Today's top opensource GitHub repo of the day:
mendableai/firecrawl
mendableai/firecrawl
turns websites into clean LLM markdown with anti-bot bypass.
why builders should care: returns clean markdown and JSON from any URL with one API call. No custom proxies.
1 like · 110 views
@arxiv Behind the scenes, the external web page is converted into Markdown using firecrawl/firecrawl
You can explore both the original and Markdown versions in the PDF reader.
2 likes · 250 views
Turn any web page into clean markdown for ChatGPT or Claude
Paste a web page into ChatGPT or Claude and most of what you send is navigation, cookie banners and script tags. Fetch it with plain requests and a JavaScript-heavy page often comes back nearly empty. Firecrawl solves both: give it a URL and it returns clean markdown of the page's main content, ready for a prompt or a vector store. Here is how to set it up from Python, Node, curl or the CLI, with the commands from the README. The short version lives on the Deduped use-case page.
What Firecrawl does
Firecrawl is an API to search, scrape and interact with the web, built for AI agents. Its scrape endpoint converts any URL to markdown, HTML, screenshots or structured JSON. It handles rotating proxies, rate limits and JavaScript-blocked content, and it can parse PDFs and DOCX files into markdown too.
It is open source under AGPL-3.0 (the SDKs are MIT) and also runs as a hosted service. The examples below use the hosted API, which needs a key from firecrawl.dev. The README links a self-hosting guide if you would rather run it yourself.
Step 1: get a key and keep it out of your code
Sign up at firecrawl.dev to get your API key. It starts with fc-. Put it in an environment variable rather than in a file you commit:
export FIRECRAWL_API_KEY="fc-YOUR_API_KEY"
Step 2: scrape a page to markdown
Python
pip install firecrawl
import os
from firecrawl import Firecrawl
app = Firecrawl(api_key=os.environ["FIRECRAWL_API_KEY"])
doc = app.scrape("https://firecrawl.dev", formats=["markdown"])
print(doc.markdown)
Node.js
npm install firecrawl
import { Firecrawl } from 'firecrawl';
const app = new Firecrawl({ apiKey: process.env.FIRECRAWL_API_KEY });
const doc = await app.scrape('https://firecrawl.dev', { formats: ['markdown'] });
curl
curl -X POST 'https://api.firecrawl.dev/v2/scrape' \
-H "Authorization: Bearer $FIRECRAWL_API_KEY" \
-H 'Content-Type: application/json' \
-d '{
"url": "firecrawl.dev"
}'
CLI, with only the main content of the page:
firecrawl https://firecrawl.dev --only-main-content
The output is plain markdown: headings, lists and text, without the page chrome. That is what you paste into a prompt or split into chunks for retrieval.
Step 3: go wider when one page is not enough
The same client covers the jobs that usually come next:
# Find URLs on a site, ordered by relevance to a word
result = app.map("https://firecrawl.dev", search="pricing")
# Scrape several URLs at once
job = app.batch_scrape([
"https://firecrawl.dev",
"https://docs.firecrawl.dev",
], formats=["markdown"])
# Crawl a docs site (the SDK waits for the job to finish)
docs = app.crawl("https://docs.firecrawl.dev", limit=50)
for d in docs.data:
print(d.metadata.source_url, d.markdown[:100])
Crawling a whole docs site this way is the fastest route to a knowledge base for a docs chatbot.
Step 4: give Claude Code or Cursor the same power
If you want your coding agent to read current docs instead of guessing from training data, install Firecrawl as a skill and restart the agent:
npx -y firecrawl-cli@latest init --all --browser
Or add it as an MCP server in any MCP client:
{
"mcpServers": {
"firecrawl-mcp": {
"command": "npx",
"args": ["-y", "firecrawl-mcp"],
"env": {
"FIRECRAWL_API_KEY": "fc-YOUR_API_KEY"
}
}
}
}
That config holds your key, so keep it out of shared or committed config files.
Caveats
- Respect each site's terms and robots rules when you scrape.
- Crawls cost credits per page on the hosted service, so set a limit while testing.
- The README examples hardcode fc-YOUR_API_KEY; reading it from the environment, as above, is the safer habit.
More like this
Compare Firecrawl with other options on best AI repos for web scraping for LLMs, or see every Firecrawl use case, including giving your coding agent live web access.
Want the setup commands for 50 AI repos people actually ship with? Get the free AI Repos That Actually Ship pack: dedupedai.com
Build vs Buy Internal Tools: When Founders Should Build Their Own
Build an internal tool when it touches your core data or core workflow, when per-seat SaaS pricing scales faster than your headcount justifies, or when the off-the-shelf version forces your team to work around it every day. Buy when the tool is a commodity, when your need is standard, and when the vendor's uptime and security are things you would rather rent than own. AI-assisted development has moved the line toward building, but it has not moved the line on maintenance, and that is where most founders get the math wrong.
Why the question is back on the table
For a decade the default advice to founders was simple: never build what you can buy. Engineering time was scarce, SaaS was cheap, and every hour spent on an internal tool was an hour not spent on the product.
That advice was written for a world where a "small" internal tool took a team a quarter. It no longer does. Developers now routinely rebuild a scoped version of a commercial product, a browser screen recorder, a photo search tool, a lightweight CRM, in a weekend with an LLM doing most of the typing. The cost of the first version has collapsed.
But the first version was never the expensive part. Owning the thing is. Our own outreach engine, described below, took far less time to get working than it has taken to keep working: scrapers break, model versions change, and one engineer still spends part of every month on it. The first version was cheap. The second year is the real price. So the question has changed from "can we afford to build this" to "can we afford to keep this alive", and that needs a different framework.
The four questions that decide it
1. Does the tool sit on your core data?
If the tool reads or writes the data that makes your business valuable, customer records, usage events, clinical notes, pricing logic, then buying means handing your most important asset to a vendor's data model and export policy. You will spend months fighting their schema and their API limits. Tools on core data lean strongly toward build.
If the tool holds data you would not miss, meeting recordings, design mockups, standup notes, buy it and move on.
2. How does the SaaS price scale?
Per-seat pricing is the trap. It looks trivial at five people and becomes a line item the finance lead asks about at forty. Do the three-year arithmetic before you sign.
An illustrative example: a tool at $30 per seat per month for 40 people is $14,400 a year, or $43,200 over three years. That is before the inevitable tier upgrade when you need SSO or an audit log. A focused internal tool built in two to three weeks and maintained a day or two a month usually lands well under that over the same period.
Usage-based pricing is friendlier. If you only pay for what you use and usage tracks revenue, buying is often fine even at scale.
3. Who fixes it when it breaks?
This is the question founders skip. An internal tool has dependencies that rot, a third-party API that changes its auth flow, a database that needs a migration, and a security patch that lands on a Friday. If nobody owns it, it quietly becomes the kind of debt we describe in technical debt management: working, unloved, and terrifying to touch.
Rule: an internal tool with no named owner is a liability, not an asset. If you cannot name the person who will maintain it next year, buy.
4. Will you keep changing it?
If your requirements for the tool shift weekly, because you are still learning your own process, SaaS will fight you at every step. Custom fields, Zapier glue, and workaround spreadsheets pile up. Building wins when the tool is a moving target.
If the process is stable and standard, invoicing, expense reports, calendar booking, the vendor has already solved it better than you will.
Our own example: the outreach engine
We run our own outbound at the agency, and this decision came up for us directly. The off-the-shelf personalization tools either produced generic emails or charged per enrichment credit in a way that scaled badly with the volume we wanted.
So we built it. A self-hosted Firecrawl instance scrapes each prospect's site, a local LLM reads the result, and the engine writes one tailored email per company. It runs on hardware we already had, so the marginal cost per prospect is close to zero.
The part that mattered for build versus buy was what happened after the first version. Our initial pipeline chained several steps: extract facts about the company, plan the angle, then draft. When we collapsed that into a single call that extracts and drafts together, it came out ahead on both cost and quality. We could only learn that because we owned the tool and could change the prompt architecture in an afternoon. With a SaaS product that experiment is not available to you. We cover the general pattern in single call vs agent chains, and the specific case in AI cold email agent: build vs buy.
The honest cost of that decision is that one engineer spends part of every month keeping it healthy, because scrapers break and model versions change. We consider that worth it. You should decide whether your equivalent is.
