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feat: fine grained access control policy (#2264)

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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>
This commit is contained in:
grs 2025-06-03 17:51:12 -04:00 • committed by GitHub
parent 8bee2954be
commit 7c1998db25
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32 changed files with 956 additions and 450 deletions
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4
llama_stack/providers/inline/agents/meta_reference/agents.py
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@ -41,6 +41,7 @@ from llama_stack.apis.inference import (
from llama_stack.apis.safety import Safety
from llama_stack.apis.tools import ToolGroups, ToolRuntime
from llama_stack.apis.vector_io import VectorIO
from llama_stack.distribution.datatypes import AccessRule
from llama_stack.providers.utils.kvstore import InmemoryKVStoreImpl, kvstore_impl
from llama_stack.providers.utils.pagination import paginate_records
from llama_stack.providers.utils.responses.responses_store import ResponsesStore
@ -62,6 +63,7 @@ class MetaReferenceAgentsImpl(Agents):
safety_api: Safety,
tool_runtime_api: ToolRuntime,
tool_groups_api: ToolGroups,
policy: list[AccessRule],
):
self.config = config
self.inference_api = inference_api
@ -72,6 +74,7 @@ class MetaReferenceAgentsImpl(Agents):
self.in_memory_store = InmemoryKVStoreImpl()
self.openai_responses_impl: OpenAIResponsesImpl | None = None
self.policy = policy
async def initialize(self) -> None:
self.persistence_store = await kvstore_impl(self.config.persistence_store)
@ -130,6 +133,7 @@ class MetaReferenceAgentsImpl(Agents):
self.persistence_store if agent_info.enable_session_persistence else self.in_memory_store
),
created_at=agent_info.created_at,
policy=self.policy,
)
async def create_agent_session(