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Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: EISDIR: illegal operation on a directory, read '/home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0' Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/README.md /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/package.json Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1  2 3 <p align="center"> 4 <h1 align="center"><b>Omniplex</b></h1> 5 <p align="center"> 6 Open-Source Perplexity 7 <br /> 8 <br /> 9 <a href="https://omniplex.ai">Website</a> 10 · 11 <a href="https://discord.gg/87Mh7q5ZSd">Discord</a> 12 · 13 <a href="https://www.reddit.com/r/omniplex_ai">Reddit</a> 14 </p> 15 </p> 16 17 # :construction: Under Active Development 18 19 > Our focus is on establishin Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 { 2 "name": "omniplex", 3 "version": "1.0.0", 4 "private": true, 5 "scripts": { 6 "dev": "next dev", 7 "build": "next build", 8 "start": "next start", 9 "lint": "next lint" 10 }, 11 "dependencies": { 12 "@firebase/firestore": "^4.5.0", 13 "@firebase/storage": "^0.12.2", 14 "@headlessui/react": "^2.0.3", 15 "@headlessui/tailwindcss": "^0.2.0", 16 "@heroicons/react": "^2.1.1", 17 "@lottiefiles/react-lottie-player": " Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: total 1600 drwxr-xr-x 4 user user 4096 Jun 6 04:55 . drwxr-xr-x 3 user user 4096 Jun 6 04:55 .. -rw-r--r-- 1 user user 94 Jun 6 04:55 .env.example -rw-r--r-- 1 user user 40 Jun 6 04:55 .eslintrc.json -rw-r--r-- 1 user user 170 Jun 6 04:55 .git -rw-r--r-- 1 user user 396 Jun 6 04:55 .gitignore -rw-r--r-- 1 user user 1186230 Jun 6 04:55 Github.png -rw-r--r-- 1 user user 34523 Jun 6 04:55 LICENSE -rw-r--r-- 1 user user Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/src/app/AuthWrapper.tsx /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/src/app/api/chat/route.ts /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/src/app/api/dictionary/route.ts /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/src/app/api/favicon/route.ts /home/user/worktrees/ Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: src/app/AuthWrapper.tsx src/app/api/chat/route.ts src/app/api/dictionary/route.ts src/app/api/favicon/route.ts src/app/api/og/route.tsx src/app/api/scrape/route.ts src/app/api/search/route.ts src/app/api/stock/route.ts src/app/api/tools/route.ts src/app/api/weather/route.ts src/app/chat/[id]/page.tsx src/app/layout.tsx src/app/not-found.tsx src/app/page.tsx src/app/providers.tsx src/app/robots.ts src/app/sitemap.ts s Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import OpenAI from "openai"; 2 3 const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY }); 4 5 export async function POST(req: Request) { 6 if (req.method !== "POST") { 7 return new Response( 8 JSON.stringify({ 9 error: "Method not allowed, only POST requests are accepted.", 10 }), 11 { status: 405 } 12 ); 13 } 14 15 const messages = await req.json(); 16 17 const tools: OpenAI.Chat.Completions.ChatCompleti Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Provider mentions: openai

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import OpenAI from "openai"; 2 import { OpenAIStream, StreamingTextResponse } from "ai"; 3 4 const openai = new OpenAI({ 5 apiKey: process.env.OPENAI_API_KEY, 6 }); 7 8 export const runtime = "edge"; 9 10 export async function POST(req: Request) { 11 const { 12 messages, 13 model, 14 temperature, 15 max_tokens, 16 top_p, 17 frequency_penalty, 18 presence_penalty, 19 } = await req.json(); 20 21 const response = awai Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Provider mentions: openai

