Tools & taking actions

from typing import Literal
from pydantic import BaseModel, Field
from langchain_core.tools import tool
import httpx

class TicketArgs(BaseModel):
    """Open an IT helpdesk ticket in Acme's ticketing system."""
    category: Literal["hardware", "software", "network", "access"] = Field(
        description="The kind of issue. Use 'access' for password / permission requests."
    )
    summary: str = Field(description="One-line description of the problem, as the user reported it.")
    urgency: Literal["low", "medium", "high"] = Field(
        description="'high' only if the user is blocked or it affects revenue."
    )
    user_email: str = Field(description="The reporting user's email, e.g. priya@acme.com.")

@tool(args_schema=TicketArgs)
async def open_it_ticket(category, summary, urgency, user_email) -> str:
    """Open an IT helpdesk ticket. Returns the ticket ID."""
    async with httpx.AsyncClient() as client:
        r = await client.post(
            "https://helpdesk.acme.com/api/tickets",
            json={"category": category, "summary": summary, "urgency": urgency, "reporter": user_email},
            timeout=10.0,
            headers={"Authorization": f"Bearer {os.environ['HELPDESK_TOKEN']}"},
        )
        r.raise_for_status()
        return r.json()["id"]   # e.g. "TICK-4821"

import { tool } from "@langchain/core/tools";
import { z } from "zod";

const TicketArgs = z.object({
  category: z.enum(["hardware", "software", "network", "access"])
    .describe("The kind of issue. Use 'access' for password / permission requests."),
  summary: z.string().describe("One-line description of the problem, as the user reported it."),
  urgency: z.enum(["low", "medium", "high"])
    .describe("'high' only if the user is blocked or it affects revenue."),
  user_email: z.string().email().describe("The reporting user's email."),
}).describe("Open an IT helpdesk ticket in Acme's ticketing system.");

export const openItTicket = tool(
  async ({ category, summary, urgency, user_email }) => {
    const r = await fetch("https://helpdesk.acme.com/api/tickets", {
      method: "POST",
      headers: {
        "Content-Type": "application/json",
        Authorization: `Bearer ${process.env.HELPDESK_TOKEN}`,
      },
      body: JSON.stringify({ category, summary, urgency, reporter: user_email }),
    });
    if (!r.ok) throw new Error(`Helpdesk API error ${r.status}`);
    const data = await r.json();
    return data.id;
  },
  {
    name: "open_it_ticket",
    description: "Open an IT helpdesk ticket. Returns the ticket ID.",
    schema: TicketArgs,
  },
);

from langgraph.prebuilt import ToolNode

tool_node = ToolNode([open_it_ticket, find_room, schedule_meeting])
graph.add_node("tools", tool_node)

import { ToolNode } from "@langchain/langgraph/prebuilt";

const toolNode = new ToolNode([openItTicket, findRoom, scheduleMeeting]);
graph.addNode("tools", toolNode);

@tool
async def open_it_ticket(category, summary, urgency, user_email) -> str:
    """Open an IT helpdesk ticket. Returns the ticket ID."""
    try:
        # ... real call ...
        return ticket_id
    except httpx.HTTPStatusError as e:
        return f"ERROR: helpdesk API returned {e.response.status_code}: {e.response.text[:200]}"
    except httpx.TimeoutException:
        return "ERROR: helpdesk API timed out. You can ask the user to retry, or pick a different action."

export const openItTicket = tool(
  async ({ category, summary, urgency, user_email }) => {
    try {
      // ... real call ...
      return ticketId;
    } catch (e: any) {
      return `ERROR: helpdesk API failed: ${e?.message ?? "unknown"}. You can ask the user to retry, or pick a different action.`;
    }
  },
  { name: "open_it_ticket", description: "...", schema: TicketArgs },
);

from langchain_core.runnables import RunnableConfig

@tool
async def open_it_ticket(category: str, summary: str, urgency: str, *, config: RunnableConfig) -> str:
    """Open an IT helpdesk ticket. Returns the ticket ID."""
    user_email = config["configurable"]["user_email"]   # set by the caller, hidden from the LLM
    # ... call API with user_email ...

# Invoking the agent, pass user_email via config:
agent.invoke(
    {"messages": [("user", "Printer jammed")], },
    config={"configurable": {"user_email": "priya@acme.com", "thread_id": "convo-123"}},
)

import type { RunnableConfig } from "@langchain/core/runnables";

export const openItTicket = tool(
  async ({ category, summary, urgency }, config?: RunnableConfig) => {
    const userEmail = config?.configurable?.user_email as string;
    // ... call API with userEmail ...
    return "TICK-4821";
  },
  { name: "open_it_ticket", description: "...", schema: TicketArgs },
);

await agent.invoke(
  { messages: [{ role: "user", content: "Printer jammed" }] },
  { configurable: { user_email: "priya@acme.com", thread_id: "convo-123" } },
);

from langchain_mcp_adapters.client import MultiServerMCPClient

client = MultiServerMCPClient({
    "slack":    {"command": "npx", "args": ["-y", "@modelcontextprotocol/server-slack"], "transport": "stdio"},
    "linear":   {"command": "npx", "args": ["-y", "@modelcontextprotocol/server-linear"], "transport": "stdio"},
})
mcp_tools = await client.get_tools()

agent = create_react_agent(model=model, tools=[*native_tools, *mcp_tools], prompt="...")

import { MultiServerMCPClient } from "@langchain/mcp-adapters";

const client = new MultiServerMCPClient({
  slack:  { command: "npx", args: ["-y", "@modelcontextprotocol/server-slack"], transport: "stdio" },
  linear: { command: "npx", args: ["-y", "@modelcontextprotocol/server-linear"], transport: "stdio" },
});
const mcpTools = await client.getTools();

const agent = createReactAgent({ llm: model, tools: [...nativeTools, ...mcpTools], prompt: "..." });