feat(chat): integrate chat project into monorepo with full app structure

- Restructure chat as apps/mobile, apps/web, apps/landing, backend
- Add NestJS backend for secure Azure OpenAI API calls
- Remove exposed API key from mobile app (security fix)
- Add shared chat-types package
- Create SvelteKit web app scaffold
- Create Astro landing page scaffold
- Update pnpm workspace configuration
- Add project-level CLAUDE.md documentation

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

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

chat/apps/mobile/utils/api.ts

@@ -0,0 +1,87 @@
+/**
+ * API-Hilfsmodul für Chat-Anfragen
+ * Verwendet das Backend für sichere AI API Aufrufe
+ */
+import { ChatMessage } from '../services/openai';
+import { sendChatCompletion, ChatCompletionResponse, TokenUsage } from './backendApi';
+
+// Re-export types for backward compatibility
+export type { TokenUsage };
+
+// Rückgabetyp für die Chat-Anfrage
+export type ChatRequestResult = {
+  content: string;
+  usage: TokenUsage;
+};
+
+/**
+ * Sendet eine Chat-Anfrage über das Backend
+ * @param messages Array von Nachrichten
+ * @param temperature Kreativität (0.0 - 1.0)
+ * @param maxTokens Maximale Token in der Antwort
+ * @param config Model-Konfiguration (für modelId Extraktion)
+ * @returns Die Antwort des Modells als Text mit Tokennutzung
+ */
+export async function sendChatRequest(
+  messages: ChatMessage[],
+  temperature: number = 0.7,
+  maxTokens: number = 800,
+  config: {
+    endpoint?: string;
+    apiKey?: string;
+    deployment: string;
+    apiVersion?: string;
+  }
+): Promise<string | ChatRequestResult> {
+  console.log('sendChatRequest via Backend:', {
+    messagesCount: messages.length,
+    deployment: config.deployment,
+    temperature,
+    maxTokens,
+  });
+
+  try {
+    // Map deployment name to model ID
+    const modelId = getModelIdFromDeployment(config.deployment);
+
+    // Send request through backend
+    const result = await sendChatCompletion(
+      messages,
+      modelId,
+      temperature,
+      maxTokens
+    );
+
+    return {
+      content: result.content,
+      usage: result.usage,
+    };
+  } catch (error) {
+    console.error('Fehler beim Backend API-Aufruf:', error);
+
+    // Return user-friendly error message
+    const errorMessage = error instanceof Error ? error.message : 'Unbekannter Fehler';
+    return `Es konnte keine Antwort generiert werden. Bitte stelle sicher, dass das Backend läuft. Fehler: ${errorMessage}`;
+  }
+}
+
+/**
+ * Maps deployment names to model IDs
+ * This ensures backward compatibility with existing code
+ */
+function getModelIdFromDeployment(deployment: string): string {
+  const deploymentToModelId: Record<string, string> = {
+    'gpt-o3-mini-se': '550e8400-e29b-41d4-a716-446655440000',
+    'gpt-4o-mini-se': '550e8400-e29b-41d4-a716-446655440004',
+    'gpt-4o-se': '550e8400-e29b-41d4-a716-446655440005',
+  };
+
+  const modelId = deploymentToModelId[deployment];
+
+  if (!modelId) {
+    console.warn(`Unknown deployment: ${deployment}, using default model`);
+    return '550e8400-e29b-41d4-a716-446655440000'; // Default to GPT-O3-Mini
+  }
+
+  return modelId;
+}