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import { createLlamaPrompt } from "@/lib/createLlamaPrompt" | |
import { dirtyLLMResponseCleaner } from "@/lib/dirtyLLMResponseCleaner" | |
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" | |
export const getStory = async ({ | |
preset, | |
prompt = "", | |
}: { | |
preset: Preset; | |
prompt: string; | |
}): Promise<LLMResponse> => { | |
const query = createLlamaPrompt([ | |
{ | |
role: "system", | |
content: [ | |
`You are a comic book author specialized in ${preset.llmPrompt}`, | |
`Please write detailed drawing instructions and a one-sentence short caption for the 4 panels of a new silent comic book page.`, | |
`Give your response as a JSON array like this: \`Array<{ panel: number; instructions: string; caption: string}>\`.`, | |
// `Give your response as Markdown bullet points.`, | |
`Be brief in your 4 instructions and captions, don't add your own comments. Be straight to the point, and never reply things like "Sure, I can.." etc.` | |
].filter(item => item).join("\n") | |
}, | |
{ | |
role: "user", | |
content: `The story is: ${prompt}`, | |
} | |
]) + "```json\n[" | |
let result = "" | |
try { | |
result = await predict(query) | |
if (!result.trim().length) { | |
throw new Error("empty result!") | |
} | |
} catch (err) { | |
console.log(`prediction of the story failed, trying again..`) | |
try { | |
result = await predict(query+".") | |
if (!result.trim().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)) | |
} |