Use Knowledge Base results in RAG, search and legal agent workflows.
Knowledge Base results are designed to be passed into product workflows as legal context. They work well in RAG systems, legal search interfaces and agent tool calls.
For a search interface:
send the user's search text to the retrieve endpoint;
show result titles, excerpts and source URLs;
group legislation results by work_frbr_uri when several portions come from the same work;
let users open portion_public_url or public_url to inspect the source.
For a RAG workflow:
retrieve the most relevant results;
build a context block from content.text, title, portion_title and source URLs;
ask the model to answer only from the provided context;
include citations or source links in the final answer.
Example context format:
Source: Animal By-law, 2011
URL: https://lawlibrary.org.za/akn/za-cpt/act/by-law/2011/animal/eng@2011-08-05#chp_7
Portion: Chapter 7 - Miscellaneous
Text: ...Knowledge Base retrieval provides legal context. It does not replace legal review, and AI-generated answers should make their sources clear.
For a legal agent, expose retrieval as a tool with inputs such as:
query: focused legal search text;
knowledge_base: the KB code to query;
place: optional place filter;
top_k: result count.
The agent should use the returned legal text and source URLs before drafting an answer or deciding whether it needs more information.
If results are too broad:
add place filters such as frbr_place;
apply principal: true and repealed: false for legislation;
reduce top_k;
rewrite the user question into more specific legal search terms.
If results are too narrow:
remove filters;
increase top_k;
query a broader Knowledge Base;
try alternative legal terms.
See the example repository for runnable integrations:
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