190 lines
6.9 KiB
TypeScript
190 lines
6.9 KiB
TypeScript
import request from "supertest";
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import dotenv from "dotenv";
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import Anthropic from "@anthropic-ai/sdk";
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import { numTokensFromString } from "./utils/tokens";
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import OpenAI from "openai";
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import { WebsiteScrapeError } from "./utils/types";
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import { logErrors } from "./utils/log";
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const websitesData = require("./data/websites.json");
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import "dotenv/config";
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const fs = require('fs');
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dotenv.config();
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interface WebsiteData {
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website: string;
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prompt: string;
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expected_output: string;
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}
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const TEST_URL = "http://127.0.0.1:3002";
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describe("Scraping/Crawling Checkup (E2E)", () => {
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beforeAll(() => {
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if (!process.env.TEST_API_KEY) {
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throw new Error("TEST_API_KEY is not set");
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}
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if (!process.env.OPENAI_API_KEY) {
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throw new Error("OPENAI_API_KEY is not set");
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}
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});
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describe("Scraping website tests with a dataset", () => {
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it("Should scrape the website and prompt it against OpenAI", async () => {
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let passedTests = 0;
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const batchSize = 15; // Adjusted to comply with the rate limit of 15 per minute
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const batchPromises = [];
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let totalTokens = 0;
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const startTime = new Date().getTime();
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const date = new Date();
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const logsDir = `logs/${date.getMonth() + 1}-${date.getDate()}-${date.getFullYear()}`;
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let errorLogFileName = `${logsDir}/run.log_${new Date().toTimeString().split(' ')[0]}`;
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const errorLog: WebsiteScrapeError[] = [];
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for (let i = 0; i < websitesData.length; i += batchSize) {
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// Introducing delay to respect the rate limit of 15 requests per minute
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await new Promise(resolve => setTimeout(resolve, 10000));
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const batch = websitesData.slice(i, i + batchSize);
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const batchPromise = Promise.all(
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batch.map(async (websiteData: WebsiteData) => {
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try {
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const scrapedContent = await request(TEST_URL || "")
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.post("/v0/scrape")
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.set("Content-Type", "application/json")
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.set("Authorization", `Bearer ${process.env.TEST_API_KEY}`)
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.send({ url: websiteData.website, pageOptions: { onlyMainContent: true } });
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if (scrapedContent.statusCode !== 200) {
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console.error(`Failed to scrape ${websiteData.website}`);
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errorLog.push({
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website: websiteData.website,
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prompt: websiteData.prompt,
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expected_output: websiteData.expected_output,
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actual_output: "",
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error: "Failed to prompt... model error."
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});
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return null;
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}
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const anthropic = new Anthropic({
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apiKey: process.env.ANTHROPIC_API_KEY,
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});
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const openai = new OpenAI({
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apiKey: process.env.OPENAI_API_KEY,
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});
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const prompt = `Based on this markdown extracted from a website html page, ${websiteData.prompt} Just say 'yes' or 'no' to the question.\nWebsite markdown: ${scrapedContent.body.data.markdown}\n`;
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let msg = null;
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const maxRetries = 3;
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let attempts = 0;
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while (!msg && attempts < maxRetries) {
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try {
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msg = await openai.chat.completions.create({
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model: "gpt-4-turbo",
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max_tokens: 100,
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temperature: 0,
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messages: [
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{
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role: "user",
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content: prompt
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},
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],
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});
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} catch (error) {
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console.error(`Attempt ${attempts + 1}: Failed to prompt for ${websiteData.website}, error: ${error}`);
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attempts++;
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if (attempts < maxRetries) {
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console.log(`Retrying... Attempt ${attempts + 1}`);
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await new Promise(resolve => setTimeout(resolve, 2000)); // Wait for 2 seconds before retrying
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}
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}
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}
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if (!msg) {
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console.error(`Failed to prompt for ${websiteData.website} after ${maxRetries} attempts`);
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errorLog.push({
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website: websiteData.website,
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prompt: websiteData.prompt,
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expected_output: websiteData.expected_output,
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actual_output: "",
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error: "Failed to prompt... model error."
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});
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return null;
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}
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const actualOutput = (msg.choices[0].message.content ?? "").toLowerCase()
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const expectedOutput = websiteData.expected_output.toLowerCase();
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const numTokens = numTokensFromString(prompt,"gpt-4") + numTokensFromString(actualOutput,"gpt-4");
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totalTokens += numTokens;
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if (actualOutput.includes(expectedOutput)) {
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passedTests++;
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} else {
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console.error(
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`This website failed the test: ${websiteData.website}`
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);
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console.error(`Actual output: ${actualOutput}`);
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errorLog.push({
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website: websiteData.website,
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prompt: websiteData.prompt,
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expected_output: websiteData.expected_output,
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actual_output: actualOutput,
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error: "Output mismatch"
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});
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}
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return {
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website: websiteData.website,
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prompt: websiteData.prompt,
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expectedOutput,
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actualOutput,
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};
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} catch (error) {
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console.error(
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`Error processing ${websiteData.website}: ${error}`
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);
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errorLog.push({
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website: websiteData.website,
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prompt: websiteData.prompt,
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expected_output: websiteData.expected_output,
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actual_output: "",
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error: "Failed to prompt... model error."
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});
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return null;
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}
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})
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);
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batchPromises.push(batchPromise);
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}
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(await Promise.all(batchPromises)).flat();
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const score = (passedTests / websitesData.length) * 100;
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const endTime = new Date().getTime();
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const timeTaken = (endTime - startTime) / 1000;
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console.log(`Score: ${score}%`);
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console.log(`Total tokens: ${totalTokens}`);
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await logErrors(errorLog, timeTaken, totalTokens, score, websitesData.length);
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if (process.env.ENV === "local" && errorLog.length > 0) {
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if (!fs.existsSync(logsDir)){
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fs.mkdirSync(logsDir, { recursive: true });
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}
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fs.writeFileSync(errorLogFileName, JSON.stringify(errorLog, null, 2));
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}
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expect(score).toBeGreaterThanOrEqual(80);
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}, 350000); // 150 seconds timeout
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});
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});
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