Re-embed the knowledge base when the embedding model changes

Vectors from two different embedding models are not comparable — Titan v2 has
1024 dimensions where nomic-embed-text has 768 — and _cosine_similarity zips
them, so a mismatch produced quietly meaningless scores rather than an error.
Nothing forced a re-embed either: sync_local_kb only looked at the content
hash, so switching models left every cached vector in place.

local_knowledge_docs now records the model each vector came from, and a row is
re-embedded when its content hash OR its model differs. Saving a new
LOCAL_KB_EMBEDDING_MODEL from the settings panel starts a background pass over
every file; the knowledge base panel also has a button for it. While that pass
runs, the per-request sync steps aside so no file is embedded twice.

The panel now shows what the embedding model is doing: model name, vector
size, how many files are embedded with the current model, how many are still
on an older one, a progress bar while a pass runs, and the last error. A
"接続テスト" button embeds one short string so a broken or unreachable model
can be told apart from one that is merely slow to warm up.

Also read TAVILY_API_KEY from os.environ at call time. It was imported as a
config constant, which is evaluated before load_into_env() runs, so a key
saved from the settings panel was stored but never used — not even after a
restart.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

docs/api.md

@@ -306,6 +306,46 @@ attachment; filename="______.md"; filename*=UTF-8''%E8%B2%B7%E3%81%84%E7%89%A9%E
 
 ---
 
+### GET /api/kb/embedding
+埋め込みモデルの現状と、再埋め込みの進捗を返す。
+
+```json
+{
+  "model": "ollama/nomic-embed-text",
+  "dimensions": 768,
+  "file_count": 36,
+  "indexed": 36,
+  "stale": 0,
+  "running": false,
+  "total": 36,
+  "done": 36,
+  "failed": 0,
+  "started_at": "2026-08-23T13:50:23.196274Z",
+  "finished_at": "2026-08-23T13:50:29.951099Z",
+  "last_error": null
+}
+```
+
+`indexed` は**現在のモデルで**埋め込まれている件数、`stale` は別モデル（またはモデル不明）のまま残っている件数。
+`running` 以下は実行中の進捗で、プロセス内のメモリにしか無い（再起動で消える。ワーカーを複数立てるとワーカーごとに別の値になる）。
+
+---
+
+### POST /api/kb/embedding/test
+短いテキストを実際に 1 回埋め込んでみて、モデルが応答するかを確かめる。失敗しても 200 で返し、`error` に理由が入る。
+
+```json
+{ "ok": true, "model": "ollama/nomic-embed-text", "dimensions": 768, "latency_ms": 412.3, "error": null }
+```
+
+---
+
+### POST /api/kb/embedding/reindex
+全ファイルの再埋め込みをバックグラウンドで開始し、開始直後の状態（`running: true`）を返す。
+すでに実行中なら何も起こさず現在の進捗を返す。
+
+---
+
 ## ログ
 
 ### GET /logs