import { openai, defaultModel, serviceOptions, supportsWebSearch, parseWithRetry } from '../agent.js';
import type { InterpreterOutput, RankingOutput, CuratorOutput, MediaType } from '../types/agents.js';
import { z } from 'zod';
import { zodTextFormat } from 'openai/helpers/zod';

const CuratorSchema = z.object({
  series: z.array(z.object({
    title: z.string(),
    explanation: z.string(),
    category: z.enum(["Full Match", "Definitely Like", "Might Like", "Questionable", "Will Not Like"]),
    genre: z.string(),
    pros: z.array(z.string()).max(3),
    cons: z.array(z.string()).max(3)
  }))
});

const CHUNK_SIZE = 20;

export async function runCurator(
  ranking: RankingOutput,
  interpreter: InterpreterOutput,
  mediaType: MediaType = 'tv_show',
  useWebSearch = false,
): Promise<CuratorOutput[]> {
  const mediaLabel = mediaType === 'movie' ? 'movie' : 'TV show';

  const allSeries = [
    ...(ranking.full_match ?? []).map((t) => ({ title: t, category: 'Full Match' as const })),
    ...ranking.definitely_like.map((t) => ({ title: t, category: 'Definitely Like' as const })),
    ...ranking.might_like.map((t) => ({ title: t, category: 'Might Like' as const })),
    ...ranking.questionable.map((t) => ({ title: t, category: 'Questionable' as const })),
    ...ranking.will_not_like.map((t) => ({ title: t, category: 'Will Not Like' as const })),
  ];

  if (allSeries.length === 0) return [];

  const canSearch = useWebSearch && supportsWebSearch;
  const preferenceSummary = `User preferences summary:
Liked: ${interpreter.liked.join(', ') || '(none)'}
Themes: ${interpreter.themes.join(', ') || '(none)'}
Tone: ${interpreter.tone.join(', ') || '(none)'}
Character preferences: ${interpreter.character_preferences.join(', ') || '(none)'}
Avoid: ${interpreter.avoid.join(', ') || '(none)'}
Requirements: ${interpreter.requirements.join(', ') || '(none)'}`;

  const instructions = `You are a ${mediaLabel} recommendation curator. For each ${mediaLabel}, write a concise explanation and surface the most useful details for the user.${useWebSearch ? '\n\nUse web search to verify details and enrich explanations with accurate information.' : ''}

Rules:
- Preserve the exact title and category as given
- explanation: 1-2 sentences explaining why it was assigned to its category, referencing specific user preferences
- genre: 1-3 words capturing the most prominent genre of the title (e.g. "Crime Drama", "Sci-Fi Thriller", "Romantic Comedy")
- pros: up to 3 short bullet points about what this title does well relative to the user's taste
- cons: up to 3 short bullet points about what the user might not like based on their preferences
- Be honest — explain why "Questionable" or "Will Not Like" ${mediaLabel}s got that rating`;

  const chunks: typeof allSeries[] = [];
  for (let i = 0; i < allSeries.length; i += CHUNK_SIZE) {
    chunks.push(allSeries.slice(i, i + CHUNK_SIZE));
  }

  const results: CuratorOutput[] = [];
  for (const chunk of chunks) {
    const showList = chunk.map((s) => `- "${s.title}" (${s.category})`).join('\n');
    const response = await parseWithRetry(() => openai.responses.parse({
      model: defaultModel,
      temperature: 0.5,
      ...serviceOptions,
      ...(canSearch ? { tools: [{ type: 'web_search' as const }] } : {}),
      text: { format: zodTextFormat(CuratorSchema, "series") },
      instructions,
      input: `${preferenceSummary}

${mediaLabel}s to describe:
${showList}`,
    }));
    results.push(...(response.output_parsed?.series ?? []));
  }

  return results;
}