feat(web): add custom provider support for embedding & vision models, and fix memory_get Windows path bug!

1. Embedding model: support custom provider
   - Add "custom" entry to EMBEDDING_VENDORS with supports_dim_param=False
   - Parse custom:<id> credentials and model fallback in agent_initializer
   - Expand custom_providers as custom:<id> entries in Web UI dropdown

2. Vision model: support custom provider
   - Add custom:<id> routing in _route_by_provider_id
   - Add _build_custom_provider reading credentials from custom_providers
   - Expand custom_providers in Web UI dropdown, add validation in _set_vision

3. Fix memory_get Windows path validation bug!
   - str.startswith(path+'/') always False on Windows due to backslashes, So All Users can not use "memory_get" tool in Windows.
   - Use os.path.realpath + os.sep, consistent with MemoryService

4. Fix historical needsModel:false bug preventing embedding provider switch
   - Change embedding needsModel to true in console.js
   - Support custom:<id> resolution in cow_cli /memory status, also for adding custom provider support

Closes #2908, Closes #2880

agent/memory/embedding/provider.py

@@ -7,10 +7,14 @@ Supports multiple OpenAI-compatible embedding vendors:
   - dashscope  (Aliyun Tongyi text-embedding-v4)
   - doubao     (ByteDance Doubao Seed1.5 / large-text on Volcengine Ark)
   - zhipu      (ZhipuAI embedding-3)
+  - custom     (any OpenAI-compatible endpoint)
 
 Vendor keys here intentionally match the project's bot_type constants in
 common.const (OPENAI, LINKAI, QWEN_DASHSCOPE, DOUBAO, ZHIPU_AI).
 
+Custom providers (bot_type "custom" or "custom:<id>") reuse the same
+OpenAI-compatible REST client with user-supplied api_key / api_base.
+
 All providers share a single OpenAI-compatible REST client. Vendor-specific
 behaviors (truncation, query instruction prefix) are configured via metadata.
 """
@@ -138,6 +142,22 @@ EMBEDDING_VENDORS = {
         "query_instruction": "",
         "max_batch_size": 64,
     },
+    # Custom provider — any OpenAI-compatible /embeddings endpoint. The
+    # user must supply api_key + api_base + model via the web console
+    # (stored in custom_providers list or legacy custom_api_key / custom_api_base).
+    # Dimensions defaults to 1024 (most Chinese vendors) but can be
+    # overridden via config's embedding_dimensions. No dim-param support
+    # assumption — safest default for unknown endpoints.
+    "custom": {
+        "default_base_url": "",
+        "default_model": "",
+        "default_dimensions": 1024,
+        "supports_dim_param": False,
+        "needs_client_truncate": False,
+        "needs_client_normalize": True,
+        "query_instruction": "",
+        "max_batch_size": 64,
+    },
 }
 
 
@@ -472,10 +492,19 @@ def create_embedding_provider(
         )
 
     final_dim = dimensions if (dimensions and dimensions > 0) else meta["default_dimensions"]
+    resolved_model = model or meta["default_model"]
+    resolved_base = api_base or meta["default_base_url"]
+    # Custom providers require explicit api_base and model — they cannot
+    # fall back to OpenAI defaults like built-in vendors do.
+    if provider == "custom":
+        if not resolved_base:
+            raise ValueError("Custom embedding provider requires an api_base URL")
+        if not resolved_model:
+            raise ValueError("Custom embedding provider requires a model name")
     return OpenAIEmbeddingProvider(
-        model=model or meta["default_model"],
+        model=resolved_model,
         api_key=api_key,
-        api_base=api_base or meta["default_base_url"],
+        api_base=resolved_base,
         extra_headers=extra_headers,
         dimensions=final_dim,
         supports_dim_param=meta["supports_dim_param"],