feat: async insight generation with SQLite job tracking

- Add insight_generation_jobs table migration and DAO
- Implement job lifecycle: create_or_get_active, complete, fail, cancel
- Refactor POST /insights/generate and /agentic to async spawn with timeout
- Add GET /insights/generation/status endpoint with job_id and file_path lookup
- Use String for enum fields in Diesel models to avoid private Bound type
- Add from_str() helpers on InsightJobStatus and InsightGenerationType
- Fix update_training_messages to return Result<usize, DbError>
- 7/7 DAO unit tests passing

src/main.rs

@@ -308,6 +308,7 @@ fn main() -> std::io::Result<()> {
                 .service(memories::list_memories)
                 .service(ai::generate_insight_handler)
                 .service(ai::generate_agentic_insight_handler)
+                .service(ai::generation_status_handler)
                 .service(ai::get_insight_handler)
                 .service(ai::delete_insight_handler)
                 .service(ai::get_all_insights_handler)