feat(ai): separate base URL and API key for chat vs embedding model

Per-workspace AI provider config previously shared a single base URL and
a single API key between the chat model and the embedding model. Add
dedicated, optional embedding endpoint/token that fall back to the chat
values when empty, preserving backward compatibility.

- db: new migration adds nullable `embedding_api_key_enc` to
  `ai_provider_credentials`; chat key stays in `api_key_enc`
- repo: add `upsertEmbeddingKey` / `clearEmbeddingKey` (on-conflict
  touches only its own column, so chat/embedding keys never overwrite)
- ai-settings.service: store non-secret `embeddingBaseUrl`; resolve()
  applies fallback (embeddingBaseUrl || baseUrl; embedding key || chat
  key); getMasked() exposes raw `embeddingBaseUrl` + `hasEmbeddingApiKey`,
  never the key; update() handles the embedding key write-only
- ai.service: getEmbeddingModel() builds openai/gemini/ollama with the
  embedding-specific URL/key; chat path unchanged
- client: new "Embedding base URL" and "Embedding API key" fields with
  fallback hints and a clear-key action

Requires running the DB migration on deploy.

apps/server/src/database/repos/workspace/workspace.repo.ts

@@ -239,7 +239,7 @@ export class WorkspaceRepo {
     // is a real jsonb object, never a double-encoded string. The CASE self-heals
     // workspaces whose settings.ai.provider was previously corrupted into an
     // array/string.
-    const ALLOWED = ['driver', 'chatModel', 'embeddingModel', 'baseUrl', 'systemPrompt'];
+    const ALLOWED = ['driver', 'chatModel', 'embeddingModel', 'baseUrl', 'embeddingBaseUrl', 'systemPrompt'];
     const entries = Object.entries(provider).filter(
       ([k, v]) => v !== undefined && ALLOWED.includes(k),
     );