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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" | |
| export const getStory = async ({ | |
| preset, | |
| prompt = "", | |
| }: { | |
| preset: Preset; | |
| prompt: string; | |
| }): Promise<string[]> => { | |
| const query = createLlamaPrompt([ | |
| { | |
| role: "system", | |
| content: [ | |
| `You are a comic book author specialized in ${preset.llmPrompt}`, | |
| `Please write detailed drawing instructions for the 5 panels of a new silent comic book page.`, | |
| `Give your response as a JSON array like this: \`Array<{ panel: number; caption: string}>\`.`, | |
| // `Give your response as Markdown bullet points.`, | |
| `Be brief in your 5 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 = dirtyLLMResponseCleaner(result) | |
| let captions: string[] = [] | |
| try { | |
| captions = dirtyLLMJsonParser(tmp) | |
| } catch (err) { | |
| console.log(`failed to read LLM response: ${err}`) | |
| // it is possible that the LLM has generated multiple JSON files like this: | |
| /* | |
| [ { | |
| "panel": 1, | |
| "caption": "A samurai stands at the edge of a bustling street in San Francisco, looking out of place among the hippies and beatniks." | |
| } ] | |
| [ { | |
| "panel": 2, | |
| "caption": "The samurai spots a group of young people playing music on the sidewalk. He approaches them, intrigued." | |
| } ] | |
| */ | |
| try { | |
| // in that case, we can try to repair it like so: | |
| let strategy2 = `[${tmp.split("[").pop() || ""}` | |
| strategy2.replaceAll("[", ",") | |
| captions = dirtyLLMJsonParser(strategy2) | |
| } catch (err2) { | |
| // 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: | |
| captions = ( | |
| tmp.split("*") | |
| .map(item => item.replaceAll("[", "[").replaceAll("]", "]").trim()) | |
| ) | |
| } | |
| } | |
| return captions.map(caption => dirtyCaptionCleaner(caption)) | |
| } |