import base64
import contextlib
import copy
import os
import re
import tempfile
import warnings
from collections.abc import AsyncIterator, Sequence
from io import BytesIO
from pathlib import Path
from typing import TYPE_CHECKING, Any, Optional, cast
from urllib.parse import unquote

import gradio_client.utils as client_utils
import httpx
from anyio.to_thread import run_sync
from gradio_client import Client, handle_file
from gradio_client.utils import Status, StatusUpdate
from PIL import Image
from pydantic import AnyUrl
from starlette.applications import Starlette
from starlette.requests import Request
from starlette.responses import JSONResponse, Response
from starlette.routing import Mount, Route
from starlette.types import Receive, Scope, Send

from gradio import processing_utils, route_utils, utils
from gradio.blocks import BlockFunction
from gradio.components import State
from gradio.route_utils import Header
from gradio.state_holder import SessionState

if TYPE_CHECKING:
    from mcp import types  # noqa: F401
    from mcp.server import Server  # noqa: F401
    from mcp.server.lowlevel.helper_types import ReadResourceContents  # noqa: F401

    from gradio.blocks import BlockContext, Blocks
    from gradio.components import Component


DEFAULT_TEMP_DIR = os.environ.get("GRADIO_TEMP_DIR") or str(
    Path(tempfile.gettempdir()) / "gradio"
)


class GradioMCPServer:
    """
    A class for creating an MCP server around a Gradio app. This class
    requires `mcp` to be installed.

    Args:
        blocks: The Blocks app to create the MCP server for.
    """

    # Imports are here to avoid needing to install `mcp` when not using this class.
    # This way, we are able to export `gr.tool`, `gr.resource`, etc. to `__init__.py`
    # without the user needing to have `mcp` installed.
    try:
        from mcp import types
        from mcp.server import Server
        from mcp.server.lowlevel.helper_types import ReadResourceContents
        from mcp.server.sse import SseServerTransport
        from mcp.server.streamable_http_manager import StreamableHTTPSessionManager
    except ImportError:
        pass

    def __init__(self, blocks: "Blocks"):
        try:
            import mcp  # noqa: F401
        except ImportError as e:
            raise ImportError(
                "The `mcp` package is required to use the Gradio MCP integration. Please install it with the `mcp` extra: `pip install gradio[mcp]`."
            ) from e

        self.blocks = blocks
        self.api_info = self.blocks.get_api_info()
        self.mcp_server = self.create_mcp_server()
        self.root_path = ""
        space_id = utils.get_space()
        self.tool_prefix = space_id.split("/")[-1] + "_" if space_id else ""
        self.tool_to_endpoint = self.get_tool_to_endpoint()
        self.warn_about_state_inputs()
        self._local_url: str | None = None
        self._client_instance: Client | None = None

        manager = self.StreamableHTTPSessionManager(  # type: ignore
            app=self.mcp_server, json_response=False, stateless=True
        )

        async def handle_streamable_http(
            scope: Scope, receive: Receive, send: Send
        ) -> None:
            path = scope.get("path", "")
            if not path.endswith(
                (
                    "/gradio_api/mcp",
                    "/gradio_api/mcp/",
                    "/gradio_api/mcp/http",
                    "/gradio_api/mcp/http/",
                )
            ):
                response = Response(
                    content=f"Path '{path}' not found. The MCP HTTP transport is available at /gradio_api/mcp.",
                    status_code=404,
                )
                await response(scope, receive, send)
                return

            await manager.handle_request(scope, receive, send)

        @contextlib.asynccontextmanager
        async def lifespan(app: Starlette) -> AsyncIterator[None]:  # noqa: ARG001
            """Context manager for managing session manager lifecycle."""
            async with manager.run():
                try:
                    yield
                finally:
                    pass

        self.lifespan = lifespan
        self.manager = manager
        self.handle_streamable_http = handle_streamable_http

    @property
    def local_url(self) -> str | None:
        return self._local_url

    def get_route_path(self, request: Request) -> str:  # type: ignore
        """
        Gets the route path of the MCP server based on the incoming request.
        Can be different depending on whether the request is coming from the MCP SSE transport or the HTTP transport.
        """
        url = httpx.URL(str(request.url))
        url = url.copy_with(query=None)
        url = str(url).rstrip("/")
        if url.endswith("/gradio_api/mcp/messages"):
            return "/gradio_api/mcp/messages"
        else:
            return "/gradio_api/mcp"

    def get_selected_tools_from_request(self) -> list[str] | None:
        """
        Extract the selected tools from the request query parameters and return the full tool names (with the tool prefix).
        Returns None if no tools parameter is specified (meaning all tools are available).
        """
        context_request: Request | None = self.mcp_server.request_context.request
        if context_request is None:
            return None
        query_params = dict(getattr(context_request, "query_params", {}))
        if "tools" in query_params:
            tools = query_params["tools"].split(",")
            full_tool_names = [self.tool_prefix + tool for tool in tools]
            return full_tool_names
        return None

