import { dirtyLLMJsonParser } from "@/lib/dirtyLLMJsonParser" import { dirtyCaptionCleaner } from "@/lib/dirtyCaptionCleaner" import { predict } from "./predict" import { Preset } from "../engine/presets" import { LLMResponse } from "@/types" import { cleanJson } from "@/lib/cleanJson" import { createZephyrPrompt } from "@/lib/createZephyrPrompt" export const getStory = async ({ preset, prompt = "", nbTotalPanels = 4, }: { preset: Preset; prompt: string; nbTotalPanels: number; }): Promise => { // throw new Error("Planned maintenance") // In case you need to quickly debug the RENDERING engine you can uncomment this: // return mockLLMResponse const query = createZephyrPrompt([ { role: "system", content: [ `You are a writer specialized in ${preset.llmPrompt}`, `Please write detailed drawing instructions and a short (2-3 sentences long) speech caption for the ${nbTotalPanels} panels of a new story. Please make sure each of the ${nbTotalPanels} panels include info about character gender, age, origin, clothes, colors, location, lights, etc.`, `Give your response as a VALID JSON array like this: \`Array<{ panel: number; instructions: string; caption: string}>\`.`, // `Give your response as Markdown bullet points.`, `Be brief in your ${nbTotalPanels} instructions and narrative captions, don't add your own comments. The whole story must be captivating, smart, entertaining. Be straight to the point, and never reply things like "Sure, I can.." etc. Reply using valid JSON.` ].filter(item => item).join("\n") }, { role: "user", content: `The story is: ${prompt}`, } ]) + "\n[{" let result = "" try { // console.log(`calling predict(${query}, ${nbTotalPanels})`) result = `${await predict(query, nbTotalPanels) || ""}`.trim() if (!result.length) { throw new Error("empty result!") } } catch (err) { // console.log(`prediction of the story failed, trying again..`) try { result = `${await predict(query+".", nbTotalPanels) || ""}`.trim() if (!result.length) { throw new Error("empty result!") } } catch (err) { console.error(`prediction of the story failed again 💩`) throw new Error(`failed to generate the story ${err}`) } } // console.log("Raw response from LLM:", result) const tmp = cleanJson(result) let llmResponse: LLMResponse = [] try { llmResponse = dirtyLLMJsonParser(tmp) } catch (err) { // console.log(`failed to read LLM response: ${err}`) // console.log(`original response was:`, result) // in case of failure here, it might be because the LLM hallucinated a completely different response, // such as markdown. There is no real solution.. but we can try a fallback: llmResponse = ( tmp.split("*") .map(item => item.trim()) .map((cap, i) => ({ panel: i, caption: cap, instructions: cap, })) ) } return llmResponse.map(res => dirtyCaptionCleaner(res)) }