import OpenAI from "openai";
import type {
  ComparisonRequest,
  ComparisonResult,
  DimensionResult,
  ItemResearch,
} from "../types";

let _client: OpenAI | null = null;

function getClient(): OpenAI {
  if (!_client) {
    _client = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
  }
  return _client;
}

const SYSTEM_PROMPT = `You are an expert research analyst. Your job is to compare items across multiple dimensions and produce structured, insightful comparison data.

When given a list of items to compare:
1. Identify 5-8 relevant comparison dimensions (e.g., price, performance, ease of use, ecosystem, community support, scalability, documentation, etc.)
2. Research each item across each dimension
3. Score each item 1-10 per dimension (10 = best)
4. Generate pros and cons lists for each item
5. Write a concise summary comparison
6. Provide a clear recommendation

You MUST respond with valid JSON matching this exact structure:
{
  "items": [
    {
      "name": "item name",
      "description": "brief overview of this item in context of the comparison",
      "overallScore": 7.5,
      "dimensions": {
        "Dimension Name": {
          "score": 8,
          "summary": "brief assessment",
          "details": "detailed analysis with specific data points",
          "pros": ["pro 1", "pro 2"],
          "cons": ["con 1", "con 2"]
        }
      },
      "pros": ["overall pro 1", "overall pro 2"],
      "cons": ["overall con 1", "overall con 2"],
      "sources": [
        { "title": "source title", "url": "https://...", "snippet": "relevant excerpt" }
      ]
    }
  ],
  "dimensions": ["Dimension 1", "Dimension 2", ...],
  "summary": "overall comparison summary highlighting key differences and trade-offs",
  "recommendation": "clear recommendation with reasoning"
}

Important:
- Be factual and specific. Include real data where possible.
- Scores should be on a 1-10 scale where 10 is best.
- Provide at least 2-3 pros and cons per item.
- The top-level pros/cons for each item should be the most significant overall points.
- Dimension-level pros/cons should be specific to that dimension.
- Sources should be realistic URLs to relevant documentation or resources.
- The recommendation should consider different use cases when appropriate.`;

const MAX_RETRIES = 3;
const RETRY_DELAY_MS = 1000;

function sleep(ms: number) {
  return new Promise((resolve) => setTimeout(resolve, ms));
}

function validateComparisonResult(data: unknown): data is ComparisonResult {
  if (!data || typeof data !== "object") return false;
  const result = data as Record<string, unknown>;
  if (!Array.isArray(result.items)) return false;
  if (!Array.isArray(result.dimensions)) return false;
  if (typeof result.summary !== "string") return false;
  if (typeof result.recommendation !== "string") return false;

  for (const item of result.items as ItemResearch[]) {
    if (typeof item.name !== "string") return false;
    if (typeof item.description !== "string") return false;
    if (typeof item.overallScore !== "number") return false;
    if (!Array.isArray(item.pros)) return false;
    if (!Array.isArray(item.cons)) return false;
    if (typeof item.dimensions !== "object") return false;

    for (const dim of Object.values(item.dimensions) as DimensionResult[]) {
      if (typeof dim.score !== "number") return false;
      if (typeof dim.summary !== "string") return false;
      if (typeof dim.details !== "string") return false;
      if (!Array.isArray(dim.pros)) return false;
      if (!Array.isArray(dim.cons)) return false;
    }
  }

  return true;
}

export async function generateComparison(
  request: ComparisonRequest
): Promise<ComparisonResult> {
  const userPrompt = `Compare the following items: ${request.items.join(", ")}
${request.query ? `Focus: ${request.query}` : ""}
${request.dimensions?.length ? `Specific dimensions to include: ${request.dimensions.join(", ")}` : ""}

Provide a comprehensive comparison with scores, pros/cons, and a recommendation.`;

  let lastError: Error | null = null;

  for (let attempt = 1; attempt <= MAX_RETRIES; attempt++) {
    try {
      const response = await getClient().chat.completions.create({
        model: "gpt-4o-mini",
        messages: [
          { role: "system", content: SYSTEM_PROMPT },
          { role: "user", content: userPrompt },
        ],
        response_format: { type: "json_object" },
        temperature: 0.3,
      });

      const content = response.choices[0]?.message?.content;
      if (!content) {
        throw new Error("Empty response from OpenAI");
      }

      const parsed: unknown = JSON.parse(content);

      if (!validateComparisonResult(parsed)) {
        throw new Error("Invalid comparison result structure from OpenAI");
      }

      return parsed;
    } catch (error) {
      lastError = error instanceof Error ? error : new Error(String(error));

      if (attempt < MAX_RETRIES) {
        await sleep(RETRY_DELAY_MS * attempt);
      }
    }
  }

  throw new Error(
    `Failed to generate comparison after ${MAX_RETRIES} attempts: ${lastError?.message}`
  );
}