    @staticmethod
    def valid_and_unique_tool_name(
        tool_name: str, existing_tool_names: set[str]
    ) -> str:
        """
        Sanitizes a tool name to make it a valid MCP tool name (only
        alphanumeric characters, underscores, <= 128 characters)
        and is unique among the existing tool names.
        """
        tool_name = re.sub(r"[^a-zA-Z0-9]", "_", tool_name)
        tool_name = tool_name[:120]  # Leave room for suffix if needed
        tool_name_base = tool_name
        suffix = 1
        while tool_name in existing_tool_names:
            tool_name = tool_name_base + f"_{suffix}"
            suffix += 1
        return tool_name

    def get_tool_to_endpoint(self) -> dict[str, str]:
        """
        Gets all of the tools that are exposed by the Gradio app and also
        creates a mapping from the tool names to the endpoint names in the API docs.
        """
        tool_to_endpoint = {}
        for endpoint_name in self.api_info["named_endpoints"]:
            block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
            if block_fn is None or block_fn.fn is None:
                continue
            fn_name = (
                getattr(block_fn.fn, "__name__", None)
                or (
                    hasattr(block_fn.fn, "__class__")
                    and getattr(block_fn.fn.__class__, "__name__", None)
                )
                or endpoint_name.lstrip("/")
            )
            tool_name = self.tool_prefix + fn_name
            tool_name = self.valid_and_unique_tool_name(
                tool_name, set(tool_to_endpoint.keys())
            )
            tool_to_endpoint[tool_name] = endpoint_name
        return tool_to_endpoint

    def warn_about_state_inputs(self) -> None:
        """
        Warn about tools that have gr.State inputs.
        """
        for _, endpoint_name in self.tool_to_endpoint.items():
            block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
            if block_fn and any(isinstance(input, State) for input in block_fn.inputs):
                warnings.warn(
                    "This MCP server includes a tool that has a gr.State input, which will not be "
                    "updated between tool calls. The original, default value of the State will be "
                    "used each time."
                )

    def _get_or_create_client(self) -> Client:
        if self._client_instance is None:
            context_request: Request | None = self.mcp_server.request_context.request
            if context_request is None:
                raise ValueError(
                    "Could not find the request object in the MCP server context. This is not expected to happen. Please raise an issue: https://github.com/gradio-app/gradio."
                )
            route_path = self.get_route_path(context_request)
            root_url = route_utils.get_root_url(
                request=context_request,
                route_path=route_path,
                root_path=self.root_path,
            )
            self._client_instance = Client(
                self.local_url or root_url,
                download_files=False,
                verbose=False,
                analytics_enabled=False,
                ssl_verify=False,
                _skip_components=False,
                headers={"x-gradio-user": "mcp"},
            )
        return self._client_instance

    def _prepare_tool_call_args(
        self, name: str, arguments: dict[str, Any]
    ) -> tuple[str, list[Any], dict[str, str], "BlockFunction"]:
        """
        Prepare and validate arguments for a tool call.

        Returns:
            A tuple of (endpoint_name, processed_args, request_headers, block_fn)
        """
        selected_tools = self.get_selected_tools_from_request()
        _, filedata_positions = self.get_input_schema(name)
        processed_kwargs = self.convert_strings_to_filedata(
            arguments, filedata_positions
        )
        endpoint_name = self.tool_to_endpoint.get(name)
        if endpoint_name is None:
            raise ValueError(f"Unknown tool for this Gradio app: {name}")

        if selected_tools is not None and name not in selected_tools:
            raise ValueError(f"Tool '{name}' is not in the selected tools list")

        block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
        assert block_fn is not None  # noqa: S101

        if endpoint_name in self.api_info["named_endpoints"]:
            parameters_info = self.api_info["named_endpoints"][endpoint_name][
                "parameters"
            ]
            processed_args = client_utils.construct_args(
                parameters_info,
                (),
                processed_kwargs,
            )
        else:
            processed_args = []

        context_request: Request | None = self.mcp_server.request_context.request
        if context_request is None:
            raise ValueError(
                "Could not find the request object in the MCP server context. This is not expected to happen. Please raise an issue: https://github.com/gradio-app/gradio."
            )
        request_headers = dict(context_request.headers.items())
        request_headers.pop("content-length", None)
        request_headers.pop("x-gradio-user", None)

        return endpoint_name, processed_args, request_headers, block_fn

    async def _execute_tool_without_progress(self, job: Any) -> list[Any]:
        """
        Execute a tool call without progress tracking (fast path).

        Calls job.result() to get the final output without processing
        intermediate status updates.

        Returns:
            The output data as a list.
        """
        result = await run_sync(job.result)
        return [result]

    @staticmethod
    def _format_progress_message(update: StatusUpdate) -> str | None:
        """
        Format a status update into a human-readable progress message.