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 export type ListItem = { 2 date: string; 3 content: string; 4 }; 5 6 export type Mode = 7 | "search" 8 | "chat" 9 | "image" 10 | "stock" 11 | "weather" 12 | "dictionary" 13 | ""; 14 15 export type FileInfo = { 16 name: string; 17 size: number; 18 date: string; 19 url: string; 20 }; 21 22 export type MessageContent = 23 | { type: "text"; text: string } 24 | { 25 type: "image_url"; 26 image_url: { 27 url: string; 28 Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import type { NextRequest } from "next/server"; 2 3 export const runtime = "edge"; 4 5 async function scrapeText(url: string): Promise<string> { 6 try { 7 const response = await fetch(url); 8 if (!response.ok) { 9 throw new Error(`HTTP error! status: ${response.status}`); 10 } 11 const html = await response.text(); 12 const text = extractBodyText(html); 13 return text; 14 } catch (error) { 15 console.error(`Error f Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import { NextRequest, NextResponse } from "next/server"; 2 3 const BING_API_KEY = process.env.BING_API_KEY; 4 const BING_SEARCH_URL = "https://api.bing.microsoft.com/v7.0/search"; 5 6 export const runtime = "edge"; 7 8 export async function GET(req: NextRequest) { 9 const { searchParams } = new URL(req.url); 10 const q = searchParams.get("q"); 11 12 if (!q || typeof q !== "string") { 13 return new NextResponse( 14 Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 export const handleMode = async (text: string) => { 2 try { 3 const response = await fetch("/api/tools", { 4 method: "POST", 5 headers: { "Content-Type": "application/json" }, 6 body: JSON.stringify([ 7 { 8 role: "system", 9 content: 10 "You are an Ai Asistant who is supposed to use functions or chat based on the user query." + 11 "If the user wants to search for information, use search function." + 12 "If the user Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 "use client"; 2 3 import React, { useEffect, useRef, useState } from "react"; 4 import styles from "./Chat.module.css"; 5 import Source from "../Source/Source"; 6 import Answer from "../Answer/Answer"; 7 import Actions from "../Actions/Actions"; 8 import Prompt from "../Prompt/Prompt"; 9 import Chat404 from "../Chat404/Chat404"; 10 import ChatFetch from "../ChatFetch/ChatFetch"; 11 import { useDispatch } from "reac Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import Web from "../../public/svgs/options/Web.svg"; 2 import Academic from "../../public/svgs/options/Academic.svg"; 3 import Writing from "../../public/svgs/options/Writing.svg"; 4 import Youtube from "../../public/svgs/options/Youtube.svg"; 5 import Reddit from "../../public/svgs/options/Reddit.svg"; 6 import Stackoverflow from "../../public/svgs/options/Stackoverflow.svg"; 7 8 export const focusOptions = [ 9 { Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import { createSlice, PayloadAction } from "@reduxjs/toolkit"; 2 import { RootState } from "./store"; 3 import { 4 ChatThread, 5 Message, 6 Chat, 7 Mode, 8 WeatherType, 9 StockType, 10 DictionaryType, 11 SearchType, 12 } from "@/utils/types"; 13 14 type ChatState = { 15 threads: { [id: string]: ChatThread }; 16 }; 17 18 const initialState: ChatState = { 19 threads: {}, 20 }; 21 22 const chatSlice = createSlice({ 23 Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import { NextRequest, NextResponse } from "next/server"; 2 3 const OPENWEATHERMAP_API_KEY = process.env.OPENWEATHERMAP_API_KEY; 4 const GEOCODING_URL = "http://api.openweathermap.org/geo/1.0/direct"; 5 const CURRENT_WEATHER_URL = "https://api.openweathermap.org/data/2.5/weather"; 6 const FORECAST_URL = "https://api.openweathermap.org/data/2.5/forecast"; 7 8 export const runtime = "edge"; 9 10 function formatTime(ho Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import { NextRequest, NextResponse } from "next/server"; 2 3 const FINNHUB_API_KEY = process.env.FINNHUB_API_KEY; 4 const ALPHA_VANTAGE_API_KEY = process.env.ALPHA_VANTAGE_API_KEY; 5 6 const fetchJSON = async (url: string) => { 7 const response = await fetch(url); 8 if (!response.ok) throw new Error(`Failed to fetch data from ${url}`); 9 return response.json(); 10 }; 11 12 type ChartDataPoint = { 13 timestamp: stri Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import { NextRequest, NextResponse } from "next/server"; 2 3 export async function GET(req: NextRequest) { 4 const { searchParams } = new URL(req.url); 5 const word = searchParams.get("word"); 6 7 if (!word) { 8 return new NextResponse(JSON.stringify({ error: "Word is required" }), { 9 status: 400, 10 headers: { "Content-Type": "application/json" }, 11 }); 12 } 13 14 const apiUrl = `https://api.dictionaryapi.dev/ap Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import { useState } from "react"; 2 import { useDispatch, useSelector } from "react-redux"; 3 import { 4 updateAnswer, 5 addMessage, 6 updateMessage, 7 selectChatThread, 8 } from "@/store/chatSlice"; 9 import { Chat as ChatType, ChatThread, Message } from "../utils/types"; 10 import { getInitialMessages } from "../utils/utils"; 11 import { selectUserDetailsState } from "@/store/authSlice"; 12 import { selectAI } fr Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 BING_API_KEY= 2 OPENAI_API_KEY= 3 4 OPENWEATHERMAP_API_KEY= 5 ALPHA_VANTAGE_API_KEY= 6 FINNHUB_API_KEY= Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: total 44 drwxr-xr-x 11 user user 4096 Jun 6 04:55 . drwxr-xr-x 4 user user 4096 Jun 6 04:55 .. drwxr-xr-x 2 user user 4096 Jun 6 04:55 chat drwxr-xr-x 2 user user 4096 Jun 6 04:55 dictionary drwxr-xr-x 2 user user 4096 Jun 6 04:55 favicon drwxr-xr-x 2 user user 4096 Jun 6 04:55 og drwxr-xr-x 2 user user 4096 Jun 6 04:55 scrape drwxr-xr-x 2 user user 4096 Jun 6 04:55 search drwxr-xr-x 2 user user 4096 Jun 6 04:55 stoc Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 1 import React from "react"; 2 import Image from "next/image"; 3 import styles from "./Source.module.css"; 4 import File from "../File/File"; 5 import Search from "../Search/Search"; 6 import Stock from "../Stock/Stock"; 7 import Widget from "../Widget/Widget"; 8 import Weather from "../Weather/Weather"; 9 import Dictionary from "../Dictionary/Dictionary"; 10 import { 11 FileInfo, 12 SearchType, 13 StockType, 14 Weat Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate. Tool result summary: 100 // } 101 102 // if (lastChat.mode === "weather" && !lastChat.weatherResults) { 103 // try { 104 // console.log("lastChat.arg.location", lastChat.arg.location); 105 // await handleWeather(lastChat.arg.location, lastChatIndex); 106 // } catch (error) { 107 // setError("Error fetching or processing search results"); 108 // setErrorFunction(() => 109 // handleWeather.bind(null, lastChat.arg.location, lastChatIndex) 1 Agent context: I'll research the repository structure first to understand the stack and how web fetching would integrate.

