# Copyright (c) Microsoft. All rights reserved.

from __future__ import annotations

import asyncio
import base64
import json
import logging
import os
import tempfile
import threading
from collections.abc import AsyncIterable, AsyncIterator, Generator, Sequence
from contextlib import AbstractAsyncContextManager, AsyncExitStack, suppress
from dataclasses import asdict, is_dataclass
from pathlib import Path
from typing import Protocol, cast

from agent_framework import (
    ChatOptions,
    Content,
    ContextProvider,
    FileCheckpointStorage,
    HistoryProvider,
    Message,
    RawAgent,
    SupportsAgentRun,
    WorkflowAgent,
)
from agent_framework.exceptions import AgentFrameworkException
from azure.ai.agentserver.responses import (
    ResponseContext,
    ResponseEventStream,
    ResponseProviderProtocol,
    ResponsesServerOptions,
)
from azure.ai.agentserver.responses._id_generator import IdGenerator
from azure.ai.agentserver.responses.hosting import ResponsesAgentServerHost
from azure.ai.agentserver.responses.models import (
    ApplyPatchToolCallItemParam,
    ApplyPatchToolCallOutputItemParam,
    ComputerCallOutputItemParam,
    ComputerScreenshotContent,
    CreateResponse,
    FunctionCallOutputItemParam,
    FunctionShellAction,
    FunctionShellCallItemParam,
    FunctionShellCallOutputContent,
    FunctionShellCallOutputExitOutcome,
    FunctionShellCallOutputItemParam,
    Item,
    ItemCodeInterpreterToolCall,
    ItemComputerToolCall,
    ItemCustomToolCall,
    ItemCustomToolCallOutput,
    ItemFileSearchToolCall,
    ItemFunctionToolCall,
    ItemImageGenToolCall,
    ItemLocalShellToolCall,
    ItemLocalShellToolCallOutput,
    ItemMcpApprovalRequest,
    ItemMcpToolCall,
    ItemMessage,
    ItemOutputMessage,
    ItemReasoningItem,
    ItemWebSearchToolCall,
    LocalEnvironmentResource,
    MCPApprovalResponse,
    MessageContent,
    MessageContentInputFileContent,
    MessageContentInputImageContent,
    MessageContentInputTextContent,
    MessageContentOutputTextContent,
    MessageContentReasoningTextContent,
    MessageContentRefusalContent,
    MessageRole,
    OAuthConsentRequestOutputItem,
    OutputItem,
    OutputItemApplyPatchToolCall,
    OutputItemApplyPatchToolCallOutput,
    OutputItemCodeInterpreterToolCall,
    OutputItemComputerToolCall,
    OutputItemComputerToolCallOutputResource,
    OutputItemCustomToolCall,
    OutputItemCustomToolCallOutput,
    OutputItemFileSearchToolCall,
    OutputItemFunctionShellCall,
    OutputItemFunctionShellCallOutput,
    OutputItemFunctionToolCall,
    OutputItemImageGenToolCall,
    OutputItemLocalShellToolCall,
    OutputItemLocalShellToolCallOutput,
    OutputItemMcpApprovalRequest,
    OutputItemMcpApprovalResponseResource,
    OutputItemMcpToolCall,
    OutputItemMessage,
    OutputItemOutputMessage,
    OutputItemReasoningItem,
    OutputItemWebSearchToolCall,
    OutputMessageContent,
    OutputMessageContentOutputTextContent,
    OutputMessageContentRefusalContent,
    ResponseStreamEvent,
    StructuredOutputsOutputItem,
    SummaryTextContent,
    TextContent,
)
from azure.ai.agentserver.responses.streaming._builders import (
    OutputItemFunctionCallBuilder,
    OutputItemMcpCallBuilder,
    OutputItemMessageBuilder,
    OutputItemReasoningItemBuilder,
    ReasoningSummaryPartBuilder,
    TextContentBuilder,
)
from mcp import McpError
from typing_extensions import Any

logger = logging.getLogger(__name__)

_AZURE_RESPONSES_MESSAGE_ROLE_TYPE = f"{MessageRole.__module__}:{MessageRole.__qualname__}"


# region Approval Storage
class ApprovalStorage(Protocol):
    """Storage for saving function approval requests."""

    async def save_approval_request(self, approval_request_id: str, request: Content) -> None:
        """Save a function approval request under the given ID."""
        ...

    async def load_approval_request(self, approval_request_id: str) -> Content:
        """Load a function approval request by its ID."""
        ...


class InMemoryFunctionApprovalStorage:
    """An in-memory storage for function approval requests."""

    def __init__(self) -> None:
        self._store: dict[str, Content] = {}

    async def save_approval_request(self, approval_request_id: str, request: Content) -> None:
        if approval_request_id in self._store:
            raise ValueError(f"Approval request with ID '{approval_request_id}' already exists.")
        self._store[approval_request_id] = request

    async def load_approval_request(self, approval_request_id: str) -> Content:
        if approval_request_id not in self._store:
            raise KeyError(f"Approval request with ID '{approval_request_id}' does not exist.")
        return self._store[approval_request_id]


class FileBasedFunctionApprovalStorage:
    """A simple file-based storage for function approval requests.

    Concurrent writes from multiple threads in the same process are
    serialized by a ``threading.Lock``, and the on-disk JSON file is
    updated atomically (write to a temp file, then ``os.replace``) so a
    crash mid-write cannot leave a partially written file behind.
    """

    def __init__(self, storage_path: str) -> None:
        self._storage_path = storage_path
        self._lock = threading.Lock()

    def _create_storage_file_if_not_exists_sync(self) -> None:
        """Lazy-create the storage file (and its parent directory) if it does not already exist.

        Uses exclusive-create mode (``"x"``) so a concurrent creator cannot
        be truncated by an ``open(..., "w")`` after a stale existence check.
        """
        os.makedirs(os.path.dirname(self._storage_path) or ".", exist_ok=True)
        with suppress(FileExistsError), open(self._storage_path, "x") as f:
            json.dump({}, f)

    def _atomic_write(self, data: dict[str, Any]) -> None:
        """Atomically replace the storage file with the serialized ``data``."""
        directory = os.path.dirname(self._storage_path) or "."
        # Serialize first so any error doesn't leave a partial file behind.
        serialized = json.dumps(data)
        fd, tmp_path = tempfile.mkstemp(prefix=".approvals-", suffix=".tmp", dir=directory)
        try:
            with os.fdopen(fd, "w") as tmp:
                tmp.write(serialized)
            os.replace(tmp_path, self._storage_path)
        except BaseException:
            with suppress(OSError):
                os.unlink(tmp_path)
            raise

    def _save_sync(self, approval_request_id: str, request: Content) -> None:
        with self._lock:
            self._create_storage_file_if_not_exists_sync()
            with open(self._storage_path) as f:
                data = json.load(f)
            if approval_request_id in data:
                raise ValueError(f"Approval request with ID '{approval_request_id}' already exists.")
            data[approval_request_id] = request.to_dict()
            self._atomic_write(data)

    def _load_sync(self, approval_request_id: str) -> Content:
        with self._lock:
            self._create_storage_file_if_not_exists_sync()
            with open(self._storage_path) as f:
                data = json.load(f)
        if approval_request_id not in data:
            raise KeyError(f"Approval request with ID '{approval_request_id}' does not exist.")
        return Content.from_dict(data[approval_request_id])

    async def save_approval_request(self, approval_request_id: str, request: Content) -> None:
        await asyncio.to_thread(self._save_sync, approval_request_id, request)

    async def load_approval_request(self, approval_request_id: str) -> Content:
        return await asyncio.to_thread(self._load_sync, approval_request_id)


def _checkpoint_storage_for_context(root: str, context_id: str) -> FileCheckpointStorage:
    """Build a ``FileCheckpointStorage`` for ``context_id`` rooted under ``root``.

