Cold Email Generator for Job Descriptions

This project is a web scraper and cold email generator that leverages LLMs (via GroqCloud API), vector databases (ChromaDB), and Streamlit for a seamless user experience. It scrapes job descriptions from the web, extracts structured job information, matches your portfolio, and generates a personalized cold email for recruiters. Usefull tool for the job applicant to write cold Emails.

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Screenshot

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Features

• Web Scraping: Extracts job descriptions from any public job posting using LangChain's WebBaseLoader.
• LLM Integration: Uses GroqCloud's LLM API for job extraction and email generation.
• Portfolio Matching: Stores your tech stack and portfolio links in ChromaDB for relevant matching.
• Streamlit UI: Simple web interface for inputting job URLs and viewing generated emails.
• Environment Management: Uses .env for secure API key management.

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How It Works

1. Input: Enter a job posting URL in the Streamlit app.
2. Scraping: The app scrapes and cleans the job description.
3. Extraction: An LLM extracts structured job data (role, experience, skills, description).
4. Portfolio Match: Your portfolio is queried for relevant projects/skills.
5. Email Generation: The LLM generates a tailored cold email using the job info and your portfolio.
6. Output: The email is displayed in the Streamlit app, ready to copy and send.

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Setup

1. Clone the repository

   git clone <repo-url>
   cd ColdEmailUsingGroq

2. Install dependencies

   pip install -r requirements.txt

3. Set up your environment variables

   • Create a .env file in the root directory:

     GROQ_API_KEY=your_groq_api_key_here
     

4. Prepare your portfolio

   • Place your my_portfolio.csv in app/resource/ with columns: Techstack, Links.

5. Run the Streamlit app

   streamlit run [main.py](http://_vscodecontentref_/0)

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Tech Stack

• LangChain (WebBaseLoader, Prompting)
• LangChain WebBaseLoader
• GroqCloud LLM API
• ChromaDB (vector database)
• Streamlit (UI)
• python-dotenv (env management)
• pandas (portfolio CSV handling)

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References

• LangChain WebBaseLoader Docs
• ChromaDB Docs
• Streamlit Docs
• python-dotenv

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License

MIT License

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