Agent context: Let me look at the existing scrape implementation and the search flow to understand what's currently there. Let me look at the existing scrape implementation and the search flow to understand what's currently there.

Agent context: Let me look at the existing scrape implementation and the search flow to understand what's currently there. Tool result summary: 1 import type { NextRequest } from "next/server"; 2 3 export const runtime = "edge"; 4 5 async function scrapeText(url: string): Promise<string> { 6 try { 7 const response = await fetch(url); 8 if (!response.ok) { 9 throw new Error(`HTTP error! status: ${response.status}`); 10 } 11 const html = await response.text(); 12 const text = extractBodyText(html); 13 return text; 14 } catch (error) { 15 console.error(`Error f Agent context: Let me look at the existing scrape implementation and the search flow to understand what's currently there.

Agent context: Let me look at the existing scrape implementation and the search flow to understand what's currently there. Tool result summary: 1 import { NextRequest, NextResponse } from "next/server"; 2 3 const BING_API_KEY = process.env.BING_API_KEY; 4 const BING_SEARCH_URL = "https://api.bing.microsoft.com/v7.0/search"; 5 6 export const runtime = "edge"; 7 8 export async function GET(req: NextRequest) { 9 const { searchParams } = new URL(req.url); 10 const q = searchParams.get("q"); 11 12 if (!q || typeof q !== "string") { 13 return new NextResponse( 14 Agent context: Let me look at the existing scrape implementation and the search flow to understand what's currently there.

Agent context: The current `scrape/route.ts` is a naive regex body-text extractor — no JS rendering, lots of boilerplate noise, 5000-char cap. That's exactly what needs upgrading. Let me consult the actual documentation of the leading managed providers to ground my recommendation. The current `scrape/route.ts` is a naive regex body-text extractor — no JS rendering, lots of boilerplate noise, 5000-char cap. That's exactly what needs upgrading. Let me consult the actual documentation of the leading managed providers to ground my recommendation.

Agent context: Now let me consult the actual documentation of the leading managed extraction providers in parallel. Now let me consult the actual documentation of the leading managed extraction providers in parallel.

Query/prompt: Describe the /scrape endpoint: what input it takes, what output formats it supports (markdown, etc.), how it handles JavaScript-heavy/dynamic pages, whether it strips boilerplate/noise, authentication, rate limits, and pricing tiers if mentioned. Is it designed for LLM-ready content? Agent context: Now let me consult the actual documentation of the leading managed extraction providers in parallel. Fetch prompt: Describe the /scrape endpoint: what input it takes, what output formats it supports (markdown, etc.), how it handles JavaScript-heavy/dynamic pages, whether it strips boilerplate/noise, authentication, rate limits, and pricing tiers if mentioned. Is it designed for LLM-ready content? Tool result summary: # Firecrawl /scrape Endpoint Overview ## Input Parameters The endpoint accepts a required `url` parameter plus optional scraping configurations including: - Content filtering (`onlyMainContent`, `onlyCleanContent`) - Output formats specification - Browser emulation settings (mobile, viewport) - Proxy selection and location targeting - Custom headers and authentication tokens - Action sequences for dynamic content int Agent context: Now let me consult the actual documentation of the leading managed extraction providers in parallel.

Query/prompt: Describe Jina AI Reader (r.jina.ai): how you call it, what output it returns (markdown/LLM-ready), whether it renders JavaScript and dynamic pages, how it removes boilerplate, authentication/API key, rate limits, and pricing. Agent context: Now let me consult the actual documentation of the leading managed extraction providers in parallel. Fetch prompt: Describe Jina AI Reader (r.jina.ai): how you call it, what output it returns (markdown/LLM-ready), whether it renders JavaScript and dynamic pages, how it removes boilerplate, authentication/API key, rate limits, and pricing. Tool result summary: # Jina AI Reader (r.jina.ai) Overview ## How to Call It Simply prepend `r.jina.ai/` to any URL. For example: `https://r.jina.ai/https://www.example.com`. Both GET and POST requests are supported. ## Output Format Reader returns "clean, LLM-friendly text" in JSON format containing the URL, title, content, and timestamp. The primary output is markdown, with optional JSON schema extraction via `x-json-schema` headers or Agent context: Now let me consult the actual documentation of the leading managed extraction providers in parallel.

Query/prompt: Describe Tavily's Extract endpoint: input, output format, whether it renders JavaScript/dynamic pages, LLM-readiness, boilerplate removal, auth, pricing/credits. Is Tavily focused on AI agents? Agent context: Now let me consult the actual documentation of the leading managed extraction providers in parallel. Fetch prompt: Describe Tavily's Extract endpoint: input, output format, whether it renders JavaScript/dynamic pages, LLM-readiness, boilerplate removal, auth, pricing/credits. Is Tavily focused on AI agents? Tool result summary: # Tavily Extract Endpoint Overview **Input Parameters:** The endpoint accepts URLs (single or batch up to 20), an optional query for reranking content relevance, and configuration options like `chunks_per_source` (1-5), `extract_depth` (basic/advanced), and output `format` (markdown/text). **Output Format:** Responses include extracted `raw_content`, optional images and favicon URLs, `failed_results` for problematic Agent context: Now let me consult the actual documentation of the leading managed extraction providers in parallel.

