Description
This application is an SEO Compatibility Checker and Optimizer that helps users analyze their content based on SEO best practices. It generates a list of relevant SEO keywords, checks if those keywords are present in the content, evaluates the content’s readability score, and suggests optimized content for SEO. The tool leverages a pre-trained large language model to enhance the content for search engine optimization.
Model Inference
The application uses the mistralai/Mistral-7B-Instruct-v0.3 model from Hugging Face for following processes.
- Keyword Generation: The model analyzes the input content and generates relevant SEO keywords.
- Content Improvement: The model is prompted to enhance the content with SEO strategies, optimizing for both readability and keyword density.
Tools Used
- Gradio: A Python library used to build the user interface for easy interaction with the application. It provides a web interface where users can input text and view the SEO analysis and optimized content.
- LangChain Hugging Face Endpoint: Interfaces with the Hugging Face model to perform the natural language processing required to generatege keywords and improve content.
- TextStat: A Python library used to calculate the Flesch Reading Ease score, a measure of how easy the content is to read.
- Python Dotenv: Manages environment variables, including the Hugging Face API token used to access the model.
This combination of tools and models provides a seamless experience for analyzing and improving content for SEO, making it more effective and easier to read.
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Preview:
