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Create AI-Ready Vector Datasets from Web Content with Claude, Ollama & Qdrant

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AI-Powered Web Data Pipeline with n8n

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How It Works

This n8n workflow builds an AI-powered web data pipeline that automates the entire process of:

  • Extraction
  • Structuring
  • Vectorization
  • Storage

It integrates multiple advanced tools to transform messy web pages into clean, searchable vector databases.

Integrated Tools

  • Scrapeless
    Bypasses JavaScript-heavy websites and anti-bot protections to reliably extract HTML content.

  • Claude AI
    Uses LLMs to analyze unstructured HTML and generate clean, structured JSON data.

  • Ollama Embeddings
    Generates local vector embeddings from structured text using the all-minilm model.

  • Qdrant Vector DB
    Stores semantic vector data for fast and meaningful search capabilities.

  • Webhook Notifications
    Sends real-time updates when workflows complete or errors occur.

From messy webpages to structured vector data — this pipeline is perfect for building intelligent agents, knowledge bases, or research automation tools.


Setup Steps

1. Install n8n

Requires Node.js v18 / v20 / v22

npm install -g n8n
n8n

After installation, access the n8n interface via:

URL: http://localhost:5678


2. Set Up Scrapeless

  1. Register at: Scrapeless
  2. Copy your API token
  3. Paste the token into the HTTP Request node labeled "Scrapeless Web Request"

3. Set Up Claude API (Anthropic)

  1. Sign up at Anthropic Console
  2. Generate your Claude API key
  3. Add the API key to the following nodes:
    • Claude Extractor
    • AI Data Checker
    • Claude AI Agent

4. Install and Run Ollama

macOS

brew install ollama

Linux

curl -fsSL https://ollama.com/install.sh | sh

Windows
Download the installer from: https://ollama.com

Start Ollama Server

ollama serve

Pull Embedding Model

ollama pull all-minilm

5. Install Qdrant (via Docker)

docker pull qdrant/qdrant

docker run -d \
  --name qdrant-server \
  -p 6333:6333 -p 6334:6334 \
  -v $(pwd)/qdrant_storage:/qdrant/storage \
  qdrant/qdrant

Test if Qdrant is running:

curl http://localhost:6333/healthz

6. Configure the n8n Workflow

  • Modify the Trigger (Manual or Scheduled)

  • Input your Target URLs and Collection Name in the designated nodes

  • Paste all required API Tokens / Keys into their corresponding nodes

  • Ensure your Qdrant and Ollama services are running

Ideal Use Cases

  • Custom AI Chatbots

  • Private Search Engines

  • Research Tools

  • Internal Knowledge Bases

  • Content Monitoring Pipelines