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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>
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Till-JS
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155 changed files with 22622 additions and 348 deletions
148
chat/apps/mobile/app/api/models+api.ts
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148
chat/apps/mobile/app/api/models+api.ts
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@ -0,0 +1,148 @@
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import { supabase } from '../../utils/supabase';
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// Definiere den Typ für ein Modell
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export type Model = {
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id: string;
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name: string;
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description: string;
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parameters?: Record<string, any>;
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created_at?: string;
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updated_at?: string;
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};
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// Fallback-Modelle, falls keine aus der Datenbank geladen werden können
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const FALLBACK_MODELS: Model[] = [
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{
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id: '550e8400-e29b-41d4-a716-446655440000',
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name: 'GPT-O3-Mini',
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description: 'Azure OpenAI O3-Mini: Effizientes Modell für schnelle Antworten.',
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parameters: {
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temperature: 0.7,
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max_tokens: 800,
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provider: 'azure',
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deployment: 'gpt-o3-mini-se',
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endpoint: 'https://memoroseopenai.openai.azure.com',
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api_version: '2024-12-01-preview'
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}
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},
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{
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id: '550e8400-e29b-41d4-a716-446655440004',
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name: 'GPT-4o-Mini',
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description: 'Azure OpenAI GPT-4o-Mini: Kompaktes, leistungsstarkes KI-Modell.',
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parameters: {
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temperature: 0.7,
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max_tokens: 1000,
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provider: 'azure',
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deployment: 'gpt-4o-mini-se',
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endpoint: 'https://memoroseopenai.openai.azure.com',
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api_version: '2024-12-01-preview'
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}
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},
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{
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id: '550e8400-e29b-41d4-a716-446655440005',
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name: 'GPT-4o',
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description: 'Azure OpenAI GPT-4o: Das fortschrittlichste multimodale KI-Modell.',
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parameters: {
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temperature: 0.7,
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max_tokens: 1200,
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provider: 'azure',
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deployment: 'gpt-4o-se',
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endpoint: 'https://memoroseopenai.openai.azure.com',
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api_version: '2024-12-01-preview'
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}
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}
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];
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// GET-Handler für Modelle
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export async function GET(request: Request) {
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try {
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// Versuche, Modelle aus der Supabase-Datenbank zu laden
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let models: Model[] = FALLBACK_MODELS;
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// Wenn Supabase konfiguriert ist, versuche die Modelle von dort zu laden
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try {
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if (supabase) {
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const { data, error } = await supabase
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.from('models')
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.select('*');
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// Entfernt: .order('created_at', { ascending: false })
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if (error) {
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console.error('Fehler beim Laden der Modelle aus Supabase:', error);
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} else if (data && data.length > 0) {
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models = data as Model[];
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}
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}
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} catch (e) {
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console.error('Fehler bei der Supabase-Verbindung:', e);
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// Fallback zu den vordefinierten Modellen
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}
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return Response.json(models);
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} catch (error) {
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console.error('Fehler beim Verarbeiten der Anfrage:', error);
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return new Response(JSON.stringify({ error: 'Interner Serverfehler' }), {
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status: 500,
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headers: {
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'Content-Type': 'application/json',
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},
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});
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}
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}
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// POST-Handler zum Erstellen eines neuen Modells
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export async function POST(request: Request) {
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try {
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const body = await request.json();
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// Validiere die Eingabedaten
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if (!body.name || !body.description) {
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return new Response(JSON.stringify({ error: 'Name und Beschreibung sind erforderlich' }), {
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status: 400,
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headers: {
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'Content-Type': 'application/json',
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},
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});
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}
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// Erstelle ein neues Modell in der Datenbank
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if (supabase) {
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const { data, error } = await supabase
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.from('models')
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.insert([{
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name: body.name,
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description: body.description,
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parameters: body.parameters || {},
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}])
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.select();
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if (error) {
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console.error('Fehler beim Erstellen des Modells:', error);
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return new Response(JSON.stringify({ error: 'Fehler beim Erstellen des Modells' }), {
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status: 500,
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headers: {
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'Content-Type': 'application/json',
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},
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});
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}
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return Response.json(data[0]);
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} else {
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// Wenn Supabase nicht verfügbar ist, gib einen Fehler zurück
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return new Response(JSON.stringify({ error: 'Datenbank nicht verfügbar' }), {
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status: 503,
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headers: {
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'Content-Type': 'application/json',
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},
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});
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}
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} catch (error) {
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console.error('Fehler beim Verarbeiten der Anfrage:', error);
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return new Response(JSON.stringify({ error: 'Interner Serverfehler' }), {
