Cold Email Generator

Overview

The Cold Email Generator leverages LLM to create personalized cold emails with ease. By integrating Llama 3.1, Langchain, Groq and other powerful tools, this project offers a streamlined interface for generating customized emails based on user input and predefined templates.

Features

• Automated Email Generation: Generate cold emails using AI.
• Customizable Templates: Tailor the email content to match specific industries or business needs.
• User-friendly Interface: Built with Streamlit for an intuitive user experience.
• API Integration: Uses Groq API for enhanced language processing.

Technologies Used

• Llama 3.1 (LLM): Large language model for generating human-like email content.
• Langchain: A framework for developing applications powered by language models.
• Groq API: Integrates Groq's powerful API to enhance language model capabilities.
• ChromaDB: Store vector embeddings for fast retrieval.
• Jupyter Notebook: Used for prototyping and experimenting with different AI models.
• Streamlit: Web application framework for creating a simple and interactive user interface.

Architecture Model

Installation

To get started with this project, follow these steps:

1. Clone the repository:

   git clone https://github.com/<username>/<repo>.git
   cd <repo>
   

2. Create a virtual environment (optional but recommended):

   python -m venv venv
   

3. Activate the virtual environment:

   • On macOS/Linux:

     source venv/bin/activate

   • On Windows:

     venv\Scripts\activate

4. Set up the Groq API key:

   • Obtain your API key from Groq and set it as an environment variable:

     export GROQ_API_KEY=your_api_key

5. Run the Streamlit app:

   streamlit run app.py
   

References:

• ChatGroq
• Vector Database
• LLM Embedding
• Python Environment