Get Most Relevant Facts for an Arbitrary Query

In this recipe, we demonstrate how to retrieve the most relevant facts from the knowledge graph using an arbitrary search query.

Search the graph

First, we perform an edge search on the knowledge graph using a sample query. The search takes the graph_uuid of the graph. For a user graph, use the graph_uuid that user.create returns, and store it next to your own user ID:

from zep_cloud.client import Zep
zep_client = Zep(api_key=API_KEY)
results = zep_client.graph.search_edges(zep_graph_uuid, query="Some search query")

Build the fact list

Then, we get the edges from the first page of search results and construct our fact list. We also include the temporal validity data to each fact string:

# Build list of formatted facts
relevant_edges = results.items or []
formatted_facts = []
for edge in relevant_edges:
    valid_at = edge.valid_at if edge.valid_at is not None else "date unknown"
    invalid_at = edge.invalid_at if edge.invalid_at is not None else "present"
    formatted_fact = f"{edge.fact} (Date range: {valid_at} - {invalid_at})"
    formatted_facts.append(formatted_fact)
# Print the results
print("\nFound facts:")
for fact in formatted_facts:
    print(f"- {fact}")

Summary

We demonstrated how to retrieve the most relevant facts for an arbitrary query using the Zep client. Adjust the query and parameters as needed to tailor the search for your specific use case.