neuron-rag-specialist

What problem does it solve?

Neuron AI RAG specialist enables agents to retrieve and reason over external documents by integrating vector stores, embeddings, loaders, and retrieval strategies, reducing manual data access and improving answer quality.

Core Features & Use Cases

• Vector stores for scalable semantic search across documents
• Embeddings providers to convert text into meaningful vector representations
• Document loaders and chunking strategies to prepare data for retrieval
• Retrieval strategies to balance relevance, coverage, and response time
• Use cases: chat with documents, knowledge-base queries, and large corpus question answering

Quick Start

Instantiate a RAG-enabled agent by wiring a vector store, an embeddings provider, and a retrieval strategy, then load documents and begin asking questions.