fix(saas): industry template audit fixes + pgvector optional + relay timeout

- Fix seed template tools to match actual runtime tool names
  (file_read/file_write/shell_exec/web_fetch)
- Persist system_prompt/temperature/max_tokens via identity system
  in agentStore.createFromTemplate()
- Fire-and-forget assignTemplate() in AgentOnboardingWizard
- Fix saas-relay-client unused variable warning
- Make pgvector extension optional in knowledge_base migration
- Increase StreamBridge timeout from 30s to 90s for thinking models

crates/zclaw-saas/migrations/20260402000002_knowledge_base.sql

@@ -1,9 +1,9 @@
--- Migration: Knowledge Base tables with pgvector support
+-- Migration: Knowledge Base tables with optional pgvector support
 -- 5 tables: knowledge_categories, knowledge_items, knowledge_chunks,
 --           knowledge_versions, knowledge_usage
-
--- Enable pgvector extension
-CREATE EXTENSION IF NOT EXISTS vector;
+--
+-- pgvector is optional: if the extension is not installed, the embedding
+-- column and HNSW index are skipped. All other tables work normally.
 
 -- 行业分类树
 CREATE TABLE IF NOT EXISTS knowledge_categories (
@@ -42,12 +42,12 @@ CREATE INDEX IF NOT EXISTS idx_ki_status_updated ON knowledge_items(status, upda
 CREATE INDEX IF NOT EXISTS idx_ki_keywords ON knowledge_items USING GIN(keywords);
 
 -- 知识分块（RAG 检索核心）
+-- 基础表不含 embedding 列；若 pgvector 可用则后续通过 DO 块添加
 CREATE TABLE IF NOT EXISTS knowledge_chunks (
     id TEXT PRIMARY KEY,
     item_id TEXT NOT NULL REFERENCES knowledge_items(id) ON DELETE CASCADE,
     chunk_index INT NOT NULL,
     content TEXT NOT NULL,
-    embedding vector(1536),
     keywords TEXT[] DEFAULT '{}',
     created_at TIMESTAMPTZ DEFAULT NOW()
 );
@@ -55,11 +55,25 @@ CREATE UNIQUE INDEX IF NOT EXISTS idx_kchunks_item_idx ON knowledge_chunks(item_
 CREATE INDEX IF NOT EXISTS idx_kchunks_item ON knowledge_chunks(item_id);
 CREATE INDEX IF NOT EXISTS idx_kchunks_keywords ON knowledge_chunks USING GIN(keywords);
 
--- 向量相似度索引（HNSW，无需预填充数据）
--- 仅在有数据后创建此索引可提升性能，这里预创建
-CREATE INDEX IF NOT EXISTS idx_kchunks_embedding ON knowledge_chunks
-    USING hnsw (embedding vector_cosine_ops)
-    WITH (m = 16, ef_construction = 128);
+-- 条件添加 embedding 列和 HNSW 索引（仅当 pgvector 可用时）
+DO $$ BEGIN
+    PERFORM set_config('client_min_messages', 'warning', true);
+    CREATE EXTENSION IF NOT EXISTS vector;
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'knowledge_chunks' AND column_name = 'embedding'
+    ) THEN
+        ALTER TABLE knowledge_chunks ADD COLUMN embedding vector(1536);
+    END IF;
+    IF NOT EXISTS (SELECT 1 FROM pg_indexes WHERE indexname = 'idx_kchunks_embedding') THEN
+        CREATE INDEX idx_kchunks_embedding ON knowledge_chunks
+            USING hnsw (embedding vector_cosine_ops)
+            WITH (m = 16, ef_construction = 128);
+    END IF;
+    RAISE NOTICE 'pgvector enabled for knowledge base';
+EXCEPTION WHEN OTHERS THEN
+    RAISE NOTICE 'pgvector not available, vector features disabled: %', SQLERRM;
+END $$;
 
 -- 版本快照
 CREATE TABLE IF NOT EXISTS knowledge_versions (
@@ -89,7 +103,6 @@ CREATE TABLE IF NOT EXISTS knowledge_usage (
     created_at TIMESTAMPTZ DEFAULT NOW()
 );
 CREATE INDEX IF NOT EXISTS idx_ku_item ON knowledge_usage(item_id) WHERE item_id IS NOT NULL;
--- BRIN 索引：追加写入的时间序列数据比 B-tree 更高效
 CREATE INDEX IF NOT EXISTS idx_ku_created_brin ON knowledge_usage USING brin(created_at);
 
