Building a Self-Learning AI Agent for Static Websites

The Problem

Clients often want a chatbot that "knows" their business. The standard way is to upload PDFs or manually enter FAQs into OpenAI assistants. This is tedious and quickly becomes outdated when the website changes.

The Solution: "Self-Scraper" Agent

We built a lightweight Python agent that treats the website itself as the source of truth.

• Autonomous Scraping: The agent crawls the client's sitemap.xml to find all public pages.
• Content Chunking: It extracts text from `p`, `h1`, `h2` tags and chunks them into logical segments.
• Instant Answers: When a user asks "What is your pricing?", the agent retrieves the exact paragraph from the Pricing page and cites the source link.

How It Works (Code Snippet)

Here is a simplified look at the Python logic used to crawl the static content:

import requests
from bs4 import BeautifulSoup

def scrape_site(url):
    response = requests.get(url)
    soup = BeautifulSoup(response.text, 'html.parser')
    
    # Extract only meaningful content
    content_chunks = []
    for tag in soup.find_all(['h1', 'h2', 'p']):
        if len(tag.get_text()) > 50: # Ignore navigation/footers
            content_chunks.append({
                "text": tag.get_text().strip(),
                "source": url
            })
            
    return content_chunks

The Result

A "Drop-in" AI widget. Add 3 lines of JavaScript to your header, and your website suddenly has a smart concierge that knows your latest pricing, contact info, and history—automatically.