What a good "build" looks like
If the four questions point toward building, keep it disciplined:
- Scope to one workflow. Not "an internal CRM", but "the view the sales lead needs every Monday morning". You can widen it later.
- Use a boring stack. For us that is Next.js, PostgreSQL or Supabase, and TypeScript. Sometimes it is a script and a cron job. The goal is that any engineer on the team can fix it.
- Time-box the first version. One to three weeks. If it does not fit, the tool is bigger than you think.
- Name an owner and budget their time. Treat it as a small product with a backlog, not a side project.
- Instrument it. A tool nobody knows is broken is worse than no tool. Log runs, alert on failures.
When buying is clearly right
Some categories are not close:
- Authentication, payments, transactional email. The vendor's security and deliverability are the product. Do not own these.
- Anything with a compliance surface. If the tool will be in scope for SOC 2, HIPAA, or a data-residency audit, you want a vendor's attestation, not your own.
- Commodity collaboration. Video calls, docs, chat. Your version will be worse and nobody will thank you.
- Anything you need this week that is not core. Buy it, set a calendar reminder for the renewal date, and re-run this framework then.
A rule you can apply in one meeting
Score the four questions. If two or more say build, build a time-boxed first version for one workflow with a named owner. If fewer than two do, buy, and revisit at the next renewal.
Run our outreach engine through it and you can see the scoring in practice. Core data: partly, since prospect research feeds our pipeline but we would survive losing it. Pricing: the per-enrichment-credit model scaled badly with the volume we wanted, so build. Owner: one engineer, named, with part of each month budgeted, so build is allowed. Changing it: we rewrote the prompt architecture from a multi-step chain to a single call once we had data, so build. Three of four said build, and the decision has held.
Write the decision and the date down, because the right answer changes as the company grows and the honest thing is to re-check it rather than defend it.
Where an agency fits
Most founders do not lack the judgment to make this call. They lack an engineer with two free weeks. That is the gap we fill: a scoped internal tool, built on a stack your team already knows, handed over with an owner's manual rather than a dependency. If you are staring at a SaaS renewal and wondering whether to build instead, let's talk.
---
Originally published on the Pykero blog.
10.7M Views 24 Din Mein: Seedha X Se 5 Viral GitHub Launches #Shorts
Top 5 trending GitHub repos, Hindi mein - har number aaj check kiya gaya hai.
Is week ke top trending repos, 356k+ stars combined:
1. NVIDIA/OpenShell (18k stars) - OpenShell is the safe, private runtime for autonomous AI agents.
2. reason-machines/reason-network (1k stars) - Reason Network: your team's coding agents, talking to each other. The engine behind `reason network`.
3. firecrawl/firecrawl (194k stars) - Supercharge your AI agents with data from the web and beyond. Building the library for superintelligence. 🔥
4. colinhacks/reylo (655 stars) - Import .sql files into TypeScript with full type inference and zero codegen.
5. Shubhamsaboo/awesome-llm-apps (143k stars) - 100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.
Repo links:
NVIDIA/OpenShell
reason-machines/reason-network
firecrawl/firecrawl
colinhacks/reylo
Shubhamsaboo/awesome-llm-apps
Comment karo "VIRAL" - saare links DM mein bhej dunga.
Kisi dev dost ko bhejo jise ye chahiye.
Save karlo, baad mein kaam aayega.
Naman AI - AI aur dev tools, Hindi mein. Har din naya repo, har number verified.
#Shorts #GitHub #AI #OpenSource #TechHindi
[github trending repos, best github repositories 2026, top 5 github repos, open source projects for beginners, ai coding agents, github stars]
[coding in hindi, tech shorts hindi, programming for beginners, developer tools 2026, ai tools for developers, learn coding free]
[bn] ২৪ দিনে ১০.৭ মিলিয়ন ভিউ: সরাসরি X থেকে ৫টি ভাইরাল গিটহাব লঞ্চ #Shorts
হিন্দিতে শীর্ষ ৫টি ট্রেন্ডিং গিটহাব রিপো - প্রতিটি নম্বর আজ চেক করা হয়েছে।
এই সপ্তাহের শীর্ষ ট্রেন্ডিং রিপো, সম্মিলিতভাবে ৩৫৬ হাজারেরও বেশি স্টার:
১. NVIDIA/OpenShell (১৮ হাজার স্টার) - OpenShell হলো স্বয়ংক্রিয় AI এজেন্টদের জন্য একটি নিরাপদ, প্রাইভেট রানটাইম।
২. reason-machines/reason-network (১ হাজার স্টার) - Reason Network: আপনার দলের কোডিং এজেন্ট, যারা একে অপরের সাথে কথা বলে। `reason network`-এর পেছনের ইঞ্জিন।
৩. firecrawl/firecrawl (১৯৪ হাজার স্টার) - ওয়েব এবং অন্যান্য উৎস থেকে পাওয়া ডেটা দিয়ে আপনার AI এজেন্টদের সুপারচার্জ করুন। সুপার ইন্টেলিজেন্সের জন্য লাইব্রেরি তৈরি করা হচ্ছে। 🔥
৪. colinhacks/reylo (৬৫৫ স্টার) - সম্পূর্ণ টাইপ ইনফারেন্স এবং জিরো কোডজেন সহ TypeScript-এ .sql ফাইল ইম্পোর্ট করুন।
5. Shubhamsaboo/awesome-llm-apps (143k তারকা) - 100+ AI এজেন্ট, এজেন্ট দক্ষতা এবং RAG অ্যাপস - বিনামূল্যে এবং ওপেন সোর্স।
রেপো লিঙ্ক:
NVIDIA/OpenShell
reason-machines/reason-network
firecrawl/firecrawl
colinhacks/reylo
Shubhamsaboo/awesome-llm-apps
মন্তব্য করুন "ভাইরাল" - সারা লিঙ্ক ডিএম মে ভেজ দুঙ্গা।
কিসি দেব দোস্ত কো ভেজো জিসে ইয়ে চাহিয়ে।
করলো বাঁচাও, বাদ মে কাম আয়েগা।
নমন এআই - এআই অর দেব টুল, হিন্দি মে। হার দিন নয়া রেপো, হার নম্বর যাচাই করা হয়েছে।
#শর্টস #গিটহাব #এআই #ওপেনসোর্স #টেকহিন্দি
[গিটহাব ট্রেন্ডিং রিপো, সেরা গিটহাব রিপোজিটরি ২০২৬, সেরা ৫টি গিটহাব রিপো, নতুনদের জন্য ওপেন সোর্স প্রজেক্ট, এআই কোডিং এজেন্ট, গিটহাব স্টারস]
[হিন্দিতে কোডিং, হিন্দি টেক শর্টস, নতুনদের জন্য প্রোগ্রামিং, ডেভেলপার টুলস ২০২৬, ডেভেলপারদের জন্য এআই টুলস, বিনামূল্যে কোডিং শিখুন]
3 likes · 69 views
3. firecrawl/firecrawl
Lo apuntas a un sitio y recorre todas las páginas automáticamente, ejecuta JavaScript, y te devuelve datos estructurados listos para tu IA.
130k+ estrellas. El motor silencioso detrás de muchas startups de IA.
Completamente open source.
4 likes · 2 reposts · 222 views
Introducing Firecrawl
Struggling to gather data from the web for your AI applications? Firecrawl is an open-source tool that makes web scraping and data extraction easy. It handles complex tasks like rotating proxies with a single command, saving you time and effort in building AI solutions.
#firecrawl #ai #webscraping #opensource #dataextraction
Follow for more AI, automation, and open-source tools you can actually use.
Link:
firecrawl/firecrawl
[ar] تعرّف على Firecrawl
هل تواجه صعوبة في جمع البيانات من الإنترنت لتطبيقات الذكاء الاصطناعي؟ Firecrawl أداة مفتوحة المصدر تُسهّل عملية استخراج البيانات من مواقع الويب. فهي تُنجز مهامًا معقدة، مثل تغيير الخوادم الوكيلة، بأمر واحد، مما يوفر عليك الوقت والجهد في بناء حلول الذكاء الاصطناعي.
#firecrawl #ai #webscraping #opensource #dataextraction
تابعنا للمزيد من أدوات الذكاء الاصطناعي والأتمتة والأدوات مفتوحة المصدر التي يمكنك استخدامها فعليًا.