    ``context_id`` originates from caller-controlled fields such as
    ``previous_response_id`` or from server-generated fields such as
    ``conversation_id`` / ``response_id``. In every case it must be treated as
    an untrusted single path segment: path separators, drive letters, parent
    references and similar would otherwise let the resulting directory escape
    the configured checkpoint root (CWE-22). The check resolves the joined
    path and verifies it stays under the resolved root before any directory is
    created on disk.
    """
    if not isinstance(context_id, str) or not context_id:
        raise RuntimeError("Invalid checkpoint context id: must be a non-empty string.")
    # Reject any segment that is not a single safe path component. This covers
    # POSIX/Windows separators, NUL bytes, drive letters, and all-dot segments
    # (``.``, ``..``, ``...``, ...). We deliberately do not URL-decode the id
    # here: the hosting layer never decodes context ids before joining them, so
    # forms such as ``%2e%2e`` are accepted as literal directory names. Do NOT
    # add decoding here without re-validating after the decode -- decode-then-
    # join is exactly the pattern that reintroduces traversal. We also do not
    # attempt to "sanitize" by stripping characters because that can introduce
    # collisions between distinct ids.
    if (
        "/" in context_id
        or "\\" in context_id
        or "\x00" in context_id
        # All-dot segments (``.``, ``..``, ``...``, ...) reduce to "" after stripping dots.
        or context_id.strip(".") == ""
        or os.path.isabs(context_id)
        or os.path.splitdrive(context_id)[0]
    ):
        raise RuntimeError(f"Invalid checkpoint context id: {context_id!r}")

    root_path = Path(root).resolve()
    storage_path = (root_path / context_id).resolve()
    if not storage_path.is_relative_to(root_path):
        raise RuntimeError(f"Invalid checkpoint context id: {context_id!r}")
    return FileCheckpointStorage(
        storage_path,
        # Keep this provider-specific allowlist narrow. Hosted workflow
        # checkpoints can persist Azure's role enum inside Message objects.
        allowed_checkpoint_types=[_AZURE_RESPONSES_MESSAGE_ROLE_TYPE],
    )


# endregion Approval Storage

# Foundry Toolbox Auth integration
# Consent-URL error code returned by the Foundry MCP gateway when calling `/list`
CONSENT_ERROR_CODE = -32007


def consent_url_from_error(exc: BaseException) -> str | None:
    """Return the consent URL when ``exc`` wraps a Foundry MCP gateway consent error.

    The Agent Framework MCP layer surfaces gateway consent failures by wrapping the underlying
    ``McpError`` inside an :class:`AgentFrameworkException` (typically a ``ToolExecutionException``
    raised from ``MCPStreamableHTTPTool.__aenter__``). This helper inspects ``exc.args`` for a
    wrapped ``McpError`` whose ``error.code`` is :data:`CONSENT_ERROR_CODE`; when found, the
    consent link the gateway returned in ``error.message`` is returned. Returns ``None`` for
    anything else, so callers can do ``if (url := consent_url_from_error(ex)) is None: raise``.

    Args:
        exc: The exception to inspect.

    Returns:
        The consent URL if ``exc`` wraps a consent ``McpError``, otherwise ``None``.
    """
    inner_exception = next((arg for arg in exc.args if isinstance(arg, McpError)), None)
    if inner_exception is not None and inner_exception.error.code == CONSENT_ERROR_CODE:
        return inner_exception.error.message
    return None


# endregion Foundry Toolbox Auth integration


# region ResponsesHostServer
class ResponsesHostServer(ResponsesAgentServerHost):
    """A responses server host for an agent."""

    # TODO(@taochen): Allow a different checkpoint storage that stores checkpoints externally
    CHECKPOINT_STORAGE_PATH = "/.checkpoints"
    FUNCTION_APPROVAL_STORAGE_PATH = "/.function_approvals/approval_requests.json"

    def __init__(
        self,
        agent: SupportsAgentRun,
        *,
        prefix: str = "",
        options: ResponsesServerOptions | None = None,
        store: ResponseProviderProtocol | None = None,
        **kwargs: Any,
    ) -> None:
        """Initialize a ResponsesHostServer.

        Args:
            agent: The agent to handle responses for.
            prefix: The URL prefix for the server.
            options: Optional server options.
            store: Optional response store.
            **kwargs: Additional keyword arguments.

        Note:
            1. The agent must not have a history provider with `load_messages=True`,
               because history is managed by the hosting infrastructure.
            2. The agent must not have any context providers that maintain context
               in memory, because the hosting environment may get deactivated between
               requests, and any in-memory context would be lost.
        """
        super().__init__(prefix=prefix, options=options, store=store, **kwargs)

        for provider in getattr(agent, "context_providers", []):
            if isinstance(provider, HistoryProvider) and provider.load_messages:
                raise RuntimeError(
                    "There shouldn't be a history provider with `load_messages=True` already present. "
                    "History is managed by the hosting infrastructure."
                )
            provider = cast(ContextProvider, provider)
            logger.warning(
                "Context provider %s is present. If it maintains context in memory, "
                "the context may be lost between requests. Use with caution.",
                provider.source_id,
            )

        self._is_workflow_agent = False
        self._checkpoint_storage_path = None
        if isinstance(agent, WorkflowAgent):
            if agent.workflow._runner_context.has_checkpointing():  # pyright: ignore[reportPrivateUsage]
                raise RuntimeError(
                    "There should not be a checkpoint storage already present in the workflow agent. "
                    "The hosting infrastructure will manage checkpoints instead."
                )
            self._checkpoint_storage_path = (
                self.CHECKPOINT_STORAGE_PATH
                if self.config.is_hosted
                else os.path.join(os.getcwd(), self.CHECKPOINT_STORAGE_PATH.lstrip("/"))
            )
            self._is_workflow_agent = True

        self._agent = agent
        self._approval_storage = (
            FileBasedFunctionApprovalStorage(self.FUNCTION_APPROVAL_STORAGE_PATH)
            if self.config.is_hosted
            else InMemoryFunctionApprovalStorage()
        )
        # Lazy agent lifecycle: the agent (and any MCP tools it owns) is entered on
        # the first request rather than at server startup, so that authentication
        # failures during MCP connect can be surfaced to the client as an
        # `oauth_consent_request` stream event instead of crashing the server.
        self._agent_stack: AsyncExitStack | None = None
        self._agent_init_lock = asyncio.Lock()
        self.shutdown_handler(self._cleanup_agent)  # pyright: ignore[reportUnknownMemberType]
        self.response_handler(self._handle_response)  # pyright: ignore[reportUnknownMemberType]

    async def _ensure_agent_ready(self) -> None:
        """Lazily enter the agent's async context exactly once.

