FuturitiPOC – Kentucky Open Science

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Futuriti AI ChatbotA conversational AI assistant for futuriti.org that helps Kentucky students and adults explore careers, education programs, and living wages through natural conversation.Built to serve two grant requirements simultaneously: Action Fund Grant — Living wage calculator delivered conversationally Lumina Grant — Anonymous student interest pipeline data collectionFeaturesConversational career exploration — Students ask questions in plain English, the AI responds…

Source code on GitHub.

Repository Info

RepositoryKentucky-Open-Science/FuturitiPOC

LanguagePython

LicenseApache-2.0

Last Updated2026-04-10

README

Futuriti AI Chatbot

A conversational AI assistant for futuriti.org that helps Kentucky students and adults explore careers, education programs, and living wages through natural conversation.

Built to serve two grant requirements simultaneously:

Action Fund Grant — Living wage calculator delivered conversationally

Lumina Grant — Anonymous student interest pipeline data collection

Features

Conversational career exploration — Students ask questions in plain English, the AI responds with Kentucky-specific data about salaries, programs, costs, and next steps
Living wage calculator — Compares career salaries against county-level cost of living
FERPA-compliant data collection — Anonymously captures career interests, schools considered, and programs explored for grant reporting
PDF summaries — Downloadable conversation summaries with action items; re-uploadable to continue a session
Session persistence — Each session gets a unique URL that can be bookmarked and shared to return later
Mobile-friendly, WCAG AA compliant — Responsive design with proper ARIA labels, keyboard navigation, and color contrast

Architecture

``src/ scraper/ Multithreaded Playwright-based web scraper for futuriti.org rag/ ChromaDB vector store with sentence-transformers embeddings chat/ OpenAI-compatible LLM client with 7 tool-calling functions analytics/ SQLite-backed anonymous interest data collection pdf/ ReportLab PDF generation and PyPDF2 parsing for re-upload data/ Excel/CSV loaders and structured data (SQLite) web/ FastAPI server with session persistence and chat UI`

`Prerequisites`

Python 3.11+


An OpenAI-compatible LLM API (OpenAI, Azure OpenAI, Ollama, vLLM, etc.)

`Quick Start`

`bash

`1. Clone and enter the project`


cd Futuriti
2. Create and activate virtual environment
python -m venv .venv
source .venv/Scripts/activate   # Windows/Git Bash
source .venv/bin/activate     # macOS/Linux
3. Install dependencies
pip install -r requirements.txt
playwright install chromium
4. Configure environment
cp .env.example .env
Edit .env with your LLM API credentials (base URL, API key, model name)
5. Scrape futuriti.org (~329 pages, ~15-20 minutes)
python scripts/scrape.py
6. Ingest all data (web + Excel) into the vector store and structured database
   Place the Futuriti Excel file at data/csv/ before running
python scripts/ingest.py
7. Start the chatbot server
python scripts/serve.py
Open http://localhost:800...