feat: add heartbeat monitor and vector memory search (Tier 2)

Heartbeat:
- HeartbeatMonitor with 5 checks: gateway, model, channels, memory, disk
- Configurable interval, failure threshold, notification channel
- Recovery notifications when health restores
- 25 new tests

Vector Memory Search:
- EmbeddingProvider interface with OpenAI, Gemini, Ollama, LlamaCpp backends
- SQLite-backed VectorStore with cosine similarity search
- Text chunker with paragraph-aware splitting and overlap
- HybridSearch merging keyword + vector results with configurable weight
- Background indexer with dirty-namespace tracking
- Graceful fallback to keyword search when embeddings unavailable
- 51 new tests

Config: automation.heartbeat + memory.embedding schema sections
Total: 950 tests passing, all types clean

src/config/schema.ts

@@ -119,9 +119,24 @@ const webhookSchema = z.object({
   enabled: z.boolean().default(true),
 });
 
+const heartbeatCheckSchema = z.enum(['gateway', 'model', 'channels', 'memory', 'disk']);
+
+const heartbeatSchema = z.object({
+  enabled: z.boolean().default(false),
+  interval: z.string().default('5m'),
+  checks: z.array(heartbeatCheckSchema).default(['gateway', 'model', 'channels', 'memory', 'disk']),
+  notify: z.object({
+    channel: z.string().min(1),
+    peer: z.string().min(1),
+  }).optional(),
+  failure_threshold: z.number().min(1).max(10).default(2),
+  disk_threshold_mb: z.number().min(10).default(100),
+}).default({});
+
 const automationSchema = z.object({
   cron: z.array(cronJobSchema).default([]),
   webhooks: z.array(webhookSchema).default([]),
+  heartbeat: heartbeatSchema,
 }).default({});
 
 const agentsSchema = z.object({
@@ -143,11 +158,27 @@ const agentsSchema = z.object({
   max_delegation_depth: z.number().min(1).max(10).default(3),
 }).default({});
 
+const embeddingProviderSchema = z.enum(['openai', 'gemini', 'ollama', 'llamacpp']);
+
+const embeddingSchema = z.object({
+  enabled: z.boolean().default(false),
+  provider: embeddingProviderSchema.default('openai'),
+  model: z.string().default('text-embedding-3-small'),
+  endpoint: z.string().optional(),
+  api_key: z.string().optional(),
+  dimensions: z.number().optional(),
+  chunk_size: z.number().min(64).max(8192).default(512),
+  chunk_overlap: z.number().min(0).max(1024).default(50),
+  top_k: z.number().min(1).max(50).default(5),
+  hybrid_weight: z.number().min(0).max(1).default(0.7),
+}).default({});
+
 const memorySchema = z.object({
   enabled: z.boolean().default(true),
   dir: z.string().optional(), // Default: ~/.local/share/flynn/memory
   auto_extract: z.boolean().default(true),
   max_context_tokens: z.number().min(100).max(10000).default(2000),
+  embedding: embeddingSchema,
 }).default({});
 
 const compactionSchema = z.object({
@@ -333,3 +364,7 @@ export type RoutingConfig = z.infer<typeof routingSchema>;
 export type ServerConfig = z.infer<typeof serverSchema>;
 export type SessionsConfig = z.infer<typeof sessionsSchema>;
 export type ThinkingConfig = z.infer<typeof thinkingSchema>;
+export type HeartbeatConfig = z.infer<typeof heartbeatSchema>;
+export type HeartbeatCheck = z.infer<typeof heartbeatCheckSchema>;
+export type EmbeddingConfig = z.infer<typeof embeddingSchema>;
+export type EmbeddingProvider = z.infer<typeof embeddingProviderSchema>;