This is a submission for the Hacktoberfest Open-Source AI Challenge — Week 4: Ghost in the Machine.
🕯️ What I Built
What if a ghost lived inside your computer—not as a character in a game, but as an AI you could actually talk to?
Introducing Phantom AI, an interactive, spooky AI chatbot inspired by the mysterious atmosphere of Halloween and the Ghost in the Machine theme.
Phantom AI combines a haunted terminal-inspired interface with an AI-powered conversational experience. Users can interact with different ghost personalities, ask questions, and generate eerie stories.
The project explores how open-weight AI models can power creative applications while giving developers more control over the technology behind them.
My goal was to create something that is not just visually spooky but also demonstrates a practical use of open-source AI.
🔮 Demo
👻 Try Phantom AI:
https://namansrivastava1.github.io/Phantom-AI/
Explore the interface and experience the concept of an AI entity living inside a machine.
Note: The GitHub Pages deployment serves the frontend. AI functionality that depends on a locally running Ollama instance requires that local setup and may not work directly on the public website.
💻 Code
🔗 GitHub Repository:
https://github.com/namansrivastava1/Phantom-AI
The project uses HTML, CSS, and JavaScript for its interface and interactions, with Ollama providing a connection to a locally running AI model.
The code is intended to be a starting point for developers interested in experimenting with local AI and creative web applications.
⚙️ How I Built It
I built Phantom AI using familiar web technologies and a local AI inference approach.
Technology stack:
- HTML5: Structures the chatbot interface.
- CSS3: Creates the dark visual theme, glowing elements, and atmospheric effects.
- JavaScript: Handles user interactions, conversation flow, and requests to the AI.
- Ollama: Runs the AI model locally and exposes a local API.
- Qwen3: The configured open-weight model for generating conversational responses.
The application is designed to send prompts to a local Ollama instance rather than relying on a remote AI API.
The idea is simple: the frontend creates the experience, while the locally running model brings the ghost to life.
This architecture also gives developers room to experiment with different compatible models and character instructions.
🌐 Why Does Open Innovation Matter?
For me, open innovation is about having the freedom to understand, experiment with, and adapt the technology we build upon.
Using a local AI model creates several opportunities:
🔒 Greater control over data
When configured for local inference, prompts can remain on the user's computer instead of being sent to a remote AI provider. This gives users greater control over their conversations.
🧠 Freedom to experiment
Developers can experiment with model choices, system prompts, personalities, and response behavior without tying the entire application to one proprietary AI API.
📡 Potential for offline use
After the model and required software have been downloaded, local inference can work without an internet connection, provided the application and its dependencies are available locally.
🛠️ Learning by building
Working with local AI makes the underlying architecture more tangible. Instead of treating AI as a black-box API, developers can explore how models are loaded, prompted, and integrated into applications.
There are trade-offs: local inference requires compatible hardware, model downloads consume storage, and performance depends on the model and device.
That trade-off is worth exploring because it gives developers more ownership of their applications.
🤖 My Agent Session
I used AI-assisted development to help design and build the project.
If I publish a DevRelay agent session for this project, I'll add it here so others can explore the development process.
🕯️ The Spirit of It
Halloween is a time for strange stories, unexplained signals, and things that seem to exist between the digital and the real.
Phantom AI takes that atmosphere and turns it into an interactive experiment.
The ghost is fictional. The AI behind it is real.
What makes the project interesting to me is the idea that an open-weight model can be given a personality, placed inside a creative interface, and run on a developer's own machine.
Perhaps the most interesting question isn't whether a ghost can live inside a computer.
It's what we can build when the intelligence inside that computer is open to experimentation.
🏆 Prize Categories
Challenge: Hacktoberfest Open-Source AI Challenge — Week 4: Ghost in the Machine.
This project explores the use of open-weight AI and local inference in a creative application.
🚀 Final Thoughts
Phantom AI is my experiment in combining creative frontend development with open-source AI.
I'm excited to keep improving it, explore different local models, and see what other developers can create with similar tools.
If you try the project or have ideas for making it better, I'd love to hear your feedback!
The machine is listening. 👻
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