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AgentQL is an AI-powered query language for web scraping and automation. It uses natural language selectors to find data on any page, including authenticated content. AgentQL queries are self-healing as UI changes and work across similar sites. Users can define structured data output, making AgentQL versatile for developers and data scientists.

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tinyfish-io/agentql

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A repository to house AgentQL Examples and tutorials

Steps to Get Started with AgentQL:

  1. Setup your python virtual environment

  2. Install Agentql in the virtual env

  3. Setup the AGENTQL_API_KEY environment variable with your API Key

  4. Navigate to the script (example) of your interest and use that code to test or build on top of it.

  5. Run the script and experience AgentQL's amazing capabilities.

Topic Example Name URL
Customizing Web Driver customizing_web_driver.py customizing_web_driver.py
Login to a website login.py login.py
Leveraging Async capabilities async_example.py async_example.py
Headless browser usage headless_browser.py headless_browser.py
to_data() method for working with data levaraging_to_data_method.py levaraging_to_data_method.py
Generalized query across sites same_query_across_sites.py same_query_across_sites.py
Save and reuse logged in state save_and_load_context.py save_and_load_context.py
Waiting for page to load wait_for_entire_page_load.py wait_for_entire_page_load.py
Default Popup Handler default_popup_handler.py default_popup_handler.py
Leveraging List Query list_query_usage.py list_query_usage.py

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AgentQL is an AI-powered query language for web scraping and automation. It uses natural language selectors to find data on any page, including authenticated content. AgentQL queries are self-healing as UI changes and work across similar sites. Users can define structured data output, making AgentQL versatile for developers and data scientists.

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