This directory hosts AI Database vector development sample applications demonstrating how to build AI-powered experiences with vector APIs. Each entry links directly to the app folder so you can dive into its README and source code.
For Python development with AI Database vector APIs, see the Oracle VecDB Python SDK.
| Title | Stack | Highlights | Path |
|---|---|---|---|
| Doc Chatbot | Streamlit, AI Database vector APIs, OpenAI/Ollama | Upload documents, embed them, and chat with retrieval-augmented answers citing source chunks. | Open |
| Fashion Product Search | FastAPI, React, AI Database vector APIs, Transformers | Multimodal search over product catalog images and descriptions with metadata filtering and streaming assets. | Open |
| Product Recommendation | FastAPI, React, AI Database vector APIs, CLIP | Semantic search and recommendation flow for catalog items with pricing filters and CLIP embeddings. | Open |
| Semantic Code Search | FastAPI, React, AI Database vector APIs, Jina Embeddings | Index Python repositories and explore relevant code via similarity search with expandable context panes. | Open |
| Ask the Parks | Python, AI Database vector APIs, Leaflet | Semantic National Park Service search with city/radius and GeoJSON QBE filters, map results, and park details. | Open |
Looking for notebook tutorials instead? Jump to the Sample Notebooks collection.