llama-stack-mirror/tests/unit
grs 7c1998db25
feat: fine grained access control policy (#2264)
This allows a set of rules to be defined for determining access to
resources. The rules are (loosely) based on the cedar policy format.

A rule defines a list of action either to permit or to forbid. It may
specify a principal or a resource that must match for the rule to take
effect. It may also specify a condition, either a 'when' or an 'unless',
with additional constraints as to where the rule applies.

A list of rules is held for each type to be protected and tried in order
to find a match. If a match is found, the request is permitted or
forbidden depening on the type of rule. If no match is found, the
request is denied. If no rules are specified for a given type, a rule
that allows any action as long as the resource attributes match the user
attributes is added (i.e. the previous behaviour is the default.

Some examples in yaml:

```
    model:
    - permit:
      principal: user-1
      actions: [create, read, delete]
      comment: user-1 has full access to all models
    - permit:
      principal: user-2
      actions: [read]
      resource: model-1
      comment: user-2 has read access to model-1 only
    - permit:
      actions: [read]
      when:
        user_in: resource.namespaces
      comment: any user has read access to models with matching attributes
    vector_db:
    - forbid:
      actions: [create, read, delete]
      unless:
        user_in: role::admin
      comment: only user with admin role can use vector_db resources
```

---------

Signed-off-by: Gordon Sim <gsim@redhat.com>
2025-06-03 14:51:12 -07:00
..
cli chore: enable pyupgrade fixes (#1806) 2025-05-01 14:23:50 -07:00
distribution feat: fine grained access control policy (#2264) 2025-06-03 14:51:12 -07:00
files feat: reference implementation for files API (#2330) 2025-06-02 21:54:24 -07:00
models chore: remove usage of load_tiktoken_bpe (#2276) 2025-06-02 07:33:37 -07:00
providers feat: fine grained access control policy (#2264) 2025-06-03 14:51:12 -07:00
rag feat: Enable ingestion of precomputed embeddings (#2317) 2025-05-31 04:03:37 -06:00
registry feat: fine grained access control policy (#2264) 2025-06-03 14:51:12 -07:00
server feat: fine grained access control policy (#2264) 2025-06-03 14:51:12 -07:00
utils feat: support postgresql inference store (#2310) 2025-05-29 14:33:09 -07:00
__init__.py chore: Add fixtures to conftest.py (#2067) 2025-05-06 13:57:48 +02:00
conftest.py chore: Add fixtures to conftest.py (#2067) 2025-05-06 13:57:48 +02:00
fixtures.py chore: Add fixtures to conftest.py (#2067) 2025-05-06 13:57:48 +02:00
README.md docs: revamp testing documentation (#2155) 2025-05-13 11:28:29 -07:00

Llama Stack Unit Tests

You can run the unit tests by running:

source .venv/bin/activate
./scripts/unit-tests.sh [PYTEST_ARGS]

Any additional arguments are passed to pytest. For example, you can specify a test directory, a specific test file, or any pytest flags (e.g., -vvv for verbosity). If no test directory is specified, it defaults to "tests/unit", e.g:

./scripts/unit-tests.sh tests/unit/registry/test_registry.py -vvv

If you'd like to run for a non-default version of Python (currently 3.10), pass PYTHON_VERSION variable as follows:

source .venv/bin/activate
PYTHON_VERSION=3.13 ./scripts/unit-tests.sh