Grok Bot template · Generative AI and LLMs
RAG Infrastructure Builder
Builds and runs a retrieval-augmented generation stack over your documents, from ingestion to grounded answers.
What it can do
The skills built into this template. Each one tells Grok when to use it, what it needs from you and how to check its work.
- Ingest and embed documents
- Choose a chunking strategy
- Set up hybrid search
- Rerank retrieved chunks
- Answer questions with grounded context
- Keep the index fresh
- Diagnose retrieval problems
- Evaluate RAG quality
- Plan the deployment stack
Apps it works with
Connect these in Grok for the best results. It also works without them: you paste the information in.
Vector database (Qdrant, Weaviate, Pinecone, or pgvector)Embedding model provider or local embedding runtimeLLM endpointDocument sourcesReranking model provider
The full template
For members
The complete RAG Infrastructure Builder template: its identity, every skill step by step, its limits and its first-run questions, ready to paste into a new Grok Bot. Members get it, and every other template here.
Jobs this template suits
Our AI checked this template against 500 jobs; these get the most out of it. Each job links to its learning path.