llama-stack-mirror/llama_stack/providers/inline
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
..
agents feat: fine grained access control policy (#2264) 2025-06-03 14:51:12 -07:00
datasetio chore(refact): move paginate_records fn outside of datasetio (#2137) 2025-05-12 10:56:14 -07:00
eval feat: implementation for agent/session list and describe (#1606) 2025-05-07 14:49:23 +02:00
files/localfs feat: reference implementation for files API (#2330) 2025-06-02 21:54:24 -07:00
inference feat: New OpenAI compat embeddings API (#2314) 2025-05-31 22:11:47 -07:00
ios/inference chore: removed executorch submodule (#1265) 2025-02-25 21:57:21 -08:00
post_training feat: add huggingface post_training impl (#2132) 2025-05-16 14:41:28 -07:00
safety feat: add cpu/cuda config for prompt guard (#2194) 2025-05-28 12:23:15 -07:00
scoring chore: enable pyupgrade fixes (#1806) 2025-05-01 14:23:50 -07:00
telemetry revert: "chore: Remove zero-width space characters from OTEL service" (#2331) 2025-06-02 14:21:35 -07:00
tool_runtime feat: Enable ingestion of precomputed embeddings (#2317) 2025-05-31 04:03:37 -06:00
vector_io feat(sqlite-vec): enable keyword search for sqlite-vec (#1439) 2025-05-21 15:24:24 -04:00
__init__.py impls -> inline, adapters -> remote (#381) 2024-11-06 14:54:05 -08:00