deepseek-r1-browser-use-seo-analysis

# 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:

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

2. Install dependencies:

   ```bash
   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:

   ```env
   DEEPSEEK_API_KEY=your_deepseek_api_key
   ```

## Usage

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

```bash
python ai_seo_crawler.py
```

The script performs the following tasks:

1. Navigates to [AppSamurai](https://appsamurai.com).
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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