ai-lab-comic / src /app /queries /predictNextPanels.ts
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import { GeneratedPanel, LLMVendorConfig } from "@/types"
import { cleanJson } from "@/lib/cleanJson"
import { dirtyGeneratedPanelCleaner } from "@/lib/dirtyGeneratedPanelCleaner"
import { dirtyGeneratedPanelsParser } from "@/lib/dirtyGeneratedPanelsParser"
import { sleep } from "@/lib/sleep"
import { Preset } from "../engine/presets"
import { predict } from "./predict"
import { getSystemPrompt } from "./getSystemPrompt"
import { getUserPrompt } from "./getUserPrompt"
export const predictNextPanels = async ({
preset,
prompt = "",
nbPanelsToGenerate,
maxNbPanels,
existingPanels = [],
llmVendorConfig,
}: {
preset: Preset
prompt: string
nbPanelsToGenerate: number
maxNbPanels: number
existingPanels: GeneratedPanel[]
llmVendorConfig: LLMVendorConfig
}): Promise<GeneratedPanel[]> => {
// console.log("predictNextPanels: ", { prompt, nbPanelsToGenerate })
// throw new Error("Planned maintenance")
// In case you need to quickly debug the RENDERING engine you can uncomment this:
// return mockGeneratedPanels
const existingPanelsTemplate = existingPanels.length
? ` To help you, here are the previous panels and their captions (note: if you see an anomaly here eg. no caption or the same description repeated multiple times, do not hesitate to fix the story): ${JSON.stringify(existingPanels, null, 2)}`
: ''
const firstNextOrLast =
existingPanels.length === 0
? "first"
: (maxNbPanels - existingPanels.length) === maxNbPanels
? "last"
: "next"
const systemPrompt = getSystemPrompt({
preset,
firstNextOrLast,
maxNbPanels,
nbPanelsToGenerate,
})
const userPrompt = getUserPrompt({
prompt,
existingPanelsTemplate,
})
let result = ""
// we don't require a lot of token for our task
// but to be safe, let's count ~130 tokens per panel
const nbTokensPerPanel = 130
const nbMaxNewTokens = nbPanelsToGenerate * nbTokensPerPanel
try {
// console.log(`calling predict:`, { systemPrompt, userPrompt, nbMaxNewTokens })
result = `${await predict({
systemPrompt,
userPrompt,
nbMaxNewTokens,
llmVendorConfig
})}`.trim()
console.log("LLM result (1st trial):", result)
if (!result.length) {
throw new Error("empty result on 1st trial!")
}
} catch (err) {
// console.log(`prediction of the story failed, trying again..`)
// this should help throttle things on a bit on the LLM API side
await sleep(2000)
try {
result = `${await predict({
systemPrompt: systemPrompt + " \n ",
userPrompt,
nbMaxNewTokens,
llmVendorConfig
})}`.trim()
console.log("LLM result (2nd trial):", result)
if (!result.length) {
throw new Error("empty result on 2nd trial!")
}
} catch (err) {
console.error(`prediction of the story failed twice 💩`)
throw new Error(`failed to generate the story twice 💩 ${err}`)
}
}
// console.log("Raw response from LLM:", result)
const tmp = cleanJson(result)
let generatedPanels: GeneratedPanel[] = []
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))
}