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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Cold Email Generator Tool\n\nAn intelligent AI-powered tool that automatically generates personalized cold emails for job applications by analyzing job postings and matching them with relevant portfolio projects.\n\n## 🚀 Features\n\n- **Smart Job Analysis**: Automatically extracts job details (role, experience, skills, description) from career pages\n- **Portfolio Matching**: Uses vector similarity search to find relevant portfolio projects based on required skills\n- **AI-Powered Email Generation**: Creates personalized cold emails using Llama 3.3-70B model via Groq API\n- **Web Interface**: User-friendly Streamlit web application\n- **Text Cleaning**: Automatically cleans and processes scraped web content\n\n## 🛠️ Technology Stack\n\n- **Frontend**: Streamlit\n- **AI/LLM**: Llama 3.3-70B (via Groq API)\n- **Vector Database**: ChromaDB for portfolio similarity search\n- **Web Scraping**: LangChain WebBaseLoader\n- **Data Processing**: Pandas, Regular Expressions\n- **Language**: Python\n\n## 📋 Prerequisites\n\n- Python 3.8+\n- Groq API key\n- Internet connection for web scraping\n\n## 🚀 Installation\n\n1. **Clone the repository**\n   ```bash\n   git clone https://github.com/45Harry/Cold_Email_Generator_Tool_GenAI_Llama3.1.git\n   cd Cold_Email_Generator_Tool_GenAI_Llama3.1\n   ```\n\n2. **Install dependencies**\n   ```bash\n   pip install streamlit langchain-groq langchain-community chromadb pandas python-dotenv\n   ```\n\n3. **Set up environment variables**\n   Create a `.env` file in the root directory:\n   ```bash\n   GROQ_API_KEY=your_groq_api_key_here\n   ```\n\n4. **Update portfolio data**\n   - Edit `app/resources/my_portfolio.csv` with your actual portfolio projects\n   - Format: `Techstack,Links` (comma-separated)\n\n## 🎯 Usage\n\n1. **Start the application**\n   ```bash\n   cd app\n   streamlit run main.py\n   ```\n\n2. **Access the web interface**\n   - Open your browser and go to `http://localhost:8501`\n   - You'll see the \"Cold Mail Generator\" interface\n\n3. **Generate a cold email**\n   - Enter a job posting URL in the text field\n   - Click \"Submit\"\n   - The tool will:\n     - Scrape and analyze the job posting\n     - Extract job requirements and skills\n     - Find relevant portfolio projects\n     - Generate a personalized cold email\n\n## 📁 Project Structure\n\n```\nCold_Email_Generator_Tool_GenAI_Llama3.1/\n├── app/\n│   ├── main.py              # Streamlit application entry point\n│   ├── chains.py            # LLM chains for job extraction and email generation\n│   ├── portfolio.py         # Portfolio management and vector search\n│   ├── utils.py             # Text cleaning utilities\n│   └── resources/\n│       └── my_portfolio.csv # Portfolio projects database\n├── vectorstore/             # ChromaDB vector database files\n├── my_portfolio.csv         # Root portfolio file\n└── README.md               # This file\n```\n\n## 🔧 Configuration\n\n### Portfolio Setup\nThe tool uses a CSV file to store your portfolio projects. Each row should contain:\n- **Techstack**: Comma-separated list of technologies/skills\n- **Links**: URL to the project or portfolio piece\n\nExample:\n```csv\nTechstack,Links\n\"Python, Pandas, Machine Learning\",\"https://github.com/username/ml-project\"\n\"React, Node.js, MongoDB\",\"https://github.com/username/web-app\"\n```\n\n### API Configuration\n- **Groq API**: Required for LLM functionality\n- Get your API key from [Groq Console](https://console.groq.com/)\n- Add it to your `.env` file\n\n## 🎨 How It Works\n\n1. **Job Analysis**: The tool scrapes the provided job URL and extracts key information using LLM\n2. **Skill Matching**: Uses ChromaDB to find portfolio projects that match the job requirements\n3. **Email Generation**: Creates a personalized cold email incorporating relevant portfolio links\n4. **Output**: Displays the generated email in markdown format\n\n## 📝 Example Output\n\nThe tool generates professional cold emails that include:\n- Personalized introduction\n- Relevant skills and experience\n- Portfolio project links\n- Professional closing\n\n## 🤝 Contributing\n\n1. Fork the repository\n2. Create a feature branch (`git checkout -b feature/amazing-feature`)\n3. Commit your changes (`git commit -m 'Add amazing feature'`)\n4. Push to the branch (`git push origin feature/amazing-feature`)\n5. Open a Pull Request\n\n## 📄 License\n\nThis project is licensed under the MIT License - see the LICENSE file for details.\n\n## 🙏 Acknowledgments\n\n- Built with [Streamlit](https://streamlit.io/)\n- Powered by [Llama 3.3-70B](https://llama.meta.com/) via [Groq](https://groq.com/)\n- Vector search powered by [ChromaDB](https://www.trychroma.com/)\n- Web scraping with [LangChain](https://www.langchain.com/)\n\n## 📞 Support\n\nIf you encounter any issues or have questions, please:\n1. Check the existing issues\n2. Create a new issue with detailed information\n3. Include error messages and steps to reproduce\n\n---\n\n**Note**: This tool is designed for educational and professional use. Always review generated emails before sending them to ensure they accurately represent your skills and experience. ","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F45harry%2Fcold_email_generator_tool_genai_llama3.1","html_url":"https://awesome.ecosyste.ms/projects/github.com%2F45harry%2Fcold_email_generator_tool_genai_llama3.1","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2F45harry%2Fcold_email_generator_tool_genai_llama3.1/lists"}