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;
    }
  }
}