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"""
MCP Integration for OpenParlData
Provides a wrapper for connecting to the OpenParlData MCP server
and executing tools from the Gradio app.
"""

import os
import sys
import json
import asyncio
from typing import Optional, Dict, Any, List
from pathlib import Path

# Add mcp directory to path
mcp_dir = Path(__file__).parent / "mcp"
sys.path.insert(0, str(mcp_dir))

from mcp.client.session import ClientSession
from mcp.client.stdio import stdio_client, StdioServerParameters


class OpenParlDataClient:
    """Client for interacting with OpenParlData MCP server."""

    def __init__(self):
        self.session: Optional[ClientSession] = None
        self.available_tools: List[Dict[str, Any]] = []

    async def connect(self):
        """Connect to the MCP server."""
        # Get the path to the MCP server script
        server_script = Path(__file__).parent / "mcp" / "openparldata_mcp.py"

        if not server_script.exists():
            raise FileNotFoundError(f"MCP server script not found at {server_script}")

        # Server parameters for stdio connection
        server_params = StdioServerParameters(
            command=sys.executable,  # Python interpreter
            args=[str(server_script)],
            env=None
        )

        # Create stdio client context
        self.stdio_context = stdio_client(server_params)
        read, write = await self.stdio_context.__aenter__()

        # Create session
        self.session = ClientSession(read, write)
        await self.session.__aenter__()

        # Initialize and get available tools
        await self.session.initialize()

        # List available tools
        tools_result = await self.session.list_tools()
        self.available_tools = [
            {
                "name": tool.name,
                "description": tool.description,
                "input_schema": tool.inputSchema
            }
            for tool in tools_result.tools
        ]

        return self.available_tools

    async def disconnect(self):
        """Disconnect from the MCP server."""
        if self.session:
            await self.session.__aexit__(None, None, None)
        if hasattr(self, 'stdio_context'):
            await self.stdio_context.__aexit__(None, None, None)

    async def call_tool(self, tool_name: str, arguments: Dict[str, Any]) -> str:
        """
        Call an MCP tool with given arguments.

        Args:
            tool_name: Name of the tool to call
            arguments: Dictionary of arguments for the tool

        Returns:
            Tool response as string
        """
        if not self.session:
            raise RuntimeError("Not connected to MCP server. Call connect() first.")

        # Wrap arguments in 'params' key as expected by MCP server
        tool_arguments = {"params": arguments}

        # Call the tool
        result = await self.session.call_tool(tool_name, arguments=tool_arguments)

        # Extract text content from result
        if result.content:
            # MCP returns list of content blocks
            text_parts = []
            for content in result.content:
                if hasattr(content, 'text'):
                    text_parts.append(content.text)
                elif isinstance(content, dict) and 'text' in content:
                    text_parts.append(content['text'])
            return "\n".join(text_parts)

        return "No response from tool"

    def get_tool_info(self) -> List[Dict[str, Any]]:
        """Get information about available tools."""
        return self.available_tools


# Convenience functions for common operations

async def search_parliamentarians(
    query: Optional[str] = None,
    canton: Optional[str] = None,
    party: Optional[str] = None,
    language: str = "en",
    limit: int = 20,
    show_debug: bool = False
) -> tuple[str, Optional[str]]:
    """
    Search for parliamentarians.

    Returns:
        Tuple of (response_text, debug_info)
    """
    client = OpenParlDataClient()

    try:
        await client.connect()

        arguments = {
            "language": language,
            "limit": limit,
            "response_format": "markdown"
        }

        if query:
            arguments["query"] = query
        if canton:
            arguments["canton"] = canton
        if party:
            arguments["party"] = party

        debug_info = None
        if show_debug:
            debug_info = f"**Tool:** openparldata_search_parliamentarians\n**Arguments:** ```json\n{json.dumps(arguments, indent=2)}\n```"

        response = await client.call_tool("openparldata_search_parliamentarians", arguments)

        return response, debug_info

    finally:
        await client.disconnect()


async def search_votes(
    query: Optional[str] = None,
    date_from: Optional[str] = None,
    date_to: Optional[str] = None,
    language: str = "en",
    limit: int = 20,
    show_debug: bool = False
) -> tuple[str, Optional[str]]:
    """
    Search for parliamentary votes.

    Returns:
        Tuple of (response_text, debug_info)
    """
    client = OpenParlDataClient()

    try:
        await client.connect()

        arguments = {
            "language": language,
            "limit": limit,
            "response_format": "markdown"
        }

        if query:
            arguments["query"] = query
        if date_from:
            arguments["date_from"] = date_from
        if date_to:
            arguments["date_to"] = date_to

        debug_info = None
        if show_debug:
            debug_info = f"**Tool:** openparldata_search_votes\n**Arguments:** ```json\n{json.dumps(arguments, indent=2)}\n```"

        response = await client.call_tool("openparldata_search_votes", arguments)

        return response, debug_info

    finally:
        await client.disconnect()


async def search_motions(
    query: Optional[str] = None,
    status: Optional[str] = None,
    language: str = "en",
    limit: int = 20,
    show_debug: bool = False
) -> tuple[str, Optional[str]]:
    """
    Search for motions and proposals.

    Returns:
        Tuple of (response_text, debug_info)
    """
    client = OpenParlDataClient()

    try:
        await client.connect()

        arguments = {
            "language": language,
            "limit": limit,
            "response_format": "markdown"
        }

        if query:
            arguments["query"] = query
        if status:
            arguments["status"] = status

        debug_info = None
        if show_debug:
            debug_info = f"**Tool:** openparldata_search_motions\n**Arguments:** ```json\n{json.dumps(arguments, indent=2)}\n```"

        response = await client.call_tool("openparldata_search_motions", arguments)

        return response, debug_info

    finally:
        await client.disconnect()


async def execute_mcp_query(
    user_query: str,
    tool_name: str,
    arguments: Dict[str, Any],
    show_debug: bool = False
) -> tuple[str, Optional[str]]:
    """
    Execute any MCP tool query.

    Args:
        user_query: The original user question (for context)
        tool_name: Name of the MCP tool to call
        arguments: Arguments for the tool
        show_debug: Whether to return debug information

    Returns:
        Tuple of (response_text, debug_info)
    """
    client = OpenParlDataClient()

    try:
        await client.connect()

        debug_info = None
        if show_debug:
            debug_info = f"**User Query:** {user_query}\n\n**Tool:** {tool_name}\n**Arguments:** ```json\n{json.dumps(arguments, indent=2)}\n```"

        response = await client.call_tool(tool_name, arguments)

        return response, debug_info

    finally:
        await client.disconnect()