        Returns:
            A formatted message string, or None if no message should be shown.
        """
        if update.code in [Status.JOINING_QUEUE, Status.STARTING]:
            return "Joined server queue."
        elif update.code in [Status.IN_QUEUE]:
            message = f"In queue. Position {update.rank} out of {update.queue_size}."
            if update.eta is not None:
                message += f" Estimated time remaining: {update.eta} seconds."
            return message
        elif update.code in [Status.PROGRESS]:
            for progress_unit in update.progress_data or []:
                title = (
                    "Progress"
                    if progress_unit.desc is None
                    else f"Progress {progress_unit.desc}"
                )
                if progress_unit.index is not None and progress_unit.length is not None:
                    return (
                        f"{title}: Step {progress_unit.index} of {progress_unit.length}"
                    )
                elif progress_unit.index is not None and progress_unit.length is None:
                    return f"{title}: Step {progress_unit.index}"
        elif update.code in [Status.PROCESSING, Status.ITERATING]:
            return "Processing"
        return None

    async def _execute_tool_with_progress(  # type: ignore
        self, job: Any, progress_token: str | int
    ) -> dict[str, Any]:
        """
        Execute a tool call with progress tracking (streaming path).

        Iterates through job updates to send progress notifications to the client.

        Returns:
            The output data as a list.
        """
        step = 0
        async for update in job:
            if update.type == "status":
                update = cast(StatusUpdate, update)
                message = self._format_progress_message(update)

                await (
                    self.mcp_server.request_context.session.send_progress_notification(
                        progress_token=progress_token,
                        progress=step,
                        message=message,  # type: ignore
                        related_request_id=str(
                            self.mcp_server.request_context.request_id
                        ),
                    )
                )
                step += 1
            elif update.type == "output" and update.final:
                output = update.outputs
                if not update.success:
                    error_title = output.get("title")
                    error_message = output.get("error")
                    if error_title and error_message:
                        msg = f"{error_title}: {error_message}"
                    elif error_message:
                        msg = error_message
                    elif error_title:
                        msg = error_title
                    else:
                        msg = "Error!"
                    raise RuntimeError(msg)
        if job.exception():
            raise job.exception()
        return output["data"]

    def create_mcp_server(self) -> "Server":
        """
        Create an MCP server for the given Gradio Blocks app.

        Parameters:
            blocks: The Blocks app to create the MCP server for.

        Returns:
            The MCP server.
        """
        server = self.Server(str(self.blocks.title or "Gradio App"))  # type: ignore

        @server.call_tool()
        async def call_tool(
            name: str, arguments: dict[str, Any]
        ) -> self.types.CallToolResult:  # type: ignore
            """
            Call a tool on the Gradio app.

            Args:
                name: The name of the tool to call.
                arguments: The arguments to pass to the tool.
            """
            endpoint_name, processed_args, request_headers, block_fn = (
                self._prepare_tool_call_args(name, arguments)
            )
            processed_args = self.insert_empty_state(block_fn.inputs, processed_args)

            if not block_fn.queue:
                # Fast path for non-queued events: call blocks.process_api()
                # directly instead of the HTTP loopback through gradio_client.
                # This eliminates thread dispatches, TCP round-trips, and SSE
                # overhead — reducing MCP tool-call latency significantly.
                session_state = SessionState(self.blocks)
                raw_output = await self.blocks.process_api(
                    block_fn=block_fn,
                    inputs=processed_args,
                    state=session_state,
                    request=self.mcp_server.request_context.request,
                )
                output_data = raw_output["data"]
            else:
                # Queued path: use the HTTP loopback to preserve streaming
                # updates, progress notifications, and queue-based features.
                progress_token = None
                if self.mcp_server.request_context.meta is not None:
                    progress_token = self.mcp_server.request_context.meta.progressToken

                client = await run_sync(self._get_or_create_client)
                job = client.submit(
                    *processed_args,
                    api_name=endpoint_name,
                    headers=request_headers,
                )

                if progress_token is None:
                    output_data = await self._execute_tool_without_progress(job)
                else:
                    output_data = await self._execute_tool_with_progress(
                        job,
                        progress_token,
                    )

            output_data = self.pop_returned_state(block_fn.outputs, output_data)

            context_request: Request | None = self.mcp_server.request_context.request
            route_path = self.get_route_path(context_request)  # type: ignore
            root_url = route_utils.get_root_url(  # type: ignore
                request=context_request,  # type: ignore
                route_path=route_path,  # type: ignore
                root_path=self.root_path,  # type: ignore
            )
            content = self.postprocess_output_data(output_data, root_url)
            if getattr(block_fn.fn, "_mcp_structured_output", False):
                structured_content = {"result": content}
            else:
                structured_content = None
            return self.types.CallToolResult(  # type: ignore
                content=content,  # type: ignore
                structuredContent=structured_content,  # type: ignore
                _meta=getattr(block_fn.fn, "_mcp_meta", None),  # type: ignore
            )