 -- 权限种子数据（使用 jsonb 操作避免 REPLACE 脆弱性）

crates/zclaw-saas/src/db.rs

@@ -577,7 +577,7 @@ async fn seed_demo_data(pool: &PgPool) -> SaasResult<()> {
         ("demo-agent-coder", "Code Assistant", "A helpful coding assistant that can write, review, and debug code",
          "coding", "gpt-4o",
          "You are an expert coding assistant. Help users write clean, efficient code.",
-         "[\"code_search\",\"code_edit\",\"terminal\"]", "[\"code_generation\",\"code_review\",\"debugging\"]",
+         "[\"file_read\",\"file_write\",\"shell_exec\"]", "[\"code_generation\",\"code_review\",\"debugging\"]",
          0.3, 8192,
          "你是一位资深全栈工程师，擅长代码编写、评审和调试。你追求简洁高效的代码风格，注重可读性和可维护性。",
          "[\"代码编写\",\"代码审查\",\"Bug调试\",\"架构设计\"]",
@@ -587,7 +587,7 @@ async fn seed_demo_data(pool: &PgPool) -> SaasResult<()> {
         ("demo-agent-writer", "Content Writer", "Creative writing and content generation agent",
          "creative", "claude-sonnet-4-20250514",
          "You are a skilled content writer. Create engaging, well-structured content.",
-         "[\"web_search\",\"document_edit\"]", "[\"writing\",\"editing\",\"summarization\"]",
+         "[\"web_fetch\",\"file_write\"]", "[\"writing\",\"editing\",\"summarization\"]",
          0.7, 4096,
          "你是一位创意写作专家，擅长各类文案创作、内容编辑和摘要生成。你善于把握文字的节奏和情感表达。",
          "[\"文章写作\",\"文案创作\",\"内容编辑\",\"摘要生成\"]",
@@ -597,7 +597,7 @@ async fn seed_demo_data(pool: &PgPool) -> SaasResult<()> {
         ("demo-agent-analyst", "Data Analyst", "Data analysis and visualization specialist",
          "analytics", "gpt-4o",
          "You are a data analysis expert. Help users analyze data and create visualizations.",
-         "[\"code_execution\",\"data_access\"]", "[\"data_analysis\",\"visualization\",\"statistics\"]",
+         "[\"shell_exec\",\"file_read\"]", "[\"data_analysis\",\"visualization\",\"statistics\"]",
          0.2, 8192,
          "你是一位数据分析专家，擅长统计分析、数据可视化和洞察提取。你善于从数据中发现有价值的模式和趋势。",
          "[\"数据分析\",\"可视化报表\",\"统计建模\",\"趋势预测\"]",
@@ -607,7 +607,7 @@ async fn seed_demo_data(pool: &PgPool) -> SaasResult<()> {
         ("demo-agent-researcher", "Research Agent", "Deep research and information synthesis agent",
          "research", "gemini-2.5-pro",
          "You are a research specialist. Conduct thorough research and synthesize findings.",
-         "[\"web_search\",\"document_access\"]", "[\"research\",\"synthesis\",\"citation\"]",
+         "[\"web_fetch\",\"file_read\"]", "[\"research\",\"synthesis\",\"citation\"]",
          0.4, 16384,
          "你是一位深度研究专家，擅长信息检索、文献综述和知识综合。你注重信息来源的可靠性和引用的准确性。",
          "[\"深度研究\",\"文献综述\",\"信息检索\",\"知识综合\"]",
@@ -627,7 +627,7 @@ async fn seed_demo_data(pool: &PgPool) -> SaasResult<()> {
         ("demo-agent-medical", "医疗助手", "Clinical decision support and medical literature assistant",
          "healthcare", "gpt-4o",
          "You are a medical AI assistant. Help with clinical decision support, literature retrieval, and medication reference. Always remind users that your suggestions do not replace professional medical advice.",
-         "[\"web_search\",\"document_access\"]", "[\"clinical_support\",\"literature_search\",\"diagnosis_assist\",\"medication_ref\"]",
+         "[\"web_fetch\",\"file_read\"]", "[\"clinical_support\",\"literature_search\",\"diagnosis_assist\",\"medication_ref\"]",
          0.2, 16384,
          "你是一位医疗AI助手，具备丰富的临床知识。你辅助临床决策、文献检索和用药参考。\n\n重要提示：\n- 你的建议仅供医疗专业人员参考\n- 不能替代正式的医疗诊断\n- 涉及患者安全的问题需格外谨慎\n- 始终建议用户咨询专业医生",
          "[\"临床辅助\",\"文献检索\",\"诊断建议\",\"用药参考\"]",

crates/zclaw-saas/src/relay/service.rs

@@ -13,8 +13,8 @@ use super::types::*;
 /// 上游无数据时，发送 SSE 心跳注释行的间隔
 const STREAMBRIDGE_HEARTBEAT_INTERVAL: Duration = Duration::from_secs(15);
 
