Tutorial: guides & tutorials
Hands-on web scraping tutorials covering selectors, headless browsers, anti-bot, and Apify deployment for developers at every skill level.
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Connect YouTube to Chatbase: Timestamped Video Answers
Chatbase YouTube Connector is a free, MIT-licensed tool that keeps a Chatbase AI agent trained on your YouTube channel, so the agent answers customers from your videos and links to the exact minute it used. It runs as a scheduled GitHub Action or a Docker container on any VPS, with no server or database of its own. Transcripts come from an Apify Actor at about $1 per 1,000 videos, and a day with no new uploads costs $0. On Chatbase Standard and above it syncs through the API; on Free and Hobby it exports ready-to-upload files instead.
Here is what a customer sees once it is running:
Customer: How do I hand a chat over to a human? Agent: Turn on the Chatbase live chat action, then ... watch at 0:24
Build a Claude Skill for Web Scraping (Calls Apify Actors) (2026)
A Claude Skill is a SKILL.md folder that packages instructions Claude loads automatically when relevant. Build one that tells Claude to run Apify Actors for scraping, and every future "get me this web data" request just works. Or install the official Apify Claude Code plugin, which ships five ready-made skills.
Agent Skills are modular capabilities that extend Claude: each Skill packages instructions, metadata, and optional resources that Claude uses automatically when they are relevant to your request. Instead of re-explaining how you like to scrape every time, you encode it once, and Claude reaches for it on its own.
This guide builds a scraping skill that calls Apify, and points you at the official plugin if you would rather not start from scratch.
Scrape Websites into a Spreadsheet with Claude Cowork + Apify (2026)
Connect Apify's remote MCP server (https://mcp.apify.com) to Claude Cowork as a custom connector, then ask Cowork in plain language to scrape a site. Cowork picks the right Apify Actor, runs it, and hands you the data to export as a spreadsheet, no code.
Claude Cowork is Anthropic's "hand Claude real work" surface: it runs on the same agentic engine as Claude Code but with no terminal, so it can take on multi-step tasks and finish them for you. Cowork can already search the web and, with computer use, drive a browser a page at a time. What it has no answer for is bulk structured extraction: paginating a result grid, holding a schema across thousands of rows, rotating proxies, and surviving anti-bot defences. That is exactly what Apify adds: a store of pre-built scrapers Cowork can call as tools.
This guide connects the two and turns "get me this web data" into a spreadsheet, with no code.
How to Scrape Trustpilot Reviews with Apify (2026 Guide)
Scrape Trustpilot reviews with an Apify Trustpilot Actor: paste a company's Trustpilot URL (or its domain), set how many reviews and which star ratings you want, run the Actor, and export the ratings, review text, dates, and company replies as JSON or CSV. No coding required.
Trustpilot is where customers rate companies at scale, so its reviews are a goldmine for reputation monitoring, competitor benchmarking, and product research. The site's UI paginates and caps what you can see, and it has no export button, which is exactly the gap a scraper fills.
This guide covers no-code Trustpilot extraction on Apify: which Actor to pick, the input fields that matter, what it costs, and how to turn the review text into insight with an LLM.
How to Scrape Google Reviews with Apify (2026 Guide)
Scrape Google reviews with Apify's Google Maps Reviews Scraper: paste the business's Google Maps URL, set how many reviews you want, run the Actor, and download review text, ratings, dates, and owner replies as JSON or CSV. No coding required.
Google reviews are one of the richest public signals a business leaves behind: star ratings, written feedback, dates, and the owner's replies. Pulling them at scale lets you monitor reputation, track sentiment over time, and benchmark competitors, none of which the Google Maps UI lets you export.
This guide walks through no-code review extraction with the Apify Google Maps Reviews Scraper (used by more than 48,000 people), the input fields that matter, what it costs, and how to turn the raw text into insight with an LLM.
Chatbase API: Integration Guide for Developers
The Chatbase API lets your own backend work with a Chatbase AI agent: send messages and stream replies, read and search conversations, manage knowledge sources, create and answer Helpdesk tickets, and start real-time voice sessions. It requires the Standard plan or above: $150/month billed monthly, or $120/month billed annually ($1,440/year), with 4,000 message credits per month that API calls share with the chat widget. Free and Hobby workspaces get a 403. Prices verified on chatbase.co/pricing on 2026-10-04.