        @server.list_tools()
        async def list_tools() -> list[self.types.Tool]:  # type: ignore
            """
            List all tools on the Gradio app.
            """
            selected_tools = self.get_selected_tools_from_request()

            tools = []
            for tool_name, endpoint_name in self.tool_to_endpoint.items():
                if selected_tools is not None and tool_name not in selected_tools:
                    continue

                block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
                if (
                    block_fn is None
                    or block_fn.fn is None
                    or (
                        hasattr(block_fn.fn, "_mcp_type")
                        and block_fn.fn._mcp_type != "tool"
                    )
                ):
                    continue

                description, parameters = self.get_fn_description(block_fn, tool_name)
                schema, _ = self.get_input_schema(tool_name, parameters)
                tool_meta = getattr(block_fn.fn, "_mcp_meta", None)

                tools.append(
                    self.types.Tool(  # type: ignore
                        name=tool_name,
                        description=description,
                        inputSchema=schema,
                        _meta=tool_meta,  # type: ignore
                    )
                )
            return tools

        @server.list_resources()
        async def list_resources() -> list[self.types.Resource]:  # type: ignore
            """
            List all available resources.
            """
            resources = []

            selected_tools = self.get_selected_tools_from_request()
            for tool_name, endpoint_name in self.tool_to_endpoint.items():
                if selected_tools is not None and tool_name not in selected_tools:
                    continue

                block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
                if (
                    block_fn
                    and block_fn.fn
                    and hasattr(block_fn.fn, "_mcp_type")
                    and block_fn.fn._mcp_type == "resource"
                ):
                    uri_template = block_fn.fn._mcp_uri_template  # type: ignore
                    parameters = re.findall(r"\{([^}]+)\}", uri_template)
                    description, parameters, _ = utils.get_function_description(
                        block_fn.fn
                    )
                    if not parameters:
                        resources.append(
                            self.types.Resource(  # type: ignore
                                uri=uri_template,
                                name=block_fn.fn.__name__,  # type: ignore
                                description=description,
                                mimeType=block_fn.fn._mcp_mime_type,  # type: ignore
                            )
                        )
            return resources

        @server.list_resource_templates()
        async def list_resource_templates() -> list[self.types.ResourceTemplate]:  # type: ignore
            """
            List all available resource templates.
            """
            templates = []
            selected_tools = self.get_selected_tools_from_request()
            for tool_name, endpoint_name in self.tool_to_endpoint.items():
                if selected_tools is not None and tool_name not in selected_tools:
                    continue

                block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
                if (
                    block_fn
                    and block_fn.fn
                    and hasattr(block_fn.fn, "_mcp_type")
                    and block_fn.fn._mcp_type == "resource"
                ):
                    uri_template = block_fn.fn._mcp_uri_template  # type: ignore
                    parameters = re.findall(r"\{([^}]+)\}", uri_template)
                    description, parameters, _ = utils.get_function_description(
                        block_fn.fn
                    )
                    if parameters:
                        templates.append(
                            self.types.ResourceTemplate(  # type: ignore
                                uriTemplate=uri_template,
                                name=block_fn.fn.__name__,  # type: ignore
                                description=description,
                                mimeType=block_fn.fn._mcp_mime_type,  # type: ignore
                            )
                        )
            return templates

        @server.read_resource()
        async def read_resource(uri: AnyUrl | str) -> list[self.ReadResourceContents]:  # type: ignore
            """
            Read a specific resource by URI.
            """
            uri = str(uri)
            client = await run_sync(self._get_or_create_client)
            for endpoint_name in self.tool_to_endpoint.values():
                block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)

                if (
                    block_fn
                    and block_fn.fn
                    and hasattr(block_fn.fn, "_mcp_type")
                    and block_fn.fn._mcp_type == "resource"
                ):
                    uri_template = block_fn.fn._mcp_uri_template  # type: ignore
                    parameters = re.findall(r"\{([^}]+)\}", uri_template)  # type: ignore

                    kwargs = {}
                    matched = False

                    if parameters:
                        pattern = re.escape(uri_template)
                        for param in parameters:
                            pattern = pattern.replace(
                                f"\\{{{param}\\}}", f"(?P<{param}>[^/]+)"
                            )
                        match = re.match(f"^{pattern}$", uri)
                        if match:
                            kwargs = match.groupdict()
                            matched = True
                    elif uri_template == uri:
                        matched = True

                    if matched:
                        if endpoint_name in self.api_info["named_endpoints"]:
                            parameters_info = self.api_info["named_endpoints"][
                                endpoint_name
                            ]["parameters"]
                            processed_args = client_utils.construct_args(
                                parameters_info,
                                (),
                                kwargs,
                            )
                        else:
                            processed_args = list(kwargs.values())

                        async for update in client.submit(
                            *processed_args, api_name=endpoint_name
                        ):
                            if update.type == "output" and update.final:  # type: ignore
                                output = update.outputs  # type: ignore
                                result = output["data"][0]
                                break

