interactive-browser-use is an open-source AI Agent framework that integrates large language models with browser automation tools like Playwright. It enables automated navigation, content extraction, form filling, and interactive browsing via natural language prompts. Developers can customize sequences of browsing actions, automate data collection tasks, test web workflows, and perform dynamic content queries, all through simple integration with LLM APIs.
AI Platforms & Frameworks
Web Tools
Workflow Automation
#browser automation
#Web Scraping
#AI interaction
#data extraction
#dynamic content access
#Automated testing
#custom prompts
#live data collection
#web page navigation
#form filling
#LLM Integration
#programmatic browsing
#real-time web tasks
#interactive web actions
#multi-step workflows
#user-friendly automation
#Python JavaScript library
#Reduce Manual Effort
#AI Agents
#Content Management
...
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interactive-browser-use
interactive-browser-use is an open-source AI Agent framework that integrates large language models with browser automation tools like Playwright. It enables automated navigation, content extraction, form filling, and interactive browsing via natural language prompts. Developers can customize sequences of browsing actions, automate data collection tasks, test web workflows, and perform dynamic content queries, all through simple integration with LLM APIs.
AI Platforms & Frameworks
Web Tools
Workflow Automation
#browser automation
#Web Scraping
#AI interaction
#data extraction
#dynamic content access
#Automated testing
#custom prompts
#live data collection
#web page navigation
#form filling
#LLM Integration
#programmatic browsing
#real-time web tasks
#interactive web actions
#multi-step workflows
#user-friendly automation
#Python JavaScript library
#Reduce Manual Effort
#AI Agents
#Content Management
...
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What is interactive-browser-use?
interactive-browser-use is a Python/JavaScript library that connects large language models (LLMs) with browser automation frameworks like Playwright or Puppeteer, allowing AI Agents to perform real-time web interactions. By defining prompts, users can instruct the agent to navigate web pages, click buttons, fill forms, extract tables, and scroll through dynamic content. The library manages browser sessions, context, and action execution, translating LLM responses into usable automation steps. It simplifies tasks like live web scraping, automated testing, and web-based Q&A by providing a programmable interface for AI-driven browsing, reducing manual effort while enabling complex multi-step web workflows.
Who will use interactive-browser-use?
- AI developers
- Data engineers
- Automation QA testers
- Research engineers
How to use the interactive-browser-use?
- Step1: Clone the repository from GitHub
- Step2: Install dependencies (pip install or npm install)
- Step3: Configure your LLM API keys and browser drivers
- Step4: Run the example script to launch the interactive browser
- Step5: Customize prompts and action handlers for your tasks
Platform
- mac
- windows
- linux
interactive-browser-use's Core Features & Benefits
The Core Features
- LLM-driven browser automation
- Website navigation and control
- Content scraping and data extraction
- Form filling and interactive actions
- Customizable action prompts
The Benefits
- Accelerates web data collection
- Enables dynamic content access
- Reduces manual browsing tasks
- Highly customizable and extensible
- Seamless integration with LLMs
interactive-browser-use's Main Use Cases & Applications
- Real-time web scraping with AI
- Automated end-to-end web testing
- Dynamic content Q&A on live sites
- Form automation and data entry
FAQs of interactive-browser-use
interactive-browser-use Company Information
- Cofounder Labs
interactive-browser-use Reviews
5/5
interactive-browser-use's Main Competitors and alternatives?
- LangChain Agents
- Agentic Playground
- AutoGen
- AgentGPT
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