        On failure the partial exit stack is closed and ``_agent_stack`` is left
        as ``None`` so a subsequent request (e.g. after the user completes OAuth
        consent) can retry the connection.
        """
        if self._agent_stack is not None:
            return
        async with self._agent_init_lock:
            if self._agent_stack is not None:
                return
            stack = AsyncExitStack()
            try:
                if isinstance(self._agent, AbstractAsyncContextManager):
                    await stack.enter_async_context(self._agent)
            except BaseException:
                await stack.aclose()
                raise
            self._agent_stack = stack

    async def _cleanup_agent(self) -> None:
        """Close the agent's async context. Registered as the server shutdown handler."""
        stack = self._agent_stack
        if stack is not None:
            self._agent_stack = None
            await stack.aclose()

    async def _handle_response(
        self,
        request: CreateResponse,
        context: ResponseContext,
        cancellation_signal: asyncio.Event,
    ) -> AsyncIterable[ResponseStreamEvent | dict[str, Any]]:
        """Handle the creation of a response."""
        if self._is_workflow_agent:
            # Workflow agents are handled differently because they require checkpoint restoration
            return self._handle_inner_workflow(request, context)
        return self._handle_inner_agent(request, context)

    async def _handle_inner_agent(
        self,
        request: CreateResponse,
        context: ResponseContext,
    ) -> AsyncIterable[ResponseStreamEvent | dict[str, Any]]:
        """Handle the creation of a response for a regular (non-workflow) agent."""
        input_items = await context.get_input_items()
        input_messages = await _items_to_messages(input_items, approval_storage=self._approval_storage)

        history = await context.get_history()
        run_kwargs: dict[str, Any] = {
            "messages": [
                *(await _output_items_to_messages(history, approval_storage=self._approval_storage)),
                *input_messages,
            ]
        }
        is_streaming_request = request.stream is not None and request.stream is True

        chat_options, are_options_set = _to_chat_options(request)

        response_event_stream = ResponseEventStream(response_id=context.response_id, model=request.model)

        yield response_event_stream.emit_created()
        yield response_event_stream.emit_in_progress()

        if are_options_set and not isinstance(self._agent, RawAgent):
            logger.warning("Agent doesn't support runtime options. They will be ignored.")
        else:
            run_kwargs["options"] = chat_options

        # Lazy-enter the agent (and any MCP tools it owns). The MCP client wraps gateway
        # consent failures (and other connection-time errors) in AgentFrameworkException; if
        # one of those is a consent error we surface the consent link to the client through
        # the already-opened response stream instead of crashing the request. Other exception
        # types propagate normally so the host can handle / log them.
        try:
            await self._ensure_agent_ready()
        except AgentFrameworkException as ex:
            consent_url = consent_url_from_error(ex)
            if consent_url is None:
                raise
            logger.warning("OAuth consent required for Foundry MCP gateway.")
            oauth_item = OAuthConsentRequestOutputItem(
                id=IdGenerator.new_id("oacr"),
                consent_link=consent_url,
                server_label="Foundry Toolbox",
            )
            builder = response_event_stream.add_output_item(oauth_item.id)
            yield builder.emit_added(oauth_item)
            yield builder.emit_done(oauth_item)
            yield response_event_stream.emit_completed()
            return

        # Track the current active output item builder for streaming;
        # lazily created on matching content, closed when a different type arrives.
        tracker: _OutputItemTracker | None = _OutputItemTracker(response_event_stream) if is_streaming_request else None

        try:
            if not is_streaming_request:
                # Run the agent in non-streaming mode
                response = await self._agent.run(stream=False, **run_kwargs)  # type: ignore[reportUnknownMemberType]

                for message in response.messages:
                    for content in message.contents:
                        async for item in _to_outputs(
                            response_event_stream,
                            content,
                            approval_storage=self._approval_storage,
                        ):
                            yield item
                yield response_event_stream.emit_completed()
            else:
                if tracker is None:  # pragma: no cover - defensive, set above
                    raise RuntimeError("Streaming tracker was not initialized.")
                # Run the agent in streaming mode
                async for update in self._agent.run(stream=True, **run_kwargs):  # type: ignore[reportUnknownMemberType]
                    for content in update.contents:
                        for event in tracker.handle(content):
                            yield event
                        if tracker.needs_async:
                            async for item in _to_outputs(
                                response_event_stream,
                                content,
                                approval_storage=self._approval_storage,
                            ):
                                yield item
                            tracker.needs_async = False

                # Close any remaining active builder
                for event in tracker.close():
                    yield event
                yield response_event_stream.emit_completed()
        except Exception:
            # Drain any in-progress streaming builder before emitting consent
            # so the resulting stream stays well-formed.
            if tracker is not None:
                for event in tracker.close():
                    yield event
                yield response_event_stream.emit_completed()
            raise

    async def _handle_inner_workflow(
        self,
        request: CreateResponse,
        context: ResponseContext,
    ) -> AsyncIterable[ResponseStreamEvent | dict[str, Any]]:
        """Handle the creation of a response for a workflow agent.

        Why this is required:
        The sandbox may be deactivated after some period of inactivity, and only data managed
        by the hosting infrastructure or files will be preserved upon deactivation.
        """
        input_items = await context.get_input_items()
        input_messages = await _items_to_messages(input_items)
        is_streaming_request = request.stream is not None and request.stream is True

        _, are_options_set = _to_chat_options(request)
        if are_options_set:
            logger.warning("Workflow agent doesn't support runtime options. They will be ignored.")

        if request.previous_response_id is not None and context.conversation_id is not None:
            raise RuntimeError("Previous response ID cannot be used in conjunction with conversation ID.")
        context_id = request.previous_response_id or context.conversation_id

        # The following should never happen due to the checks above.
        # This is for type safety and defensive programming.
        if self._checkpoint_storage_path is None:
            raise RuntimeError("Checkpoint storage path is not configured for workflow agent.")
        if not isinstance(self._agent, WorkflowAgent):
            raise RuntimeError("Agent is not a workflow agent.")