                        mime_type = block_fn.fn._mcp_mime_type  # type: ignore
                        if mime_type and not mime_type.startswith("text/"):
                            result = base64.b64decode(result.encode("ascii"))
                        return [
                            self.ReadResourceContents(  # type: ignore
                                content=result, mime_type=mime_type
                            )
                        ]

            raise ValueError(f"Resource not found: {uri}")

        @server.list_prompts()
        async def list_prompts() -> list[self.types.Prompt]:  # type: ignore
            """
            List all available prompts.
            """
            prompts = []
            selected_tools = self.get_selected_tools_from_request()
            for tool_name, endpoint_name in self.tool_to_endpoint.items():
                if selected_tools is not None and tool_name not in selected_tools:
                    continue

                block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
                if (
                    block_fn
                    and block_fn.fn
                    and hasattr(block_fn.fn, "_mcp_type")
                    and block_fn.fn._mcp_type == "prompt"
                ):
                    description, parameters, _ = utils.get_function_description(
                        block_fn.fn
                    )
                    function_params = utils.get_function_params(block_fn.fn)
                    arguments = [
                        self.types.PromptArgument(  # type: ignore
                            name=param_name,
                            description=parameters.get(param_name, ""),
                            required=not has_default,
                        )
                        for param_name, has_default, _, _ in function_params
                    ]
                    prompts.append(
                        self.types.Prompt(  # type: ignore
                            name=tool_name,
                            description=description,
                            arguments=arguments,
                        )
                    )
            return prompts

        @server.get_prompt()
        async def get_prompt(
            name: str, arguments: dict[str, Any] | None = None
        ) -> self.types.GetPromptResult:  # type: ignore
            """
            Get a specific prompt with filled-in arguments.
            """
            client = await run_sync(self._get_or_create_client)

            endpoint_name = None
            for endpoint_name in self.tool_to_endpoint.values():
                block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
                if (
                    block_fn
                    and block_fn.fn
                    and hasattr(block_fn.fn, "_mcp_type")
                    and block_fn.fn._mcp_type == "prompt"
                    and block_fn.fn._mcp_name == name  # type: ignore
                ):
                    break

            if not endpoint_name:
                raise ValueError(f"Prompt not found: {name}")

            arguments = arguments or {}

            block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
            assert block_fn is not None  # noqa: S101

            if endpoint_name in self.api_info["named_endpoints"]:
                parameters_info = self.api_info["named_endpoints"][endpoint_name][
                    "parameters"
                ]
                processed_args = client_utils.construct_args(
                    parameters_info,
                    (),
                    arguments,
                )
            else:
                processed_args = list(arguments.values())

            async for update in client.submit(*processed_args, api_name=endpoint_name):
                if update.type == "output" and update.final:  # type: ignore
                    output = update.outputs  # type: ignore
                    result = output["data"][0]
                    break

            return self.types.GetPromptResult(  # type: ignore
                messages=[
                    self.types.PromptMessage(  # type: ignore
                        role="user",
                        content=self.types.TextContent(type="text", text=str(result)),  # type: ignore
                    )
                ]
            )

        return server

    def launch_mcp_on_sse(self, app: Starlette, subpath: str, root_path: str) -> None:
        """
        Launch the MCP server on the SSE transport.

        Parameters:
            app: The Gradio app to mount the MCP server on.
            subpath: The subpath to mount the MCP server on. E.g. "/gradio_api/mcp"
            root_path: The root path of the Gradio Blocks app.
        """
        messages_path = "/messages/"
        sse = self.SseServerTransport(messages_path)  # type: ignore
        self.root_path = root_path

        async def handle_sse(request):
            try:
                async with sse.connect_sse(
                    request.scope, request.receive, request._send
                ) as streams:
                    await self.mcp_server.run(
                        streams[0],
                        streams[1],
                        self.mcp_server.create_initialization_options(),
                    )
                return Response()
            except Exception as e:
                print(f"MCP SSE connection error: {str(e)}")
                raise

        app.mount(
            subpath,
            Starlette(
                routes=[
                    Route(
                        "/schema",
                        endpoint=self.get_complete_schema,  # Not required for MCP but used by the Hugging Face MCP server to get the schema for MCP Spaces without needing to establish an SSE connection
                    ),
                    Route("/sse", endpoint=handle_sse),
                    Mount("/messages/", app=sse.handle_post_message),
                    Mount("/", app=self.handle_streamable_http),
                ],
            ),
        )

    def get_block_fn_from_endpoint_name(
        self, endpoint_name: str
    ) -> "BlockFunction | None":
        """
        Get the BlockFunction for a given endpoint name (e.g. "/predict").

        Parameters:
            endpoint_name: The name of the endpoint to get the BlockFunction for.

