Guides
Learn how to build RAG applications with the Neutron API
How Neutron Works
Ingestion
Upload and process your documentsDocument/Text
PDF, Text, Markdown
Seed
Content record
Chunks + Embeddings
~300 tokens, 1024-dim vectors
Vector DB
pgvector storage
Query (RAG)
Search and generate responsesQuestion
Natural language
Embedding
Query vectorization
Similarity Search
Find relevant chunks
Context
Merged results
LLM Response
GPT-4, Claude, etc.
5 min
Getting Started
Set up your first project and make your first API call in 5 minutes
Read guide
10 min
Core Concepts
Understand Seeds, Chunks, Bundles, and how the system works
Read guide
8 min
Data Ingestion
Learn how to upload documents, text, and manage your content
Read guide
8 min
Semantic Search
Query your content using natural language and get relevant results
Read guide
15 min
Building RAG Apps
Build a complete RAG application with OpenAI or Claude
Read guide
Quick Reference
Base API URL
https://api-neutron.vanarchain.comAuthentication
Authorization: Bearer nk_...