/**
 * Perplexity LLM provider.
 *
 * Uses Perplexity's OpenAI-compatible API with real-time web search.
 * Reads config from PERPLEXITY_API_KEY, PERPLEXITY_MODEL.
 */

import type { ChatCompletionRequest, ChatCompletionResponse, LLMProvider } from '../types.js';

export interface PerplexityConfig {
  apiKey: string;
  model?: string;
}

export class PerplexityProvider implements LLMProvider {
  private config: PerplexityConfig;

  constructor(config?: Partial<PerplexityConfig>) {
    this.config = {
      apiKey: config?.apiKey || process.env.PERPLEXITY_API_KEY || '',
      model: config?.model || process.env.PERPLEXITY_MODEL || 'sonar',
    };
  }

  isConfigured(): boolean {
    return Boolean(this.config.apiKey);
  }

  async chatCompletion(req: ChatCompletionRequest): Promise<ChatCompletionResponse> {
    if (!this.isConfigured()) {
      throw new Error('Perplexity is not configured (missing PERPLEXITY_API_KEY)');
    }

    const body = {
      model: req.model || this.config.model,
      messages: req.messages,
      temperature: req.temperature,
      max_tokens: req.maxTokens,
      top_p: req.topP,
    };

    const response = await fetch('https://api.perplexity.ai/chat/completions', {
      method: 'POST',
      headers: {
        'Content-Type': 'application/json',
        Authorization: `Bearer ${this.config.apiKey}`,
      },
      body: JSON.stringify(body),
    });

    if (!response.ok) {
      const text = await response.text();
      throw new Error(`Perplexity error ${response.status}: ${text}`);
    }

    const data = (await response.json()) as {
      choices: Array<{ message: { content: string }; finish_reason: string }>;
      model: string;
      usage: { prompt_tokens: number; completion_tokens: number; total_tokens: number };
    };

    return {
      content: data.choices[0]?.message?.content ?? '',
      model: data.model,
      finishReason:
        (data.choices[0]?.finish_reason as ChatCompletionResponse['finishReason']) ?? null,
      usage: {
        promptTokens: data.usage?.prompt_tokens ?? 0,
        completionTokens: data.usage?.completion_tokens ?? 0,
        totalTokens: data.usage?.total_tokens ?? 0,
      },
    };
  }
}