RAG Chatbot Template for Next.js
A Next.js RAG chatbot template with document ingestion, embeddings, vector search, reranking, and citation rendering. pgvector-based. WCAG AA accessible. In development.
0RAG (Retrieval-Augmented Generation) is what separates a chatbot from a generic LLM wrapper. Real RAG handles document ingestion at scale, semantic chunking, embedding generation, vector storage, hybrid retrieval, and reranking — then renders answers with clickable citations to the source. This Next.js RAG chatbot template is being built with all of that done correctly from day one.
Key Features
Document Ingestion
PDF, DOCX, HTML, Markdown via Unstructured.io. Async processing.
Semantic Chunking
Chunk by semantic boundaries, not fixed size. Better retrieval quality.
Hybrid Retrieval
Keyword + semantic search combined. Reranking via Cohere or OpenAI.
pgvector Storage
Postgres extension for vector embeddings. Cheaper than Pinecone, easier than Weaviate.
Citation Rendering
Inline [1] [2] references with source preview on hover. Clickable to underlying document.
WCAG AA Accessible
Keyboard-navigable, screen-reader-tested, color-contrast verified.
How thefrontkit Compares
| Feature | thefrontkit | Typical Alternatives |
|---|---|---|
| Production-Ready | Yes (in development) | Often demo-quality |
| WCAG AA Accessible | Built-in from day one | Usually missing |
| Source Ownership | You own the code | Often locked SaaS |
| Pricing Model | One-time payment | Per-seat monthly |
Ready to Ship Faster?
Skip the boilerplate and start building what matters. Production-ready, accessible, and token-synced.
View All Access (AI Chatbot Kit in Development) →