        Returns:
            The BlockFunction for the given endpoint name, or None if it is not found.
        """
        block_fn = next(
            (
                fn
                for fn in self.blocks.fns.values()
                if fn.api_name == endpoint_name.lstrip("/")
            ),
            None,
        )
        return block_fn

    @property
    def _file_data_tool_description(self) -> str:
        """
        Sentence prompting the agent to use the upload_file_to_gradio tool if a file is passed as an input.
        """
        return " If a user passes a file as an input, use the upload_file_to_gradio tool, if present, to upload the file to the gradio app and create a Gradio File Input. Then use the returned path as the input to the tool"

    def get_fn_description(
        self, block_fn: "BlockFunction", tool_name: str
    ) -> tuple[str, dict[str, str]]:
        """
        Get the description of a function, which is used to describe the tool in the MCP server.
        Also returns the description of each parameter of the function as a dictionary.
        """
        description, parameters, returns = utils.get_function_description(block_fn.fn)  # type: ignore
        _, filedata_positions = self.get_input_schema(tool_name, parameters)
        if block_fn.api_description is False:
            description = ""
        elif block_fn.api_description is None:
            if len(filedata_positions) > 0:
                description += self._file_data_tool_description
            if returns:
                description += (
                    ("" if description.endswith(".") else ".")
                    + " Returns: "
                    + ", ".join(returns)
                )
        else:
            description = block_fn.api_description
            if len(filedata_positions) > 0:
                description += self._file_data_tool_description  # type: ignore
        assert isinstance(description, str)  # noqa: S101
        return description, parameters

    @staticmethod
    def insert_empty_state(
        inputs: Sequence["Component | BlockContext"], data: list
    ) -> list:
        """
        Insert None placeholder values for any State input components, as State inputs
        are not included in the endpoint schema.
        """
        for i, input_component_type in enumerate(inputs):
            if isinstance(input_component_type, State):
                data.insert(i, None)
        return data

    @staticmethod
    def pop_returned_state(
        components: Sequence["Component | BlockContext"], data: Any
    ) -> list:
        """
        Remove any values corresponding to State output components from the data
        as State outputs are not included in the endpoint schema.
        """
        for i, component_type in enumerate(components):
            if isinstance(component_type, State):
                data.pop(i)
        return data

    def get_input_schema(
        self,
        tool_name: str,
        parameters: dict[str, str] | None = None,
    ) -> tuple[dict[str, Any], list[list[str | int]]]:
        """
        Get the input schema of the Gradio app API, appropriately formatted for MCP.

        Parameters:
            tool_name: The name of the tool to get the schema for, e.g. "predict"
            parameters: The description and parameters of the tool to get the schema for.
        Returns:
            - The input schema of the Gradio app API.
            - A list of positions of FileData objects in the input schema.
        """
        endpoint_name = self.tool_to_endpoint.get(tool_name)
        if endpoint_name is None:
            raise ValueError(f"Unknown tool for this Gradio app: {tool_name}")
        named_endpoints = self.api_info["named_endpoints"]
        endpoint_info = named_endpoints.get(endpoint_name)
        assert endpoint_info is not None  # noqa: S101

        schema = {
            "type": "object",
            "properties": {
                p["parameter_name"]: {
                    **p["type"],
                    **(
                        {"description": parameters[p["parameter_name"]]}
                        if parameters and p["parameter_name"] in parameters
                        else {}
                    ),
                    **(
                        {"default": p["parameter_default"]}
                        if "parameter_default" in p and p["parameter_default"]
                        else {}
                    ),
                }
                for p in endpoint_info["parameters"]
            },
        }
        return self.simplify_filedata_schema(schema)

    async def get_complete_schema(self, request) -> JSONResponse:
        """
        Get the complete schema of the Gradio app API. For debugging purposes, also used by
        the Hugging Face MCP server to get the schema for MCP Spaces without needing to
        establish an SSE connection.

        Parameters:
            request: The Starlette request object.

        Returns:
            A JSONResponse containing a dictionary mapping tool names to their input schemas.
        """
        if not self.api_info:
            return JSONResponse({})

        query_params = dict(getattr(request, "query_params", {}))
        selected_tools = None
        if "tools" in query_params:
            tools = query_params["tools"].split(",")
            selected_tools = set(tools)

        file_data_present = False

        schemas = []
        for tool_name, endpoint_name in self.tool_to_endpoint.items():
            if selected_tools is not None and tool_name not in selected_tools:
                continue
            block_fn = self.get_block_fn_from_endpoint_name(endpoint_name)
            assert block_fn is not None and block_fn.fn is not None  # noqa: S101

            description, parameters = self.get_fn_description(block_fn, tool_name)
            schema, filedata_positions = self.get_input_schema(tool_name, parameters)
            if len(filedata_positions) > 0 and not file_data_present:
                file_data_present = True

