Run your first query
This tutorial searches a HSSMCortex store that has already been populated. You will confirm the local prerequisites, issue a semantic search, and then compare it with a graph query.
Execution status
Documentation CI strictly builds this page, but it does not execute the
runtime query subcommands. They require a populated local Cognee store and
configured model credentials; verify them manually against the store you
intend to use. The --help check below does not access the store.
Prerequisites
You need:
- Python 3.11 or newer and uv;
- a clone of HSSMCortex with
uv synccompleted; - an existing populated Cognee data directory; and
ANTHROPIC_API_KEYin the environment or in~/.secrets/anthropic-api-key.
By default, Cortex reads the store from .cognee/ in the repository. To use a
different store, set COGNEE_DATA_PATH before running a query.
1. Confirm the command surface
From the repository root, inspect the installed command:
The command lists search, graph, summaries, and ask. This tutorial uses
the first two because they expose the distinction between vector retrieval and
graph-assisted retrieval most directly.
2. Search paper chunks
Run a semantic search and request three results:
uv run cortex-query search \
"What likelihood methods are used for drift-diffusion models?" \
--top-k 3
Successful output begins with 3 result(s) (semantic search) when at least
three matches are available. Each result is a chunk from the ingested corpus;
it is retrieval context, not a new reviewed Cortex document.
3. Follow an entity through the graph
Now query relationships associated with an entity:
Graph results are generated from relationships extracted during ingestion. Use them to discover connections, then verify important claims against the reviewed summary and source paper before relying on them.
4. Try the other retrieval modes
uv run cortex-query summaries "likelihood approximation networks" --top-k 3
uv run cortex-query ask "How do LANs relate to analytic likelihoods?" --top-k 5
summaries searches document-level summaries. ask asks Cognee to combine
graph and summary context and may use more model calls; it should not be
treated as a canonical publication record.
Troubleshooting
- No API key: set
ANTHROPIC_API_KEY; the CLI exits before configuring Cognee when the key is absent. - No results or missing tables: populate the selected store by following Ingest reviewed content.
- Wrong local store: set
COGNEE_DATA_PATHto the directory used during ingestion and retry.