        # Workflow agents are not async context managers in any built-in path,
        # but call _ensure_agent_ready for symmetry with the regular path so
        # any future async resources owned by the workflow are entered here.
        await self._ensure_agent_ready()

        # Determine the latest checkpoint (if any) so we can resume the
        # workflow's prior state for this turn. The directory is keyed by
        # the inbound context id (conversation_id when set, otherwise
        # previous_response_id). Multi-turn declarative workflows need the
        # workflow's internal state (e.g. Conversation.messages,
        # intermediate Local.* variables) to survive across user turns;
        # the only place that state lives is the workflow checkpoint, so
        # on every turn we restore the latest checkpoint and feed the new
        # input back into the start executor as a continuation rather than
        # a fresh run.
        latest_checkpoint_id: str | None = None
        restore_storage: FileCheckpointStorage | None = None
        if context_id is not None:
            restore_storage = _checkpoint_storage_for_context(self._checkpoint_storage_path, context_id)
            latest_checkpoint = await restore_storage.get_latest(workflow_name=self._agent.workflow.name)
            if latest_checkpoint is not None:
                latest_checkpoint_id = latest_checkpoint.checkpoint_id

        # Storage that will receive checkpoints written during this turn.
        # When the caller chains with previous_response_id, the next turn
        # will reference the current response_id as its previous_response_id,
        # so new checkpoints must land under the current response_id (or the
        # conversation_id when set). When conversation_id is set, this
        # matches restore_storage; when only previous_response_id was
        # supplied, restore_storage points at the *prior* response's
        # directory and write_storage points at the *current* response's.
        write_context_id = context.conversation_id or context.response_id
        write_storage = _checkpoint_storage_for_context(self._checkpoint_storage_path, write_context_id)

        # Multi-turn pattern: when we have a prior checkpoint, restore it
        # first (drive the workflow back to idle with prior state intact),
        # then make a separate call that delivers the new user input. This
        # depends on Workflow.run preserving shared state across calls. The
        # restore-only call may yield events from any pending in-flight
        # work in the checkpoint; we consume those internally here so they
        # don't surface to the response stream as duplicates.
        #
        # If the restored checkpoint had pending request_info events, the
        # restore-only call replays them through
        # ``WorkflowAgent._convert_workflow_event_to_agent_response_updates``
        # and populates ``self._agent.pending_requests``. That is the correct
        # state: those requests are genuinely outstanding, and the next
        # ``run(input_messages, ...)`` call may contain ``function_call_output``
        # items (carried as FunctionResult/FunctionApprovalResponse content)
        # that fulfill them via :meth:`WorkflowAgent._process_pending_requests`.
        if latest_checkpoint_id is not None:
            if is_streaming_request:
                async for _ in self._agent.run(
                    stream=True,
                    checkpoint_id=latest_checkpoint_id,
                    checkpoint_storage=restore_storage,
                ):
                    pass
            else:
                await self._agent.run(
                    stream=False,
                    checkpoint_id=latest_checkpoint_id,
                    checkpoint_storage=restore_storage,
                )

        # Now run the agent with the latest input
        response_event_stream = ResponseEventStream(response_id=context.response_id, model=request.model)

        yield response_event_stream.emit_created()
        yield response_event_stream.emit_in_progress()

        if not is_streaming_request:
            # Run the agent in non-streaming mode with the new user input.
            response = await self._agent.run(
                input_messages,
                stream=False,
                checkpoint_storage=write_storage,
            )

            for message in response.messages:
                for content in message.contents:
                    async for item in _to_outputs(response_event_stream, content):
                        yield item

            await self._delete_not_latest_checkpoints(write_storage, self._agent.workflow.name)
            yield response_event_stream.emit_completed()
            return

        # Track the current active output item builder for streaming;
        # lazily created on matching content, closed when a different type arrives.
        tracker = _OutputItemTracker(response_event_stream)

        # Run the workflow agent in streaming mode with the new user input.
        async for update in self._agent.run(
            input_messages,
            stream=True,
            checkpoint_storage=write_storage,
        ):
            for content in update.contents:
                for event in tracker.handle(content):
                    yield event
                if tracker.needs_async:
                    async for item in _to_outputs(response_event_stream, content):
                        yield item
                    tracker.needs_async = False

        # Close any remaining active builder
        for event in tracker.close():
            yield event

        await self._delete_not_latest_checkpoints(write_storage, self._agent.workflow.name)
        yield response_event_stream.emit_completed()

    @staticmethod
    async def _delete_not_latest_checkpoints(checkpoint_storage: FileCheckpointStorage, workflow_name: str) -> None:
        """Delete all checkpoints except the latest one.

        We only need the last checkpoint for each invocation.
        """
        latest_checkpoint = await checkpoint_storage.get_latest(workflow_name=workflow_name)
        if latest_checkpoint is not None:
            all_checkpoints = await checkpoint_storage.list_checkpoints(workflow_name=workflow_name)
            for checkpoint in all_checkpoints:
                if checkpoint.checkpoint_id != latest_checkpoint.checkpoint_id:
                    await checkpoint_storage.delete(checkpoint.checkpoint_id)


# endregion ResponsesHostServer

# region Active Builder State


class _OutputItemTracker:
    """Tracks the current active output item builder during streaming.

    Handles lazy creation, delta emission, and closing of streaming builders
    for text messages, reasoning, function calls, and MCP calls.
    """

    _DELTA_TYPES = frozenset({"text", "text_reasoning", "function_call", "mcp_server_tool_call"})

    def __init__(self, stream: ResponseEventStream) -> None:
        self._stream = stream
        self._active_type: str | None = None
        self._active_id: str | None = None
        # Accumulated delta text for the current active builder
        self._accumulated: list[str] = []
        # Builder state — only one is active at a time
        self._message_item: OutputItemMessageBuilder | None = None
        self._text_content: TextContentBuilder | None = None
        self._reasoning_item: OutputItemReasoningItemBuilder | None = None
        self._summary_part: ReasoningSummaryPartBuilder | None = None
        self._fc_builder: OutputItemFunctionCallBuilder | None = None
        self._mcp_builder: OutputItemMcpCallBuilder | None = None
        self.needs_async = False

    def handle(self, content: Content) -> Generator[ResponseStreamEvent]:
        """Process a content item, yielding sync events.

        Sets ``needs_async = True`` if the caller must also drain an
        async ``_to_outputs`` call for this content.
        """
        if content.type == "text" and content.text is not None:
            if self._active_type != "text":
                yield from self._close()
                yield from self._open_message()
            self._accumulated.append(content.text)
            if self._text_content is not None:
                yield self._text_content.emit_delta(content.text)

        elif content.type == "text_reasoning" and content.text is not None:
            if self._active_type != "text_reasoning":
                yield from self._close()
                yield from self._open_reasoning()
            self._accumulated.append(content.text)
            if self._summary_part is not None:
                yield self._summary_part.emit_text_delta(content.text)

        elif content.type == "function_call" and content.call_id is not None:
            if self._active_type != "function_call" or self._active_id != content.call_id:
                yield from self._close()
                yield from self._open_function_call(content)
            args_str = _arguments_to_str(content.arguments)
            self._accumulated.append(args_str)
            if self._fc_builder is not None:
                yield self._fc_builder.emit_arguments_delta(args_str)

        elif content.type == "mcp_server_tool_call" and content.tool_name:
            key = f"{content.server_name or 'default'}::{content.tool_name}"
            if self._active_type != "mcp_server_tool_call" or self._active_id != key:
                yield from self._close()
                yield from self._open_mcp_call(content)
            args_str = _arguments_to_str(content.arguments)
            self._accumulated.append(args_str)
            if self._mcp_builder is not None:
                yield self._mcp_builder.emit_arguments_delta(args_str)

        else:
            yield from self._close()
            self.needs_async = True

    def close(self) -> Generator[ResponseStreamEvent]:
        """Close any remaining active builder."""
        yield from self._close()

