moca-reader-llamaindex
A LlamaIndex retriever over MOCA packages, built on the MOCA Reader for Python.
pip install moca-reader-llamaindexfrom moca_reader import LexicalBackend, Library, Search, read_packagefrom moca_reader_llamaindex import MocaRetriever
pkg = read_package("support-kb.moca", trust_root="trust-root.json")library = Library().add(pkg)search = Search(library, LexicalBackend(library), audiences=["public"])
retriever = MocaRetriever(search, limit=3)for result in retriever.retrieve("How long is the refund window?"): print(result.node.metadata["moca_node_ref"], result.score) print(result.node.get_content()[:80])MocaRetriever wraps the Search you build: its backend (lexical, dense,
hybrid or your own store), its audiences and its hooks. Every call goes through
the Reader’s gate, so content that is out of force, superseded, deprecated or
outside your audiences never comes back, and nothing a caller passes can widen
that. Use it anywhere LlamaIndex takes a retriever, such as a
RetrieverQueryEngine.
Each result is a NodeWithScore holding a TextNode:
| Field | Holds |
|---|---|
text |
The text of the node, or of a sidecar chunk |
node_id |
The node’s versioned reference and byte span |
metadata["moca_citation"] |
The whole citation record: package, version and digest, trust signals, evidence |
metadata["moca_*"] |
The flat fields of the consuming guide (moca_node_ref, moca_package_digest, moca_status, moca_signed, …) |
score |
The search score |
The MOCA metadata keys are excluded from the text LlamaIndex sends to a model or an embedder, so they travel with the node without filling the prompt.
Package text is untrusted input. Present it to a model as quoted reference
material to cite, never as instructions
(Reader contract §12).
Show users the source (moca_node_ref, the package version) with each answer.
Licence
Section titled “Licence”Apache-2.0.