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/database/insights_dao.rs

@@ -90,13 +90,15 @@ pub trait InsightDao: Sync + Send {
     /// Replace the `training_messages` JSON blob on the current row for
     /// `(library_id, rel_path)`. Used by chat-turn append mode to persist
     /// the extended conversation without inserting a new insight version.
+    /// Returns the number of rows affected (0 if no current row matched,
+    /// indicating a concurrent regenerate/reconcile flipped `is_current`).
     fn update_training_messages(
         &mut self,
         context: &opentelemetry::Context,
         library_id: i32,
         file_path: &str,
         training_messages_json: &str,
-    ) -> Result<(), DbError>;
+    ) -> Result<usize, DbError>;
 }
 
 pub struct SqliteInsightDao {
@@ -372,7 +374,7 @@ impl InsightDao for SqliteInsightDao {
         lib_id: i32,
         path: &str,
         training_messages_json: &str,
-    ) -> Result<(), DbError> {
+    ) -> Result<usize, DbError> {
         trace_db_call(context, "update", "update_training_messages", |_span| {
             use schema::photo_insights::dsl::*;
 
@@ -386,7 +388,6 @@ impl InsightDao for SqliteInsightDao {
             )
             .set(training_messages.eq(Some(training_messages_json.to_string())))
             .execute(connection.deref_mut())
-            .map(|_| ())
             .map_err(|_| anyhow::anyhow!("Update error"))
         })
         .map_err(|_| DbError::new(DbErrorKind::UpdateError))