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Mobile travel feed
A React Native feed for practicing content rendering, navigation, state, uploads and user-generated exploration content.
Project overview
A collaborative AI travel project where contributors practice mobile engineering, backend design, geospatial data, and grounded conversational AI.
Explorix gives contributors hands-on experience with React Native and Expo across feed design, maps, user profiles, uploads, GPS, camera access and offline storage.
FastAPI powers REST APIs, authentication, AI endpoints, POI retrieval, feed management and upload processing. PostgreSQL and PostGIS help contributors learn nearby place search, distance calculations, radius queries and geo-deduplication.
The AI layer uses Llama 3.2 for travel Q&A, recommendations and trip planning. MongoDB stores lightweight AI memory and chat context, while RAG helps contributors understand grounded AI responses using places retrieved from PostgreSQL.
A React Native feed for practicing content rendering, navigation, state, uploads and user-generated exploration content.
PostGIS powers ST_DWithin radius queries, ST_Distance calculations and nearby place discovery.
Contributors learn mobile permissions, profile workflows, media handling and content contribution flows.
Llama 3.2 supports city exploration, travel Q&A, recommendations and trip planning.
PostgreSQL retrieval injects real place context into prompts before the assistant generates an answer.
JWT authentication and Google SSO support secure mobile sessions and quick onboarding.
The contributors behind the build and the engineering areas they owned.
Originally built Explorix as his thesis project and led the architecture, backend, cloud, ML fine-tuning, RAG and AI learning path.
Enhanced user matching in local places workflows and later improved the RAG connection using prepared engineering data.
Worked with Manoj on frontend improvements and helped with fine-tuning data preparation, testing and DNS handling.
Helped with data extraction and database handling, collaborating with Manoj on the data layer behind the project.