TalentScout – AI Hiring Assistant 🤖

TalentScout is an intelligent, interactive hiring assistant chatbot built using Streamlit and powered by Cohere's Command-R LLM. It helps recruitment agencies screen candidates by gathering personal information, assessing technical expertise, and conducting follow-up Q&A chats — all in a sleek, responsive UI.

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🧠 Features

• Clean Streamlit UI for candidate interaction
• Gathers:
  • Full Name
  • Email
  • Phone
  • Years of Experience
  • Desired Position(s)
  • Current Location
  • Tech Stack (Languages, Frameworks, Tools)
• Generates 3–5 custom technical interview questions based on candidate’s tech stack
• Allows live follow-up questions with context-awareness
• Graceful fallback for unclear prompts
• Personalized responses based on provided user info
• Elegant styling with custom CSS

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🖥️ Demo

Watch the Demo on YouTube!

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🚀 Getting Started

1. Clone the Repository

git clone https://github.com/antarades/TalentScout-AI-Hiring-Assistant
cd TalentScout-AI-Hiring-Assistant

2. Install Dependencies

pip install -r requirements.txt

3. Set up environment variables

Create a .env file in the root directory with your Cohere API key:

COHERE_API_KEY=your_api_key_here

💡 Get your free API key at https://dashboard.cohere.com/

4. Run the App

streamlit run main.py

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🗂️ File Structure

├── main.py                # Main Streamlit UI + Logic
├── prompts.py             # Modular prompt functions for Cohere
├── .env                   
├── requirements.txt
├── README.md  

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🧪 Technologies Used

• Streamlit – Frontend & state management
• Cohere Command-R – LLM for Q&A and context
• dotenv – Manage API secrets

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✨ Optional Enhancements Implemented

• Personalized responses based on candidate information
• Custom UI with styled buttons and layout

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📝 Prompt Engineering Overview

We use structured system prompts to guide the LLM:

• Initial greeting prompt
• Information gathering prompt
• Tech-stack specific question generation
• Fallback instructions for edge cases
• Context-aware follow-up responses
• Conversation exit summary

All prompts are modularized in prompts.py.

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📃 License

This project is for academic purposes under fair use. For commercial or extended use, contact the project creator.

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🙋‍♀️ Author

Built by Antara Srivastava 📧 antarakyw05@gmail.com 🌐 github.com/antarades