Leon Serfaty
49 lines
1.6 KiB
TypeScript
49 lines
1.6 KiB
TypeScript
import { z } from "zod";
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import { openai, SCRIPT_MODEL } from "./openai";
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import type { TokenUsage } from "./types";
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const seasonSchema = z.object({
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title: z.string().min(1),
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description: z.string().min(1),
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episodes: z
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.array(z.object({ title: z.string().min(1), topic: z.string().min(1), summary: z.string().min(1) }))
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.min(1),
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});
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export type SeasonPlan = z.infer<typeof seasonSchema>;
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export async function planSeason(input: {
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theme: string;
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count: number;
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tone: string;
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audience?: string;
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language: string;
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}): Promise<{ plan: SeasonPlan; usage: TokenUsage }> {
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const res = await openai().chat.completions.create({
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model: SCRIPT_MODEL,
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messages: [
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{
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role: "system",
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content:
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"You are a podcast showrunner planning a cohesive season. Return STRICT JSON: { \"title\": string, \"description\": string, \"episodes\": [{ \"title\": string, \"topic\": string, \"summary\": string }] }.",
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},
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{
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role: "user",
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content: `Plan a ${input.count}-episode podcast season about: ${input.theme}.
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Tone: ${input.tone}. ${input.audience ? `Audience: ${input.audience}.` : ""} Language: ${input.language}.
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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.`,
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},
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],
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response_format: { type: "json_object" },
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temperature: 0.85,
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});
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const plan = seasonSchema.parse(JSON.parse(res.choices[0]?.message?.content ?? "{}"));
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return {
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plan,
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usage: {
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inputTokens: res.usage?.prompt_tokens ?? 0,
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outputTokens: res.usage?.completion_tokens ?? 0,
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},
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};
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}
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