This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine
What I Built
I built the Supernatural Hunter's Journal, a 100% offline, AI-powered paranormal investigation dashboard.
Inspired by investigative horror games like Phasmophobia and the TV show Supernatural, I wanted to create a highly classified, digital "government-style" database for ghost hunters. Users input their eerie evidence (e.g., "The room suddenly got freezing cold, and I heard scratching in the walls"), and the system analyzes the data completely offline.
It identifies the supernatural entity, provides a chilling backstory (lore), warns of the imminent danger, and details the ancient method of defeat. To make it truly terrifying, the UI features flickering tech-grid glassmorphism and dynamically triggers specific jump-scare audio files (like glass shattering for Poltergeists or demonic growls for Demons) based on the AI's classification!
Demo
Code
shan2003034
/
Supernatural-Hunter-s-Journal
A 100% offline, AI-powered paranormal investigation dashboard. Built with React, Spring Boot, and local LLMs (Ollama) to analyze supernatural evidence, identify entities, and provide dynamic horror audio experiences.
🕵️♂️ Supernatural Hunter's Journal
A 100% Offline, AI-Powered Paranormal Investigation Dashboard
📖 About The Project
The Supernatural Hunter's Journal is a modern, classified digital dashboard designed for paranormal investigators. It allows users to input eerie paranormal evidence and uses a 100% offline Local LLM to analyze the data, identify the supernatural entity, and provide ancient lore, danger levels, and methods of defeat.
Built with an immersive, atmospheric UI featuring flickering tech-grids, GSAP animations, and dynamic jump-scare audio themes that react to the identified entity.
✨ Key Features
- 🧠 100% Offline AI Analysis: Powered by Spring AI and local Ollama models (no internet required, ensuring complete privacy).
- 🎨 Immersive Investigator Dashboard: A modern, split-screen UI built with React and Tailwind CSS, resembling a classified government or SCP database.
- 🔊 Dynamic Audio Themes: Automatically plays specific background ambient noises and jump-scare sounds based on the identified entity (e.g., glass…
How I Built It
To keep the theme truly "Ghost in the Machine," the entire intelligence of this app lives locally on the machine. No data is sent to the cloud.
- The AI Brain (Gemma): I used Google's Gemma (gemma:2b) running completely locally via Ollama.
- The Backend: I utilized Java Spring Boot integrated with Spring AI. I engineered a highly specific prompt instructing the local Gemma model to act as an ancient, battle-hardened demonologist. I also implemented a local SQLite database to automatically log every encounter into the "Database Archives" (Bestiary).
- The Frontend: Built with React and Tailwind CSS. I shifted from a classic "old book" look to a modern "Classified Investigator Dashboard" using dark glassmorphism, glowing cyan terminal fonts, and GSAP for smooth fade-ins and cinematic loading states.
- Dynamic Audio: The backend scans the AI's response for keywords and sends an
audioThemevariable to the frontend, which plays specific jump-scares dynamically.
Why Does Open Innovation Matter?
My Agent Session
When you're hunting demons, you don't want your private paranormal evidence being sent to a corporate cloud server!
Open innovation made this project possible because open-weight models like Gemma combined with Ollama allow developers to build powerful, immersive, and highly customized AI agents that run 100% locally. A closed API would have introduced latency, privacy concerns, and potential rate limits. With an open local model, the response is entirely self-contained, free, and incredibly fast—perfect for real-time paranormal investigations.
The Spirit of It
The most satisfying moment of building this was getting the dynamic audio jump-scares to sync perfectly with the AI's generation.
During testing, I typed in: "I woke up to a heavy feeling on my chest and saw a tall shadow with red eyes at the foot of my bed." When the loading radar finished sweeping, the dashboard suddenly flashed red, identified the entity as a "Shadow Demon," and a horrifying, guttural demon growl played perfectly on cue through my headphones. It genuinely gave me chills and made me jump out of my chair. That was the moment I knew the "Ghost in the Machine" had truly come alive.
Prize Categories
I am entering the following category for this submission:
- Google (Best use of Gemma)
Top comments (2)
Hey everyone! 👋 I had an absolute blast building this for the Week 4 challenge. The hardest (but most fun) part was syncing the dynamic jump-scare audio with the AI's response! 😅
Let me know if you have any questions about setting up Spring AI with local Ollama models. Would love to hear your feedback! 👻👇
I love that you went all in with the atmosphere, from the classified dashboard aesthetic to the dynamic audio and jump scares. The idea of the AI identifying some horrifying entity and then actually scaring you with the sound effects is great. I also really appreciate that everything runs locally. This is a good example of how much you can do with smaller models when you give them a focused, creative purpose. Good luck!