refactor(ux): consolidate BMAD skills, update design system, and clean up Prisma generated client

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

@@ -1,11 +1,13 @@
 import { createOpenAI } from '@ai-sdk/openai';
-import { generateObject, generateText, embed } from 'ai';
+import { generateObject, generateText as aiGenerateText, embed, stepCountIs } from 'ai';
 import { z } from 'zod';
-import { AIProvider, TagSuggestion, TitleSuggestion } from '../types';
+import { AIProvider, TagSuggestion, TitleSuggestion, ToolUseOptions, ToolCallResult } from '../types';
 
 export class CustomOpenAIProvider implements AIProvider {
   private model: any;
   private embeddingModel: any;
+  private apiKey: string;
+  private baseUrl: string;
 
   constructor(
     apiKey: string,
@@ -13,13 +15,22 @@ export class CustomOpenAIProvider implements AIProvider {
     modelName: string = 'gpt-4o-mini',
     embeddingModelName: string = 'text-embedding-3-small'
   ) {
+    this.apiKey = apiKey;
+    this.baseUrl = baseUrl.endsWith('/') ? baseUrl.slice(0, -1) : baseUrl;
     // Create OpenAI-compatible client with custom base URL
+    // Use .chat() to force /chat/completions endpoint (avoids Responses API)
     const customClient = createOpenAI({
       baseURL: baseUrl,
       apiKey: apiKey,
+      fetch: async (url, options) => {
+        const headers = new Headers(options?.headers);
+        headers.set('HTTP-Referer', 'https://localhost:3000');
+        headers.set('X-Title', 'Memento AI');
+        return fetch(url, { ...options, headers });
+      }
     });
 
-    this.model = customClient(modelName);
+    this.model = customClient.chat(modelName);
     this.embeddingModel = customClient.embedding(embeddingModelName);
   }
 
@@ -79,7 +90,7 @@ export class CustomOpenAIProvider implements AIProvider {
 
   async generateText(prompt: string): Promise<string> {
     try {
-      const { text } = await generateText({
+      const { text } = await aiGenerateText({
         model: this.model,
         prompt: prompt,
       });
@@ -90,4 +101,47 @@ export class CustomOpenAIProvider implements AIProvider {
       throw e;
     }
   }
+
+  async chat(messages: any[], systemPrompt?: string): Promise<any> {
+    try {
+      const { text } = await aiGenerateText({
+        model: this.model,
+        system: systemPrompt,
+        messages: messages,
+      });
+
+      return { text: text.trim() };
+    } catch (e) {
+      console.error('Erreur chat Custom OpenAI:', e);
+      throw e;
+    }
+  }
+
+  async generateWithTools(options: ToolUseOptions): Promise<ToolCallResult> {
+    const { tools, maxSteps = 10, systemPrompt, messages, prompt } = options
+    const opts: Record<string, any> = {
+      model: this.model,
+      tools,
+      stopWhen: stepCountIs(maxSteps),
+    }
+    if (systemPrompt) opts.system = systemPrompt
+    if (messages) opts.messages = messages
+    else if (prompt) opts.prompt = prompt
+
+    const result = await aiGenerateText(opts as any)
+    return {
+      toolCalls: result.toolCalls?.map((tc: any) => ({ toolName: tc.toolName, input: tc.input })) || [],
+      toolResults: result.toolResults?.map((tr: any) => ({ toolName: tr.toolName, input: tr.input, output: tr.output })) || [],
+      text: result.text,
+      steps: result.steps?.map((step: any) => ({
+        text: step.text,
+        toolCalls: step.toolCalls?.map((tc: any) => ({ toolName: tc.toolName, input: tc.input })) || [],
+        toolResults: step.toolResults?.map((tr: any) => ({ toolName: tr.toolName, input: tr.input, output: tr.output })) || []
+      })) || []
+    }
+  }
+
+  getModel() {
+    return this.model;
+  }
 }