Digital Welfare Companion

This project was made as part of the GydeXP Hackathon (in collaboration with the AI/ML Society of IIT Delhi), where our team was selected as Finalists among the top 14 teams at the National Level (India).

Team Members:

• Urvi Agrawal
• Rutuja Nimje
• Simran Hedaoo

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🚀 Installation

Welcome to the Digital Welfare Companion 👋
This is an AI-powered agentic system built with CrewAI, Streamlit, and Gemini API to make government schemes accessible in local languages.

Get Started

1️⃣ Clone the Repository

git clone https://github.com/yourusername/Resume-Screening-Crew.git
cd resume_checker

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Set Up API Keys

Create a .env file and add your API credentials:

GEMINI_API_KEY="your_api_key"

4️⃣ Run the Application

streamlit run streamlit_app.py

Screening Workflow

• Home Page – User lands on a simple, multilingual interface with voice and text query options.
• Voice/Text Query Processing – Input is sent to Google Gemini API for scheme discovery and interpretation.
• Agentic Scheme Matching – CrewAI agents identify relevant government schemes, extract eligibility, documents, and application steps.
• Document Upload & OCR – Users can upload Aadhaar, income certificate, etc., which are parsed via Pytesseract OCR.
• AI-based Document Verification – Agents check compliance of uploaded documents with scheme requirements.
• Structured Response Generation – A personalized, step-by-step report is generated with eligible schemes, required documents, and next actions.

Tech Stack

• Frontend/UI – Streamlit with Custom CSS for an accessible and simple user experience
• Voice Input & Query Handling – Streamlit + Google Gemini API for natural language understanding
• Multi-Agent System – CrewAI for distributed reasoning and task delegation
• OCR & Document Processing – Pytesseract (Tesseract OCR) for extracting text from uploaded documents
• APIs/Integrations – Google Gemini API for scheme discovery & language support
• Deployment Ready – Streamlit app structure for easy hosting and demoing