🤖 AI Recruitment Agent

An intelligent recruitment assistant that automates resume screening using a local LLM via Ollama and offers both CLI and web-based interaction.

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✨ Features

• ⚡ AI-Powered Analysis: Leverages Gemma 3:4b via Ollama for deep resume-job fit evaluation.
• 📊 Vector-Based Context Matching: Uses FAISS to store and retrieve job description vectors.
• 📦 Structured Output: LLM output is parsed into JSON for decision, compatibility score, and justification.
• 💾 Persistent Storage: Stores all results in an SQLite database for audit and analysis.
• 🧰 Dual Interface: Available as a CLI tool or through a React + FastAPI web UI.

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💻 Screenshot

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🧠 How It Works

1. 📥 Job Description Embedding

   • Converts job text into vectors using nomic-embed-text via OllamaEmbeddings
   • Stored in FAISS for fast retrieval

2. 📄 Resume Parsing

   • Extracts text from uploaded PDF resumes using PyPDF.

3. 🔍 AI Analysis via LangChain

   • Uses:
     • 🔁 Retriever (FAISS)
     • 🧠 LLM: gemma3:4b via Ollama
     • ✏️ Prompt Template with strict rules
     • 📦 PydanticOutputParser for structured JSON

4. 💾 Store Results

   • Data is persisted in recruitment_results.db via a custom database function.

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🧰 Tech Stack

Category	Tools
💡 AI/LLM	LangChain, Gemma, Ollama, nomic-embed-text
⚙️ Backend	FastAPI, pydantic, faiss-cpu, PyPDF
🖥️ Frontend	React, Vite, TailwindCSS (optional)
🛢️ Database	SQLite
🧠 Vector DB	FAISS
📦 Package Managers	pip, npm

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🚀 Getting Started

✅ Prerequisites

• Python 3.9+
• Node.js & npm
• Ollama installed and running

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⚙️ Setup Guide

🔹 Pull LLM and Embed Models

ollama pull gemma3:4b
ollama pull nomic-embed-text

🔹 Backend Setup

cd MainAPI
# Create this requirements.txt file:

📄 MainAPI/requirements.txt

fastapi
uvicorn[standard]
langchain
langchain-community
langchain-ollama
pydantic
pypdf
faiss-cpu
python-dotenv
python-multipart

pip install -r requirements.txt

🔹 Frontend Setup (Optional)

cd frontend-react
npm install

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🧪 Usage

💻 Command-Line Mode

python recruitmentagent.py

Follow the prompts to upload a resume and see results in the console.

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🌐 Web Interface Mode

1. Start the Backend API

cd MainAPI
uvicorn main:app --reload

API accessible at http://127.0.0.1:8000

2. Start the React Frontend

cd frontend-react
npm run dev

Open http://localhost:5173 in your browser.

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🧑‍💼 Use Case

Perfect for HR teams, recruitment firms, or tech hiring platforms looking to automate and scale their screening process with AI-driven insights.

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🛠️ Future Improvements

• ✅ Resume ranking
• ✅ Multi-role analysis
• ⏳ Email integration
• ⏳ Feedback loop learning

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📬 Contact

For collaboration or questions, feel free to reach out!