            type_hints = utils.get_type_hints(block_fn.fn)
            required_headers = []
            for param_name, type_hint in type_hints.items():
                if type_hint is Header or type_hint is Optional[Header]:
                    header_name = param_name.replace("_", "-").lower()
                    required_headers.append(header_name)

            mcp_type = "tool"  # Default
            if hasattr(block_fn.fn, "_mcp_type"):
                mcp_type = block_fn.fn._mcp_type

            meta = {
                "file_data_present": file_data_present,
                "mcp_type": mcp_type,
                "endpoint_name": block_fn.api_name,
            }
            if required_headers:
                meta["headers"] = required_headers

            info = {
                "name": tool_name,
                "description": description,
                "inputSchema": schema,
                "meta": meta,
            }
            schemas.append(info)

        return JSONResponse(schemas)

    def simplify_filedata_schema(
        self, schema: dict[str, Any]
    ) -> tuple[dict[str, Any], list[list[str | int]]]:
        """
        Parses a schema of a Gradio app API to identify positions of FileData objects. Replaces them with base64
        strings while keeping track of their positions so that they can be converted back to FileData objects
        later.

        Parameters:
            schema: The original schema of the Gradio app API.

        Returns:
            A tuple containing the simplified schema and the positions of the FileData objects.
        """

        def is_gradio_filedata(obj: Any, defs: dict[str, Any]) -> bool:
            if not isinstance(obj, dict):
                return False

            if "$ref" in obj:
                ref = obj["$ref"]
                if ref.startswith("#/$defs/"):
                    key = ref.split("/")[-1]
                    obj = defs.get(key, {})
                else:
                    return False

            props = obj.get("properties", {})
            meta = props.get("meta", {})

            if "$ref" in meta:
                ref = meta["$ref"]
                if ref.startswith("#/$defs/"):
                    key = ref.split("/")[-1]
                    meta = defs.get(key, {})
                else:
                    return False

            type_field = meta.get("properties", {}).get("_type", {})
            default_type = meta.get("default", {}).get("_type")
            return (
                type_field.get("const") == "gradio.FileData"
                or default_type == "gradio.FileData"
            )

        def traverse(
            node: Any,
            path: list[str | int] | None = None,
            defs: dict[str, Any] | None = None,
        ) -> Any:
            if path is None:
                path = []
            if defs is None:
                defs = {}
            # Deep copy the node to avoid modifying the original node
            node = copy.deepcopy(node)

            if isinstance(node, dict):
                if "$defs" in node:
                    defs.update(node["$defs"])

                if is_gradio_filedata(node, defs):
                    filedata_positions.append(path.copy())
                    for key in ["properties", "additional_description", "$defs"]:
                        node.pop(key, None)
                    node["type"] = "string"
                    node["format"] = "Gradio File Input - a http or https url to a file"

                result = {}
                is_schema_root = "type" in node and "properties" in node
                for key, value in node.items():
                    if is_schema_root and key == "properties":
                        result[key] = traverse(value, path, defs)
                    else:
                        path.append(key)
                        result[key] = traverse(value, path, defs)
                        path.pop()
                return result

            elif isinstance(node, list):
                result = []
                for i, item in enumerate(node):
                    path.append(i)
                    result.append(traverse(item, path, defs))
                    path.pop()
                return result

            return node

        filedata_positions: list[list[str | int]] = []
        simplified_schema = traverse(schema)
        return simplified_schema, filedata_positions

    def convert_strings_to_filedata(
        self, value: Any, filedata_positions: list[list[str | int]]
    ) -> Any:
        """
        Convert specific string values back to FileData objects based on their positions.
        This is used to convert string values (as base64 encoded strings) to FileData
        dictionaries so that they can be passed into .preprocess() logic of a Gradio app.

        Parameters:
            value: The input data to process, which can be an arbitrary nested data structure
                that may or may not contain strings that should be converted to FileData objects.
            filedata_positions: List of paths to positions in the input data that should be converted to FileData objects.

        Returns:
            The processed data with strings converted to FileData objects where appropriate. Base64
            encoded strings are first saved to a temporary file and then converted to a FileData object.

        Example:
            >>> convert_strings_to_filedata(
                {"image": "data:image/jpeg;base64,..."},
                [["image"]]
            )
            >>> {'image': FileData(path='<temporary file path>')},
        """

        def traverse(node: Any, path: list[str | int] | None = None) -> Any:
            if path is None:
                path = []

            if isinstance(node, dict):
                return {
                    key: traverse(value, path + [key]) for key, value in node.items()
                }
            elif isinstance(node, list):
                return [traverse(item, path + [i]) for i, item in enumerate(node)]
            elif isinstance(node, str) and path in filedata_positions:
                if node.startswith("data:"):
                    # Even though base64 is not officially part of our schema, some MCP clients
                    # might return base64 encoded strings, so try to save it to a temporary file.
                    return handle_file(
                        processing_utils.save_base64_to_cache(node, DEFAULT_TEMP_DIR)
                    )
                elif node.startswith(("http://", "https://")):
                    return handle_file(node)
                else:
                    raise ValueError(
                        f"Invalid file data format, provide a url ('http://...' or 'https://...'). Received: {node}"
                    )
            return node

        return traverse(value)

