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# What does this PR do? These were maybe be included in the webmethod? The unit test was pointless too since the request was never used anywhere? This shouldn't be in the API definition, if we never consume it. ## Test Plan CI with pre-commit on OpenAPI spec generation. Signed-off-by: Sébastien Han <seb@redhat.com>
272 lines
10 KiB
Python
272 lines
10 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from enum import StrEnum
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from typing import Annotated, Literal, Protocol, runtime_checkable
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from pydantic import BaseModel, Field
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from llama_stack.apis.agents.openai_responses import (
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OpenAIResponseInputFunctionToolCallOutput,
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OpenAIResponseMCPApprovalRequest,
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OpenAIResponseMCPApprovalResponse,
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OpenAIResponseMessage,
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OpenAIResponseOutputMessageFileSearchToolCall,
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OpenAIResponseOutputMessageFunctionToolCall,
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OpenAIResponseOutputMessageMCPCall,
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OpenAIResponseOutputMessageMCPListTools,
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OpenAIResponseOutputMessageWebSearchToolCall,
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)
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from llama_stack.apis.version import LLAMA_STACK_API_V1
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from llama_stack.core.telemetry.trace_protocol import trace_protocol
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from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
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Metadata = dict[str, str]
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@json_schema_type
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class Conversation(BaseModel):
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"""OpenAI-compatible conversation object."""
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id: str = Field(..., description="The unique ID of the conversation.")
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object: Literal["conversation"] = Field(
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default="conversation", description="The object type, which is always conversation."
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)
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created_at: int = Field(
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..., description="The time at which the conversation was created, measured in seconds since the Unix epoch."
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)
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metadata: Metadata | None = Field(
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default=None,
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description="Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.",
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)
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items: list[dict] | None = Field(
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default=None,
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description="Initial items to include in the conversation context. You may add up to 20 items at a time.",
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)
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@json_schema_type
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class ConversationMessage(BaseModel):
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"""OpenAI-compatible message item for conversations."""
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id: str = Field(..., description="unique identifier for this message")
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content: list[dict] = Field(..., description="message content")
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role: str = Field(..., description="message role")
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status: str = Field(..., description="message status")
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type: Literal["message"] = "message"
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object: Literal["message"] = "message"
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ConversationItem = Annotated[
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OpenAIResponseMessage
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| OpenAIResponseOutputMessageWebSearchToolCall
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| OpenAIResponseOutputMessageFileSearchToolCall
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| OpenAIResponseOutputMessageFunctionToolCall
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| OpenAIResponseInputFunctionToolCallOutput
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| OpenAIResponseMCPApprovalRequest
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| OpenAIResponseMCPApprovalResponse
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| OpenAIResponseOutputMessageMCPCall
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| OpenAIResponseOutputMessageMCPListTools
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| OpenAIResponseOutputMessageMCPCall
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| OpenAIResponseOutputMessageMCPListTools,
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Field(discriminator="type"),
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]
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register_schema(ConversationItem, name="ConversationItem")
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# Using OpenAI types directly caused issues but some notes for reference:
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# Note that ConversationItem is a Annotated Union of the types below:
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# from openai.types.responses import *
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# from openai.types.responses.response_item import *
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# from openai.types.conversations import ConversationItem
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# f = [
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# ResponseFunctionToolCallItem,
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# ResponseFunctionToolCallOutputItem,
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# ResponseFileSearchToolCall,
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# ResponseFunctionWebSearch,
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# ImageGenerationCall,
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# ResponseComputerToolCall,
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# ResponseComputerToolCallOutputItem,
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# ResponseReasoningItem,
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# ResponseCodeInterpreterToolCall,
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# LocalShellCall,
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# LocalShellCallOutput,
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# McpListTools,
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# McpApprovalRequest,
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# McpApprovalResponse,
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# McpCall,
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# ResponseCustomToolCall,
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# ResponseCustomToolCallOutput
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# ]
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@json_schema_type
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class ConversationDeletedResource(BaseModel):
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"""Response for deleted conversation."""
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id: str = Field(..., description="The deleted conversation identifier")
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object: str = Field(default="conversation.deleted", description="Object type")
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deleted: bool = Field(default=True, description="Whether the object was deleted")
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@json_schema_type
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class ConversationItemCreateRequest(BaseModel):
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"""Request body for creating conversation items."""
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items: list[ConversationItem] = Field(
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...,
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description="Items to include in the conversation context. You may add up to 20 items at a time.",
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max_length=20,
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)
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class ConversationItemInclude(StrEnum):
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"""
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Specify additional output data to include in the model response.