الرابط:
firecrawl/firecrawl
[bn] ফায়ারক্রল (Firecrawl) পরিচিতি
আপনার AI অ্যাপ্লিকেশনের জন্য ওয়েব থেকে ডেটা সংগ্রহ করতে হিমশিম খাচ্ছেন? ফায়ারক্রল (Firecrawl) একটি ওপেন-সোর্স টুল যা ওয়েব স্ক্র্যাপিং এবং ডেটা এক্সট্র্যাকশনকে সহজ করে তোলে। এটি একটিমাত্র কমান্ডের মাধ্যমে প্রক্সি ঘোরানোর (rotating proxys) মতো জটিল কাজগুলো সামলে নেয়, যা AI সলিউশন তৈরিতে আপনার সময় ও শ্রম বাঁচায়।
#firecrawl #ai #webscraping #opensource #dataextraction
আরও AI, অটোমেশন এবং ওপেন-সোর্স টুলের জন্য ফলো করুন যা আপনি সত্যিই ব্যবহার করতে পারবেন।
লিঙ্ক:
firecrawl/firecrawl
[de-DE] Wir stellen vor: Firecrawl
Haben Sie Schwierigkeiten, Daten aus dem Web für Ihre KI-Anwendungen zu sammeln? Firecrawl ist ein Open-Source-Tool, das Web-Scraping und Datenextraktion vereinfacht. Es erledigt komplexe Aufgaben wie das Rotieren von Proxys mit nur einem Befehl und spart Ihnen so Zeit und Aufwand bei der Entwicklung von KI-Lösungen.
#firecrawl #ai #webscraping #opensource #dataextraction
Folgen Sie uns für weitere KI-, Automatisierungs- und Open-Source-Tools, die Sie tatsächlich nutzen können.
Link:
firecrawl/firecrawl
[es-US] Presentando Firecrawl
¿Te cuesta recopilar datos de la web para tus aplicaciones de IA? Firecrawl es una herramienta de código abierto que facilita el web scraping y la extracción de datos. Gestiona tareas complejas como la rotación de proxies con un solo comando, ahorrándote tiempo y esfuerzo en el desarrollo de soluciones de IA.
#firecrawl #ia #webscraping #opensource #dataextraction
Síguenos para descubrir más herramientas de IA, automatización y código abierto que puedes usar.
Enlace: firecrawl/firecrawl
[fr-FR] Présentation de Firecrawl
Vous avez du mal à collecter des données web pour vos applications d'IA ? Firecrawl est un outil open source qui simplifie le web scraping et l'extraction de données. Il gère des tâches complexes comme la rotation des proxys en une seule commande, vous faisant ainsi gagner du temps et de l'énergie dans le développement de vos solutions d'IA.
#firecrawl #ai #webscraping #opensource #dataextraction
Suivez-nous pour découvrir d'autres outils d'IA, d'automatisation et open source vraiment utiles.
Lien :
firecrawl/firecrawl
[hi] Firecrawl का परिचय
क्या आप अपने AI अनुप्रयोगों के लिए वेब से डेटा एकत्र करने में कठिनाई का सामना कर रहे हैं? फायरक्रॉल एक ओपन-सोर्स टूल है जो वेब स्क्रैपिंग और डेटा एक्सट्रैक्शन को आसान बनाता है। यह प्रॉक्सी रोटेट करने जैसे जटिल कार्यों को एक ही कमांड से संभाल लेता है, जिससे AI समाधान बनाने में आपका समय और मेहनत बचती है।
#firecrawl #ai #webscraping #opensource #dataextraction
उपयोग में आने वाले अन्य AI, ऑटोमेशन और ओपन-सोर्स टूल्स के लिए हमें फॉलो करें।
लिंक:
firecrawl/firecrawl
[id] Memperkenalkan Firecrawl
Kesulitan mengumpulkan data dari web untuk aplikasi AI Anda? Firecrawl adalah alat sumber terbuka yang memudahkan web scraping dan ekstraksi data. Alat ini menangani tugas-tugas kompleks seperti rotasi proxy hanya dengan satu perintah, menghemat waktu dan tenaga Anda dalam membangun solusi AI.
#firecrawl #ai #webscraping #opensource #dataextraction
Ikuti untuk mendapatkan lebih banyak alat AI, otomatisasi, dan sumber terbuka yang benar-benar dapat Anda gunakan.
Tautan:
firecrawl/firecrawl
[it] Presentazione di Firecrawl
Hai difficoltà a raccogliere dati dal web per le tue applicazioni di intelligenza artificiale? Firecrawl è uno strumento open source che semplifica il web scraping e l'estrazione dei dati. Gestisce attività complesse come la rotazione dei proxy con un singolo comando, facendoti risparmiare tempo e fatica nella creazione di soluzioni di IA.
#firecrawl #ai #webscraping #opensource #dataextraction
Seguici per scoprire altri strumenti open source per l'IA, l'automazione e l'utilizzo concreto.
Link:
firecrawl/firecrawl
[iw] הכירו את Firecrawl
מתקשים לאסוף נתונים מהאינטרנט עבור יישומי הבינה המלאכותית שלכם? Firecrawl הוא כלי קוד פתוח שהופך את גירוד וחילוץ הנתונים לקל. הוא מטפל במשימות מורכבות כמו סיבוב פרוקסי בפקודה אחת, וחוסך לכם זמן ומאמץ בבניית פתרונות בינה מלאכותית.
#firecrawl #ai #גירוד_אתרים #קוד_פתוח #חילוץ_נתונים
עקבו אחרינו לעוד כלים של בינה מלאכותית, אוטומציה וקוד פתוח שתוכלו להשתמש בהם בפועל.
קישור:
firecrawl/firecrawl
[ja] Firecrawlとは
AIアプリケーション用のWebデータ収集にお困りですか？Firecrawlは、Webスクレイピングとデータ抽出を容易にするオープンソースツールです。プロキシのローテーションといった複雑なタスクも、たった1つのコマンドで処理できるため、AIソリューション構築にかかる時間と労力を大幅に節約できます。
#firecrawl #ai #webscraping #opensource #dataextraction
AI、自動化、そして実際に使えるオープンソースツールをもっと知りたい方は、ぜひフォローしてください。
リンク：
firecrawl/firecrawl
[ko] Firecrawl 소개
AI 애플리케이션에 필요한 웹 데이터 수집에 어려움을 겪고 계신가요? Firecrawl은 웹 스크래핑 및 데이터 추출을 간편하게 해주는 오픈 소스 도구입니다. 프록시 변경과 같은 복잡한 작업도 단 한 번의 명령으로 처리하여 AI 솔루션 개발에 드는 시간과 노력을 절약해 줍니다.
#firecrawl #ai #webscraping #opensource #dataextraction
더 많은 AI, 자동화 및 실제로 사용할 수 있는 오픈 소스 도구를 보려면 팔로우하세요.
링크:
firecrawl/firecrawl
[ml] ഫയർക്രോൾ (Firecrawl) പരിചയപ്പെടുത്തുന്നു
നിങ്ങളുടെ AI ആപ്ലിക്കേഷനുകൾക്കായി വെബിൽ നിന്ന് ഡാറ്റ ശേഖരിക്കാൻ പാടുപെടുകയാണോ? വെബ് സ്ക്രാപ്പിംഗും ഡാറ്റ എക്സ്ട്രാക്ഷനും എളുപ്പമാക്കുന്ന ഒരു ഓപ്പൺ സോഴ്സ് ഉപകരണമാണ് ഫയർക്രാൾ. ഒരൊറ്റ കമാൻഡ് ഉപയോഗിച്ച് പ്രോക്സികൾ റൊട്ടേറ്റ് ചെയ്യുന്നത് പോലുള്ള സങ്കീർണ്ണമായ ജോലികൾ ഇത് കൈകാര്യം ചെയ്യുന്നു, AI പരിഹാരങ്ങൾ നിർമ്മിക്കുന്നതിൽ നിങ്ങളുടെ സമയവും പരിശ്രമവും ലാഭിക്കുന്നു.
#firecrawl #ai #webscraping #opensource #dataextraction
നിങ്ങൾക്ക് യഥാർത്ഥത്തിൽ ഉപയോഗിക്കാൻ കഴിയുന്ന കൂടുതൽ AI, ഓട്ടോമേഷൻ, ഓപ്പൺ സോഴ്സ് ഉപകരണങ്ങൾക്കായി പിന്തുടരുക.
ലിങ്ക്:
firecrawl/firecrawl
[nl-NL] Maak kennis met Firecrawl
Vind je het lastig om data van het web te verzamelen voor je AI-toepassingen? Firecrawl is een open-source tool die webscraping en data-extractie eenvoudig maakt. Het voert complexe taken zoals het roteren van proxy's uit met één commando, waardoor je tijd en moeite bespaart bij het bouwen van AI-oplossingen.
#firecrawl #ai #webscraping #opensource #dataextraction
Volg ons voor meer AI, automatisering en open-source tools die je daadwerkelijk kunt gebruiken.
Link:
firecrawl/firecrawl
[pa] Firecrawl ਦੀ ਜਾਣ-ਪਛਾਣ
ਕੀ ਤੁਸੀਂ ਆਪਣੀਆਂ AI ਐਪਲੀਕੇਸ਼ਨਾਂ ਲਈ ਵੈੱਬ ਤੋਂ ਡਾਟਾ ਇਕੱਠਾ ਕਰਨ ਲਈ ਸੰਘਰਸ਼ ਕਰ ਰਹੇ ਹੋ? ਫਾਇਰਕ੍ਰੌਲ ਇੱਕ ਓਪਨ-ਸੋਰਸ ਟੂਲ ਹੈ ਜੋ ਵੈੱਬ ਸਕ੍ਰੈਪਿੰਗ ਅਤੇ ਡੇਟਾ ਐਕਸਟਰੈਕਸ਼ਨ ਨੂੰ ਆਸਾਨ ਬਣਾਉਂਦਾ ਹੈ। ਇਹ ਇੱਕ ਸਿੰਗਲ ਕਮਾਂਡ ਨਾਲ ਪ੍ਰੌਕਸੀਆਂ ਨੂੰ ਘੁੰਮਾਉਣ ਵਰਗੇ ਗੁੰਝਲਦਾਰ ਕੰਮਾਂ ਨੂੰ ਸੰਭਾਲਦਾ ਹੈ, AI ਹੱਲ ਬਣਾਉਣ ਵਿੱਚ ਤੁਹਾਡਾ ਸਮਾਂ ਅਤੇ ਮਿਹਨਤ ਬਚਾਉਂਦਾ ਹੈ।
#firecrawl #ai #webscraping #opensource #dataextraction
ਹੋਰ AI, ਆਟੋਮੇਸ਼ਨ, ਅਤੇ ਓਪਨ-ਸੋਰਸ ਟੂਲਸ ਲਈ ਫਾਲੋ ਕਰੋ ਜੋ ਤੁਸੀਂ ਅਸਲ ਵਿੱਚ ਵਰਤ ਸਕਦੇ ਹੋ।
ਲਿੰਕ:
firecrawl/firecrawl
[pl] Przedstawiamy Firecrawl
Masz problemy z gromadzeniem danych z internetu na potrzeby swoich aplikacji AI? Firecrawl to narzędzie open source, które ułatwia scrapowanie i ekstrakcję danych z internetu. Obsługuje złożone zadania, takie jak rotacja serwerów proxy, za pomocą jednego polecenia, oszczędzając czas i wysiłek w budowaniu rozwiązań AI.
#firecrawl #sztuczna inteligencja #webscraping #opensource #ekstrakcjadanych
Obserwuj, aby dowiedzieć się więcej o AI, automatyzacji i narzędziach open source, z których możesz skorzystać.
Link:
firecrawl/firecrawl
[pt-BR] Apresentando o Firecrawl
Com dificuldades para coletar dados da web para suas aplicações de IA? O Firecrawl é uma ferramenta de código aberto que facilita a extração de dados e o web scraping. Ele lida com tarefas complexas, como a rotação de proxies, com um único comando, economizando tempo e esforço na criação de soluções de IA.
#firecrawl #ai #webscraping #opensource #dataextraction
Siga para mais ferramentas de IA, automação e código aberto que você pode usar na prática.
Link:
firecrawl/firecrawl
[ru] Знакомство с Firecrawl
Возникают трудности со сбором данных из интернета для ваших приложений ИИ? Firecrawl — это инструмент с открытым исходным кодом, который упрощает веб-скрейпинг и извлечение данных. Он справляется со сложными задачами, такими как ротация прокси-серверов, с помощью одной команды, экономя ваше время и усилия при создании решений на основе ИИ.
#firecrawl #ai #webscraping #opensource #dataextraction
Подписывайтесь, чтобы узнать больше об ИИ, автоматизации и инструментах с открытым исходным кодом, которые вы действительно можете использовать.
Ссылка:
firecrawl/firecrawl
[ta] Firecrawl-ஐ அறிமுகப்படுத்துகிறோம்
உங்கள் AI பயன்பாடுகளுக்காக இணையத்திலிருந்து தரவுகளைச் சேகரிப்பதில் சிரமப்படுகிறீர்களா? ஃபயர்கிரால் (Firecrawl) என்பது இணைய வழித் தரவுச் சேகரிப்பையும் (web scraping) தரவுப் பிரித்தெடுப்பையும் (data extraction) எளிதாக்கும் ஒரு திறந்த மூலக் கருவியாகும். இது ப்ராக்ஸிகளை (proxies) சுழற்றுவது போன்ற சிக்கலான பணிகளை ஒரே கட்டளையில் கையாள்வதன் மூலம், AI தீர்வுகளை உருவாக்குவதில் உங்கள் நேரத்தையும் உழைப்பையும் மிச்சப்படுத்துகிறது.
#firecrawl #ai #webscraping #opensource #dataextraction
நீங்கள் உண்மையில் பயன்படுத்தக்கூடிய மேலும் பல AI, ஆட்டோமேஷன் மற்றும் திறந்த மூலக் கருவிகளுக்குப் பின்தொடரவும்.
இணைப்பு:
firecrawl/firecrawl
[te] Firecrawl పరిచయం
మీ AI అప్లికేషన్ల కోసం వెబ్ నుండి డేటాను సేకరించడంలో ఇబ్బంది పడుతున్నారా? ఫైర్క్రాల్ అనేది వెబ్ స్క్రాపింగ్ మరియు డేటా సంగ్రహణను సులభతరం చేసే ఒక ఓపెన్-సోర్స్ సాధనం. ఇది ప్రాక్సీలను మార్చడం వంటి సంక్లిష్టమైన పనులను ఒకే ఆదేశంతో నిర్వహిస్తుంది, తద్వారా AI పరిష్కారాలను రూపొందించడంలో మీ సమయాన్ని మరియు శ్రమను ఆదా చేస్తుంది.
#ఫైర్క్రాల్ #ఏఐ #వెబ్స్క్రాపింగ్ #ఓపెన్సోర్స్ #డేటాసంగ్రహణ
మీరు నిజంగా ఉపయోగించగల మరిన్ని AI, ఆటోమేషన్ మరియు ఓపెన్-సోర్స్ సాధనాల కోసం అనుసరించండి.
లింక్:
firecrawl/firecrawl
[uk] Знайомство з Firecrawl
Важко збирати дані з Інтернету для ваших ШІ-додатків? Firecrawl — це інструмент з відкритим кодом, який спрощує веб-скрейпінг та вилучення даних. Він обробляє складні завдання, такі як ротація проксі-серверів, за допомогою однієї команди, заощаджуючи ваш час та зусилля під час створення ШІ-рішень.
#firecrawl #ai #webscraping #opensource #dataextraction
Підпишіться, щоб дізнатися більше про ШІ, автоматизацію та інструменти з відкритим кодом, які ви можете використовувати.
Посилання:
firecrawl/firecrawl
22 likes · 978 views
Крутой открытый софт: Firecrawl превращает любой firecrawl/firecrawl в чистый Markdown для AI-агентов, JS и капчи под капотом. Разбор в Telegram: t.me #софт #ai #opensource #нейросети #разработка
2 likes
Awesome open-source AI: Firecrawl turns any firecrawl/firecrawl into clean Markdown for AI agents, handling JS and captchas. Full setup & guide in Telegram: t.me #ai #tech #opensource #coding #devtools #automation
2 likes · 1 repost
firecrawl: The Hottest TypeScript Repo on GitHub Right Now
In this video, we break down firecrawl/firecrawl - one of the hottest open-source projects on GitHub right now.
Supercharge your AI agents with data from the web and beyond. Building the library for superintelligence. 🔥. It has already earned 192,943 stars on GitHub and is written primarily in TypeScript. We look at what it does, why developers are paying attention to it right now, and who should try it.
📂 Repo: firecrawl/firecrawl
🌐 Stars: 192,943 | Language: TypeScript | Forks: 10,188
🔔 Subscribe for daily picks of the hottest GitHub repos: / @reporadar
#github #opensource #programming
keywords: coding, developer tools, github, opensource, programming, software, tech
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Today's top opensource GitHub repo of the day: mendableai/firecrawl mendableai/firecrawl turns websites into clean LLM markdown with anti-bot bypass. why builders should care: returns clean markdown and JSON from any URL with one API call. No custom proxies.
@arxiv Behind the scenes, the external web page is converted into Markdown using firecrawl/firecrawl You can explore both the original and Markdown versions in the PDF reader.
Turn any web page into clean markdown for ChatGPT or Claude Paste a web page into ChatGPT or Claude and most of what you send is navigation, cookie banners and script tags. Fetch it with plain requests and a JavaScript-heavy page often comes back nearly empty. Firecrawl solves both: give it a URL and it returns clean markdown of the page's main content, ready for a prompt or a vector store. Here is how to set it up from Python, Node, curl or the CLI, with the commands from the README. The short version lives on the Deduped use-case page. What Firecrawl does Firecrawl is an API to search, scrape and interact with the web, built for AI agents. Its scrape endpoint converts any URL to markdown, HTML, screenshots or structured JSON. It handles rotating proxies, rate limits and JavaScript-blocked content, and it can parse PDFs and DOCX files into markdown too. It is open source under AGPL-3.0 (the SDKs are MIT) and also runs as a hosted service. The examples below use the hosted API, which needs a key from firecrawl.dev. The README links a self-hosting guide if you would rather run it yourself. Step 1: get a key and keep it out of your code Sign up at firecrawl.dev to get your API key. It starts with fc-. Put it in an environment variable rather than in a file you commit: export FIRECRAWL_API_KEY="fc-YOUR_API_KEY" Step 2: scrape a page to markdown Python pip install firecrawl import os from firecrawl import Firecrawl app = Firecrawl(api_key=os.environ["FIRECRAWL_API_KEY"]) doc = app.scrape("https://firecrawl.dev", formats=["markdown"]) print(doc.markdown) Node.js npm install firecrawl import { Firecrawl } from 'firecrawl'; const app = new Firecrawl({ apiKey: process.env.FIRECRAWL_API_KEY }); const doc = await app.scrape('https://firecrawl.dev', { formats: ['markdown'] }); curl curl -X POST 'https://api.firecrawl.dev/v2/scrape' \ -H "Authorization: Bearer $FIRECRAWL_API_KEY" \ -H 'Content-Type: application/json' \ -d '{ "url": "firecrawl.dev" }' CLI, with only the main content of the page: firecrawl https://firecrawl.dev --only-main-content The output is plain markdown: headings, lists and text, without the page chrome. That is what you paste into a prompt or split into chunks for retrieval. Step 3: go wider when one page is not enough The same client covers the jobs that usually come next: # Find URLs on a site, ordered by relevance to a word result = app.map("https://firecrawl.dev", search="pricing") # Scrape several URLs at once job = app.batch_scrape([ "https://firecrawl.dev", "https://docs.firecrawl.dev", ], formats=["markdown"]) # Crawl a docs site (the SDK waits for the job to finish) docs = app.crawl("https://docs.firecrawl.dev", limit=50) for d in docs.data: print(d.metadata.source_url, d.markdown[:100]) Crawling a whole docs site this way is the fastest route to a knowledge base for a docs chatbot. Step 4: give Claude Code or Cursor the same power If you want your coding agent to read current docs instead of guessing from training data, install Firecrawl as a skill and restart the agent: npx -y firecrawl-cli@latest init --all --browser Or add it as an MCP server in any MCP client: { "mcpServers": { "firecrawl-mcp": { "command": "npx", "args": ["-y", "firecrawl-mcp"], "env": { "FIRECRAWL_API_KEY": "fc-YOUR_API_KEY" } } } } That config holds your key, so keep it out of shared or committed config files. Caveats - Respect each site's terms and robots rules when you scrape. - Crawls cost credits per page on the hosted service, so set a limit while testing. - The README examples hardcode fc-YOUR_API_KEY; reading it from the environment, as above, is the safer habit. More like this Compare Firecrawl with other options on best AI repos for web scraping for LLMs, or see every Firecrawl use case, including giving your coding agent live web access. Want the setup commands for 50 AI repos people actually ship with? Get the free AI Repos That Actually Ship pack: dedupedai.com
Build vs Buy Internal Tools: When Founders Should Build Their Own Build an internal tool when it touches your core data or core workflow, when per-seat SaaS pricing scales faster than your headcount justifies, or when the off-the-shelf version forces your team to work around it every day. Buy when the tool is a commodity, when your need is standard, and when the vendor's uptime and security are things you would rather rent than own. AI-assisted development has moved the line toward building, but it has not moved the line on maintenance, and that is where most founders get the math wrong. Why the question is back on the table For a decade the default advice to founders was simple: never build what you can buy. Engineering time was scarce, SaaS was cheap, and every hour spent on an internal tool was an hour not spent on the product. That advice was written for a world where a "small" internal tool took a team a quarter. It no longer does. Developers now routinely rebuild a scoped version of a commercial product, a browser screen recorder, a photo search tool, a lightweight CRM, in a weekend with an LLM doing most of the typing. The cost of the first version has collapsed. But the first version was never the expensive part. Owning the thing is. Our own outreach engine, described below, took far less time to get working than it has taken to keep working: scrapers break, model versions change, and one engineer still spends part of every month on it. The first version was cheap. The second year is the real price. So the question has changed from "can we afford to build this" to "can we afford to keep this alive", and that needs a different framework. The four questions that decide it 1. Does the tool sit on your core data? If the tool reads or writes the data that makes your business valuable, customer records, usage events, clinical notes, pricing logic, then buying means handing your most important asset to a vendor's data model and export policy. You will spend months fighting their schema and their API limits. Tools on core data lean strongly toward build. If the tool holds data you would not miss, meeting recordings, design mockups, standup notes, buy it and move on. 2. How does the SaaS price scale? Per-seat pricing is the trap. It looks trivial at five people and becomes a line item the finance lead asks about at forty. Do the three-year arithmetic before you sign. An illustrative example: a tool at $30 per seat per month for 40 people is $14,400 a year, or $43,200 over three years. That is before the inevitable tier upgrade when you need SSO or an audit log. A focused internal tool built in two to three weeks and maintained a day or two a month usually lands well under that over the same period. Usage-based pricing is friendlier. If you only pay for what you use and usage tracks revenue, buying is often fine even at scale. 3. Who fixes it when it breaks? This is the question founders skip. An internal tool has dependencies that rot, a third-party API that changes its auth flow, a database that needs a migration, and a security patch that lands on a Friday. If nobody owns it, it quietly becomes the kind of debt we describe in technical debt management: working, unloved, and terrifying to touch. Rule: an internal tool with no named owner is a liability, not an asset. If you cannot name the person who will maintain it next year, buy. 4. Will you keep changing it? If your requirements for the tool shift weekly, because you are still learning your own process, SaaS will fight you at every step. Custom fields, Zapier glue, and workaround spreadsheets pile up. Building wins when the tool is a moving target. If the process is stable and standard, invoicing, expense reports, calendar booking, the vendor has already solved it better than you will. Our own example: the outreach engine We run our own outbound at the agency, and this decision came up for us directly. The off-the-shelf personalization tools either produced generic emails or charged per enrichment credit in a way that scaled badly with the volume we wanted. So we built it. A self-hosted Firecrawl instance scrapes each prospect's site, a local LLM reads the result, and the engine writes one tailored email per company. It runs on hardware we already had, so the marginal cost per prospect is close to zero. The part that mattered for build versus buy was what happened after the first version. Our initial pipeline chained several steps: extract facts about the company, plan the angle, then draft. When we collapsed that into a single call that extracts and drafts together, it came out ahead on both cost and quality. We could only learn that because we owned the tool and could change the prompt architecture in an afternoon. With a SaaS product that experiment is not available to you. We cover the general pattern in single call vs agent chains, and the specific case in AI cold email agent: build vs buy. The honest cost of that decision is that one engineer spends part of every month keeping it healthy, because scrapers break and model versions change. We consider that worth it. You should decide whether your equivalent is. What a good "build" looks like If the four questions point toward building, keep it disciplined: - Scope to one workflow. Not "an internal CRM", but "the view the sales lead needs every Monday morning". You can widen it later. - Use a boring stack. For us that is Next.js, PostgreSQL or Supabase, and TypeScript. Sometimes it is a script and a cron job. The goal is that any engineer on the team can fix it. - Time-box the first version. One to three weeks. If it does not fit, the tool is bigger than you think. - Name an owner and budget their time. Treat it as a small product with a backlog, not a side project. - Instrument it. A tool nobody knows is broken is worse than no tool. Log runs, alert on failures. When buying is clearly right Some categories are not close: - Authentication, payments, transactional email. The vendor's security and deliverability are the product. Do not own these. - Anything with a compliance surface. If the tool will be in scope for SOC 2, HIPAA, or a data-residency audit, you want a vendor's attestation, not your own. - Commodity collaboration. Video calls, docs, chat. Your version will be worse and nobody will thank you. - Anything you need this week that is not core. Buy it, set a calendar reminder for the renewal date, and re-run this framework then. A rule you can apply in one meeting Score the four questions. If two or more say build, build a time-boxed first version for one workflow with a named owner. If fewer than two do, buy, and revisit at the next renewal. Run our outreach engine through it and you can see the scoring in practice. Core data: partly, since prospect research feeds our pipeline but we would survive losing it. Pricing: the per-enrichment-credit model scaled badly with the volume we wanted, so build. Owner: one engineer, named, with part of each month budgeted, so build is allowed. Changing it: we rewrote the prompt architecture from a multi-step chain to a single call once we had data, so build. Three of four said build, and the decision has held. Write the decision and the date down, because the right answer changes as the company grows and the honest thing is to re-check it rather than defend it. Where an agency fits Most founders do not lack the judgment to make this call. They lack an engineer with two free weeks. That is the gap we fill: a scoped internal tool, built on a stack your team already knows, handed over with an owner's manual rather than a dependency. If you are staring at a SaaS renewal and wondering whether to build instead, let's talk. --- Originally published on the Pykero blog.
10.7M Views 24 Din Mein: Seedha X Se 5 Viral GitHub Launches #Shorts Top 5 trending GitHub repos, Hindi mein - har number aaj check kiya gaya hai. Is week ke top trending repos, 356k+ stars combined: 1. NVIDIA/OpenShell (18k stars) - OpenShell is the safe, private runtime for autonomous AI agents. 2. reason-machines/reason-network (1k stars) - Reason Network: your team's coding agents, talking to each other. The engine behind `reason network`. 3. firecrawl/firecrawl (194k stars) - Supercharge your AI agents with data from the web and beyond. Building the library for superintelligence. 🔥 4. colinhacks/reylo (655 stars) - Import .sql files into TypeScript with full type inference and zero codegen. 5. Shubhamsaboo/awesome-llm-apps (143k stars) - 100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source. Repo links: NVIDIA/OpenShell reason-machines/reason-network firecrawl/firecrawl colinhacks/reylo Shubhamsaboo/awesome-llm-apps Comment karo "VIRAL" - saare links DM mein bhej dunga. Kisi dev dost ko bhejo jise ye chahiye. Save karlo, baad mein kaam aayega. Naman AI - AI aur dev tools, Hindi mein. Har din naya repo, har number verified. #Shorts #GitHub #AI #OpenSource #TechHindi [github trending repos, best github repositories 2026, top 5 github repos, open source projects for beginners, ai coding agents, github stars] [coding in hindi, tech shorts hindi, programming for beginners, developer tools 2026, ai tools for developers, learn coding free] [bn] ২৪ দিনে ১০.৭ মিলিয়ন ভিউ: সরাসরি X থেকে ৫টি ভাইরাল গিটহাব লঞ্চ #Shorts হিন্দিতে শীর্ষ ৫টি ট্রেন্ডিং গিটহাব রিপো - প্রতিটি নম্বর আজ চেক করা হয়েছে। এই সপ্তাহের শীর্ষ ট্রেন্ডিং রিপো, সম্মিলিতভাবে ৩৫৬ হাজারেরও বেশি স্টার: ১. NVIDIA/OpenShell (১৮ হাজার স্টার) - OpenShell হলো স্বয়ংক্রিয় AI এজেন্টদের জন্য একটি নিরাপদ, প্রাইভেট রানটাইম। ২. reason-machines/reason-network (১ হাজার স্টার) - Reason Network: আপনার দলের কোডিং এজেন্ট, যারা একে অপরের সাথে কথা বলে। `reason network`-এর পেছনের ইঞ্জিন। ৩. firecrawl/firecrawl (১৯৪ হাজার স্টার) - ওয়েব এবং অন্যান্য উৎস থেকে পাওয়া ডেটা দিয়ে আপনার AI এজেন্টদের সুপারচার্জ করুন। সুপার ইন্টেলিজেন্সের জন্য লাইব্রেরি তৈরি করা হচ্ছে। 🔥 ৪. colinhacks/reylo (৬৫৫ স্টার) - সম্পূর্ণ টাইপ ইনফারেন্স এবং জিরো কোডজেন সহ TypeScript-এ .sql ফাইল ইম্পোর্ট করুন। 5. Shubhamsaboo/awesome-llm-apps (143k তারকা) - 100+ AI এজেন্ট, এজেন্ট দক্ষতা এবং RAG অ্যাপস - বিনামূল্যে এবং ওপেন সোর্স। রেপো লিঙ্ক: NVIDIA/OpenShell reason-machines/reason-network firecrawl/firecrawl colinhacks/reylo Shubhamsaboo/awesome-llm-apps মন্তব্য করুন "ভাইরাল" - সারা লিঙ্ক ডিএম মে ভেজ দুঙ্গা। কিসি দেব দোস্ত কো ভেজো জিসে ইয়ে চাহিয়ে। করলো বাঁচাও, বাদ মে কাম আয়েগা। নমন এআই - এআই অর দেব টুল, হিন্দি মে। হার দিন নয়া রেপো, হার নম্বর যাচাই করা হয়েছে। #শর্টস #গিটহাব #এআই #ওপেনসোর্স #টেকহিন্দি [গিটহাব ট্রেন্ডিং রিপো, সেরা গিটহাব রিপোজিটরি ২০২৬, সেরা ৫টি গিটহাব রিপো, নতুনদের জন্য ওপেন সোর্স প্রজেক্ট, এআই কোডিং এজেন্ট, গিটহাব স্টারস] [হিন্দিতে কোডিং, হিন্দি টেক শর্টস, নতুনদের জন্য প্রোগ্রামিং, ডেভেলপার টুলস ২০২৬, ডেভেলপারদের জন্য এআই টুলস, বিনামূল্যে কোডিং শিখুন]
3. firecrawl/firecrawl Lo apuntas a un sitio y recorre todas las páginas automáticamente, ejecuta JavaScript, y te devuelve datos estructurados listos para tu IA. 130k+ estrellas. El motor silencioso detrás de muchas startups de IA. Completamente open source.
Introducing Firecrawl Struggling to gather data from the web for your AI applications? Firecrawl is an open-source tool that makes web scraping and data extraction easy. It handles complex tasks like rotating proxies with a single command, saving you time and effort in building AI solutions. #firecrawl #ai #webscraping #opensource #dataextraction Follow for more AI, automation, and open-source tools you can actually use. Link: firecrawl/firecrawl [ar] تعرّف على Firecrawl هل تواجه صعوبة في جمع البيانات من الإنترنت لتطبيقات الذكاء الاصطناعي؟ Firecrawl أداة مفتوحة المصدر تُسهّل عملية استخراج البيانات من مواقع الويب. فهي تُنجز مهامًا معقدة، مثل تغيير الخوادم الوكيلة، بأمر واحد، مما يوفر عليك الوقت والجهد في بناء حلول الذكاء الاصطناعي. #firecrawl #ai #webscraping #opensource #dataextraction تابعنا للمزيد من أدوات الذكاء الاصطناعي والأتمتة والأدوات مفتوحة المصدر التي يمكنك استخدامها فعليًا. الرابط: firecrawl/firecrawl [bn] ফায়ারক্রল (Firecrawl) পরিচিতি আপনার AI অ্যাপ্লিকেশনের জন্য ওয়েব থেকে ডেটা সংগ্রহ করতে হিমশিম খাচ্ছেন? ফায়ারক্রল (Firecrawl) একটি ওপেন-সোর্স টুল যা ওয়েব স্ক্র্যাপিং এবং ডেটা এক্সট্র্যাকশনকে সহজ করে তোলে। এটি একটিমাত্র কমান্ডের মাধ্যমে প্রক্সি ঘোরানোর (rotating proxys) মতো জটিল কাজগুলো সামলে নেয়, যা AI সলিউশন তৈরিতে আপনার সময় ও শ্রম বাঁচায়। #firecrawl #ai #webscraping #opensource #dataextraction আরও AI, অটোমেশন এবং ওপেন-সোর্স টুলের জন্য ফলো করুন যা আপনি সত্যিই ব্যবহার করতে পারবেন। লিঙ্ক: firecrawl/firecrawl [de-DE] Wir stellen vor: Firecrawl Haben Sie Schwierigkeiten, Daten aus dem Web für Ihre KI-Anwendungen zu sammeln? Firecrawl ist ein Open-Source-Tool, das Web-Scraping und Datenextraktion vereinfacht. Es erledigt komplexe Aufgaben wie das Rotieren von Proxys mit nur einem Befehl und spart Ihnen so Zeit und Aufwand bei der Entwicklung von KI-Lösungen. #firecrawl #ai #webscraping #opensource #dataextraction Folgen Sie uns für weitere KI-, Automatisierungs- und Open-Source-Tools, die Sie tatsächlich nutzen können. Link: firecrawl/firecrawl [es-US] Presentando Firecrawl ¿Te cuesta recopilar datos de la web para tus aplicaciones de IA? Firecrawl es una herramienta de código abierto que facilita el web scraping y la extracción de datos. Gestiona tareas complejas como la rotación de proxies con un solo comando, ahorrándote tiempo y esfuerzo en el desarrollo de soluciones de IA. #firecrawl #ia #webscraping #opensource #dataextraction Síguenos para descubrir más herramientas de IA, automatización y código abierto que puedes usar. Enlace: firecrawl/firecrawl [fr-FR] Présentation de Firecrawl Vous avez du mal à collecter des données web pour vos applications d'IA ? Firecrawl est un outil open source qui simplifie le web scraping et l'extraction de données. Il gère des tâches complexes comme la rotation des proxys en une seule commande, vous faisant ainsi gagner du temps et de l'énergie dans le développement de vos solutions d'IA. #firecrawl #ai #webscraping #opensource #dataextraction Suivez-nous pour découvrir d'autres outils d'IA, d'automatisation et open source vraiment utiles. Lien : firecrawl/firecrawl [hi] Firecrawl का परिचय क्या आप अपने AI अनुप्रयोगों के लिए वेब से डेटा एकत्र करने में कठिनाई का सामना कर रहे हैं? फायरक्रॉल एक ओपन-सोर्स टूल है जो वेब स्क्रैपिंग और डेटा एक्सट्रैक्शन को आसान बनाता है। यह प्रॉक्सी रोटेट करने जैसे जटिल कार्यों को एक ही कमांड से संभाल लेता है, जिससे AI समाधान बनाने में आपका समय और मेहनत बचती है। #firecrawl #ai #webscraping #opensource #dataextraction उपयोग में आने वाले अन्य AI, ऑटोमेशन और ओपन-सोर्स टूल्स के लिए हमें फॉलो करें। लिंक: firecrawl/firecrawl [id] Memperkenalkan Firecrawl Kesulitan mengumpulkan data dari web untuk aplikasi AI Anda? Firecrawl adalah alat sumber terbuka yang memudahkan web scraping dan ekstraksi data. Alat ini menangani tugas-tugas kompleks seperti rotasi proxy hanya dengan satu perintah, menghemat waktu dan tenaga Anda dalam membangun solusi AI. #firecrawl #ai #webscraping #opensource #dataextraction Ikuti untuk mendapatkan lebih banyak alat AI, otomatisasi, dan sumber terbuka yang benar-benar dapat Anda gunakan. Tautan: firecrawl/firecrawl [it] Presentazione di Firecrawl Hai difficoltà a raccogliere dati dal web per le tue applicazioni di intelligenza artificiale? Firecrawl è uno strumento open source che semplifica il web scraping e l'estrazione dei dati. Gestisce attività complesse come la rotazione dei proxy con un singolo comando, facendoti risparmiare tempo e fatica nella creazione di soluzioni di IA. #firecrawl #ai #webscraping #opensource #dataextraction Seguici per scoprire altri strumenti open source per l'IA, l'automazione e l'utilizzo concreto. Link: firecrawl/firecrawl [iw] הכירו את Firecrawl מתקשים לאסוף נתונים מהאינטרנט עבור יישומי הבינה המלאכותית שלכם? Firecrawl הוא כלי קוד פתוח שהופך את גירוד וחילוץ הנתונים לקל. הוא מטפל במשימות מורכבות כמו סיבוב פרוקסי בפקודה אחת, וחוסך לכם זמן ומאמץ בבניית פתרונות בינה מלאכותית. #firecrawl #ai #גירוד_אתרים #קוד_פתוח #חילוץ_נתונים עקבו אחרינו לעוד כלים של בינה מלאכותית, אוטומציה וקוד פתוח שתוכלו להשתמש בהם בפועל. קישור: firecrawl/firecrawl [ja] Firecrawlとは AIアプリケーション用のWebデータ収集にお困りですか？Firecrawlは、Webスクレイピングとデータ抽出を容易にするオープンソースツールです。プロキシのローテーションといった複雑なタスクも、たった1つのコマンドで処理できるため、AIソリューション構築にかかる時間と労力を大幅に節約できます。 #firecrawl #ai #webscraping #opensource #dataextraction AI、自動化、そして実際に使えるオープンソースツールをもっと知りたい方は、ぜひフォローしてください。 リンク： firecrawl/firecrawl [ko] Firecrawl 소개 AI 애플리케이션에 필요한 웹 데이터 수집에 어려움을 겪고 계신가요? Firecrawl은 웹 스크래핑 및 데이터 추출을 간편하게 해주는 오픈 소스 도구입니다. 프록시 변경과 같은 복잡한 작업도 단 한 번의 명령으로 처리하여 AI 솔루션 개발에 드는 시간과 노력을 절약해 줍니다. #firecrawl #ai #webscraping #opensource #dataextraction 더 많은 AI, 자동화 및 실제로 사용할 수 있는 오픈 소스 도구를 보려면 팔로우하세요. 