Manage RAG libraries for context-aware AI responses.
Libraries are collections of documents that are indexed and embedded for semantic search. When connected to an admin, they provide context for LLM queries, enabling more accurate and relevant responses.
Create a new library and index documents.
$ cicerone library new docs --path ~/Documents Creating library 'docs'... Path: /home/user/Documents Model: nomic-embed-text Indexing files... +42 files added Library created successfully!
--path, -p - Path to library documents--model, -m - Embedding model (default: nomic-embed-text)Display all configured libraries.
$ cicerone library show NAME MODEL DOCS PATH ────────────────────────────────────────────────── docs nomic-embed-text 42 /home/user/Documents projects mxbai-embed-large 128 /home/user/projects
Reindex library documents.
$ cicerone library refresh docs Refreshing library 'docs'... Added: 5 Updated: 3 ✓ Refresh complete!
--all, -a - Refresh all librariesRemove a library from the registry.
$ cicerone library remove docs Removing library 'docs'... Path: /home/user/Documents Files indexed: 42 Note: Documents remain in RAG database until refresh. ✓ Library removed from registry.
Text files are automatically indexed:
.go .py .js .ts .java .c .cpp .h .sh
.json .yaml .yml .xml .toml .conf .cfg .ini
.md .txt .rst .adoc .tex .bib .csv .sql
No libraries configured. Run cicerone library new <name> --path <path> to create one.
~/.cicerone/libraries.json # Library registry ~/.cicerone/rag.json # RAG database (embeddings)