https://github.com/aravinda-1402/cold_email_generator
An automated cold email generator leveraging Retrieval-Augmented Generation (RAG), combining LangChain's ChatGroq model with ChromaDB for targeted outreach. The project includes a Streamlit for intuitive job description parsing, skill matching, and personalized email generation.
https://github.com/aravinda-1402/cold_email_generator
Last synced: 2 months ago
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An automated cold email generator leveraging Retrieval-Augmented Generation (RAG), combining LangChain's ChatGroq model with ChromaDB for targeted outreach. The project includes a Streamlit for intuitive job description parsing, skill matching, and personalized email generation.
- Host: GitHub
- URL: https://github.com/aravinda-1402/cold_email_generator
- Owner: aravinda-1402
- License: mit
- Created: 2024-11-14T14:19:41.000Z (6 months ago)
- Default Branch: main
- Last Pushed: 2024-11-14T15:47:51.000Z (6 months ago)
- Last Synced: 2025-01-19T09:13:30.662Z (4 months ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 492 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 📧 Cold Email Generator
This Cold Email Generator automates the process of extracting job listings from career pages and generating targeted cold emails. Leveraging **Groq LLM**, **LangChain**, and **Streamlit**, this tool ensures that outreach emails are personalized with relevant portfolio links stored in a **vector database**.
---
## 🔍 Overview
Many businesses spend significant resources on recruiting and hiring talent. This tool assists **service-oriented companies** by identifying job openings and generating **customized outreach emails** to highlight relevant solutions.
For example, if a company is **hiring software engineers**, a **business development executive** from an AI & Software Consulting company (like "ABC") can use this tool to send personalized cold emails, offering skilled professionals or consulting solutions to fulfill the company's hiring needs.
---
## ⚙️ How It Works
The Cold Email Generator follows a structured pipeline:
1. **Scrape Job Listings**:
- The user enters a **career page URL** (e.g., Nike Careers).
- The tool **scrapes job listings** and **extracts details** (job title, skills, experience, description).
2. **Match Portfolio Links**:
- The tool queries a **vector store** to find **relevant portfolio projects** that match the job’s skillset.
3. **Generate Cold Email**:
- A **LLM (Large Language Model)** crafts a **personalized email**, introducing ABC’s services and **attaching relevant portfolio links**.
4. **Display the Email**:
- The **email is generated** in markdown format, ready for outreach.
---
## 🛠️ Tech Stack
- **Streamlit** – User interface for entering job URLs and displaying emails.
- **LangChain** – Handles job extraction and email generation.
- **Groq LLM** – Processes extracted job data and generates cold emails.
- **ChromaDB** – Stores and retrieves relevant portfolio links based on job descriptions.
---
## 📥 Installation & Setup
### 1️⃣ Generate API Key
- Obtain an API key from **[Groq API Console](https://console.groq.com/keys)**.
- Add the key to your `.env` file:
```bash
echo "GROQ_API_KEY=your_api_key_here" > app/.env
### 2️⃣ Install Dependencies
```bash
pip install -r requirements.txt
```
### 3️⃣ Run the Application
```bash
streamlit run app/main.py
```
## 🎯 Future Enhancements
- ✅ **Multi-company outreach**: Automate cold emails for multiple companies in a batch.
- ✅ **Enhanced filtering**: Improve skill-matching with vector embeddings.
- ✅ **Automated follow-ups**: Generate follow-up emails based on client responses.
## 📝 License
This project is open-source and available under the **MIT License**.