AgentQL
Overview of AgentQL
AgentQL: Connecting LLMs and AI Agents to the Web
AgentQL by TinyFish is a suite of tools designed to connect Large Language Models (LLMs) and AI agents to the entire web. It offers a query language and parser for interacting with web elements and extracting data quickly, precisely, and at scale. AgentQL aims to make web data accessible and actionable for AI applications.
What is AgentQL?
AgentQL is a tool that allows developers to use natural language queries to extract data from websites. It provides a robust alternative to traditional methods like XPath and CSS selectors, which can be fragile and difficult to maintain. AgentQL leverages AI to analyze the page structure and find the desired data, even in dynamic content or when the page structure changes.
How does AgentQL work?
AgentQL uses a combination of techniques to extract data from websites:
- AI-powered analysis: AgentQL analyzes the structure of the web page using AI to understand its layout and identify the relevant elements.
- Natural language queries: Developers can use natural language to describe the data they want to extract.
- Versatile SDK: AgentQL provides SDKs in Python and JavaScript for interacting with web page elements via Playwright and headless browsers.
- Browser-based debugger: A browser extension allows developers to optimize queries in real time on any web page.
- REST API: A REST API allows developers to retrieve public-facing data from any URL without requiring a browser.
- PDF parsing: AgentQL can parse difficult information like tables from PDFs.
Key Features and Benefits of AgentQL
- Natural Language Queries: Describe the data you need without complex code.
- Structured Data: Define the shape of your data with your query for consistent results.
- Self-Healing: Get consistent results even with dynamic content and page changes.
- Reusable Code: Use the same query across multiple similar pages.
- Browserless API: Retrieve data from any URL without a browser.
- PDF Parsing: Extract data from PDFs, including tables.
Who is AgentQL for?
AgentQL is designed for developers, data scientists, and AI engineers who need to extract data from the web for various applications, including:
- E-commerce: Extract product information, prices, and reviews.
- Job boards: Collect job postings and candidate information.
- Social media: Gather social media data for analysis.
- Data workflows: Automate data extraction tasks.
- Web automation: Build web automation pipelines.
How to use AgentQL?
- Sign up: Sign up for a free trial to get started with AgentQL.
- Explore the Playground: Use the AgentQL Playground to experiment with queries and see how AgentQL works.
- Integrate: Integrate AgentQL into your projects using the Python or JavaScript SDKs.
- Use the Browser Extension: Optimize your queries in real time with the browser extension.
Why choose AgentQL?
- Robustness: AgentQL is a robust alternative to fragile XPath and CSS selectors.
- Versatility: AgentQL can be used on any page, public or private, even behind authentication.
- Efficiency: AgentQL saves time by automating data extraction tasks.
- Ease of Use: AgentQL is easy to use, even for developers without extensive web scraping experience.
Integrations
AgentQL offers integrations that can elevate your projects. You can explore the documentation or contact them to learn more.
Pricing
AgentQL offers a variety of plans to fit your needs:
- Starter: Free, with 300 API calls, 10 API calls per minute, and 1 hour of remote browser time.
- Professional: $99/month, with 10,000 API calls, 50 API calls per minute, and 500 hours of remote browser time.
- Enterprise: Custom, with fully managed solutions for accessing data from websites and documents.
Customer Testimonials
- Vladimir de Turckheim, Founder of Heal.dev: "With AgentQL sending the query and getting the results is a gamechanger for text grounding."
- Fahd Mirza, AI YouTuber, Lead AI Engineer: "AgentQL handles web automation painlessly... It's awesome stuff — very easy to use and with very well-written responses."
- Reda Marzouk, AI/RPA Senior Developer: "Love the fact that we can describe the elements that we can work with, or we can just give a prompt and AgentQL will go to the websites and define the elements that it will have to deal with."
- Mahmoud Masmoudi, Data Engineer, Hove: "AgentQL has been a game-changer in my data extraction process! The ability to create reusable configurations across similar website layouts has saved me considerable time and effort"
AgentQL simplifies web automation and data extraction with AI-powered queries, making it an ideal solution for developers looking to streamline their data workflows.
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