This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine
What if debugging your code felt a little less scary? 👻
As a first-year Computer Science student, I'm still learning programming and exploring how AI can make development easier. For the Hacktoberfest Week 4 challenge, I built PhantomCode – Haunted AI Lab.
What I Built
PhantomCode is a Python-based AI coding assistant designed to help developers understand code, identify common errors, and spot basic security risks.
✨ Features
AI Code Assistant: Helps explain and review Python code.
Error Analyzer: Helps understand common programming errors.
Security Scanner: Checks for potentially risky coding patterns.
AI Chat Assistant: Lets users ask programming-related questions.
Haunted Interface: A spooky-themed dashboard built with Streamlit.
Demo
codesnippet-lab
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PhantomCode--Week4
AI-powered haunted coding assistant
👻 PhantomCode – Haunted AI Coding Lab
Your AI Coding Companion — Debugging Beyond the Grave.
PhantomCode is a colourful, Halloween-inspired AI coding assistant built with Python and Streamlit.
✨ Features
- 💻 Code Assistant – Understand Python code with AI explanations.
- 🔍 Error Analyzer – Investigate Python errors and get suggested fixes.
- 🛡️ Security Scanner – Detect common security risks in Python code.
- 💬 AI Chat – Ask programming questions using an open-weight AI model.
🛠️ Tech Stack
- Python
- Streamlit
- Groq API
- Open-weight GPT-OSS model
🚀 Run Locally
-
Clone this repository:
git clone YOUR_GITHUB_REPOSITORY_URL -
Enter the project folder:
cd PhantomCode-Week4 -
Install dependencies:
pip install -r requirements.txt -
Add your Groq API key using Streamlit secrets or the app's API key field.
-
Start the application:
streamlit run app.py
🔐 API Key Security
Never commit API keys or secrets to GitHub. For deployment, configure sensitive values using Streamlit Community Cloud secrets.
🎃 Hacktoberfest
…Code
Github repository : https://github.com/codesnippet-lab/PhantomCode--Week4
How I Built It
🛠️ Tech Stack
Python
Streamlit
Groq API
Open-weight GPT-OSS model
Why Does Open Innovation Matter?
used an open-weight AI model through Groq to power the AI features. Open-weight models give developers more flexibility to explore how AI works, experiment with different models, and build applications without being limited to one closed model ecosystem.
As a beginner, this project helped me understand how AI APIs can be integrated into a real application.
My Agent Session
The Spirit of It
Prize Categories
Built with curiosity, code, and a little bit of spooky energy. 👻
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