링크: firecrawl/firecrawl [ml] ഫയർക്രോൾ (Firecrawl) പരിചയപ്പെടുത്തുന്നു നിങ്ങളുടെ AI ആപ്ലിക്കേഷനുകൾക്കായി വെബിൽ നിന്ന് ഡാറ്റ ശേഖരിക്കാൻ പാടുപെടുകയാണോ? വെബ് സ്ക്രാപ്പിംഗും ഡാറ്റ എക്സ്ട്രാക്ഷനും എളുപ്പമാക്കുന്ന ഒരു ഓപ്പൺ സോഴ്സ് ഉപകരണമാണ് ഫയർക്രാൾ. ഒരൊറ്റ കമാൻഡ് ഉപയോഗിച്ച് പ്രോക്സികൾ റൊട്ടേറ്റ് ചെയ്യുന്നത് പോലുള്ള സങ്കീർണ്ണമായ ജോലികൾ ഇത് കൈകാര്യം ചെയ്യുന്നു, AI പരിഹാരങ്ങൾ നിർമ്മിക്കുന്നതിൽ നിങ്ങളുടെ സമയവും പരിശ്രമവും ലാഭിക്കുന്നു. #firecrawl #ai #webscraping #opensource #dataextraction നിങ്ങൾക്ക് യഥാർത്ഥത്തിൽ ഉപയോഗിക്കാൻ കഴിയുന്ന കൂടുതൽ AI, ഓട്ടോമേഷൻ, ഓപ്പൺ സോഴ്സ് ഉപകരണങ്ങൾക്കായി പിന്തുടരുക. ലിങ്ക്: firecrawl/firecrawl [nl-NL] Maak kennis met Firecrawl Vind je het lastig om data van het web te verzamelen voor je AI-toepassingen? Firecrawl is een open-source tool die webscraping en data-extractie eenvoudig maakt. Het voert complexe taken zoals het roteren van proxy's uit met één commando, waardoor je tijd en moeite bespaart bij het bouwen van AI-oplossingen. #firecrawl #ai #webscraping #opensource #dataextraction Volg ons voor meer AI, automatisering en open-source tools die je daadwerkelijk kunt gebruiken. Link: firecrawl/firecrawl [pa] Firecrawl ਦੀ ਜਾਣ-ਪਛਾਣ ਕੀ ਤੁਸੀਂ ਆਪਣੀਆਂ AI ਐਪਲੀਕੇਸ਼ਨਾਂ ਲਈ ਵੈੱਬ ਤੋਂ ਡਾਟਾ ਇਕੱਠਾ ਕਰਨ ਲਈ ਸੰਘਰਸ਼ ਕਰ ਰਹੇ ਹੋ? ਫਾਇਰਕ੍ਰੌਲ ਇੱਕ ਓਪਨ-ਸੋਰਸ ਟੂਲ ਹੈ ਜੋ ਵੈੱਬ ਸਕ੍ਰੈਪਿੰਗ ਅਤੇ ਡੇਟਾ ਐਕਸਟਰੈਕਸ਼ਨ ਨੂੰ ਆਸਾਨ ਬਣਾਉਂਦਾ ਹੈ। ਇਹ ਇੱਕ ਸਿੰਗਲ ਕਮਾਂਡ ਨਾਲ ਪ੍ਰੌਕਸੀਆਂ ਨੂੰ ਘੁੰਮਾਉਣ ਵਰਗੇ ਗੁੰਝਲਦਾਰ ਕੰਮਾਂ ਨੂੰ ਸੰਭਾਲਦਾ ਹੈ, AI ਹੱਲ ਬਣਾਉਣ ਵਿੱਚ ਤੁਹਾਡਾ ਸਮਾਂ ਅਤੇ ਮਿਹਨਤ ਬਚਾਉਂਦਾ ਹੈ। #firecrawl #ai #webscraping #opensource #dataextraction ਹੋਰ AI, ਆਟੋਮੇਸ਼ਨ, ਅਤੇ ਓਪਨ-ਸੋਰਸ ਟੂਲਸ ਲਈ ਫਾਲੋ ਕਰੋ ਜੋ ਤੁਸੀਂ ਅਸਲ ਵਿੱਚ ਵਰਤ ਸਕਦੇ ਹੋ। ਲਿੰਕ: firecrawl/firecrawl [pl] Przedstawiamy Firecrawl Masz problemy z gromadzeniem danych z internetu na potrzeby swoich aplikacji AI? Firecrawl to narzędzie open source, które ułatwia scrapowanie i ekstrakcję danych z internetu. Obsługuje złożone zadania, takie jak rotacja serwerów proxy, za pomocą jednego polecenia, oszczędzając czas i wysiłek w budowaniu rozwiązań AI. #firecrawl #sztuczna inteligencja #webscraping #opensource #ekstrakcjadanych Obserwuj, aby dowiedzieć się więcej o AI, automatyzacji i narzędziach open source, z których możesz skorzystać. Link: firecrawl/firecrawl [pt-BR] Apresentando o Firecrawl Com dificuldades para coletar dados da web para suas aplicações de IA? O Firecrawl é uma ferramenta de código aberto que facilita a extração de dados e o web scraping. Ele lida com tarefas complexas, como a rotação de proxies, com um único comando, economizando tempo e esforço na criação de soluções de IA. #firecrawl #ai #webscraping #opensource #dataextraction Siga para mais ferramentas de IA, automação e código aberto que você pode usar na prática. Link: firecrawl/firecrawl [ru] Знакомство с Firecrawl Возникают трудности со сбором данных из интернета для ваших приложений ИИ? Firecrawl — это инструмент с открытым исходным кодом, который упрощает веб-скрейпинг и извлечение данных. Он справляется со сложными задачами, такими как ротация прокси-серверов, с помощью одной команды, экономя ваше время и усилия при создании решений на основе ИИ. #firecrawl #ai #webscraping #opensource #dataextraction Подписывайтесь, чтобы узнать больше об ИИ, автоматизации и инструментах с открытым исходным кодом, которые вы действительно можете использовать. Ссылка: firecrawl/firecrawl [ta] Firecrawl-ஐ அறிமுகப்படுத்துகிறோம் உங்கள் AI பயன்பாடுகளுக்காக இணையத்திலிருந்து தரவுகளைச் சேகரிப்பதில் சிரமப்படுகிறீர்களா? ஃபயர்கிரால் (Firecrawl) என்பது இணைய வழித் தரவுச் சேகரிப்பையும் (web scraping) தரவுப் பிரித்தெடுப்பையும் (data extraction) எளிதாக்கும் ஒரு திறந்த மூலக் கருவியாகும். இது ப்ராக்ஸிகளை (proxies) சுழற்றுவது போன்ற சிக்கலான பணிகளை ஒரே கட்டளையில் கையாள்வதன் மூலம், AI தீர்வுகளை உருவாக்குவதில் உங்கள் நேரத்தையும் உழைப்பையும் மிச்சப்படுத்துகிறது. #firecrawl #ai #webscraping #opensource #dataextraction நீங்கள் உண்மையில் பயன்படுத்தக்கூடிய மேலும் பல AI, ஆட்டோமேஷன் மற்றும் திறந்த மூலக் கருவிகளுக்குப் பின்தொடரவும். இணைப்பு: firecrawl/firecrawl [te] Firecrawl పరిచయం మీ AI అప్లికేషన్ల కోసం వెబ్ నుండి డేటాను సేకరించడంలో ఇబ్బంది పడుతున్నారా? ఫైర్క్రాల్ అనేది వెబ్ స్క్రాపింగ్ మరియు డేటా సంగ్రహణను సులభతరం చేసే ఒక ఓపెన్-సోర్స్ సాధనం. ఇది ప్రాక్సీలను మార్చడం వంటి సంక్లిష్టమైన పనులను ఒకే ఆదేశంతో నిర్వహిస్తుంది, తద్వారా AI పరిష్కారాలను రూపొందించడంలో మీ సమయాన్ని మరియు శ్రమను ఆదా చేస్తుంది. #ఫైర్క్రాల్ #ఏఐ #వెబ్స్క్రాపింగ్ #ఓపెన్సోర్స్ #డేటాసంగ్రహణ మీరు నిజంగా ఉపయోగించగల మరిన్ని AI, ఆటోమేషన్ మరియు ఓపెన్-సోర్స్ సాధనాల కోసం అనుసరించండి. లింక్: firecrawl/firecrawl [uk] Знайомство з Firecrawl Важко збирати дані з Інтернету для ваших ШІ-додатків? Firecrawl — це інструмент з відкритим кодом, який спрощує веб-скрейпінг та вилучення даних. Він обробляє складні завдання, такі як ротація проксі-серверів, за допомогою однієї команди, заощаджуючи ваш час та зусилля під час створення ШІ-рішень. #firecrawl #ai #webscraping #opensource #dataextraction Підпишіться, щоб дізнатися більше про ШІ, автоматизацію та інструменти з відкритим кодом, які ви можете використовувати. Посилання: firecrawl/firecrawl
Крутой открытый софт: Firecrawl превращает любой firecrawl/firecrawl в чистый Markdown для AI-агентов, JS и капчи под капотом. Разбор в Telegram: t.me #софт #ai #opensource #нейросети #разработка
Awesome open-source AI: Firecrawl turns any firecrawl/firecrawl into clean Markdown for AI agents, handling JS and captchas. Full setup & guide in Telegram: t.me #ai #tech #opensource #coding #devtools #automation
firecrawl: The Hottest TypeScript Repo on GitHub Right Now In this video, we break down firecrawl/firecrawl - one of the hottest open-source projects on GitHub right now. Supercharge your AI agents with data from the web and beyond. Building the library for superintelligence. 🔥. It has already earned 192,943 stars on GitHub and is written primarily in TypeScript. We look at what it does, why developers are paying attention to it right now, and who should try it. 📂 Repo: firecrawl/firecrawl 🌐 Stars: 192,943 | Language: TypeScript | Forks: 10,188 🔔 Subscribe for daily picks of the hottest GitHub repos: / @reporadar #github #opensource #programming keywords: coding, developer tools, github, opensource, programming, software, tech