📄 AI-Powered PDF-to-Article Generator

An AI-driven CrewAI Multi-Agent application that converts PDF content into polished articles. This app empowers users to generate professional articles by leveraging AI agents for PDF analysis, content creation, and editing.

🚀 Features

• Multi-Agent System: Employs CrewAI to manage specialized agents for reading, writing, and refining articles.
• PDF Parsing: Extracts meaningful content from uploaded PDFs.
• AI-Powered Workflow: Seamlessly converts PDF insights into engaging articles with minimal user input.
• Custom Search Tool: Integrates user queries to tailor article content to specific needs.
• Session Management: Tracks and saves user interactions for future reference.
• Streamlit Interface: User-friendly and interactive UI for uploading PDFs and generating articles.

🛠️ Tech Stack

• Agents Framework: CrewAI
• Frontend: Streamlit
• Backend: Python, SQLite (for conversation storage)
• LLM: OpenAI API for advanced content generation
• Document Parsing: Python (handling uploaded PDFs)
• Environment Management: dotenv for seamless API key and environment variable configuration
• Deployed URL: https://ragagentarticle.streamlit.app/

🌟 How It Works

1. PDF Upload: Users upload a PDF file through the Streamlit interface.
2. Query Input: Users enter a search query to tailor the content extraction.
3. CrewAI Workflow:
   • PDF Reader Agent: Parses and extracts relevant content from the uploaded PDF.
   • Content Writer Agent: Generates a draft article based on the parsed content and user query.
   • Title Creator Agent: Suggests an engaging title for the article.
   • Editor Agent: Proofreads and finalizes the article for publication.
4. Output: The generated article is displayed in the app for the user to review and save.

🚀 Getting Started

1. Clone the repository:

   git clone git@github.com:Chukwuebuka-2003/rag_agentarticle.git
   cd rag_agentarticle

2. Install the required dependencies:

   pip install -r requirements.txt

3. Set up environment variables:

   • Create a .env file in the root directory.
   • Add your API keys:

     OPENAI_API_KEY=your_openai_api_key
     GROQ_API_KEY=your_groq_api_key
     GEMINI_API_KEY=your_gemini_api_key

4. Run the application:

   streamlit run rag_article.py

📄 Example Use Case

1. Upload a PDF: Upload a research paper, report, or any document in PDF format.
2. Enter a Query: Provide a specific topic or question to guide the article generation process.
3. Generate an Article: The AI-powered agents work collaboratively to extract insights, write content, and finalize an article.
4. View Results: Review and save the generated article directly from the Streamlit app.

💬 Future Enhancements

• Support for additional file formats (e.g., Word documents, HTML).
• Multi-language support for PDF content and generated articles.
• Integration with cloud storage platforms for uploading and saving files.
• Customization options for article formatting and style.