Prerequisite: a Standard (or higher) workspace. Compare Chatbase plans with API access, or read our Chatbase pricing breakdown first. Each reply costs credits based on the AI model the agent uses (see Best Practices).
Chatbase ships two REST API versions. API v1 is the original integration path; API v2 is a redesign with structured error codes, cursor-based pagination, Server-Sent Events (SSE) streaming, a cleaner response contract, and endpoints for agents, knowledge sources, the Helpdesk, and voice. This guide covers v2 only, since it is the forward path for new integrations in 2026. The agent you call is the same one you configure in the dashboard, with its knowledge, instructions, actions, and procedures.
How Developers Use Wispr Flow to Code and Communicate Faster
Wispr Flow won't write code for you. Say "write a function that fetches JSON from a URL" and it types those words literally — no code generation, no autocomplete. What it does is eliminate the friction of typing everything that surrounds your code: the comments, the commit messages, the PR descriptions, the Slack threads, the documentation, the emails.
For developers, that's a substantial portion of the workday. And dictating it is meaningfully faster than typing it.
This guide covers the practical ways developers use Wispr Flow, how to configure it for a technical workflow, and where it genuinely helps versus where you shouldn't expect it to.
RAG in Production: From Website Crawl to Vector Search That Actually Works (2026)
Many RAG (Retrieval-Augmented Generation) projects fail in production not because the technology doesn't work, but because teams skip the hard parts: chunking strategy, embedding model selection, retrieval quality measurement, and stale data management. Validate each step on your own corpus — field names, SDK versions, and Actor outputs change over time.
The pipeline: crawl websites → chunk intelligently → embed → store in vector DB → retrieve with reranking → generate answers with citations.
TL;DR:
| Stage | Tool | Key decisions |
|---|---|---|
| Crawl | Apify Website Content Crawler | Markdown output, max depth, content filtering |
| Chunk | LangChain RecursiveCharacterTextSplitter | ~2000 character chunks, ~200 overlap (~500 tokens/chunk at ~4 chars/token — tune for your content) |
| Embed | OpenAI text-embedding-3-small or local all-MiniLM-L6-v2 | Cost vs quality trade-off |
| Store | Qdrant or pgvector | Managed vs self-hosted |
| Retrieve | Dense vector search + Cohere rerank (sample below) | Top-k=20 candidates, rerank to top-5 — add BM25 / sparse hybrid in Qdrant if you need keyword-heavy queries |
| Generate | Claude Sonnet | With source citations |
Prerequisites:
- Python 3.10+ or Node.js 18+
- Apify account (sign up)
- Vector database (Qdrant Cloud free tier or self-hosted)
- LLM API key (Claude, GPT-4, or self-hosted Ollama)
Vibe Coding with Claude Code: Build and Ship a SaaS MVP in a Weekend
Andrej Karpathy coined "vibe coding" in early 2025 — the practice of describing what you want to an AI and letting it generate the code, barely reading the output, and just running it until it works. By April 2026, developers are using Claude Code to go from idea to deployed, revenue-ready SaaS MVP in days, not months.
This guide provides the practical framework: what actually works, what breaks, and the phase-by-phase approach that turns "vibes" into a product people pay for.
TL;DR:
| Phase | Time | What you ship |
|---|---|---|
| 1. Spec + CLAUDE.md | 2 hours | Architecture decision, tech stack, project structure |
| 2. Core features | 6–8 hours | Auth, database, API routes, basic UI |
| 3. AI features | 3–4 hours | Apify scraping + LLM processing |
| 4. Testing + deploy | 2–3 hours | Vercel/Railway deployment, domain, SSL |
| 5. Marketing page | 2 hours | Landing page with value prop and signup |
| Total | 15–19 hours | Deployed MVP with AI features |
Prerequisites:
- Claude Code installed with Claude Pro ($20/mo) or Max ($100/mo)
- GitHub account
- Vercel account (free tier)
- Supabase account (free tier)
- Comfortable reading and editing code (TypeScript/JavaScript), working with CLI tools, and following API documentation. You don't need to write complex algorithms from scratch — Claude Code handles most generation — but you should be able to review and adjust the code it produces.











