LeadGen AI

AI-powered B2B lead generation built with Flask + Google Gemini. Users sign in, describe their offering, target client, and region, and the app returns 10 structured leads with a clean Excel download.

Stack

• Backend: Flask, Flask-Login, Flask-SQLAlchemy
• DB: SQLite (leadforge.db, auto-created on first run)
• AI: Google Gemini (gemini-2.5-flash — free tier, no credit card)
• Excel: openpyxl
• Frontend: HTML + Tailwind CSS via CDN
• Deploy: Render.com (free tier)

Run locally

cd leadgen-ai
pip install -r requirements.txt
cp .env.example .env       # then edit .env and set GEMINI_API_KEY
python app.py

Open http://localhost:5000.

Get a free Gemini API key at https://aistudio.google.com/app/apikey

Deploy to Render

1. Push this folder to a GitHub repo.
2. In Render, create a new Web Service → "Use existing render.yaml".
3. Set the GEMINI_API_KEY environment variable in the Render dashboard.
4. Deploy. Render runs gunicorn app:app.

File structure

leadgen-ai/
├── app.py
├── requirements.txt
├── render.yaml
├── .env.example
├── .gitignore
├── README.md
├── templates/
│   ├── login.html
│   ├── register.html
│   ├── dashboard.html
│   └── results.html
└── static/

Routes

Route	Method	Purpose
/	GET	Redirect to login or dashboard
/login	GET/POST	Sign in
/register	GET/POST	Create account
/dashboard	GET	Lead-generation form (auth)
/generate	POST	Call Gemini, store leads (auth)
/results	GET	Preview generated leads (auth)
/download	GET	Download leads as .xlsx (auth)
/logout	GET	Sign out