browser-use and Deepseek R1 advanced, automated SEO agent analysis Python script

Automated AI Agenct SEO Crawler with browser-use and DeepSeek R1

This project demonstrates how to use an AI-powered browser-use agent to analyze and suggest semantic improvements for a webpage. The script uses the langchain_openai library with the ChatOpenAI model and is designed to interact with and extract insights from web pages for semantic content optimization.

Features

• browser-use: Open-source AI operator, using Chromium.
• Semantic Analysis: Automatically analyzes a webpage's content for semantic placements.
• Content Extraction: Extracts current semantic content placements.
• Suggestions: Provides recommendations for missing long-tail queries.
• Task Automation: Fully automated using asyncio and an AI agent.

Prerequisites

Ensure you have the following installed and configured:

• Python 3.9+
• browser-use library
• langchain_openai library
• dotenv library
• pydantic library

You also need an API key for DeepSeek, which should be stored in an .env file. Check browser-use documentation here: https://github.com/browser-use/browser-use

Installation

1. Clone the repository:

   git clone https://github.com/metehan777/deepseek-r1-browser-use-seo-analysis.git
   cd deepseek-r1-browser-use-seo-analysis
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Set up your .env file:

   Create a file named .env in the root directory of the project and add your DeepSeek API key:

   DEEPSEEK_API_KEY=your_deepseek_api_key
   

Usage

Run the script to analyze the webpage and save the results to output.txt:

python ai_seo_crawler.py

The script performs the following tasks:

1. Navigates to AppSamurai.
2. Analyzes the page for the best semantic placements of content.
3. Extracts the current semantic content placements.
4. Suggests missing semantic long-tail queries.

Code Overview

ai_seo_crawler.py

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