🚀 Recruitify

An intelligent recruitment and interview assistant built with Streamlit, LangChain, Google Gemini API, Groq API, and Deepgram API. This app helps recruiters, candidates, and career coaches by:

• 📄 Analyzing Resumes against job requirements or custom job descriptions
• ❓ Q&A on Resumes using Retrieval-Augmented Generation (RAG)
• 🎯 Generating Personalized Interview Questions
• 🛠️ Providing Resume Improvement Suggestions with before/after examples
• 📝 Creating Optimized Improved Resumes tailored for a target role
• 🎙️ Simulating Real-Time Interviews with voice input, AI-generated feedback, and performance scoring

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✨ Features

🔍 Resume Requirement Analyst

• Upload a resume (PDF) and analyze it against:

  • Predefined role-based skill sets (e.g., Data Scientist, AI/ML Engineer, DevOps Engineer)
  • Or a custom job description (PDF/TXT)

• Get:

  • Overall Score & Shortlisting Status
  • Strengths & Weaknesses
  • Detailed Skill Gap Analysis
  • 📊 Downloadable Resume Analysis Report

🤖 Resume Q&A

• Ask any question about the uploaded resume
• Example: “What is the candidate’s most recent role?” or “Does the candidate have cloud experience?”

📝 Interview Question Generator

• Generate personalized interview questions based on resume & skills
• Supports multiple question types: Basic, Technical, Scenario, Coding, Behavioral
• Difficulty levels: Easy, Medium, Hard
• Download generated questions in Markdown format

🛠️ Resume Improvement

• AI-powered suggestions for improvement in:

  • Content
  • Skills Highlighting
  • Experience & Projects
  • Format & Structure

• Includes Before vs. After examples for better clarity

📑 Improved Resume Generator

• Automatically rewrite and optimize resumes for:

  • A specific target role
  • Or a given job description

• Highlights missing & key skills

🎙️ AI Interview Assistant

• Upload interview question files (Markdown/TXT)

• Voice-based interview simulation:

  • Questions are read aloud using Groq TTS
  • Candidate answers via microphone input
  • Transcribed using Deepgram STT

• AI evaluates responses with:

  • ✅ Strengths & Weaknesses
  • 📌 Actionable Improvement Suggestions
  • 📊 Confidence & Accuracy Scoring (1–10)

• 📉 Performance Report with visual graphs (Plotly)

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🛠️ Tech Stack

• Frontend/UI: Streamlit
• AI & NLP: LangChain, Google Gemini API
• LLMs: Groq (LLaMA 3.3-70B), Google Gemini
• Vector Database: FAISS
• Speech-to-Text: Deepgram
• Text-to-Speech: Groq Audio API
• Charts & Visualization: Plotly, Matplotlib

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🚀 Installation

1️⃣ Clone the Repository

git clone https://github.com/yourusername/recruitment-agent.git
cd recruitment-agent

2️⃣ Create a Virtual Environment

python -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Set Environment Variables

Create a .env file in the project root:

GOOGLE_API_KEY=your_google_api_key
GROQ_API_KEY=your_groq_api_key
DEEPGRAM_API_KEY=your_deepgram_api_key

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▶️ Usage

Run the app with:

streamlit run app.py

Modes:

• Requirement Analyst → Resume analysis, Q&A, improvements, and interview question generation
• Interview Assistant → Voice-enabled AI-powered interview simulation

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📂 Project Structure

.
├── app.py               # Main Streamlit app entry point
├── agents.py            # Resume analysis agent (LLM, RAG, scoring, improvements)
├── interview.py         # AI-powered voice interview assistant
├── ui.py                # Streamlit UI components and styling
├── requirements.txt     # Dependencies
└── README.md            # Project documentation

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📊 Example Screenshots

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🤝 Contributing

Contributions are welcome!

• Fork the repo
• Create a feature branch
• Commit your changes
• Open a Pull Request

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📜 License

This project is licensed under the MIT License.