perf: memo GridCard, fuse save fns, fix slash tab active color

memento-note/lib/ai/providers/custom-openai.ts

@@ -1,7 +1,7 @@
 import { createOpenAI } from '@ai-sdk/openai';
-import { generateObject, generateText as aiGenerateText, embed, stepCountIs } from 'ai';
-import { z } from 'zod';
+import { generateText as aiGenerateText, embed, stepCountIs } from 'ai';
 import { AIProvider, TagSuggestion, TitleSuggestion, ToolUseOptions, ToolCallResult } from '../types';
+import { cleanAIJsonResponse, cleanAITextResponse } from '../utils/clean-ai-response';
 
 export class CustomOpenAIProvider implements AIProvider {
   private model: any;
@@ -49,19 +49,20 @@ export class CustomOpenAIProvider implements AIProvider {
 
   async generateTags(content: string): Promise<TagSuggestion[]> {
     try {
-      const { object } = await generateObject({
+      const { text } = await aiGenerateText({
         model: this.model,
-        schema: z.object({
-          tags: z.array(z.object({
-            tag: z.string().describe('Short tag name in lowercase'),
-            confidence: z.number().min(0).max(1).describe('Confidence level between 0 and 1')
-          }))
-        }),
         prompt: `Analyze the following note and suggest 1 to 5 relevant tags.
-        Note content: "${content}"`,
+Note content: "${content.substring(0, 1500)}"
+Return ONLY a JSON array of tag objects, like: [{"tag":"example","confidence":0.9}]`,
       });
 
-      return object.tags;
+      const cleaned = cleanAIJsonResponse(text)
+      const parsed = JSON.parse(cleaned);
+      const arr = Array.isArray(parsed) ? parsed : (parsed.tags || parsed.suggestions || []);
+      return arr.map((t: any) => ({
+        tag: t.tag || t.label || t.name || '',
+        confidence: t.confidence || t.score || 0.7,
+      }));
     } catch (e) {
       console.error('Error generating tags (Custom OpenAI):', e);
       return [];
@@ -83,15 +84,15 @@ export class CustomOpenAIProvider implements AIProvider {
 
   async generateTitles(prompt: string): Promise<TitleSuggestion[]> {
     try {
-      // Use generateText instead of generateObject — DeepSeek doesn't support
+      // Use generateText instead of generateObject — DeepSeek/MiniMax don't support
       // response_format: json_schema via the OpenAI compat layer
       const { text } = await aiGenerateText({
         model: this.model,
         prompt: prompt,
       })
 
-      // Parse the JSON array from the text response — strip markdown code fences if present
-      const parsed = JSON.parse(text.replace(/^```json\n?/,'').replace(/\n?```$/,'').trim())
+      const cleaned = cleanAIJsonResponse(text)
+      const parsed = JSON.parse(cleaned)
       const titles = Array.isArray(parsed) ? parsed : (parsed.titles || parsed.suggestions || [])
       return titles.map((t: any) => ({
         title: typeof t === 'string' ? t : t.title || t.name || '',
@@ -103,6 +104,8 @@ export class CustomOpenAIProvider implements AIProvider {
     }
   }
 
+
+
   async generateText(prompt: string): Promise<string> {
     try {
       const { text } = await aiGenerateText({
@@ -110,7 +113,7 @@ export class CustomOpenAIProvider implements AIProvider {
         prompt: prompt,
       });
 
-      return text.trim();
+      return cleanAITextResponse(text).trim();
     } catch (e) {
       console.error('Error generating text (Custom OpenAI):', e);
       throw e;