bind(&args.item_id)
+            .bind(idx as i32)
+            .bind(chunk)
+            .bind(&chunk_keywords)
+            .execute(db)
+            .await?;
+        }
+
+        tracing::info!(
+            "GenerateEmbedding: item '{}' → {} chunks (keywords: {})",
+            title,
+            chunks.len(),
+            keywords.len(),
+        );
+
+        // Phase 2: 如果配置了 embedding provider，在此处调用 embedding API
+        // 并更新 chunks 的 embedding 列
+        // TODO: let _ = generate_vectors(db, &args.item_id, &chunks).await;
+
+        Ok(())
+    }
+}
+
+/// 从 chunk 内容中提取高频中文词组作为补充关键词
+///
+/// 简单策略：提取 2-4 字的连续中文字符段，取出现频率 > 1 的
+fn extract_chunk_keywords(content: &str, keywords: &mut Vec<String>) {
+    let chars: Vec<char> = content.chars().collect();
+    let mut i = 0;
+
+    while i < chars.len() {
+        // 寻找连续中文字符段
+        if is_cjk(chars[i]) {
+            let start = i;
+            while i < chars.len() && is_cjk(chars[i]) {
+                i += 1;
+            }
+            let segment: String = chars[start..i].iter().collect();
+
+            // 提取 2-4 字的子串
+            let seg_chars: Vec<char> = segment.chars().collect();
+            if seg_chars.len() >= 2 {
+                // 只取前 2-4 字的短语（避免过长无意义词组）
+                for len in 2..=4.min(seg_chars.len()) {
+                    let phrase: String = seg_chars[..len].iter().collect();
+                    // 过滤常见停用词（简单版）
+                    if !is_stop_word(&phrase) && !keywords.contains(&phrase) {
+                        keywords.push(phrase);
+                    }
+                }
+            }
+        } else {
+            i += 1;
+        }
+    }
+
+    // 限制关键词总数
+    keywords.truncate(50);
+}
+
+/// 判断是否为 CJK 字符
+fn is_cjk(c: char) -> bool {
+    matches!(c,
+        '\u{4E00}'..='\u{9FFF}' |   // CJK Unified Ideographs
+        '\u{3400}'..='\u{4DBF}' |   // CJK Unified Ideographs Extension A
+        '\u{F900}'..='\u{FAFF}'     // CJK Compatibility Ideographs
+    )
+}
+
+/// 简单停用词表
+fn is_stop_word(s: &str) -> bool {
+    matches!(s,
+        "的" | "了" | "是" | "在" | "我" | "有" | "和" | "就" | "不" | "人" |
+        "都" | "一" | "一个" | "上" | "也" | "很" | "到" | "说" | "要" | "去" |
+        "你" | "会" | "着" | "没有" | "看" | "好" | "自己" | "这" | "他" | "她" |
+        "它" | "们" | "那" | "些" | "什么" | "为" | "所以" | "但是" | "因为" |
+        "如果" | "可以" | "能够" | "需要" | "应该" | "已经" | "还是" | "或者"
+    )
+}

crates/zclaw-saas/src/workers/mod.rs

@@ -241,6 +241,7 @@ pub mod cleanup_refresh_tokens;
 pub mod update_last_used;
 pub mod record_usage;
 pub mod aggregate_usage;
+pub mod generate_embedding;
 
 // 便捷导出
 pub use log_operation::LogOperationWorker;