import { tool, Tool, ToolsProviderController } from "@lmstudio/sdk";
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
import { z } from "zod";
import path from "path";
import { configSchematics } from "./config";

const pluginRoot = path.resolve(__dirname, "..");

let client: Client | null = null;
let currentUserAgent: string = "";

export async function toolsProvider(ctl: ToolsProviderController) {
  const userAgent = ctl.getPluginConfig(configSchematics).get("secEdgarUserAgent") as string;
  
  if (!client || currentUserAgent !== userAgent) {
    if (client) {
      await client.close();
      client = null;
    }
    
    const isWindows = process.platform === "win32";
    const venvScript = isWindows 
      ? path.join(pluginRoot, "venv", "Scripts", "sec-edgar-mcp.exe") 
      : path.join(pluginRoot, "venv", "bin", "sec-edgar-mcp");
    
    const transport = new StdioClientTransport({
      command: venvScript,
      args: [],
      env: {
        ...process.env,
        SEC_EDGAR_USER_AGENT: userAgent,
      },
    });

    client = new Client({
      name: "sec-edgar-lmstudio-client",
      version: "1.0.0"
    });

    try {
      await client.connect(transport);
      currentUserAgent = userAgent;
    } catch (e) {
      console.error("Failed to connect to MCP server:", e);
      return [];
    }
  }

  try {
    const { tools: mcpTools } = await client.listTools();
    
    return mcpTools.map(mcpTool => {
      // 將原始 JSON Schema 注入描述中，並明確指示 LLM 將參數放入 'params' 物件中
      const schemaString = mcpTool.inputSchema 
        ? `\n\nIMPORTANT: Pass all arguments inside the 'params' object.\nExpected Input Structure:\n${JSON.stringify(mcpTool.inputSchema, null, 2)}` 
        : "";
        
      return tool({
        name: mcpTool.name,
        description: `${mcpTool.description || ""}${schemaString}`,
        // 符合 LM Studio SDK 型別要求：使用物件結構，並用 z.any() 確保絕對不崩潰
        parameters: { params: z.any() }, 
        implementation: async ({ params }: any) => {
          // 將 LLM 傳入的 params 物件解包，直接作為 MCP Server 的 arguments
          const result = await client!.callTool({
            name: mcpTool.name,
            arguments: params, 
          }) as any;
          return result.content.map((c: any) => c.text).join("\n");
        }
      });
    });
  } catch (e) {
    console.error("Failed to list/call tools:", e);
    return [];
  }
}

import { tool, Tool, ToolsProviderController } from "@lmstudio/sdk";
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StdioClientTransport } from "@modelcontextprotocol/sdk/client/stdio.js";
import { z } from "zod";
import path from "path";
import { configSchematics } from "./config";

const pluginRoot = path.resolve(__dirname, "..");

let client: Client | null = null;
let currentUserAgent: string = "";

export async function toolsProvider(ctl: ToolsProviderController) {
  const userAgent = ctl.getPluginConfig(configSchematics).get("secEdgarUserAgent") as string;
  
  if (!client || currentUserAgent !== userAgent) {
    if (client) {
      await client.close();
      client = null;
    }
    
    const isWindows = process.platform === "win32";
    const venvScript = isWindows 
      ? path.join(pluginRoot, "venv", "Scripts", "sec-edgar-mcp.exe") 
      : path.join(pluginRoot, "venv", "bin", "sec-edgar-mcp");
    
    const transport = new StdioClientTransport({
      command: venvScript,
      args: [],
      env: {
        ...process.env,
        SEC_EDGAR_USER_AGENT: userAgent,
      },
    });

    client = new Client({
      name: "sec-edgar-lmstudio-client",
      version: "1.0.0"
    });

    try {
      await client.connect(transport);
      currentUserAgent = userAgent;
    } catch (e) {
      console.error("Failed to connect to MCP server:", e);
      return [];
    }
  }

  try {
    const { tools: mcpTools } = await client.listTools();
    
    return mcpTools.map(mcpTool => {
      // 將原始 JSON Schema 注入描述中，並明確指示 LLM 將參數放入 'params' 物件中
      const schemaString = mcpTool.inputSchema 
        ? `\n\nIMPORTANT: Pass all arguments inside the 'params' object.\nExpected Input Structure:\n${JSON.stringify(mcpTool.inputSchema, null, 2)}` 
        : "";
        
      return tool({
        name: mcpTool.name,
        description: `${mcpTool.description || ""}${schemaString}`,
        // 符合 LM Studio SDK 型別要求：使用物件結構，並用 z.any() 確保絕對不崩潰
        parameters: { params: z.any() }, 
        implementation: async ({ params }: any) => {
          // 將 LLM 傳入的 params 物件解包，直接作為 MCP Server 的 arguments
          const result = await client!.callTool({
            name: mcpTool.name,
            arguments: params, 
          }) as any;
          return result.content.map((c: any) => c.text).join("\n");
        }
      });
    });
  } catch (e) {
    console.error("Failed to list/call tools:", e);
    return [];
  }
}