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feat(agents)!: changing agents API signatures to use OpenAI types
Replace legacy Message/SamplingParams usage with OpenAI chat message structures across agents: schemas, meta-reference implementation, and tests now rely on OpenAI message/tool payloads and generation knobs.
This commit is contained in:
Ashwin Bharambe
parent
548ccff368
commit
c56b2deb7d
6 changed files with 392 additions and 305 deletions
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@ -11,19 +11,18 @@ from typing import Annotated, Any, Literal, Protocol, runtime_checkable
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from pydantic import BaseModel, ConfigDict, Field
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from llama_stack.apis.common.content_types import URL, ContentDelta, InterleavedContent
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from llama_stack.apis.common.content_types import URL, ContentDelta
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from llama_stack.apis.common.responses import Order, PaginatedResponse
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from llama_stack.apis.inference import (
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CompletionMessage,
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ResponseFormat,
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SamplingParams,
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ToolCall,
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OpenAIAssistantMessageParam,
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OpenAIChatCompletionMessageContent,
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OpenAIChatCompletionToolCall,
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OpenAIMessageParam,
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OpenAIResponseFormatParam,
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OpenAIToolMessageParam,
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ToolChoice,
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ToolConfig,
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ToolPromptFormat,
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ToolResponse,
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ToolResponseMessage,
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UserMessage,
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)
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from llama_stack.apis.safety import SafetyViolation
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from llama_stack.apis.tools import ToolDef
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@ -63,7 +62,7 @@ class Attachment(BaseModel):
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:param mime_type: The MIME type of the attachment.
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"""
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content: InterleavedContent | URL
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content: OpenAIChatCompletionMessageContent | URL
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mime_type: str
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@ -74,7 +73,7 @@ class Document(BaseModel):
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:param mime_type: The MIME type of the document.
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"""
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content: InterleavedContent | URL
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content: OpenAIChatCompletionMessageContent | URL
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mime_type: str
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@ -108,6 +107,7 @@ class StepType(StrEnum):
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memory_retrieval = "memory_retrieval"
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@json_schema_type
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@json_schema_type
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class InferenceStep(StepCommon):
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"""An inference step in an agent turn.
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@ -118,7 +118,8 @@ class InferenceStep(StepCommon):
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model_config = ConfigDict(protected_namespaces=())
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step_type: Literal[StepType.inference] = StepType.inference
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model_response: CompletionMessage
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model_response: OpenAIAssistantMessageParam
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finish_reason: str | None = None
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@json_schema_type
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@ -130,8 +131,8 @@ class ToolExecutionStep(StepCommon):
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"""
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step_type: Literal[StepType.tool_execution] = StepType.tool_execution
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tool_calls: list[ToolCall]
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tool_responses: list[ToolResponse]
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tool_calls: list[OpenAIChatCompletionToolCall]
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tool_responses: list[OpenAIToolMessageParam]
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@json_schema_type
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@ -156,7 +157,7 @@ class MemoryRetrievalStep(StepCommon):
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step_type: Literal[StepType.memory_retrieval] = StepType.memory_retrieval
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# TODO: should this be List[str]?
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vector_db_ids: str
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inserted_context: InterleavedContent
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inserted_context: OpenAIChatCompletionMessageContent
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Step = Annotated[
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@ -181,9 +182,10 @@ class Turn(BaseModel):
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turn_id: str
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session_id: str
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input_messages: list[UserMessage | ToolResponseMessage]
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input_messages: list[OpenAIMessageParam]
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steps: list[Step]
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output_message: CompletionMessage
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output_message: OpenAIAssistantMessageParam
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finish_reason: str | None = None
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output_attachments: list[Attachment] | None = Field(default_factory=lambda: [])
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started_at: datetime
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@ -216,31 +218,22 @@ register_schema(AgentToolGroup, name="AgentTool")
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class AgentConfigCommon(BaseModel):
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sampling_params: SamplingParams | None = Field(default_factory=SamplingParams)
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max_output_tokens: int | None = None
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temperature: float | None = None
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top_p: float | None = None
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stop: list[str] | None = None
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input_shields: list[str] | None = Field(default_factory=lambda: [])
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output_shields: list[str] | None = Field(default_factory=lambda: [])
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toolgroups: list[AgentToolGroup] | None = Field(default_factory=lambda: [])
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client_tools: list[ToolDef] | None = Field(default_factory=lambda: [])
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tool_choice: ToolChoice | None = Field(default=None, deprecated="use tool_config instead")
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tool_prompt_format: ToolPromptFormat | None = Field(default=None, deprecated="use tool_config instead")
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input_shields: list[str] | None = Field(default_factory=list)
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output_shields: list[str] | None = Field(default_factory=list)
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toolgroups: list[AgentToolGroup] | None = Field(default_factory=list)
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client_tools: list[OpenAIResponseInputTool | ToolDef] | None = Field(default_factory=list)
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tool_config: ToolConfig | None = Field(default=None)
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max_infer_iters: int | None = 10
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def model_post_init(self, __context):
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if self.tool_config:
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if self.tool_choice and self.tool_config.tool_choice != self.tool_choice:
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raise ValueError("tool_choice is deprecated. Use tool_choice in tool_config instead.")
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if self.tool_prompt_format and self.tool_config.tool_prompt_format != self.tool_prompt_format:
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raise ValueError("tool_prompt_format is deprecated. Use tool_prompt_format in tool_config instead.")
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else:
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params = {}
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if self.tool_choice:
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params["tool_choice"] = self.tool_choice
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if self.tool_prompt_format:
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params["tool_prompt_format"] = self.tool_prompt_format
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self.tool_config = ToolConfig(**params)
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if self.tool_config is None:
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self.tool_config = ToolConfig()
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@json_schema_type
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@ -258,7 +251,7 @@ class AgentConfig(AgentConfigCommon):
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instructions: str
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name: str | None = None
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enable_session_persistence: bool | None = False
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response_format: ResponseFormat | None = None
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response_format: OpenAIResponseFormatParam | None = None
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@json_schema_type
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@ -434,10 +427,7 @@ class AgentTurnCreateRequest(AgentConfigOverridablePerTurn):
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agent_id: str
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session_id: str
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# TODO: figure out how we can simplify this and make why
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# ToolResponseMessage needs to be here (it is function call
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# execution from outside the system)
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messages: list[UserMessage | ToolResponseMessage]
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messages: list[OpenAIMessageParam]
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documents: list[Document] | None = None
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toolgroups: list[AgentToolGroup] | None = Field(default_factory=lambda: [])
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@ -460,7 +450,7 @@ class AgentTurnResumeRequest(BaseModel):
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agent_id: str
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session_id: str
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turn_id: str
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tool_responses: list[ToolResponse]
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tool_responses: list[OpenAIToolMessageParam]
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stream: bool | None = False
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@ -531,7 +521,7 @@ class Agents(Protocol):
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self,
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agent_id: str,
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session_id: str,
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messages: list[UserMessage | ToolResponseMessage],
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messages: list[OpenAIMessageParam],
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stream: bool | None = False,
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documents: list[Document] | None = None,
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toolgroups: list[AgentToolGroup] | None = None,
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@ -569,7 +559,7 @@ class Agents(Protocol):
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agent_id: str,
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session_id: str,
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turn_id: str,
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tool_responses: list[ToolResponse],
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tool_responses: list[OpenAIToolMessageParam],
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stream: bool | None = False,
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) -> Turn | AsyncIterator[AgentTurnResponseStreamChunk]:
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"""Resume an agent turn with executed tool call responses.
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