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chore(api): add mypy coverage to meta_reference

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Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>
This commit is contained in:
Mustafa Elbehery 2025-07-08 20:55:17 +02:00
parent 1d8c00635c
commit f617a28164
3 changed files with 55 additions and 29 deletions
Download patch file Download diff file Expand all files Collapse all files

49
llama_stack/providers/inline/agents/meta_reference/openai_responses.py
View file

@ -91,7 +91,7 @@ async def _convert_response_content_to_chat_content(
if isinstance(content, str):
return content
converted_parts = []
converted_parts: list[OpenAIChatCompletionContentPartParam] = []
for content_part in content:
if isinstance(content_part, OpenAIResponseInputMessageContentText):
converted_parts.append(OpenAIChatCompletionContentPartTextParam(text=content_part.text))
@ -136,7 +136,7 @@ async def _convert_response_input_to_chat_messages(
),
)
messages.append(OpenAIAssistantMessageParam(tool_calls=[tool_call]))
else:
elif isinstance(input_item, OpenAIResponseMessage):
content = await _convert_response_content_to_chat_content(input_item.content)
message_type = await _get_message_type_by_role(input_item.role)
if message_type is None:
@ -144,6 +144,11 @@ async def _convert_response_input_to_chat_messages(
f"Llama Stack OpenAI Responses does not yet support message role '{input_item.role}' in this context"
)
messages.append(message_type(content=content))
else:
# Handle other tool call types that don't have content/role attributes
raise ValueError(
f"Llama Stack OpenAI Responses does not yet support input item type '{type(input_item)}' in this context"
)
else:
messages.append(OpenAIUserMessageParam(content=input))
return messages
@ -175,13 +180,17 @@ async def _convert_response_text_to_chat_response_format(text: OpenAIResponseTex
"""
Convert an OpenAI Response text parameter into an OpenAI Chat Completion response format.
"""
if not text.format or text.format["type"] == "text":
if not text.format or text.format.get("type") == "text":
return OpenAIResponseFormatText(type="text")
if text.format["type"] == "json_object":
if text.format.get("type") == "json_object":
return OpenAIResponseFormatJSONObject()
if text.format["type"] == "json_schema":
if text.format.get("type") == "json_schema":
name = text.format.get("name")
schema = text.format.get("schema")
if name is None or schema is None:
raise ValueError(f"json_schema format requires both name and schema fields")
return OpenAIResponseFormatJSONSchema(
json_schema=OpenAIJSONSchema(name=text.format["name"], schema=text.format["schema"])
json_schema=OpenAIJSONSchema(name=name, schema=schema)
)
raise ValueError(f"Unsupported text format: {text.format}")
@ -472,11 +481,12 @@ class OpenAIResponsesImpl:
response_tool_call = chat_response_tool_calls.get(tool_call.index, None)
if response_tool_call:
# Don't attempt to concatenate arguments if we don't have any new argumentsAdd commentMore actions
if tool_call.function.arguments:
if tool_call.function and tool_call.function.arguments:
# Guard against an initial None argument before we concatenate
response_tool_call.function.arguments = (
response_tool_call.function.arguments or ""
) + tool_call.function.arguments
if response_tool_call.function:
response_tool_call.function.arguments = (
response_tool_call.function.arguments or ""
) + tool_call.function.arguments
else:
tool_call_dict: dict[str, Any] = tool_call.model_dump()
tool_call_dict.pop("type", None)
@ -530,15 +540,16 @@ class OpenAIResponsesImpl:
next_turn_messages.append(tool_response_message)
for tool_call in function_tool_calls:
output_messages.append(
OpenAIResponseOutputMessageFunctionToolCall(
arguments=tool_call.function.arguments or "",
call_id=tool_call.id,
name=tool_call.function.name or "",
id=f"fc_{uuid.uuid4()}",
status="completed",
if tool_call.function:
output_messages.append(
OpenAIResponseOutputMessageFunctionToolCall(
arguments=tool_call.function.arguments or "",
call_id=tool_call.id,
name=tool_call.function.name or "",
id=f"fc_{uuid.uuid4()}",
status="completed",
)
)
)
if not function_tool_calls and not non_function_tool_calls:
break
@ -602,7 +613,7 @@ class OpenAIResponsesImpl:
required=param.required,
default=param.default,
)
for param in tool.parameters
for param in (tool.parameters or [])
},
)
return convert_tooldef_to_openai_tool(tool_def)

