Semantic Image Search
This is an open-source AI semantic image search application template designed for developers looking to build intelligent image search capabilities into their projects. It leverages the power of Next.js, Vercel AI SDK, and various Vercel storage solutions to provide a robust and scalable solution.
Key Features:
- Next.js App Router: Utilizes the latest Next.js features for efficient routing and server-side rendering.
- Vercel AI SDK: Simplifies integration with AI models for multimodal prompting, metadata generation, and image embedding.
- Flexible AI Model Support: Supports OpenAI (GPT-4o default), Gemini, Anthropic, Cohere, and custom AI models via Vercel AI SDK.
- Vercel KV: Implements query caching for improved performance and reduced latency.
- Vercel Postgres with pgvector: Stores image embeddings for semantic search, leveraging the power of Vercel Postgres and the pgvector extension.
- Vercel Blob: Provides scalable and reliable file (image) storage.
- Tailwind CSS and Radix UI: Offers a modern and customizable user interface with Tailwind CSS and Radix UI component primitives.
Use Cases:
- E-commerce: Enable users to search for products based on semantic descriptions rather than just keywords.
- Content Management Systems: Allow content creators to easily find relevant images based on their meaning.
- Image Libraries: Provide a more intuitive way for users to explore and discover images in large collections.
- AI-powered applications: Build applications that require understanding the content of images.
