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| title: 🧠 BlogBrain Genius AI | |
| emoji: 📉 | |
| colorFrom: yellow | |
| colorTo: purple | |
| sdk: streamlit | |
| sdk_version: 1.39.0 | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
| AI-BLOG | |
| 🧠 BlogBrain Genius AI | |
| Table of Contents | |
| Introduction | |
| Features | |
| How It Works | |
| Installation | |
| Usage | |
| Technologies Used | |
| Future Improvements | |
| Contributing | |
| License | |
| Introduction | |
| BlogBrain Genius AI is an innovative AI-powered application that transforms raw content into comprehensive, engaging blog posts. Whether you have a YouTube video or a piece of text, our application uses advanced AI algorithms to generate well-structured, informative blog content. | |
| Features | |
| YouTube video to blog post conversion | |
| Custom text to expanded blog post transformation | |
| AI-powered content generation | |
| User-friendly interface built with Streamlit | |
| Customizable output options | |
| How It Works | |
| Input Selection: Users can choose between two input methods: | |
| YouTube Video URL | |
| Custom Text | |
| Content Extraction: | |
| For YouTube videos, the application fetches the transcript. | |
| For custom text, it directly uses the provided input. | |
| AI Processing: The extracted content is then processed by our AI model, which: | |
| Analyzes the main topics and themes | |
| Expands on key points | |
| Structures the information into a coherent blog post format | |
| Output Generation: The AI generates a comprehensive blog post, which includes: | |
| An engaging title | |
| Well-structured paragraphs | |
| Relevant subheadings | |
| A conclusion | |
| User Review and Editing: Users can review the generated blog post and make any necessary edits or refinements. | |
| Installation | |
| Clone the repository: git clone "..." | |
| Edit Copy code | |
| Navigate to the project directory: cd .. | |
| Edit Copy code | |
| Install the required dependencies: pip install -r requirements.txt | |
| Edit Copy code | |
| Usage | |
| Run the Streamlit app: streamlit run app.py | |
| Edit Copy code | |
| Open your web browser and go to the local URL provided by Streamlit (usually http://localhost:8501). | |
| Choose your input method (YouTube Video or Custom Text). | |
| Enter your content and click "Generate Blog Post". | |
| Review and edit the generated blog post as needed. | |
| Technologies Used | |
| Python | |
| Streamlit | |
| Google-Gemini-Flsh (for AI text generation) | |
| YouTube API (for transcript fetching) | |
| Natural Language Processing (NLP) libraries | |
| Future Improvements | |
| Multiple Language Support: Implement functionality to generate blog posts in various languages. | |
| SEO Optimization: Integrate SEO analysis and suggestions for the generated content. | |
| Template Selection: Allow users to choose from different blog post templates or styles. | |
| Image Integration: Automatically suggest and integrate relevant images into the blog post. | |
| Voice-to-Blog: Add functionality to generate blog posts from audio files or voice recordings. | |
| Content Summarization: Implement an option to generate both full blog posts and concise summaries. | |
| Plagiarism Check: Integrate a plagiarism checking tool to ensure the uniqueness of generated content. | |
| Export Options: Add the ability to export blog posts in various formats (PDF, Markdown, HTML). | |
| User Accounts: Implement user accounts to save and manage multiple blog posts. | |
| API Integration: Develop an API for the blog post generation service to integrate with other applications. | |
| Contributing | |
| We welcome contributions to ContentCraft AI! Please read our CONTRIBUTING.md for details on our code of conduct and the process for submitting pull requests. | |
| License | |
| This project is licensed under the MIT License - see the LICENSE.md file for details. |