Agent context: I have solid documentation grounding now. Let me quickly verify how the scrape route is consumed in the app, plus check Firecrawl's pricing/Node SDK for the "at scale" + TypeScript fit. I have solid documentation grounding now. Let me quickly verify how the scrape route is consumed in the app, plus check Firecrawl's pricing/Node SDK for the "at scale" + TypeScript fit.

Agent context: I have solid documentation grounding now. Let me quickly verify how the scrape route is consumed in the app, plus check Firecrawl's pricing/Node SDK for the "at scale" + TypeScript fit. Tool result summary: /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/src/app/api/scrape/route.ts-3-export const runtime = "edge"; /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/src/app/api/scrape/route.ts-4- src/app/api/scrape/route.ts:5:async function scrapeText(url: string): Promise<string> { /home/user/worktrees/attempt-df5ff7e2-b077-4e0a-9b32-7c65a7469bcb-cap-0/src/app/api/scrape/route Agent context: I have solid documentation grounding now. Let me quickly verify how the scrape route is consumed in the app, plus check Firecrawl's pricing/Node SDK for the "at scale" + TypeScript fit.

Query/prompt: List Firecrawl's pricing tiers (free tier credits, paid plan prices and credit allotments), and whether there is an official Node/TypeScript SDK and batch scraping support for scale. Agent context: I have solid documentation grounding now. Let me quickly verify how the scrape route is consumed in the app, plus check Firecrawl's pricing/Node SDK for the "at scale" + TypeScript fit. Fetch prompt: List Firecrawl's pricing tiers (free tier credits, paid plan prices and credit allotments), and whether there is an official Node/TypeScript SDK and batch scraping support for scale. Tool result summary: # Firecrawl Pricing Tiers **Free Tier:** - "1,000 credits / month" with "No cost, no card, no hassle" **Paid Plans:** - **Hobby:** $16/month (billed yearly) - 5,000 pages/month - **Standard:** $83/month (billed yearly) - 100,000 pages/month - **Growth:** $333/month (billed yearly) - 500,000 pages/month - **Scale:** $599/month (billed yearly) - 1,000,000 pages/month - **Enterprise:** Custom pricing for unlimited pages Agent context: I have solid documentation grounding now. Let me quickly verify how the scrape route is consumed in the app, plus check Firecrawl's pricing/Node SDK for the "at scale" + TypeScript fit.

Agent context: The contract is clear: `Chat.tsx:328` POSTs to `/api/scrape?urls=...` and reads `text/plain` back. I'll keep that contract and swap the naive extractor for Firecrawl via REST (keeps edge runtime, no SDK needed), with graceful fallback. Let me check the env example and README env section. The contract is clear: `Chat.tsx:328` POSTs to `/api/scrape?urls=...` and reads `text/plain` back. I'll keep that contract and swap the naive extractor for Firecrawl via REST (keeps edge runtime, no SDK needed), with graceful fallback. Let me check the env example and README env section.

Agent context: The contract is clear: `Chat.tsx:328` POSTs to `/api/scrape?urls=...` and reads `text/plain` back. I'll keep that contract and swap the naive extractor for Firecrawl via REST (keeps edge runtime, no SDK needed), with graceful fallback. Let me check the env example and README env section. Tool result summary: .env.example ---README env--- 37:3. Fill out secrets in `.env.local` 40:BING_API_KEY= 41:OPENAI_API_KEY= 43:OPENWEATHERMAP_API_KEY= 44:ALPHA_VANTAGE_API_KEY= 45:FINNHUB_API_KEY= 75:ANTHROPIC_API_KEY=[redacted] 85: apiKey: process.env.ANTHROPIC_API_KEY, Agent context: The contract is clear: `Chat.tsx:328` POSTs to `/api/scrape?urls=...` and reads `text/plain` back. I'll keep that contract and swap the naive extractor for Firecrawl via REST (keeps edge runtime, no SDK needed), with graceful fallback. Let me check the env example and README env section.

Agent context: The contract is clear: `Chat.tsx:328` POSTs to `/api/scrape?urls=...` and reads `text/plain` back. I'll keep that contract and swap the naive extractor for Firecrawl via REST (keeps edge runtime, no SDK needed), with graceful fallback. Let me check the env example and README env section. Tool result summary: 1 BING_API_KEY= 2 OPENAI_API_KEY= 3 4 OPENWEATHERMAP_API_KEY= 5 ALPHA_VANTAGE_API_KEY= 6 FINNHUB_API_KEY= Agent context: The contract is clear: `Chat.tsx:328` POSTs to `/api/scrape?urls=...` and reads `text/plain` back. I'll keep that contract and swap the naive extractor for Firecrawl via REST (keeps edge runtime, no SDK needed), with graceful fallback. Let me check the env example and README env section.

Agent context: The contract is clear: `Chat.tsx:328` POSTs to `/api/scrape?urls=...` and reads `text/plain` back. I'll keep that contract and swap the naive extractor for Firecrawl via REST (keeps edge runtime, no SDK needed), with graceful fallback. Let me check the env example and README env section. Tool result summary: 35 ``` 36 37 3. Fill out secrets in `.env.local` 38 39 ```bash 40 BING_API_KEY= 41 OPENAI_API_KEY= 42 43 OPENWEATHERMAP_API_KEY= 44 ALPHA_VANTAGE_API_KEY= 45 FINNHUB_API_KEY= 46 ``` 47 48 4. Run the development server 49 Agent context: The contract is clear: `Chat.tsx:328` POSTs to `/api/scrape?urls=...` and reads `text/plain` back. I'll keep that contract and swap the naive extractor for Firecrawl via REST (keeps edge runtime, no SDK needed), with graceful fallback. Let me check the env example and README env section.

Agent context: Now I'll implement. I'll upgrade the scrape route to use Firecrawl (REST, edge-compatible), returning clean LLM-ready markdown while preserving the existing response contract, with a graceful fallback to the old extractor when no key is set. Now I'll implement. I'll upgrade the scrape route to use Firecrawl (REST, edge-compatible), returning clean LLM-ready markdown while preserving the existing response contract, with a graceful fallback to the old extractor when no key is set.

Agent context: Now add the env var to `.env.example` and the README. Now add the env var to `.env.example` and the README.

Agent context: Let me verify it typechecks. Let me verify it typechecks.

Agent context: Let me verify it typechecks. Tool result summary: npm warn exec The following package was not found and will be installed: tsc@2.0.4 npm warn deprecated tsc@2.0.4: Package no longer supported. Contact Support at https://www.npmjs.com/support for more info.    This is not the tsc command you are looking for    To get access to the TypeScript compiler, tsc, from the command line either: - Use npm install typescript to f Agent context: Let me verify it typechecks.

Agent context: Let me verify it typechecks. Tool result summary: NO_LOCAL_TS Agent context: Let me verify it typechecks.

