llm-pdf/index.js

Command Line tool to automate LLM and image models to generate a pdf by converting the generated text into markdown format and save it as a pdf document.

#!/usr/bin/env node

import * as p from "@clack/prompts";
import color from "picocolors";
import { promises as fs } from "fs";
import main from "./bookGenerator.js";

(async () => {
    console.clear();
    p.intro(color.bold(color.magenta(" 📚 Book Content Generator 📚 ")));

    const metadata = await p.group({
        author: () =>
            p.text({
                message: color.cyan("Author's Name"),
                placeholder: "Khaled Hosseini",
                validate: (value) => {
                    if (!value) return "Please enter an author name!";
                }
            }),
        title: () =>
            p.text({
                message: color.cyan("Book Title"),
                placeholder: "The Kite Runner",
                validate: (value) => {
                    if (!value) return "Please enter a book title!";
                }
            }),
        mentions: () =>
            p.text({
                message: color.cyan("Special Mentions"),
                placeholder: "Dedicated to my wonderful readers.",
            }),
        model: () =>
            p.select({
                message: color.cyan("Select generation model"),
                initialValue: 'deepseek',
                options: [
                    {
                        value: 'deepseek-ai/DeepSeek-R1-Distill-Llama-70B-free',
                        label: color.yellow('Deepseek') + color.gray(' - Quality'),
                        hint: 'Recommended for final drafts'
                    },
                    {
                        value: 'meta-llama/Llama-3.3-70B-Instruct-Turbo-Free',
                        label: color.yellow('Llama') + color.gray(' - Speed'),
                        hint: 'Recommended for quick drafts'
                    }
                ]
            })
    });

    if (p.isCancel(metadata)) {
        p.cancel(color.yellow("Operation cancelled by user"));
        process.exit(0);
    }

    try {
        await fs.writeFile("./content.txt", "");
        p.log.success(color.green("New Book project initialized successfully"));
    } catch (err) {
        p.log.error(color.red("Error initializing file:"), err);
        process.exit(1);
    }

    const inputs = [];
    let counter = 0;

    while (true) {
        const input = await p.text({
            message: color.cyan(`Content Entry #${counter + 1}`),
            placeholder: "Enter your topic here...\n(Type -img at the end for image and /start to start generation)",
            validate: (value) => {
                if (value.length > 500) return "Entry too long! (max 500 characters)";
            }
        });

        if (p.isCancel(input)) {
            p.cancel(color.yellow("Operation cancelled by user"));
            process.exit(0);
        }

        if (input === "/start") {
            if (inputs.length === 0) {
                p.log.warning(color.yellow("No content entries!"));
                const cont = await p.confirm({
                    message: "Start generation with empty content?",
                });
                if (p.isCancel(cont)) process.exit(0);
                if (!cont) continue;
            }
            break;
        }

        try {
            await fs.appendFile("./content.txt", input + "\n");
            inputs.push(input);
            counter++;
            p.log.success(color.green(`Entry #${counter} saved successfully`));
        } catch (err) {
            p.log.error(color.red("Error saving entry:"), err);
        }
    }

    p.note(
        [
            `${color.bold('Author:')} ${metadata.author}`,
            `${color.bold('Title:')} ${metadata.title}`,
            `${color.bold('Mentions:')} ${metadata.mentions}`,
            `${color.bold('Model:')} ${metadata.model === 'deepseek' ? 'Deepseek 🐢' : 'Llama 🚀'}`,
            `\n${color.bold('CONTENT:')}\n${inputs.join("\n")}`
        ].join("\n\n"),
        color.bgMagenta(color.white(" Book Summary "))
    );

    try {
        await main(metadata.author, metadata.title, metadata.mentions, metadata.model);
        p.log.success(color.green("Book generated successfully! 🎉"));
        p.outro(color.bold(color.green("Happy reading!")));
    } catch (err) {
        p.log.error(color.red("Generation failed! ❌"));
        p.log.error(color.red("Error details:"), err);
        process.exit(1);
    }
})();