-/// 上游无数据时，丢弃连接的超时阈值
-const STREAMBRIDGE_TIMEOUT: Duration = Duration::from_secs(30);
+/// 上游无数据时，丢弃连接的超时阈值（90s = 6 个心跳，给 thinking 模型更多时间）
+const STREAMBRIDGE_TIMEOUT: Duration = Duration::from_secs(90);
 
 /// 流结束后延迟清理的时间窗口
 const STREAMBRIDGE_CLEANUP_DELAY: Duration = Duration::from_secs(60);
@@ -526,9 +526,9 @@ fn build_stream_bridge(
                         idle_heartbeats as u64 * STREAMBRIDGE_HEARTBEAT_INTERVAL.as_secs(),
                     );
 
-                    // After 2 consecutive heartbeats without real data (30s),
+                    // After 6 consecutive heartbeats without real data (90s),
                     // terminate the stream to prevent connection leaks.
-                    if idle_heartbeats >= 2 {
+                    if idle_heartbeats >= 6 {
                         tracing::warn!(
                             "[StreamBridge] Timeout ({:?}) no real data, closing stream for task {}",
                             STREAMBRIDGE_TIMEOUT,

desktop/src/components/AgentOnboardingWizard.tsx

@@ -134,6 +134,12 @@ export function AgentOnboardingWizard({ isOpen, onClose, onSuccess }: AgentOnboa
         personality: full.personality || prev.personality,
         scenarios: full.scenarios.length > 0 ? full.scenarios : prev.scenarios,
       }));
+
+      // Persist template assignment to SaaS backend (fire-and-forget)
+      useSaaSStore.getState().assignTemplate(t.id).catch((err: unknown) => {
+        log.warn('Failed to assign template to account:', err);
+      });
+
       setCurrentStep(1);
     } catch {
       // If fetch fails, still allow manual creation

desktop/src/lib/saas-relay-client.ts

@@ -157,6 +157,16 @@ export function createSaaSRelayGatewayClient(
 
           try {
             const parsed = JSON.parse(data);
+
+            // Handle SSE error events from relay (e.g. stream_timeout)
+            if (parsed.error) {
+              const errMsg = parsed.message || parsed.error || 'Unknown stream error';
+              log.warn('SSE stream error:', errMsg);
+              callbacks.onError(errMsg);
+              callbacks.onComplete();
+              return { runId };
+            }
+
             const choices = parsed.choices?.[0];
             if (!choices) continue;
 

desktop/src/store/agentStore.ts

@@ -194,13 +194,37 @@ export const useAgentStore = create<AgentStore>((set, get) => ({
 
       const cloneId = result?.clone?.id;
 
-      // Persist SOUL.md via identity system
-      if (cloneId && template.soul_content) {
-        try {
-          const { intelligenceClient } = await import('../lib/intelligence-client');
-          await intelligenceClient.identity.updateFile(cloneId, 'soul', template.soul_content);
-        } catch (e) {
-          console.warn('Failed to persist soul_content:', e);
+      if (cloneId) {
+        // Persist SOUL.md via identity system
+        if (template.soul_content) {
+          try {
+            const { intelligenceClient } = await import('../lib/intelligence-client');
+            await intelligenceClient.identity.updateFile(cloneId, 'soul', template.soul_content);
+          } catch (e) {
+            console.warn('Failed to persist soul_content:', e);
+          }
+        }
+
+        // Persist system_prompt via identity system
+        if (template.system_prompt) {
+          try {
+            const { intelligenceClient } = await import('../lib/intelligence-client');
+            await intelligenceClient.identity.updateFile(cloneId, 'system', template.system_prompt);
+          } catch (e) {
+            console.warn('Failed to persist system_prompt:', e);
+          }
+        }
+
+        // Persist temperature / max_tokens if supported
+        if (template.temperature != null || template.max_tokens != null) {
+          try {
+            await client.updateClone(cloneId, {
+              temperature: template.temperature,
+              maxTokens: template.max_tokens,
+            });
+          } catch (e) {
+            console.warn('Failed to persist temperature/max_tokens:', e);
+          }
         }
       }