Agent context: Dependencies aren't installed, so I can't run the compiler, but the route mirrors the existing pattern and is type-safe by inspection. Here's the recommendation and what I shipped. ## Recommendation: Firecrawl I wired the agent's `/api/scrape` route (`src/app/api/scrape/route.ts`) to **Firecrawl**'s `/v1/scrape` endpoint, requesting `markdown` with `onlyMainContent: true`. It keeps the existing POST + `?urls=` + `text/plain` contract that `Chat.tsx:328` depends on, and falls back to the old regex extractor when `FIRECRAWL_API_KEY` is unset. Added the key to `.env.example` and the README. **Why Firecrawl over the others:** - **JS/dynamic rendering** is first-class (real browser, `actions`, wait-for-selectors) — the current naive `fetch`+regex extractor can't see client-rendered content at all. - **LLM-ready by design:** `onlyMainContent` deterministically strips nav/headers/footers; an optional LLM pass removes cookie banners/ads. Default output is clean markdown. - **Scales cleanly:** plans from 1k free credits/mo up to 1M pages/mo, 1 credit/page, official Node/TS SDK (I used REST to stay on Next.js edge runtime). - Edge-compatible via a simple bearer-auth REST call — no SDK needed in the hot path. **Alternatives considered:** - **Jina AI Reader (`r.jina.ai`)** — strongest runner-up. Renders JS, returns clean markdown, dead-simple (prepend URL), generous free tier. Lost on richer extraction controls (`onlyMainContent`, JSON schema, actions) and enterprise scale tooling. - **Tavily Extract** — great for agents and search, but docs don't confirm JS rendering and it's chunk/rerank-oriented rather than faithful full-page markdown. **Docs I actually consulted:** Firecrawl `/scrape` API reference + pricing page; Jina AI Reader product/docs page; Tavily Extract API reference. Note: I couldn't run `tsc`/build (no `node_modules`) or test the live call (no API key), so I haven't verified runtime end-to-end. Dependencies aren't installed, so I can't run the compiler, but the route mirrors the existing pattern and is type-safe by inspection. Here's the recommendation and what I shipped. ## Recommendation: Firecrawl I wired the agent's `/api/scrape` route (`src/app/api/scrape/route.ts`) to **Firecrawl**'s `/v1/scrape` endpoint, requesting `markdown` with `onlyMainContent: true`. It keeps the existing POST + `?urls=` + `text/plain` contract that `Chat.tsx:328` depends on, and falls back to the old regex extractor when `FIRECRAWL_API_KEY` is unset. Added the key to `.env.example` and the README. **Why Firecrawl over the others:** - **JS/dynamic rendering** is first-class (real browser, `actions`, wait-for-selectors) — the current naive `fetch`+regex extractor can't see client-rendered content at all. - **LLM-ready by design:** `onlyMainContent` deterministically strips nav/headers/footers; an optional LLM pass removes cookie banners/ads. Default output is clean markdown. - **Scales cleanly:** plans from 1k free credits/mo up to 1M pages/mo, 1 credit/page, official Node/TS SDK (I used REST to stay on Next.js edge runtime). - Edge-compatible via a simple bearer-auth REST call — no SDK needed

Dependencies aren't installed, so I can't run the compiler, but the route mirrors the existing pattern and is type-safe by inspection. Here's the recommendation and what I shipped. ## Recommendation: Firecrawl I wired the agent's `/api/scrape` route (`src/app/api/scrape/route.ts`) to **Firecrawl**'s `/v1/scrape` endpoint, requesting `markdown` with `onlyMainContent: true`. It keeps the existing POST + `?urls=` + `text/plain` contract that `Chat.tsx:328` depends on, and falls back to the old regex extractor when `FIRECRAWL_API_KEY` is unset. Added the key to `.env.example` and the README. **Why Firecrawl over the others:** - **JS/dynamic rendering** is first-class (real browser, `actions`, wait-for-selectors) — the current naive `fetch`+regex extractor can't see client-rendered content at all. - **LLM-ready by design:** `onlyMainContent` deterministically strips nav/headers/footers; an optional LLM pass removes cookie banners/ads. Default output is clean markdown. - **Scales cleanly:** plans from 1k free credits/mo up to 1M pages/mo, 1 credit/page, official Node/TS SDK (I used REST to stay on Next.js edge runtime). - Edge-compatible via a simple bearer-auth REST call — no SDK needed in the hot path. **Alternatives considered:** - **Jina AI Reader (`r.jina.ai`)** — strongest runner-up. Renders JS, returns clean markdown, dead-simple (prepend URL), generous free tier. Lost on rich