
LangChain v0.3 Tutorial & Migration Guide for 2026
Learn what’s new in LangChain v0.3 and how to migrate: Runnables, new agents, tools, middleware, MCP, and testing patterns for modern AI agents in Python.
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Discover the latest tutorials, guides, and updates about web scraping, API development, and AI-powered search.

Learn what’s new in LangChain v0.3 and how to migrate: Runnables, new agents, tools, middleware, MCP, and testing patterns for modern AI agents in Python.

Sixteen gigabytes of memory is the current sweet spot for developers exploring local large language models. With this capacity, you can efficiently run 7B to 14B parameter models using modern quantization techniques—delivering near-cloud performance while keeping your data on-premise. Whether you're...

OpenClaw’s skills system makes it easy to plug in powerful web search capabilities directly into your AI agents. This guide shows you how to install a Crawleo-powered search skill, wire it up with your API key, and start running live web queries from inside OpenClaw in just a few minutes.

Choosing between Perplexity's Sonar API and Crawleo for your AI application? This in-depth comparison breaks down pricing, features, privacy, and scalability to help you pick the right search API for your next project.

Choosing the right web data source is critical for AI apps, search products, and automation workflows. This guide compares Brave Search API and Crawleo side-by-side, explaining how they differ in search data, crawling flexibility, and developer use cases so you can pick the best tool for your project.

Looking for a reliable web scraping API for LLM training data or RAG workflows? Discover how Crawleo delivers clean, real-time, privacy-first web data optimized for AI pipelines, without the complexity of traditional scraping infrastructure.

Learn how to crawl Android freelancer job listings using Beautiful Soup in Python. This guide explains the structure behind a real crawling script and how to scale job data extraction across multiple pages.

Training modern large language models requires massive, continuously updated datasets sourced from the open web. This guide explains how AI teams can build scalable, high quality LLM training datasets using web crawling, with practical architecture patterns and best practices.

Building your own web scraping stack seems simple at first, until rate limits, proxy bans, and CAPTCHAs bring everything to a halt. This article explains why DIY scraping fails at scale and how Crawleo removes these hidden costs for developers and AI teams.

Learn how to bridge the gap between internal company knowledge and the live web. This guide explores a powerful pattern for building AI agents that can query private handbooks while simultaneously performing filtered real-time web searches to provide the most accurate, cited responses.

Search engines power most modern applications, but accessing their data reliably is not always straightforward. This article compares common ways developers work with search engine data and explains where Crawleo fits in a modern, AI-focused stack.

Building an AI agent or RAG pipeline? Learn the critical difference between Crawleo (data acquisition) and OpenAI Embeddings (data representation). Discover how these two tools work together to power semantic search and live web retrieval.