feat: update origin 20.2.0

Update origin submodule and English source files for version 20.2.0

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

Author: lacolaco

adev-ja/src/app/sub-navigation-data.en.ts

@@ -685,6 +685,11 @@ const DOCS_SUB_NAVIGATION_DATA: NavigationItem[] = [
         path: 'ai/develop-with-ai',
         contentPath: 'ai/develop-with-ai',
       },
+      {
+        label: 'Design Patterns',
+        path: 'ai/design-patterns',
+        contentPath: 'ai/design-patterns',
+      },
       {
         label: 'Angular CLI MCP Server setup',
         path: 'ai/mcp',

adev-ja/src/content/ai/mcp-server-setup.en.md

@@ -136,4 +136,4 @@ The Angular CLI MCP server provides several tools to assist you in your developm
 
 ## Feedback and New Ideas
 
-The Angular team welcomes your feedback on the existing MCP capabilities and any ideas you have for new tools or features. Please share your thoughts by opening an issue on the [angular/angular GitHub repository](https://github.com/angular/angular/issues).
+The Angular team welcomes your feedback on the existing MCP capabilities and any ideas you have for new tools or features. Please share your thoughts by opening an issue on the [angular/angular GitHub repository](https://github.com/angular/angular/issues).

adev-ja/src/content/ai/overview.en.md

@@ -60,60 +60,6 @@ The [Gemini API](https://ai.google.dev/gemini-api/docs) provides access to state
 
 * [AI Chatbot app template](https://github.com/FirebaseExtended/firebase-framework-tools/tree/main/starters/angular/ai-chatbot) - This template starts with a chatbot user interface that communicates with the Gemini API via HTTP. 
 
-## AI patterns in action: Streaming chat responses
-Having text appear as the response is received from the model is a common UI pattern for web apps using AI. You can achieve this asynchronous task with Angular's `resource` API. The `stream` property of `resource` accepts an asynchronous function you can use to apply updates to a signal value over time. The signal being updated represents the data being streamed.
-
-```ts
-characters = resource({
-    stream: async () => {
-      const data = signal<{ value: string } | { error: unknown }>({
-        value: "",
-      });
-
-      fetch(this.url).then(async (response) => {
-        if (!response.body) return;
-        
-        for await (const chunk of response.body) {
-          const chunkText = this.decoder.decode(chunk);
-          data.update((prev) => {
-            if ("value" in prev) {
-              return { value: `${prev.value} ${chunkText}` };
-            } else {
-              return { error: chunkText };
-            }
-          });
-        }
-      });
-
-      return data;
-    },
-  });
-
-```
-
-The `characters` member is updated asynchronously and can be displayed in the template.
-
-```html
-<p>{{ characters.value() }}</p>
-```
-
-On the server side, in `server.ts` for example, the defined endpoint sends the data to be streamed to the client. The following code uses the Gemini API but this technique is applicable to other tools and frameworks that support streaming responses from LLMs:
-
-```ts
- app.get("/api/stream-response", async (req, res) => {
-   ai.models.generateContentStream({
-     model: "gemini-2.0-flash",
-     contents: "Explain how AI works",
-   }).then(async (response) => {
-     for await (const chunk of response) {
-       res.write(chunk.text);
-     }
-   });
- });
-
-```
-This example connects to the Gemini API but other APIs that support streaming responses can be used here as well. [You can find the complete example on the Angular Github](https://github.com/angular/examples/tree/main/streaming-example).
-
 ## Best Practices
 ### Connecting to model providers and keeping your API Credentials Secure
 When connecting to model providers, it is important to keep your API secrets safe. *Never put your API key in a file that ships to the client, such as `environments.ts`*.