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"""
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web_search_call_action_sources = "web_search_call.action.sources"
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code_interpreter_call_outputs = "code_interpreter_call.outputs"
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computer_call_output_output_image_url = "computer_call_output.output.image_url"
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file_search_call_results = "file_search_call.results"
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message_input_image_image_url = "message.input_image.image_url"
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message_output_text_logprobs = "message.output_text.logprobs"
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reasoning_encrypted_content = "reasoning.encrypted_content"
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@json_schema_type
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class ConversationItemList(BaseModel):
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"""List of conversation items with pagination."""
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object: str = Field(default="list", description="Object type")
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data: list[ConversationItem] = Field(..., description="List of conversation items")
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first_id: str | None = Field(default=None, description="The ID of the first item in the list")
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last_id: str | None = Field(default=None, description="The ID of the last item in the list")
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has_more: bool = Field(default=False, description="Whether there are more items available")
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@json_schema_type
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class ConversationItemDeletedResource(BaseModel):
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"""Response for deleted conversation item."""
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id: str = Field(..., description="The deleted item identifier")
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object: str = Field(default="conversation.item.deleted", description="Object type")
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deleted: bool = Field(default=True, description="Whether the object was deleted")
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@runtime_checkable
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@trace_protocol
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class Conversations(Protocol):
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"""Conversations
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Protocol for conversation management operations."""
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@webmethod(route="/conversations", method="POST", level=LLAMA_STACK_API_V1)
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async def create_conversation(
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self, items: list[ConversationItem] | None = None, metadata: Metadata | None = None
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) -> Conversation:
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"""Create a conversation.
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Create a conversation.
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:param items: Initial items to include in the conversation context.
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:param metadata: Set of key-value pairs that can be attached to an object.
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:returns: The created conversation object.
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"""
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...
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@webmethod(route="/conversations/{conversation_id}", method="GET", level=LLAMA_STACK_API_V1)
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async def get_conversation(self, conversation_id: str) -> Conversation:
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"""Retrieve a conversation.
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Get a conversation with the given ID.
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:param conversation_id: The conversation identifier.
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:returns: The conversation object.
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"""
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...
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@webmethod(route="/conversations/{conversation_id}", method="POST", level=LLAMA_STACK_API_V1)
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async def update_conversation(self, conversation_id: str, metadata: Metadata) -> Conversation:
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"""Update a conversation.
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Update a conversation's metadata with the given ID.
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:param conversation_id: The conversation identifier.
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:param metadata: Set of key-value pairs that can be attached to an object.
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:returns: The updated conversation object.
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"""
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...
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@webmethod(route="/conversations/{conversation_id}", method="DELETE", level=LLAMA_STACK_API_V1)
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async def openai_delete_conversation(self, conversation_id: str) -> ConversationDeletedResource:
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"""Delete a conversation.
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Delete a conversation with the given ID.
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:param conversation_id: The conversation identifier.
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:returns: The deleted conversation resource.
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"""
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...
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@webmethod(route="/conversations/{conversation_id}/items", method="POST", level=LLAMA_STACK_API_V1)
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async def add_items(self, conversation_id: str, items: list[ConversationItem]) -> ConversationItemList:
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"""Create items.
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Create items in the conversation.
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:param conversation_id: The conversation identifier.
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:param items: Items to include in the conversation context.
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:returns: List of created items.
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"""
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...
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@webmethod(route="/conversations/{conversation_id}/items/{item_id}", method="GET", level=LLAMA_STACK_API_V1)
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async def retrieve(self, conversation_id: str, item_id: str) -> ConversationItem:
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"""Retrieve an item.
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Retrieve a conversation item.
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:param conversation_id: The conversation identifier.
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:param item_id: The item identifier.
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:returns: The conversation item.
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"""
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...
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@webmethod(route="/conversations/{conversation_id}/items", method="GET", level=LLAMA_STACK_API_V1)
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async def list_items(
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self,
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conversation_id: str,
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after: str | None = None,
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include: list[ConversationItemInclude] | None = None,
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limit: int | None = None,
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order: Literal["asc", "desc"] | None = None,
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) -> ConversationItemList:
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"""List items.
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List items in the conversation.
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:param conversation_id: The conversation identifier.
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:param after: An item ID to list items after, used in pagination.
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:param include: Specify additional output data to include in the response.
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:param limit: A limit on the number of objects to be returned (1-100, default 20).
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:param order: The order to return items in (asc or desc, default desc).
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:returns: List of conversation items.
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"""
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...
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@webmethod(route="/conversations/{conversation_id}/items/{item_id}", method="DELETE", level=LLAMA_STACK_API_V1)
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async def openai_delete_conversation_item(
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self, conversation_id: str, item_id: str
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) -> ConversationItemDeletedResource:
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"""Delete an item.
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Delete a conversation item.
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:param conversation_id: The conversation identifier.
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:param item_id: The item identifier.
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:returns: The deleted item resource.
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"""
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...
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