knowledge: stamp model + backend on facts for audit

Adds two nullable TEXT columns to entity_facts —
`created_by_model` (LLM identifier) and `created_by_backend`
("local" / "hybrid" / "manual" / NULL) — so the curator can audit
which configurations produce good fact-keeping and which produce
noise.

photo_insights already carries model_version + backend, and
entity_facts.source_insight_id links to it, but:
  - source_insight_id is set post-loop, so chat-continuation and
    regenerated-insight facts lose the link.
  - JOINing per read is more friction than embedding provenance on
    the row itself.
  - Manual facts (POST /knowledge/facts) have no insight at all and
    need their own "manual" provenance marker.

Threading: execute_tool grows `model` + `backend` params, passed
from the three call sites (agentic insight loop, chat single-turn,
chat stream) using the loop-time `chat_backend.primary_model()` +
`effective_backend` already in scope. tool_store_fact stamps the
new fact accordingly; manual create_fact stamps backend="manual".
Legacy rows leave both NULL — pre-tracking data can't be back-
filled reliably from training_messages without burning compute.

Indexes are partial (WHERE NOT NULL) so legacy rows don't bloat
them, and "show me all facts from model X" stays fast.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

src/ai/insight_chat.rs

@@ -497,6 +497,8 @@ impl InsightChatService {
                             &normalized,
                             req.user_id,
                             &active_persona,
+                            &model_used,
+                            &effective_backend,
                             &loop_cx,
                         )
                         .await;
@@ -870,6 +872,8 @@ impl InsightChatService {
                 &normalized,
                 req.user_id,
                 &active_persona,
+                &model_used,
+                &effective_backend,
                 max_iterations,
                 &tx,
             )
@@ -1059,6 +1063,8 @@ impl InsightChatService {
                 &normalized,
                 req.user_id,
                 &active_persona,
+                &model_used,
+                &effective_backend,
                 max_iterations,
                 &tx,
             )
@@ -1210,6 +1216,10 @@ impl InsightChatService {
         normalized: &str,
         user_id: i32,
         active_persona: &str,
+        // Provenance — stamped onto any store_fact tool call made
+        // during this loop. Mirrors the non-streaming chat path.
+        model_used: &str,
+        effective_backend: &str,
         max_iterations: usize,
         tx: &tokio::sync::mpsc::Sender<ChatStreamEvent>,
     ) -> Result<AgenticLoopOutcome> {
@@ -1290,6 +1300,8 @@ impl InsightChatService {
                             normalized,
                             user_id,
                             active_persona,
+                            model_used,
+                            effective_backend,
                             &cx,
                         )
                         .await;