Day 4 ยท Fri, Oct 2, 2026
RAG with Hermes
A local LLM only knows what it was trained on โ ask it about a document it's never seen and it will either say so or, worse, confidently guess. Today grounds Hermes Agent in real data instead: standing up a vector store, feeding it real documents, and connecting Hermes to it as a tool it can query before answering.
Objectives
- Stand up a standalone vector store (ChromaDB) and load it with real documents
- Wire retrieval into Hermes as a tool it can call, not a manual copy-paste step
- Ask Hermes questions that require the retrieved context to answer correctly
- Deliberately test a question the documents don't cover, to see how Hermes handles it
Lab: ground Hermes in a real document set
With a ChromaDB instance already loaded with course material (following the same setup as our earlier ChromaDB RAG walkthrough), register it as an MCP tool Hermes can call, then ask it a grounded question:
$ hermes mcp add chroma-rag --command uvx --args mcp-server-chroma$ hermes -z "Using the retrieval tool, what does our course material say about MCP servers? Cite what you found." --cli --yoloBefore running this live:confirm which document set is loaded into the vector store โ pointing the RAG tool at the wrong collection produces a confidently wrong answer instead of an honest "I don't know," which is worse for teaching than no RAG at all.
Session notes: to be filled in after the live session on Oct 2, 2026 โ document set used, the real grounded answer we got, and what happened on the out-of-scope question.