feat: AI provider testing page + multi-provider support + UX design spec

- Add AI Provider Testing page (/admin/ai-test) with Tags and Embeddings tests
- Add new AI providers: CustomOpenAI, DeepSeek, OpenRouter
- Add API routes for AI config, models listing, and testing endpoints
- Add UX Design Specification document for Phase 1 MVP AI
- Add PRD Phase 1 MVP AI planning document
- Update admin settings and sidebar navigation
- Fix AI factory for multi-provider support

keep-notes/lib/ai/providers/custom-openai.ts

@@ -0,0 +1,59 @@
+import { createOpenAI } from '@ai-sdk/openai';
+import { generateObject, embed } from 'ai';
+import { z } from 'zod';
+import { AIProvider, TagSuggestion } from '../types';
+
+export class CustomOpenAIProvider implements AIProvider {
+  private model: any;
+  private embeddingModel: any;
+
+  constructor(
+    apiKey: string,
+    baseUrl: string,
+    modelName: string = 'gpt-4o-mini',
+    embeddingModelName: string = 'text-embedding-3-small'
+  ) {
+    // Create OpenAI-compatible client with custom base URL
+    const customClient = createOpenAI({
+      baseURL: baseUrl,
+      apiKey: apiKey,
+    });
+
+    this.model = customClient(modelName);
+    this.embeddingModel = customClient.embedding(embeddingModelName);
+  }
+
+  async generateTags(content: string): Promise<TagSuggestion[]> {
+    try {
+      const { object } = await generateObject({
+        model: this.model,
+        schema: z.object({
+          tags: z.array(z.object({
+            tag: z.string().describe('Le nom du tag, court et en minuscules'),
+            confidence: z.number().min(0).max(1).describe('Le niveau de confiance entre 0 et 1')
+          }))
+        }),
+        prompt: `Analyse la note suivante et suggère entre 1 et 5 tags pertinents.
+        Contenu de la note: "${content}"`,
+      });
+
+      return object.tags;
+    } catch (e) {
+      console.error('Erreur génération tags Custom OpenAI:', e);
+      return [];
+    }
+  }
+
+  async getEmbeddings(text: string): Promise<number[]> {
+    try {
+      const { embedding } = await embed({
+        model: this.embeddingModel,
+        value: text,
+      });
+      return embedding;
+    } catch (e) {
+      console.error('Erreur embeddings Custom OpenAI:', e);
+      return [];
+    }
+  }
+}