This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend
What I Built
I built the DC Roommate Slang Bridgeâa 100% offline, local-first cultural translator and roommate linguistic bridge designed specifically for trainees at the Infosys Mysore DC campus.
During training, thousands of trainees from all across India converge onto the massive 337-acre Mysore campus. This brings a massive collision of regional languages, heavy regional slangs, GEC academic panic, JC food court plans, and ECC hostel banter. Communication barriers and cultural misunderstandings between roommates can sometimes lead to hilarious confusion. I built this app for my hostel roomies and batchmates to instantly decode regional slang, hostel jokes, and campus lingo with zero cloud dependency and 100% privacy, ensuring that unstable hostel Wi-Fi never breaks the vibe or the communication loop.
Demo
Because this application runs entirely offline using Ollama for absolute privacy and zero-latency hostel Wi-Fi resilience, it runs locally on your machine:
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Frontend UI (
localhost:8501): Built with Streamlit, featuring real-time campus status badges (indicating 337-Acre Mysore DC, GEC/JC/ECC zones, active dictionary term counts, and offline engine state), structured 3-part breakdown cards (Direct Meaning, Vibe & Tone, and On-Campus Context), cultural nuance notes, and ready-to-use roommate response suggestions. -
Local LAN Sharing: Can be seamlessly hosted locally across roomies' devices via
streamlit run frontend/app.py --server.address 0.0.0.0over the local hostel Wi-Fi network so roommates can access it instantly on their phones or laptops.
Code
Get the complete code: https://github.com/AbhavyaManchanda/SlangBridgeDC
The project follows a clean, modular full-stack architecture separating local inference, dictionary management, and the reactive UI:
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backend/main.py: The FastAPI server entry point handling translation endpoints, CORS configuration, and real-time backend health status checks. -
backend/ollama_service.py: Manages communication with the local Ollama daemon, structuring system prompts to ground model responses strictly in campus context. -
backend/dictionary_service.py: Loads and queries the local campus dictionary database (data/campus_dictionary.json), handling localized term matching. -
frontend/app.py&frontend/components.py: Streamlit-powered reactive frontend rendering clean UI components, breakdown cards, and sidebar controls. -
frontend/styles.css: Custom CSS styling tuned for a modern, dark-mode friendly campus aesthetic.
How I Built It
The project is architected as a local-first, privacy-focused full-stack application using open-source tools:
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Local Inference Engine (
Ollama): Powered by open-weight local models (llama3/gemma2) running locally on port11434. This ensures 100% offline functionality without requiring external API keys, internet connectivity, or paid cloud tokens. -
Backend Architecture (
FastAPI&Pydantic): Built using FastAPI for high-performance asynchronous request handling. Pydantic models (TranslationBreakdown,DictionaryTerm,AddTermRequest) ensure strict data validation and structured JSON responses between the UI and the inference engine. -
Frontend & UI Layer (
Streamlit): Designed with custom container layouts, clean Markdown cards, and real-time backend health monitoring to deliver a seamless user experience.
Why Does Open Innovation Matter?
Open innovation and open-weight local models made this project possible in a way a closed commercial API (like OpenAI or Anthropic) never could.
Hostel and campus networks can often be throttled, restricted, or plagued by high latency, and relying on cloud APIs means absolute internet dependency. By leveraging open-weight models via Ollama, trainees can run heavy intelligence directly on their local laptops without internet access, zero API costs, and complete data privacy regarding personal hostel banter and regional expressions. Open-source local tooling gives developers true sovereignty over their software stack.
Prize Categories
- Open Source AI / Local-First Apps
- Hacktoberfest Weekend Challenge
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