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https://github.com/metehan777/deepseek-r1-browser-use-seo-analysis
browser-use and Deepseek R1 advanced, automated SEO agent analysis Python script
https://github.com/metehan777/deepseek-r1-browser-use-seo-analysis
browser-use deepseek deepseek-r1 seo seo-optimization seotools
Last synced: 9 days ago
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browser-use and Deepseek R1 advanced, automated SEO agent analysis Python script
- Host: GitHub
- URL: https://github.com/metehan777/deepseek-r1-browser-use-seo-analysis
- Owner: metehan777
- Created: 2025-01-26T12:09:08.000Z (11 days ago)
- Default Branch: main
- Last Pushed: 2025-01-26T12:43:36.000Z (11 days ago)
- Last Synced: 2025-01-26T13:22:41.573Z (11 days ago)
- Topics: browser-use, deepseek, deepseek-r1, seo, seo-optimization, seotools
- Language: Python
- Homepage:
- Size: 20.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# 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
```python
import asyncio
import os
from dotenv import load_dotenv
from langchain_openai import ChatOpenAI
from pydantic import SecretStr
from browser_use import Agent
# Load environment
load_dotenv()
async def run_search():
# Initialize agent with tasks
agent = Agent(
task=(
'1. Go to https://appsamurai.com\n'
'2. Analyze the page for the best semantic placements of contents\n'
'3. Extract the current semantic content placements\n'
'4. Suggest missing semantic long-tail queries'
),
llm=ChatOpenAI(
base_url='https://api.deepseek.com/v1',
model='deepseek-reasoner',
api_key=SecretStr(os.getenv('DEEPSEEK_API_KEY', '')),
),
use_vision=False,
)
# Execute tasks and save raw output
result = await agent.run()
# Basic text file output
with open('output.txt', 'w', encoding='utf-8') as f:
f.write(str(result))
if __name__ == '__main__':
asyncio.run(run_search())
```
### browser_use
This file contains the `Agent` class, which performs tasks such as browsing, analyzing, and suggesting improvements for a webpage. Ensure this module is implemented correctly to support the main script.
## Output
The results of the analysis will be saved in `output.txt`, which includes:
- Extracted semantic content placements.
- Suggested long-tail queries for semantic optimization.
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
## Contributing
Contributions are welcome! Feel free to open an issue or submit a pull request.
## Author
[Metehan Yesilyurt](https://metehan.ai)
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