Initial commit: deardiary project setup

backend/src/services/ai/lmstudio.ts

@@ -0,0 +1,52 @@
+import type { AIProvider, AIProviderConfig } from './provider';
+
+export class LMStudioProvider implements AIProvider {
+  provider = 'lmstudio' as const;
+  private baseUrl: string;
+  private model: string;
+
+  constructor(config: AIProviderConfig) {
+    this.baseUrl = config.baseUrl || 'http://localhost:1234/v1';
+    this.model = config.model || 'local-model';
+  }
+
+  async generate(prompt: string, systemPrompt?: string): Promise<string> {
+    const messages: Array<{ role: string; content: string }> = [];
+    
+    if (systemPrompt) {
+      messages.push({ role: 'system', content: systemPrompt });
+    }
+    
+    messages.push({ role: 'user', content: prompt });
+
+    const response = await fetch(`${this.baseUrl}/chat/completions`, {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        model: this.model,
+        messages,
+        temperature: 0.7,
+        max_tokens: 2000,
+      }),
+    });
+
+    if (!response.ok) {
+      const error = await response.text();
+      throw new Error(`LM Studio API error: ${response.status} ${error}`);
+    }
+
+    const data = await response.json() as { choices: Array<{ message: { content: string } }> };
+    return data.choices[0]?.message?.content || '';
+  }
+
+  async validate(): Promise<boolean> {
+    try {
+      const response = await fetch(`${this.baseUrl}/models`);
+      return response.ok;
+    } catch {
+      return false;
+    }
+  }
+}