feat: Unified Embedding Pool with auto-discovery

Architecture refactoring for multi-provider rotation:

Backend:
- Add EmbeddingPoolConfig type with autoDiscover support
- Implement discoverProvidersForModel() for auto-aggregation
- Add GET/PUT /api/litellm-api/embedding-pool endpoints
- Add GET /api/litellm-api/embedding-pool/discover/:model preview
- Convert ccw-litellm status check to async with 5-min cache
- Maintain backward compatibility with legacy rotation config

Frontend:
- Add "Embedding Pool" tab in API Settings
- Auto-discover providers when target model selected
- Show provider/key count with include/exclude controls
- Increase sidebar width (280px → 320px)
- Add sync result feedback on save

Other:
- Remove worker count limits (was max=32)
- Add i18n translations (EN/CN)
- Update .gitignore for .mcp.json

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

codex-lens/src/codexlens/cli/commands.py

@@ -103,12 +103,12 @@ def init(
         "-l",
         help="Limit indexing to specific languages (repeat or comma-separated).",
     ),
-    workers: Optional[int] = typer.Option(None, "--workers", "-w", min=1, max=32, help="Parallel worker processes (default: auto-detect based on CPU count, max 32)."),
+    workers: Optional[int] = typer.Option(None, "--workers", "-w", min=1, help="Parallel worker processes (default: auto-detect based on CPU count)."),
     force: bool = typer.Option(False, "--force", "-f", help="Force full reindex (skip incremental mode)."),
     no_embeddings: bool = typer.Option(False, "--no-embeddings", help="Skip automatic embedding generation (if semantic deps installed)."),
     embedding_backend: str = typer.Option("fastembed", "--embedding-backend", help="Embedding backend: fastembed (local) or litellm (remote API)."),
     embedding_model: str = typer.Option("code", "--embedding-model", help="Embedding model: profile name for fastembed (fast/code/multilingual/balanced) or model name for litellm (e.g. text-embedding-3-small)."),
-    max_workers: int = typer.Option(1, "--max-workers", min=1, max=32, help="Max concurrent API calls for embedding generation. Recommended: 4-8 for litellm backend."),
+    max_workers: int = typer.Option(1, "--max-workers", min=1, help="Max concurrent API calls for embedding generation. Recommended: 4-8 for litellm backend."),
     json_mode: bool = typer.Option(False, "--json", help="Output JSON response."),
     verbose: bool = typer.Option(False, "--verbose", "-v", help="Enable debug logging."),
 ) -> None:
@@ -478,6 +478,7 @@ def search(
                     "path": r.path,
                     "score": r.score,
                     "excerpt": r.excerpt,
+                    "content": r.content,  # Full function/class body
                     "source": getattr(r, "search_source", None),
                     "symbol": getattr(r, "symbol", None),
                 }
@@ -1852,7 +1853,6 @@ def embeddings_generate(
         "--max-workers",
         "-w",
         min=1,
-        max=32,
         help="Max concurrent API calls. Recommended: 4-8 for litellm backend. Default: 1 (sequential).",
     ),
     json_mode: bool = typer.Option(False, "--json", help="Output JSON response."),

codex-lens/src/codexlens/cli/embedding_manager.py

@@ -331,7 +331,7 @@ def generate_embeddings(
     if max_workers is None:
         if embedding_backend == "litellm":
             if endpoint_count > 1:
-                max_workers = min(endpoint_count * 2, 32)  # Cap at 32 workers
+                max_workers = endpoint_count * 2  # No cap, scale with endpoints
             else:
                 max_workers = 4
         else:
@@ -806,7 +806,7 @@ def generate_embeddings_recursive(
     if max_workers is None:
         if embedding_backend == "litellm":
             if endpoint_count > 1:
-                max_workers = min(endpoint_count * 2, 32)
+                max_workers = endpoint_count * 2  # No cap, scale with endpoints
             else:
                 max_workers = 4
         else: