13 web scraping tools every dev should know, from Requests + Beautiful Soup to Scrapy, Playwright & Apify. Which one’s your go-to? 💬

Your team has answered this before. I’m building a tool that remembers.

I built a tool to help with community support. Then I kept building. I spend a good part of my day working with the community at CopilotKit, answering questions in Discord, GitHub, and Slack, helping…

• answerLoops consolidates community support questions from GitHub, Discord, and Slack.
• Knowledge base populated via direct entry, documentation import, file upload, or syncing files.
• Resolved tickets can be turned into knowledge-base articles with Promote to KB action.

5h ago ·dev.to

CodeDrill: Master Java Collections and DSA Through Deliberate Practice 🧠💻

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady . What I Built Meet CodeDrill — a deep learning and practice platform designed to help developers go beyond…

• CodeDrill platform enhances Java Collections and DSA understanding through deliberate practice.
• Focuses on Java Collections internals and structured DSA practice with spaced repetition.
• Open architecture and learning resources designed for community contributions and adaptability.

5h ago ·dev.to

Vector API Metadata Filter Support: Safer Per-Customer Logistics Search

Treat query-time metadata filtering as an admission-control boundary for a shared vector collection. For an internal logistics knowledge bot, every chunk must receive an immutable customer identifier…

5h ago ·dev.to

Shoebox: a small model reads your receipts overnight, slowly, and never guesses a number

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 3: Slow and Steady What I Built Receipts are the paperwork nobody does on time.

• Shoebox is an open-source AI model for processing receipts overnight.
• The model examines each receipt photo one at a time on your computer.
• Shoebox confirms receipt totals and files them with date, shop name, and amount.

5h ago ·dev.to

Tokenization is why your agent bill looks weird

Models don't read text. They read integers. Between your string and the model there's a tokenizer, and it quietly decides how much you pay, how much fits in the context window, and why your model is…

• Tokenization divides strings into vocabulary pieces from 30k-200k entries
• Byte Pair Encoding (BPE) merges frequent character pairs into new symbols
• Hindi tokenization differs significantly from other languages, using 24 tokens vs 111

5h ago ·dev.to

The KV cache is eating your GPU. MQA and GQA are how models fight back

Quick recap from the last post: the KV cache saves you from recomputing old tokens, and it's the reason generation is fast. But it has a bill. And the bill is memory.

• KV cache consumes 512 KB per token for Llama-2 7B
• MQA reduces memory usage by 32x compared to traditional MHA
• GQA balances MQA and MHA, reducing cache size by 4x

5h ago ·dev.to