build/services/lm.js

"use strict";
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var _a;
Object.defineProperty(exports, "__esModule", { value: true });
exports.LmControl = void 0;
const async_service_1 = require("civkit/async-service");
const tsyringe_1 = require("tsyringe");
const logger_1 = require("./logger");
const civkit_1 = require("civkit");
const common_llm_1 = require("../shared/services/common-llm");
const jsdom_1 = require("./jsdom");
const tripleBackTick = '```';
let LmControl = class LmControl extends async_service_1.AsyncService {
    constructor(globalLogger, commonLLM, jsdomControl) {
        super(...arguments);
        this.globalLogger = globalLogger;
        this.commonLLM = commonLLM;
        this.jsdomControl = jsdomControl;
        this.logger = this.globalLogger.child({ service: this.constructor.name });
    }
    async init() {
        await this.dependencyReady();
        this.emit('ready');
    }
    async *geminiFromBrowserSnapshot(snapshot) {
        const pageshot = snapshot?.pageshotUrl || snapshot?.pageshot;
        if (!pageshot) {
            throw new civkit_1.AssertionFailureError('Screenshot of the page is not available');
        }
        const html = await this.jsdomControl.cleanHTMLforLMs(snapshot.html, 'script,link,style,textarea,select>option,svg');
        const it = this.commonLLM.iterRun('vertex-gemini-1.5-flash-002', {
            prompt: [
                `HTML: \n${html}\n\nSCREENSHOT: \n`,
                typeof pageshot === 'string' ? new URL(pageshot) : pageshot,
                `Convert this webpage into a markdown source file that does not contain HTML tags, retaining the page language and visual structures.`,
            ],
            options: {
                system: 'You are ReaderLM-v7, a model that generates Markdown source files only. No HTML, notes and chit-chats allowed',
                stream: true
            }
        });
        const chunks = [];
        for await (const txt of it) {
            chunks.push(txt);
            const output = {
                ...snapshot,
                parsed: {
                    ...snapshot?.parsed,
                    textContent: chunks.join(''),
                }
            };
            yield output;
        }
        return;
    }
    async *readerLMMarkdownFromSnapshot(snapshot) {
        if (!snapshot) {
            throw new civkit_1.AssertionFailureError('Snapshot of the page is not available');
        }
        const html = await this.jsdomControl.cleanHTMLforLMs(snapshot.html, 'script,link,style,textarea,select>option,svg');
        const it = this.commonLLM.iterRun('readerlm-v2', {
            prompt: `Extract the main content from the given HTML and convert it to Markdown format.\n\n${tripleBackTick}html\n${html}\n${tripleBackTick}\n`,
            options: {
                // system: 'You are an AI assistant developed by VENDOR_NAME',
                stream: true,
                modelSpecific: {
                    top_k: 1,
                    temperature: 0,
                    repetition_penalty: 1.13,
                    presence_penalty: 0.25,
                    frequency_penalty: 0.25,
                    max_tokens: 8192,
                }
            },
            maxTry: 1,
        });
        const chunks = [];
        for await (const txt of it) {
            chunks.push(txt);
            const output = {
                ...snapshot,
                parsed: {
                    ...snapshot?.parsed,
                    textContent: chunks.join(''),
                }
            };
            yield output;
        }
        return;
    }
    async *readerLMFromSnapshot(schema, instruction = 'Infer useful information from the HTML and present it in a structured JSON object.', snapshot) {
        if (!snapshot) {
            throw new civkit_1.AssertionFailureError('Snapshot of the page is not available');
        }
        const html = await this.jsdomControl.cleanHTMLforLMs(snapshot.html, 'script,link,style,textarea,select>option,svg');
        const it = this.commonLLM.iterRun('readerlm-v2', {
            prompt: `${instruction}\n\n${tripleBackTick}html\n${html}\n${tripleBackTick}\n${schema ? `The JSON schema:\n${tripleBackTick}json\n${schema}\n${tripleBackTick}\n` : ''}`,
            options: {
                // system: 'You are an AI assistant developed by VENDOR_NAME',
                stream: true,
                modelSpecific: {
                    top_k: 1,
                    temperature: 0,
                    repetition_penalty: 1.13,
                    presence_penalty: 0.25,
                    frequency_penalty: 0.25,
                    max_tokens: 8192,
                }
            },
            maxTry: 1,
        });
        const chunks = [];
        for await (const txt of it) {
            chunks.push(txt);
            const output = {
                ...snapshot,
                parsed: {
                    ...snapshot?.parsed,
                    textContent: chunks.join(''),
                }
            };
            yield output;
        }
        return;
    }
};
exports.LmControl = LmControl;
exports.LmControl = LmControl = __decorate([
    (0, tsyringe_1.singleton)(),
    __metadata("design:paramtypes", [logger_1.GlobalLogger, typeof (_a = typeof common_llm_1.LLMManager !== "undefined" && common_llm_1.LLMManager) === "function" ? _a : Object, jsdom_1.JSDomControl])
], LmControl);
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