    # -- Private open/close helpers --

    def _open_message(self) -> Generator[ResponseStreamEvent]:
        self._message_item = self._stream.add_output_item_message()
        self._text_content = self._message_item.add_text_content()
        self._active_type = "text"
        self._active_id = None
        yield self._message_item.emit_added()
        yield self._text_content.emit_added()

    def _open_reasoning(self) -> Generator[ResponseStreamEvent]:
        self._reasoning_item = self._stream.add_output_item_reasoning_item()
        self._summary_part = self._reasoning_item.add_summary_part()
        self._active_type = "text_reasoning"
        self._active_id = None
        yield self._reasoning_item.emit_added()
        yield self._summary_part.emit_added()

    def _open_function_call(self, content: Content) -> Generator[ResponseStreamEvent]:
        self._fc_builder = self._stream.add_output_item_function_call(
            name=content.name or "",
            call_id=content.call_id or "",
        )
        self._active_type = "function_call"
        self._active_id = content.call_id
        yield self._fc_builder.emit_added()

    def _open_mcp_call(self, content: Content) -> Generator[ResponseStreamEvent]:
        self._mcp_builder = self._stream.add_output_item_mcp_call(
            server_label=content.server_name or "default",
            name=content.tool_name or "",
        )
        self._active_type = "mcp_server_tool_call"
        self._active_id = f"{content.server_name or 'default'}::{content.tool_name}"
        yield self._mcp_builder.emit_added()

    def _close(self) -> Generator[ResponseStreamEvent]:
        accumulated = "".join(self._accumulated)

        if self._active_type == "text" and self._text_content and self._message_item:
            yield self._text_content.emit_text_done(accumulated)
            yield self._text_content.emit_done()
            yield self._message_item.emit_done()
            self._text_content = None
            self._message_item = None

        elif self._active_type == "text_reasoning" and self._summary_part and self._reasoning_item:
            yield self._summary_part.emit_text_done(accumulated)
            yield self._summary_part.emit_done()
            yield self._reasoning_item.emit_done()
            self._summary_part = None
            self._reasoning_item = None

        elif self._active_type == "function_call" and self._fc_builder:
            yield self._fc_builder.emit_arguments_done(accumulated)
            yield self._fc_builder.emit_done()
            self._fc_builder = None

        elif self._active_type == "mcp_server_tool_call" and self._mcp_builder:
            yield self._mcp_builder.emit_arguments_done(accumulated)
            yield self._mcp_builder.emit_completed()
            yield self._mcp_builder.emit_done()
            self._mcp_builder = None

        self._active_type = None
        self._active_id = None
        self._accumulated.clear()


# endregion


# region Option Conversion


def _to_chat_options(request: CreateResponse) -> tuple[ChatOptions, bool]:
    """Converts a CreateResponse request to ChatOptions.

    Args:
        request (CreateResponse): The request to convert.

    Returns:
        ChatOptions: The converted ChatOptions.
        bool: Whether any options were set.

    """
    chat_options = ChatOptions()
    are_options_set = False

    if request.temperature is not None:
        chat_options["temperature"] = request.temperature
        are_options_set = True
    if request.top_p is not None:
        chat_options["top_p"] = request.top_p
        are_options_set = True
    if request.max_output_tokens is not None:
        chat_options["max_tokens"] = request.max_output_tokens
        are_options_set = True
    if request.parallel_tool_calls is not None:
        chat_options["allow_multiple_tool_calls"] = request.parallel_tool_calls
        are_options_set = True

    return chat_options, are_options_set


# endregion


# region Input Message Conversion


async def _items_to_messages(
    input_items: Sequence[Item], *, approval_storage: ApprovalStorage | None = None
) -> list[Message]:
    """Converts a sequence of input items to a list of Messages, one per item.

    Args:
        input_items: The input items to convert.
        approval_storage: An optional ApprovalStorage instance used to look up
            approval requests when converting MCP approval response items.

    Returns:
        A list of Messages, one per supported input item.
    """
    messages: list[Message] = []
    for item in input_items:
        messages.append(await _item_to_message(item, approval_storage=approval_storage))
    return messages


async def _item_to_message(item: Item, *, approval_storage: ApprovalStorage | None = None) -> Message:
    """Converts an Item to a Message.

    Args:
        item: The Item to convert.
        approval_storage: An optional ApprovalStorage instance used to look up
            approval requests when converting MCP approval response items.

    Returns:
        The converted Message.

    Raises:
        ValueError: If the Item type is not supported.
    """
    if item.type == "message":
        msg = cast(ItemMessage, item)
        if isinstance(msg.content, str):
            return Message(role=msg.role, contents=[Content.from_text(msg.content)])
        return Message(role=msg.role, contents=[_convert_message_content(part) for part in msg.content])

    if item.type == "output_message":
        output_msg = cast(ItemOutputMessage, item)
        return Message(
            role=output_msg.role, contents=[_convert_output_message_content(part) for part in output_msg.content]
        )

    if item.type == "function_call":
        fc = cast(ItemFunctionToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_function_call(fc.call_id, fc.name, arguments=fc.arguments)],
        )

    if item.type == "function_call_output":
        fco = cast(FunctionCallOutputItemParam, item)
        output = fco.output if isinstance(fco.output, str) else str(fco.output)
        return Message(
            role="tool",
            contents=[Content.from_function_result(fco.call_id, result=output)],
        )

    if item.type == "reasoning":
        reasoning = cast(ItemReasoningItem, item)
        reason_contents: list[Content] = []
        if reasoning.summary:
            for summary in reasoning.summary:
                reason_contents.append(Content.from_text(summary.text))
        return Message(role="assistant", contents=reason_contents)

    if item.type == "mcp_call":
        mcp = cast(ItemMcpToolCall, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_mcp_server_tool_call(
                    mcp.id,
                    mcp.name,
                    server_name=mcp.server_label,
                    arguments=mcp.arguments,
                )
            ],
        )

    if item.type == "mcp_approval_request":
        mcp_req = cast(ItemMcpApprovalRequest, item)
        if approval_storage is not None:
            function_approval_request_content = await approval_storage.load_approval_request(mcp_req.id)
        else:
            raise ValueError("ApprovalStorage is required to load approval request.")
        return Message(
            role="assistant",
            contents=[function_approval_request_content],
        )

    if item.type == "mcp_approval_response":
        mcp_resp = cast(MCPApprovalResponse, item)
        if approval_storage is not None:
            function_approval_request_content = await approval_storage.load_approval_request(
                mcp_resp.approval_request_id
            )
        else:
            raise ValueError("ApprovalStorage is required to load approval request.")
        return Message(
            role="user",
            contents=[function_approval_request_content.to_function_approval_response(mcp_resp.approve)],
        )

