Pydantic AI
Web Scraping Agent with Pydantic AI
Build an intelligent web scraping agent that fetches pages, extracts structured data, and handles pagination — powered by Pydantic AI.
web scrapingdata extractionHTTPparsing
Working Code
from pydantic_ai import Agent, RunContext
agent = Agent( "openai:gpt-4o", system_prompt="You are a web scraping agent. Fetch pages, extract the requested data, and return it in structured format. Respect robots.txt.",)
@agent.toolasync def fetch_url(ctx: RunContext, url: str) -> str: """Fetch a webpage and return its content as markdown.""" import httpx from markdownify import markdownify async with httpx.AsyncClient() as client: response = await client.get(url, headers={"User-Agent": "Mozilla/5.0"}, timeout=15) return markdownify(response.text)[:5000]
@agent.toolasync def extract_data(ctx: RunContext, text: str, instruction: str) -> str: """Extract structured data from text based on instruction.""" return f"Extracting from {len(text)} chars: {instruction}"
result = await agent.run("Scrape the pricing page at example.com/pricing and extract all plan names and prices")print(result.output)Step by Step
1
Install dependencies
Install Pydantic AI and the required tools for this use case.
2
Define your tools
Create the domain-specific tool functions your agent will use to interact with external services.
3
Create the agent and run
Initialize the Pydantic AI agent with your tools, set the system prompt, and execute a query.
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