feat(agent): add Querit Contents tool (#18156)

### Summary

Add Querit Contents as a built-in page content tool for RAGFlow Agents
and Canvas workflows.

Querit Contents crawls one or more known URLs and returns their page
content and optional metadata. It complements the existing Querit Search
tool: Search discovers relevant pages, while Contents retrieves pages
already selected by an Agent or workflow.

This integration supports two usage modes:

- A standalone `QueritContents` node in Canvas workflows.
- An embedded content tool available to RAGFlow Agents.

internal/agent/component/tool_component_test.go

@@ -193,6 +193,13 @@ func TestToolBackedComponentRegisteredFactories(t *testing.T) {
 			outputKey: "success",
 			inputKey:  "to_email",
 		},
+		{
+			name:      "QueritContents",
+			toolName:  "QueritContents",
+			params:    map[string]any{"api_key": "stored-key", "format": "markdown", "crawl_timeout": float64(10), "extras_meta": true, "outputs": map[string]any{"json": map[string]any{}}},
+			outputKey: "json",
+			inputKey:  "urls",
+		},
 		{
 			name:      "QueritSearch",
 			toolName:  "QueritSearch",
@@ -283,7 +290,7 @@ func TestToolBackedComponentWenCaiInvoke(t *testing.T) {
 }
 
 func TestToolBackedComponentRegisteredBuildWorkflow(t *testing.T) {
-	for _, componentName := range []string{"ArXiv", "BGPT", "DuckDuckGo", "Email", "Google", "GoogleScholar", "KeenableSearch", "PubMed", "QueritSearch", "SearXNG", "WenCai", "TavilyExtract", "TavilySearch", "Wikipedia", "YahooFinance"} {
+	for _, componentName := range []string{"ArXiv", "BGPT", "DuckDuckGo", "Email", "Google", "GoogleScholar", "KeenableSearch", "PubMed", "QueritContents", "QueritSearch", "SearXNG", "WenCai", "TavilyExtract", "TavilySearch", "Wikipedia", "YahooFinance"} {
 		t.Run(componentName, func(t *testing.T) {
 			c := &canvas.Canvas{
 				Components: map[string]canvas.CanvasComponent{