    if item.type == "code_interpreter_call":
        ci = cast(ItemCodeInterpreterToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_code_interpreter_tool_call(call_id=ci.id)],
        )

    if item.type == "image_generation_call":
        ig = cast(ItemImageGenToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_image_generation_tool_call(image_id=ig.id)],
        )

    if item.type == "shell_call":
        sc = cast(FunctionShellCallItemParam, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_shell_tool_call(
                    call_id=sc.call_id,
                    commands=sc.action.commands,
                    status=str(sc.status),
                )
            ],
        )

    if item.type == "shell_call_output":
        sco = cast(FunctionShellCallOutputItemParam, item)
        outputs = [
            Content.from_shell_command_output(
                stdout=out.stdout or "",
                stderr=out.stderr or "",
                exit_code=getattr(out.outcome, "exit_code", None) if hasattr(out, "outcome") else None,
            )
            for out in (sco.output or [])
        ]
        return Message(
            role="tool",
            contents=[
                Content.from_shell_tool_result(
                    call_id=sco.call_id,
                    outputs=outputs,
                    max_output_length=sco.max_output_length,
                )
            ],
        )

    if item.type == "local_shell_call":
        lsc = cast(ItemLocalShellToolCall, item)
        commands = lsc.action.command if hasattr(lsc.action, "command") and lsc.action.command else []
        return Message(
            role="assistant",
            contents=[
                Content.from_shell_tool_call(
                    call_id=lsc.call_id,
                    commands=commands,
                    status=str(lsc.status),
                )
            ],
        )

    if item.type == "local_shell_call_output":
        lsco = cast(ItemLocalShellToolCallOutput, item)
        return Message(
            role="tool",
            contents=[
                Content.from_shell_tool_result(
                    call_id=lsco.id,
                    outputs=[Content.from_shell_command_output(stdout=lsco.output)],
                )
            ],
        )

    if item.type == "file_search_call":
        fs = cast(ItemFileSearchToolCall, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_function_call(
                    fs.id,
                    "file_search",
                    arguments=json.dumps({"queries": fs.queries}),
                )
            ],
        )

    if item.type == "web_search_call":
        ws = cast(ItemWebSearchToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_function_call(ws.id, "web_search")],
        )

    if item.type == "computer_call":
        cc = cast(ItemComputerToolCall, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_function_call(
                    cc.call_id,
                    "computer_use",
                    arguments=str(cc.action),
                )
            ],
        )

    if item.type == "computer_call_output":
        cco = cast(ComputerCallOutputItemParam, item)
        return Message(
            role="tool",
            contents=[Content.from_function_result(cco.call_id, result=str(cco.output))],
        )

    if item.type == "custom_tool_call":
        ct = cast(ItemCustomToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_function_call(ct.call_id, ct.name, arguments=ct.input)],
        )

    if item.type == "custom_tool_call_output":
        cto = cast(ItemCustomToolCallOutput, item)
        output = cto.output if isinstance(cto.output, str) else str(cto.output)
        # Hosted-MCP results land here because the host writes them via
        # `aoutput_item_custom_tool_call_output` (see `_to_outputs` for
        # `mcp_server_tool_result`). The persisted `call_id` keeps its
        # `mcp_*` prefix; on read, route those back to a hosted-MCP result
        # Content so the chat-client serialize layer can coalesce them
        # onto a single `mcp_call` input item with `output` populated.
        # Issue #5546.
        if cto.call_id and cto.call_id.startswith("mcp_"):
            return Message(
                role="tool",
                contents=[Content.from_mcp_server_tool_result(call_id=cto.call_id, output=output)],
            )
        return Message(
            role="tool",
            contents=[Content.from_function_result(cto.call_id, result=output)],
        )

    if item.type == "apply_patch_call":
        ap = cast(ApplyPatchToolCallItemParam, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_function_call(
                    ap.call_id,
                    "apply_patch",
                    arguments=str(ap.operation),
                )
            ],
        )

    if item.type == "apply_patch_call_output":
        apo = cast(ApplyPatchToolCallOutputItemParam, item)
        return Message(
            role="tool",
            contents=[Content.from_function_result(apo.call_id, result=apo.output or "")],
        )

    raise ValueError(f"Unsupported Item type: {item.type}")


async def _output_items_to_messages(
    history: Sequence[OutputItem],
    *,
    approval_storage: ApprovalStorage | None = None,
) -> list[Message]:
    """Converts a sequence of OutputItem objects to a list of Message objects.

    Args:
        history (Sequence[OutputItem]): The sequence of OutputItem objects to convert.
        approval_storage (ApprovalStorage | None, optional): The approval storage to use for
            resolving MCP approval requests. Defaults to None.

    Returns:
        list[Message]: The list of Message objects.
    """
    messages: list[Message] = []
    for item in history:
        messages.append(await _output_item_to_message(item, approval_storage=approval_storage))
    return messages


async def _output_item_to_message(item: OutputItem, *, approval_storage: ApprovalStorage | None = None) -> Message:
    """Converts an OutputItem to a Message.

    Args:
        item (OutputItem): The OutputItem to convert.
        approval_storage (ApprovalStorage | None, optional): The approval storage to use for
            resolving MCP approval requests. Defaults to None.

    Returns:
        Message: The converted Message.

    Raises:
        ValueError: If the OutputItem type is not supported.
    """
    if item.type == "output_message":
        output_msg = cast(OutputItemOutputMessage, item)
        return Message(
            role=output_msg.role, contents=[_convert_output_message_content(part) for part in output_msg.content]
        )

    if item.type == "message":
        msg = cast(OutputItemMessage, item)
        return Message(role=msg.role, contents=[_convert_message_content(part) for part in msg.content])

    if item.type == "function_call":
        fc = cast(OutputItemFunctionToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_function_call(fc.call_id, fc.name, arguments=fc.arguments)],
        )

    if item.type == "function_call_output":
        fco = cast(FunctionCallOutputItemParam, item)
        output = fco.output if isinstance(fco.output, str) else str(fco.output)
        return Message(
            role="tool",
            contents=[Content.from_function_result(fco.call_id, result=output)],
        )

    if item.type == "reasoning":
        reasoning = cast(OutputItemReasoningItem, item)
        contents: list[Content] = []
        if reasoning.summary:
            for summary in reasoning.summary:
                contents.append(Content.from_text(summary.text))
        return Message(role="assistant", contents=contents)

    if item.type == "mcp_call":
        mcp = cast(OutputItemMcpToolCall, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_mcp_server_tool_call(
                    mcp.id,
                    mcp.name,
                    server_name=mcp.server_label,
                    arguments=mcp.arguments,
                )
            ],
        )

    if item.type == "mcp_approval_request":
        mcp_req = cast(OutputItemMcpApprovalRequest, item)
        if approval_storage is not None:
            function_approval_request_content = await approval_storage.load_approval_request(mcp_req.id)
        else:
            raise ValueError("ApprovalStorage is required to load approval request.")
        return Message(
            role="assistant",
            contents=[function_approval_request_content],
        )

    if item.type == "mcp_approval_response":
        mcp_resp = cast(OutputItemMcpApprovalResponseResource, item)
        if approval_storage is not None:
            function_approval_request_content = await approval_storage.load_approval_request(
                mcp_resp.approval_request_id
            )
        else:
            raise ValueError("ApprovalStorage is required to load approval request.")

