AP

API to turn entire websites into Markdown

Hacker News

API to turn entire websites into Markdown

While building mendable - we found that feeding LLMs well-structured markdown improved accuracy. We also found it surprisingly hard. We found some great tools online, but none reliably handled the entire process. We wanted an API that took a URL, crawled the pages in the URL, and gave us an easy-to-use, up-to-date markdown we could feed into our index. So, we released an open-source repo and an API that crawls and turns entire websites into a markdown with just a few lines of code The API handles: - Crawling without consistent sitemaps - Infra to handle running many crawling jobs - Proxying, hosting headless browsers at scale - Conversion to clean markdown - Caching - Handling images, videos (soon), and tables(soon) - LLM extraction (soon) It is open source, and we also offer an easy-to-use API that starts free. It has built-in loaders for both @llama_index and @langchain. Excited to see people try it

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: code, open · Missing: mac, agents, macos
86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: excited, open source, llama · Missing: https docs, just released, exist
74%74% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: video · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: host, soon · Missing: plus, platform, intuitive
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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