Hermes retrieves register details from an AMD manual

Barnet1123 wanted to ask detailed questions of very large technical manuals while running a local model. The author built a document-structuring skill for Hermes with SQLite FTS5 retrieval, avoiding a large vector database and the need to put an entire manual into the model’s context.

The reported test used 3,799 pages of AMD technical documentation, about 1.05 million words. Parsing took roughly fourteen minutes on an AMD FireRange processor. The setup was Windows 11, Ollama and Qwen3.6:27b.

For comparison, the author asked a specific, colloquially phrased question about a register’s bit functions. Dumping all text consumed roughly 2,794,829 tokens and produced an unfocused, hallucinating response. Targeted retrieval used about 2,244 tokens; the author says the agent found the exact section and answered correctly.

The important research pattern is structural indexing followed by retrieval of the relevant definition, rather than treating text extraction alone as the end of document preparation. The account links the implementation and explains that its aim is finding a register definition without loading thousands of pages.

This is an author-run local comparison, not an independently reproduced benchmark. The exact register, full question and evaluated answer are not published in the post, and the author explicitly says cloud-model effects remain untested. The result supports one reported retrieval success without establishing universal accuracy for hardware specifications.

Prompt
Suggested prompt (written by Agents In Use, not the author's)

Source: Reddit · u/Barnet1123 on Reddit