        return Message(
            role="user",
            contents=[function_approval_request_content.to_function_approval_response(mcp_resp.approve)],
        )

    if item.type == "code_interpreter_call":
        ci = cast(OutputItemCodeInterpreterToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_code_interpreter_tool_call(call_id=ci.id)],
        )

    if item.type == "image_generation_call":
        ig = cast(OutputItemImageGenToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_image_generation_tool_call(image_id=ig.id)],
        )

    if item.type == "shell_call":
        sc = cast(OutputItemFunctionShellCall, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_shell_tool_call(
                    call_id=sc.call_id,
                    commands=sc.action.commands,
                    status=str(sc.status),
                )
            ],
        )

    if item.type == "shell_call_output":
        sco = cast(OutputItemFunctionShellCallOutput, item)
        outputs = [
            Content.from_shell_command_output(
                stdout=out.stdout or "",
                stderr=out.stderr or "",
                exit_code=getattr(out.outcome, "exit_code", None) if hasattr(out, "outcome") else None,
            )
            for out in (sco.output or [])
        ]
        return Message(
            role="tool",
            contents=[
                Content.from_shell_tool_result(
                    call_id=sco.call_id,
                    outputs=outputs,
                    max_output_length=sco.max_output_length,
                )
            ],
        )

    if item.type == "local_shell_call":
        lsc = cast(OutputItemLocalShellToolCall, item)
        commands = lsc.action.command if hasattr(lsc.action, "command") and lsc.action.command else []
        return Message(
            role="assistant",
            contents=[
                Content.from_shell_tool_call(
                    call_id=lsc.call_id,
                    commands=commands,
                    status=str(lsc.status),
                )
            ],
        )

    if item.type == "local_shell_call_output":
        lsco = cast(OutputItemLocalShellToolCallOutput, item)
        return Message(
            role="tool",
            contents=[
                Content.from_shell_tool_result(
                    call_id=lsco.id,
                    outputs=[Content.from_shell_command_output(stdout=lsco.output)],
                )
            ],
        )

    if item.type == "file_search_call":
        fs = cast(OutputItemFileSearchToolCall, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_function_call(
                    fs.id,
                    "file_search",
                    arguments=json.dumps({"queries": fs.queries}),
                )
            ],
        )

    if item.type == "web_search_call":
        ws = cast(OutputItemWebSearchToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_function_call(ws.id, "web_search")],
        )

    if item.type == "computer_call":
        cc = cast(OutputItemComputerToolCall, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_function_call(
                    cc.call_id,
                    "computer_use",
                    arguments=str(cc.action),
                )
            ],
        )

    if item.type == "computer_call_output":
        cco = cast(OutputItemComputerToolCallOutputResource, item)
        return Message(
            role="tool",
            contents=[Content.from_function_result(cco.call_id, result=str(cco.output))],
        )

    if item.type == "custom_tool_call":
        ct = cast(OutputItemCustomToolCall, item)
        return Message(
            role="assistant",
            contents=[Content.from_function_call(ct.call_id, ct.name, arguments=ct.input)],
        )

    if item.type == "custom_tool_call_output":
        cto = cast(OutputItemCustomToolCallOutput, item)
        output = cto.output if isinstance(cto.output, str) else str(cto.output)
        # Hosted-MCP results land here because the host writes them via
        # `aoutput_item_custom_tool_call_output`. Route `mcp_*` call_ids
        # back to a hosted-MCP result Content so the chat-client serialize
        # layer can coalesce onto the matching `mcp_call` input item.
        # Issue #5546.
        if cto.call_id and cto.call_id.startswith("mcp_"):
            return Message(
                role="tool",
                contents=[Content.from_mcp_server_tool_result(call_id=cto.call_id, output=output)],
            )
        return Message(
            role="tool",
            contents=[Content.from_function_result(cto.call_id, result=output)],
        )

    if item.type == "apply_patch_call":
        ap = cast(OutputItemApplyPatchToolCall, item)
        return Message(
            role="assistant",
            contents=[
                Content.from_function_call(
                    ap.call_id,
                    "apply_patch",
                    arguments=str(ap.operation),
                )
            ],
        )

    if item.type == "apply_patch_call_output":
        apo = cast(OutputItemApplyPatchToolCallOutput, item)
        return Message(
            role="tool",
            contents=[Content.from_function_result(apo.call_id, result=apo.output or "")],
        )

    if item.type == "oauth_consent_request":
        oauth = cast(OAuthConsentRequestOutputItem, item)
        return Message(
            role="assistant",
            contents=[Content.from_oauth_consent_request(oauth.consent_link)],
        )

    if item.type == "structured_outputs":
        so = cast(StructuredOutputsOutputItem, item)
        text = json.dumps(so.output) if not isinstance(so.output, str) else so.output
        return Message(role="assistant", contents=[Content.from_text(text)])

    raise ValueError(f"Unsupported OutputItem type: {item.type}")


def _convert_output_message_content(content: OutputMessageContent) -> Content:
    """Converts an OutputMessageContent to a Content object.

    Args:
        content (OutputMessageContent): The OutputMessageContent to convert.

    Returns:
        Content: The converted Content object.

    Raises:
        ValueError: If the OutputMessageContent type is not supported.
    """
    if content.type == "output_text":
        text_content = cast(OutputMessageContentOutputTextContent, content)
        return Content.from_text(text_content.text)
    if content.type == "refusal":
        refusal_content = cast(OutputMessageContentRefusalContent, content)
        return Content.from_text(refusal_content.refusal)

    raise ValueError(f"Unsupported OutputMessageContent type: {content.type}")


def _convert_file_data(data_uri: str, filename: str | None = None) -> Content:
    """Convert a file_data data URI to a Content object.

    For text/* MIME types, decodes the base64 content and returns it as text.
    For other types, returns a URI-based Content with the filename preserved.
    """
    # Parse data URI: data:<media_type>;base64,<data>
    if data_uri.startswith("data:") and ";base64," in data_uri:
        header, encoded = data_uri.split(";base64,", 1)
        media_type = header[len("data:") :]
        if media_type.startswith("text/"):
            try:
                decoded_text = base64.b64decode(encoded).decode("utf-8")
            except (ValueError, UnicodeDecodeError):
                logger.warning(
                    "Failed to decode text/* file_data as UTF-8, falling through to URI passthrough.",
                    exc_info=True,
                )
            else:
                prefix = f"[File: {filename}]\n" if filename else ""
                return Content.from_text(f"{prefix}{decoded_text}")
    additional_properties = {"filename": filename} if filename else None
    return Content.from_uri(data_uri, additional_properties=additional_properties)


def _convert_message_content(content: MessageContent) -> Content:
    """Converts a MessageContent to a Content object.