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status: 500,
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headers: {
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'Content-Type': 'application/json',
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},
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});
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}
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}
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137
chat/apps/mobile/app/api/usage+api.ts
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137
chat/apps/mobile/app/api/usage+api.ts
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import { supabase } from '../../utils/supabase';
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// Typ für die Token-Nutzung pro Modell
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export type ModelUsage = {
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model_id: string;
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model_name: string;
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total_prompt_tokens: number;
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total_completion_tokens: number;
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total_tokens: number;
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total_cost: number;
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};
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// Typ für die Token-Nutzung nach Zeitraum
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export type UsageByPeriod = {
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time_period: string;
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total_tokens: number;
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total_cost: number;
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};
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// Typ für die Token-Nutzung einer Konversation
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export type ConversationUsage = {
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message_id: string;
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created_at: string;
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prompt_tokens: number;
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completion_tokens: number;
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total_tokens: number;
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estimated_cost: number;
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};
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// Handler für GET /api/usage
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export async function GET(request: Request) {
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try {
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const url = new URL(request.url);
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const userId = url.searchParams.get('userId');
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const period = url.searchParams.get('period') || 'month';
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if (!userId) {
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return new Response(JSON.stringify({ error: 'User ID ist erforderlich' }), {
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status: 400,
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headers: { 'Content-Type': 'application/json' }
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});
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}
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// Lade die Tokennutzung nach Modell
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const { data: modelUsage, error: modelError } = await supabase
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.rpc('get_user_model_usage', { user_id: userId });
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if (modelError) {
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console.error('Fehler beim Laden der Modellnutzung:', modelError);
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return new Response(JSON.stringify({ error: 'Fehler beim Laden der Modellnutzung' }), {
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status: 500,
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headers: { 'Content-Type': 'application/json' }
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});
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}
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// Lade die Tokennutzung nach Zeitraum
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const { data: periodUsage, error: periodError } = await supabase
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.rpc('get_user_usage_by_period', {
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user_id: userId,
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period: period
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});
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if (periodError) {
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console.error('Fehler beim Laden der Zeitraumnutzung:', periodError);
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return new Response(JSON.stringify({ error: 'Fehler beim Laden der Zeitraumnutzung' }), {
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status: 500,
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headers: { 'Content-Type': 'application/json' }
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});
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}
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// Berechne Gesamtkosten und Token
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const totalCost = (modelUsage as ModelUsage[]).reduce((sum, model) => sum + model.total_cost, 0);
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const totalTokens = (modelUsage as ModelUsage[]).reduce((sum, model) => sum + model.total_tokens, 0);
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return Response.json({
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modelUsage,
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periodUsage,
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summary: {
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totalCost,
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totalTokens
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}
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});
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} catch (error) {
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console.error('Fehler beim Verarbeiten der Anfrage:', error);
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return new Response(JSON.stringify({ error: 'Interner Serverfehler' }), {
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status: 500,
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headers: { 'Content-Type': 'application/json' }
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});
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}
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}
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// Handler für GET /api/usage/conversation
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export async function GET_conversation(request: Request) {
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try {
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const url = new URL(request.url);
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const conversationId = url.searchParams.get('conversationId');
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if (!conversationId) {
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return new Response(JSON.stringify({ error: 'Conversation ID ist erforderlich' }), {
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status: 400,
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headers: { 'Content-Type': 'application/json' }
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});
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}
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// Lade die Tokennutzung für die Konversation
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const { data: conversationUsage, error } = await supabase
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.rpc('get_conversation_usage', { conversation_id: conversationId });
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if (error) {
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console.error('Fehler beim Laden der Konversationsnutzung:', error);
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return new Response(JSON.stringify({ error: 'Fehler beim Laden der Konversationsnutzung' }), {
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status: 500,
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headers: { 'Content-Type': 'application/json' }
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});
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}
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// Berechne Gesamtkosten und Token für diese Konversation
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const usage = conversationUsage as ConversationUsage[];
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const totalCost = usage.reduce((sum, item) => sum + item.estimated_cost, 0);
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const totalTokens = usage.reduce((sum, item) => sum + item.total_tokens, 0);
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return Response.json({
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conversationUsage,
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summary: {
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totalCost,
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totalTokens,
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messageCount: usage.length
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}
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});
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} catch (error) {
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console.error('Fehler beim Verarbeiten der Anfrage:', error);
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return new Response(JSON.stringify({ error: 'Interner Serverfehler' }), {
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status: 500,
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headers: { 'Content-Type': 'application/json' }
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});
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}
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}
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