import { VoltAgent, Agent, createTool, MCPConfiguration } from "@voltagent/core";
import { VercelAIProvider } from "@voltagent/vercel-ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";
import path from "node:path";

// Your existing weather tool
const getWeatherTool = createTool({
  name: "get_weather",
  description: "Get current weather for any city",
  parameters: z.object({
    location: z.string().describe("City and state, e.g. New York, NY"),
  }),
  execute: async ({ location }) => {
    console.log("Getting weather for " + location + "...");
    if (location.toLowerCase().includes("new york")) {
      return { temperature: "18°C", condition: "Partly cloudy" };
    }
    return { temperature: "24°C", condition: "Sunny" };
  },
});

// NEW: Add MCP for file system access
const mcpConfig = new MCPConfiguration({
  servers: {
    filesystem: {
      type: "stdio", // Connects via standard input/output
      command: "npx", // The command to execute
      args: [
        // Arguments for the command
        "-y",
        "@modelcontextprotocol/server-filesystem", // Example: A filesystem server package
        // Optional arguments for the server itself, like specifying allowed paths:
        path.join(process.env.HOME || "", "Desktop"),
      ],
      // Optional: Specify the working directory for the command
      cwd: process.env.HOME,
      // Optional: Request timeout in milliseconds (default: 30000)
      timeout: 10000,
    },
  },
});

(async () => {
  const tools = await mcpConfig.getTools();
  const agent = new Agent({
    name: "my-agent",
    instructions: `You are a helpful assistant that can check weather and manage files. You can:
  - Get weather information for any city
  - Read and write files
  - Save weather reports to files
  - Manage data storage
  
  Always be helpful and provide clear information.`,
    llm: new VercelAIProvider(),
    model: openai("gpt-4o-mini"),
    tools: [
      getWeatherTool,
      ...tools
    ],
  });

  new VoltAgent({
    agents: { agent },
  });
})();

// Now your agent can do both weather AND file operations!
// Try: "Check weather in London and save it to a file"
// Or: "What files are in the Desktop directory?"
// Or: "Read yesterday's weather report"

import { VoltAgent, Agent, createTool, MCPConfiguration } from "@voltagent/core";
import { VercelAIProvider } from "@voltagent/vercel-ai";
import { openai } from "@ai-sdk/openai";
import { z } from "zod";
import path from "node:path";

// Your existing weather tool (keep it!)
const getWeatherTool = createTool({
  name: "get_weather",
  description: "Get current weather for any city",
  parameters: z.object({
    location: z.string().describe("City and state, e.g. New York, NY"),
  }),
  execute: async ({ location }) => {
    console.log("Getting weather for " + location + "...");
    if (location.toLowerCase().includes("new york")) {
      return { temperature: "18°C", condition: "Partly cloudy" };
    }
    return { temperature: "24°C", condition: "Sunny" };
  },
});

// UPGRADE: Now we have BOTH local filesystem AND remote AI models!
const mcpConfig = new MCPConfiguration({
  servers: {
    // Local filesystem access (from previous example)
    filesystem: {
      type: "stdio",
      command: "npx",
      args: [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        path.join(process.env.HOME || "", "Desktop"),
      ],
      cwd: process.env.HOME,
      // Optional: Request timeout in milliseconds (default: 30000)
      timeout: 10000,
    },
    // NEW: Remote Hugging Face AI models
    "hf-mcp-server": {
      url: "https://huggingface.co/mcp",
      requestInit: {
        headers: { 
          Authorization: `Bearer ${process.env.HUGGING_FACE_TOKEN}`
        },
      },
      type: "http",
      // Optional: Request timeout in milliseconds (default: 30000)
      timeout: 30000,
    },
  },
});

(async () => {
  try {
    const tools = await mcpConfig.getTools();
    
    const agent = new Agent({
      name: "my-agent",
      instructions: `You are a powerful assistant with comprehensive capabilities:
        
        Weather Services:
        - Get current weather for any city
        
        File Management (Local MCP):
        - Read and write files
        - List directory contents
        - Manage file storage
        - Save weather reports to files
        
        AI & ML Services (Remote MCP via Hugging Face):
        - Generate images from text descriptions
        - Analyze and classify images
        - Process and understand text
        - Translate between languages
        - Answer questions about various topics
        
        You can combine ALL these capabilities in creative ways!
        Always explain what you're doing when using different tools.`,
      llm: new VercelAIProvider(),
      model: openai("gpt-4o-mini"),
      tools: [
        getWeatherTool,  // Local weather tool
        ...tools         // BOTH filesystem + AI tools
      ],
    });

    new VoltAgent({
      agents: { agent },
    });
  } catch (error) {
    console.error("Failed to initialize VoltAgent:", error);
  }
})();

// Now your agent is a POWERHOUSE with weather + files + AI!
// Try these incredible combinations:
// "Check weather in Paris, generate an image of that weather, and save the report to a file"
// "Read my todo.txt file, translate it to Spanish, and generate an image for each task"
// "Create a weather report file for Tokyo with generated weather images"