    Args:
        content (MessageContent): The MessageContent to convert.

    Returns:
        Content: The converted Content object.

    Raises:
        ValueError: If the MessageContent type is not supported.
    """
    if content.type == "input_text":
        input_text = cast(MessageContentInputTextContent, content)
        return Content.from_text(input_text.text)
    if content.type == "output_text":
        output_text = cast(MessageContentOutputTextContent, content)
        return Content.from_text(output_text.text)
    if content.type == "text":
        text = cast(TextContent, content)
        return Content.from_text(text.text)
    if content.type == "summary_text":
        summary = cast(SummaryTextContent, content)
        return Content.from_text(summary.text)
    if content.type == "refusal":
        refusal = cast(MessageContentRefusalContent, content)
        return Content.from_text(refusal.refusal)
    if content.type == "reasoning_text":
        reasoning = cast(MessageContentReasoningTextContent, content)
        return Content.from_text_reasoning(text=reasoning.text)
    if content.type == "input_image":
        image = cast(MessageContentInputImageContent, content)
        if image.image_url:
            if image.image_url.startswith("data:"):
                return Content.from_uri(image.image_url)
            return Content.from_uri(image.image_url, media_type="image/*")
        if image.file_id:
            return Content.from_hosted_file(image.file_id)
    if content.type == "input_file":
        file = cast(MessageContentInputFileContent, content)
        if file.file_url:
            return Content.from_uri(file.file_url)
        if file.file_id:
            return Content.from_hosted_file(file.file_id, name=file.filename)
        if file.file_data:
            return _convert_file_data(file.file_data, file.filename)
    if content.type == "computer_screenshot":
        screenshot = cast(ComputerScreenshotContent, content)
        return Content.from_uri(screenshot.image_url)

    raise ValueError(f"Unsupported MessageContent type: {content.type}")


# endregion

# region Output Item Conversion


def _argument_json_default(value: Any) -> Any:
    if is_dataclass(value) and not isinstance(value, type):
        return asdict(value)
    to_dict = getattr(value, "to_dict", None)
    if callable(to_dict):
        return to_dict()
    raise TypeError(f"Object of type {type(value).__name__} is not JSON serializable")


def _arguments_to_str(arguments: Any | None) -> str:
    """Convert arguments to a JSON string.

    Args:
        arguments: The arguments to convert, can be a string, JSON-like object, or None.

    Returns:
        The arguments as a JSON string.
    """
    if arguments is None:
        return ""
    if isinstance(arguments, str):
        return arguments
    return json.dumps(arguments, default=_argument_json_default)


async def _to_outputs(
    stream: ResponseEventStream,
    content: Content,
    *,
    approval_storage: ApprovalStorage | None = None,
) -> AsyncIterator[ResponseStreamEvent]:
    """Converts a Content object to an async sequence of ResponseStreamEvent objects.

    Args:
        stream: The ResponseEventStream to use for building events.
        content: The Content to convert.
        approval_storage: An optional ApprovalStorage instance to use for saving and loading function approval requests.

    Yields:
        ResponseStreamEvent: The converted event objects.

    Raises:
        ValueError: If the Content type is not supported.
    """
    if content.type == "text" and content.text is not None:
        async for event in stream.aoutput_item_message(content.text):
            yield event
    elif content.type == "text_reasoning" and content.text is not None:
        async for event in stream.aoutput_item_reasoning_item(content.text):
            yield event
    elif content.type == "function_call":
        async for event in stream.aoutput_item_function_call(
            content.name,  # type: ignore[arg-type]
            content.call_id,  # type: ignore[arg-type]
            _arguments_to_str(content.arguments),
        ):
            yield event
    elif content.type == "function_result":
        async for event in stream.aoutput_item_function_call_output(
            content.call_id,  # type: ignore[arg-type]
            str(content.result or ""),
        ):
            yield event
    elif content.type == "image_generation_tool_result" and content.outputs is not None:
        async for event in stream.aoutput_item_image_gen_call(str(content.outputs)):
            yield event
    elif content.type == "mcp_server_tool_call":
        mcp_call = stream.add_output_item_mcp_call(
            server_label=content.server_name or "default",
            name=content.tool_name or "",
        )
        yield mcp_call.emit_added()
        async for event in mcp_call.aarguments(_arguments_to_str(content.arguments)):
            yield event
        yield mcp_call.emit_completed()
        yield mcp_call.emit_done()
    elif content.type == "mcp_server_tool_result":
        output = (
            content.output
            if isinstance(content.output, str)
            else str(content.output)
            if content.output is not None
            else ""
        )
        async for event in stream.aoutput_item_custom_tool_call_output(content.call_id or "", output):
            yield event
    elif content.type == "shell_tool_call":
        action = FunctionShellAction(commands=content.commands or [], timeout_ms=0, max_output_length=0)
        async for event in stream.aoutput_item_function_shell_call(
            content.call_id or "",
            action,
            LocalEnvironmentResource(),
            status=content.status or "completed",
        ):
            yield event
    elif content.type == "shell_tool_result":
        output_items: list[FunctionShellCallOutputContent] = []
        if content.outputs:
            for out in content.outputs:
                exit_code = getattr(out, "exit_code", None)
                output_items.append(
                    FunctionShellCallOutputContent(
                        stdout=getattr(out, "stdout", "") or "",
                        stderr=getattr(out, "stderr", "") or "",
                        outcome=FunctionShellCallOutputExitOutcome(exit_code=exit_code if exit_code is not None else 0),
                    )
                )
        async for event in stream.aoutput_item_function_shell_call_output(
            content.call_id or "",
            output_items,
            status=content.status or "completed",
            max_output_length=content.max_output_length,
        ):
            yield event
    elif content.type == "function_approval_request":
        function_call: Content = content.function_call  # type: ignore
        server_label = function_call.additional_properties.get("server_label", "agent_framework")
        request_saved = False
        async for event in stream.aoutput_item_mcp_approval_request(
            server_label,
            function_call.name,  # type: ignore
            _arguments_to_str(function_call.arguments),
        ):
            if approval_storage is not None and not request_saved:
                # Extract the approval request ID generated by the infrastructure
                # when the approval request item is added to the stream. Save the
                # approval request to the approval storage so it can be retrieved later
                # for round trips where the original approval request needs to be looked up.
                item = getattr(event, "item", None)
                if item is not None and getattr(item, "id", None) is not None:
                    approval_request_id = cast(str, item.id)  # type: ignore
                    await approval_storage.save_approval_request(approval_request_id, content)
                    request_saved = True
            yield event
        if approval_storage is not None and not request_saved:
            logger.warning(
                "Approval request was not saved to approval storage because the approval request ID "
                "could not be extracted from the stream event."
            )
    else:
        # Log a warning for unsupported content types instead of raising an error to avoid breaking the response stream.
        logger.warning(f"Content type '{content.type}' is not supported yet. This is usually safe to ignore.")


# endregion
