CoffeeStarter: Personal Networking Agent

CoffeeStarter is the ultimate networking tool. It leverages your resume to craft personalized coffee chat emails to alumni professionals in your desired field, helping you stand out in today's market.

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🎉 CoffeeStarter: Your Personal Networking Agent 🚀

Names: Sutharsika Kumar, Aarav Jindal, Tanush Changani & Pranjay Kumar

Welcome to CoffeeStarter, a cutting-edge tool designed to revolutionize personal networking by connecting you with alumni from your school's network effortlessly. Perfect for hackathons and beyond, CoffeeStarter blends advanced technology with user-friendly features to help you build meaningful professional relationships.

🌟 Inspiration

In a world where connections matter more than ever, we envisioned a tool that bridges the gap between ambition and opportunity. CoffeeStarter was born out of the desire to empower individuals to effortlessly connect with alumni within their school's network, fostering meaningful relationships that propel careers forward.

🛠️ What It Does

CoffeeStarter leverages the power of a fine-tuned LLaMA model to craft personalized emails tailored to each alumnus in your school's network. Here's how it transforms your networking experience:

  • 📧 Personalized Outreach: Generates authentic, customized emails using your resume to highlight relevant experiences and interests.
  • 🔍 Smart Alumnus Matching: Identifies and connects you with alumni that align with your professional preferences and career goals.
  • 🔗 Seamless Integration: Utilizes your existing data to ensure every interaction feels genuine and impactful.

🏗️ How We Built It

Our robust technology stack ensures reliability and scalability:

  • 🗄️ Database: Powered by SQLite for flexible and efficient data management.
  • 🐍 Machine Learning: Developed using Python to handle complex ML tasks with precision.
  • ⚙️ Fine-Tuning: Employed Tune for meticulous model fine-tuning, ensuring optimal performance and personalization.

⚔️ Challenges We Faced

Building CoffeeStarter wasn't without its hurdles:

  • 🔒 SQLite Integration: Navigating the complexities of SQLite required innovative solutions.
  • 🚧 Firewall Obstacles: Overcoming persistent firewall issues to maintain seamless connectivity.
  • 📉 Model Overfitting: Balancing the model to avoid overfitting while ensuring high personalization.
  • 🌐 Diverse Dataset Creation: Ensuring a rich and varied dataset to support effective networking outcomes.
  • API Integration: Working with various API's to get as diverse a dataset and functionality as possible.

🏆 Accomplishments We're Proud Of

  • 🌈 Diverse Dataset Development: Successfully created a comprehensive and diverse dataset that enhances the accuracy and effectiveness of our networking tool.
  • Authentic messages that reflect user writing styles which contributes to personalization.

📚 What We Learned

The journey taught us invaluable lessons:

  • 🤝 The Complexity of Networking: Understanding that building meaningful connections is inherently challenging.
  • 🔍 Model Fine-Tuning Nuances: Mastering the delicate balance between personalization and generalization in our models.
  • 💬 Authenticity in Automation: Ensuring our automated emails resonate as authentic and genuine, without echoing our training data.

🔮 What's Next for CoffeeStarter

We're just getting started! Future developments include:

  • 🔗 Enhanced Integrations: Expanding data integrations to provide even more personalized networking experiences and actionable recommendations for enhancing networking effectiveness.
  • 🧠 Advanced Fine-Tuned Models: Developing additional models tailored to specific networking needs and industries.
  • 🤖 Smart Choosing Algorithms: Implementing intelligent algorithms to optimize alumnus matching and connection strategies.

📂 Submission Details for PennApps XXV

📝 Prompt

You are specializing in professional communication, tasked with composing a networking-focused cold email from an input {student, alumni, professional}, name {your_name}. Given the data from the receiver {student, alumni, professional}, your mission is to land a coffee chat. Make the networking text {email, message} personalized to the receiver’s work experience, preferences, and interests provided by the data. The text must sound authentic and human. Keep the text {email, message} short, 100 to 200 words is ideal.

📄 Version Including Resume

You are specializing in professional communication, tasked with composing a networking-focused cold email from an input {student, alumni, professional}, name {your_name}. The student's resume is provided as an upload {resume_upload}. Given the data from the receiver {student, alumni, professional}, your mission is to land a coffee chat. Use the information from the given resume of the sender and their interests from {website_survey} and information of the receiver to make this message personalized to the intersection of both parties. Talk specifically about experiences that {student, alumni, professional} would find interesting about the receiver {student, alumni, professional}. Compare the resume and other input {information} to find commonalities and make a positive impression. Make the networking text {email, message} personalized to the receiver’s work experience, preferences, and interests provided by the data. The text must sound authentic and human. Keep the text {email, message} short, 100 to 200 words is ideal. Once completed with the email, create a 1 - 10 score with 1 being a very generic email and 10 being a very personalized email. Write this score at the bottom of the email.

🧑‍💻 Technologies Used

  • Frameworks & Libraries:

    • Python: For backend development and machine learning tasks.
    • SQLite: As our primary database for managing user data.
    • Tune: Utilized for fine-tuning our LLaMA3 model.

  • External/Open Source Resources:

    • LLaMA Model: Leveraged for generating personalized emails.
    • Various Python Libraries: Including Pandas for data processing and model training.

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