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import { predict } from "./predict"
import { Preset } from "../engine/presets"
import { GeneratedPanels } from "@/types"
import { cleanJson } from "@/lib/cleanJson"
import { createZephyrPrompt } from "@/lib/createZephyrPrompt"
import { dirtyGeneratedPanelCleaner } from "@/lib/dirtyGeneratedPanelCleaner"
import { dirtyGeneratedPanelsParser } from "@/lib/dirtyGeneratedPanelsParser"
export const getStory = async ({
preset,
prompt = "",
nbTotalPanels = 4,
}: {
preset: Preset;
prompt: string;
nbTotalPanels: number;
}): Promise<GeneratedPanels> => {
throw new Error("legacy, deprecated")
// In case you need to quickly debug the RENDERING engine you can uncomment this:
// return mockGeneratedPanels
const query = createZephyrPrompt([
{
role: "system",
content: [
`You are a writer specialized in ${preset.llmPrompt}`,
`Please write detailed drawing instructions and short (2-3 sentences long) speech captions 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 GeneratedPanels: GeneratedPanels = []
try {
GeneratedPanels = dirtyGeneratedPanelsParser(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:
GeneratedPanels = (
tmp.split("*")
.map(item => item.trim())
.map((cap, i) => ({
panel: i,
caption: cap,
instructions: cap,
}))
)
}
return GeneratedPanels.map(res => dirtyGeneratedPanelCleaner(res))
} |