import { z } from "zod";
import { openai, SCRIPT_MODEL } from "./openai";
import type { TokenUsage } from "./types";

const seasonSchema = z.object({
  title: z.string().min(1),
  description: z.string().min(1),
  episodes: z
    .array(z.object({ title: z.string().min(1), topic: z.string().min(1), summary: z.string().min(1) }))
    .min(1),
});

export type SeasonPlan = z.infer<typeof seasonSchema>;

export async function planSeason(input: {
  theme: string;
  count: number;
  tone: string;
  audience?: string;
  language: string;
}): Promise<{ plan: SeasonPlan; usage: TokenUsage }> {
  const res = await openai().chat.completions.create({
    model: SCRIPT_MODEL,
    messages: [
      {
        role: "system",
        content:
          "You are a podcast showrunner planning a cohesive season. Return STRICT JSON: { \"title\": string, \"description\": string, \"episodes\": [{ \"title\": string, \"topic\": string, \"summary\": string }] }.",
      },
      {
        role: "user",
        content: `Plan a ${input.count}-episode podcast season about: ${input.theme}.
Tone: ${input.tone}. ${input.audience ? `Audience: ${input.audience}.` : ""} Language: ${input.language}.
Give the season a title and short description, then ${input.count} episodes, each with a catchy title, a specific topic to cover, and a one-sentence summary.`,
      },
    ],
    response_format: { type: "json_object" },
    temperature: 0.85,
  });
  const plan = seasonSchema.parse(JSON.parse(res.choices[0]?.message?.content ?? "{}"));
  return {
    plan,
    usage: {
      inputTokens: res.usage?.prompt_tokens ?? 0,
      outputTokens: res.usage?.completion_tokens ?? 0,
    },
  };
}