33
llama_stack/providers/inline/agents/meta_reference/persistence.py
View file

@ -11,7 +11,8 @@ from datetime import UTC, datetime
from llama_stack.apis.agents import AgentConfig, Session, ToolExecutionStep, Turn
from llama_stack.distribution.access_control.access_control import AccessDeniedError, is_action_allowed
from llama_stack.distribution.access_control.datatypes import AccessRule
from llama_stack.distribution.access_control.conditions import User as ProtectedResourceUser
from llama_stack.distribution.access_control.datatypes import AccessRule, Action
from llama_stack.distribution.datatypes import User
from llama_stack.distribution.request_headers import get_authenticated_user
from llama_stack.providers.utils.kvstore import KVStore
@ -23,8 +24,8 @@ class AgentSessionInfo(Session):
# TODO: is this used anywhere?
vector_db_id: str | None = None
started_at: datetime
owner: User | None = None
identifier: str | None = None
owner: ProtectedResourceUser
identifier: str
type: str = "session"
@ -43,17 +44,21 @@ class AgentPersistence:
# Get current user's auth attributes for new sessions
user = get_authenticated_user()
# If no user is authenticated, create a default user for backward compatibility
if user is None:
user = User(principal="anonymous", attributes=None)
session_info = AgentSessionInfo(
session_id=session_id,
session_name=name,
started_at=datetime.now(UTC),
owner=user,
owner=user, # User from datatypes is compatible with ProtectedResourceUser protocol
turns=[],
identifier=name, # should this be qualified in any way?
)
if not is_action_allowed(self.policy, "create", session_info, user):
raise AccessDeniedError("create", session_info, user)
if not is_action_allowed(self.policy, Action.CREATE, session_info, user):
raise AccessDeniedError(Action.CREATE, session_info, user)
await self.kvstore.set(
key=f"session:{self.agent_id}:{session_id}",
@ -68,7 +73,17 @@ class AgentPersistence:
if not value:
return None
session_info = AgentSessionInfo(**json.loads(value))
session_data = json.loads(value)
# Handle backward compatibility for sessions without owner field
if "owner" not in session_data or session_data["owner"] is None:
session_data["owner"] = User(principal="anonymous", attributes=None)
# Handle backward compatibility for sessions without identifier field
if "identifier" not in session_data or session_data["identifier"] is None:
session_data["identifier"] = session_data.get("session_name", "unknown")
session_info = AgentSessionInfo(**session_data)
# Check access to session
if not self._check_session_access(session_info):
@ -79,10 +94,10 @@ class AgentPersistence:
def _check_session_access(self, session_info: AgentSessionInfo) -> bool:
"""Check if current user has access to the session."""
# Handle backward compatibility for old sessions without access control
if not hasattr(session_info, "access_attributes") and not hasattr(session_info, "owner"):
if not hasattr(session_info, "access_attributes"):
return True
return is_action_allowed(self.policy, "read", session_info, get_authenticated_user())
return is_action_allowed(self.policy, Action.READ, session_info, get_authenticated_user())
async def get_session_if_accessible(self, session_id: str) -> AgentSessionInfo | None:
"""Get session info if the user has access to it. For internal use by sub-session methods."""

2
pyproject.toml
View file

@ -242,7 +242,7 @@ exclude = [
"^llama_stack/models/llama/llama3/interface\\.py$",
"^llama_stack/models/llama/llama3/tokenizer\\.py$",
"^llama_stack/models/llama/llama3/tool_utils\\.py$",
"^llama_stack/providers/inline/agents/meta_reference/",
"^llama_stack/models/llama/llama3_3/prompts\\.py$",
"^llama_stack/providers/inline/agents/meta_reference/agent_instance\\.py$",
"^llama_stack/providers/inline/agents/meta_reference/agents\\.py$",
"^llama_stack/providers/inline/datasetio/localfs/",