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chore(package): migrate to src/ layout (#3920)
Migrates package structure to src/ layout following Python packaging best practices. All code moved from `llama_stack/` to `src/llama_stack/`. Public API unchanged - imports remain `import llama_stack.*`. Updated build configs, pre-commit hooks, scripts, and GitHub workflows accordingly. All hooks pass, package builds cleanly. **Developer note**: Reinstall after pulling: `pip install -e .`
This commit is contained in:
Ashwin Bharambe
GitHub
parent
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commit
471b1b248b
791 changed files with 2983 additions and 456 deletions
298
src/llama_stack/apis/conversations/conversations.py
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298
src/llama_stack/apis/conversations/conversations.py
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# 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 ConversationCreateRequest(BaseModel):
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"""Request body for creating a conversation."""
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items: list[ConversationItem] | None = Field(
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default=[],
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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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max_length=20,
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)
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metadata: Metadata | None = Field(
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default={},
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description="Set of 16 key-value pairs that can be attached to an object. Useful for storing additional information",
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max_length=16,
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)
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@json_schema_type
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class ConversationUpdateRequest(BaseModel):
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"""Request body for updating a conversation."""
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metadata: Metadata = Field(
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...,
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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. Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.",
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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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