    @staticmethod
    def get_image(file_path: str) -> Image.Image | None:
        """
        If a filepath is a valid image, returns a PIL Image object. Otherwise returns None.
        """
        if not os.path.exists(file_path):
            return None
        ext = os.path.splitext(file_path.lower())[1]
        if ext not in Image.registered_extensions():
            return None
        try:
            return Image.open(file_path)
        except Exception:
            return None

    @staticmethod
    def get_svg(file_data: Any) -> bytes | None:
        """
        If a file_data is a valid FileDataDict with a url that is a data:image/svg+xml, returns bytes of the svg. Otherwise returns None.
        """
        if isinstance(file_data, dict) and (url := file_data.get("url")):
            if isinstance(url, str) and url.startswith("data:image/svg"):
                return unquote(url.split(",", 1)[1]).encode()
            else:
                return None
        else:
            return None

    @staticmethod
    def get_base64_data(image: Image.Image, format: str) -> str:
        """
        Returns a base64 encoded string of the image.
        """
        buffer = BytesIO()
        image.save(buffer, format=format)
        return base64.b64encode(buffer.getvalue()).decode("utf-8")

    def postprocess_output_data(
        self, data: Any, root_url: str
    ) -> list["types.TextContent | types.ImageContent"]:
        """
        Postprocess the output data from the Gradio app to convert FileData objects back to base64 encoded strings.

        Parameters:
            data: The output data to postprocess.
        """
        return_values = []
        data = processing_utils.add_root_url(data, root_url, None)
        for output in data:
            if svg_bytes := self.get_svg(output):
                base64_data = base64.b64encode(svg_bytes).decode("utf-8")
                mimetype = "image/svg+xml"
                svg_path = processing_utils.save_bytes_to_cache(
                    svg_bytes, f"{output['orig_name']}", DEFAULT_TEMP_DIR
                )
                svg_url = f"{root_url}/gradio_api/file={svg_path}"
                return_value = [
                    self.types.ImageContent(  # type: ignore
                        type="image", data=base64_data, mimeType=mimetype
                    ),
                    self.types.TextContent(  # type: ignore
                        type="text",
                        text=f"SVG Image URL: {svg_url}",
                    ),
                ]
            elif client_utils.is_file_obj_with_meta(output):
                if image := self.get_image(output["path"]):
                    image_format = image.format or "png"
                    base64_data = self.get_base64_data(image, image_format)
                    mimetype = f"image/{image_format.lower()}"
                    return_value = [
                        self.types.ImageContent(  # type: ignore
                            type="image", data=base64_data, mimeType=mimetype
                        ),
                        self.types.TextContent(  # type: ignore
                            type="text",
                            text=f"Image URL: {output['url'] or output['path']}",
                        ),
                    ]
                else:
                    return_value = [
                        self.types.TextContent(  # type: ignore
                            type="text", text=str(output["url"] or output["path"])
                        )
                    ]
            else:
                return_value = [self.types.TextContent(type="text", text=str(output))]  # type: ignore
            return_values.extend(return_value)
        return return_values


######################################################
### MCP decorators that add metadata to functions.
######################################################


def resource(
    uri_template: str, description: str | None = None, mime_type: str | None = None
):
    """Decorator to mark a function as an MCP resource."""

    def decorator(fn):
        fn._mcp_type = "resource"
        fn._mcp_uri_template = uri_template
        fn._mcp_description = description
        fn._mcp_mime_type = mime_type or "text/plain"
        return fn

    return decorator


def prompt(name: str | None = None, description: str | None = None):
    """Decorator to mark a function as an MCP prompt."""

    def decorator(fn):
        fn._mcp_type = "prompt"
        fn._mcp_name = name or fn.__name__
        fn._mcp_description = description
        return fn

    return decorator


def tool(
    name: str | None = None,
    description: str | None = None,
    structured_output: bool = False,
    _meta: dict[str, Any] | None = None,
):
    """
    Decorator to mark a function as an MCP tool (optional, since functions are registered as tools by default).
    Can be used to configure various aspects of the tool.

    Parameters:
        name: The name of the tool. Overrides the default name of the function.
        description: The description of the tool. Overrides the default description from the function's docstring.
        structured_output: Whether the tool should return structured output (implementation is quite limited at the moment). If True, the output will be wrapped in a dictionary with the key "result" and the value being the output of the function. Recommended to keep this False unless you have a specific reason to need the structured output.
        _meta: Additional metadata for the tool.
    """

    def decorator(fn):
        fn._mcp_type = "tool"
        fn._mcp_name = name
        fn._mcp_structured_output = structured_output
        fn._mcp_description = description
        fn._mcp_meta = _meta
        return fn

    return decorator
