Runtime

import * as z from "zod";
import { createAgent } from "langchain";

const contextSchema = z.object({ 
  userName: z.string(), 
}); 

const agent = createAgent({
  model: "gpt-4.1",
  tools: [
    /* ... */
  ],
  contextSchema, 
});

const result = await agent.invoke(
  { messages: [{ role: "user", content: "What's my name?" }] },
  { context: { userName: "John Smith" } } 
);

import * as z from "zod";
import { tool } from "langchain";
import { type ToolRuntime } from "@langchain/core/tools"; 

const contextSchema = z.object({
  userName: z.string(),
});

const fetchUserEmailPreferences = tool(
  async (_, runtime: ToolRuntime<any, typeof contextSchema>) => { 
    const userName = runtime.context?.userName; 
    if (!userName) {
      throw new Error("userName is required");
    }

    let preferences = "The user prefers you to write a brief and polite email.";
    if (runtime.store) { 
      const memory = await runtime.store?.get(["users"], userName); 
      if (memory) {
        preferences = memory.value.preferences;
      }
    }
    return preferences;
  },
  {
    name: "fetch_user_email_preferences",
    description: "Fetch the user's email preferences.",
    schema: z.object({}),
  }
);

import * as z from "zod";
import { createAgent, createMiddleware, SystemMessage } from "langchain";

const contextSchema = z.object({
  userName: z.string(),
});

// Dynamic prompt middleware
const dynamicPromptMiddleware = createMiddleware({
  name: "DynamicPrompt",
  contextSchema,
  beforeModel: (state, runtime) => { 
    const userName = runtime.context?.userName; 
    if (!userName) {
      throw new Error("userName is required");
    }

    const systemMsg = `You are a helpful assistant. Address the user as ${userName}.`;
    return {
      messages: [new SystemMessage(systemMsg), ...state.messages],
    };
  },
});

// Logging middleware
const loggingMiddleware = createMiddleware({
  name: "Logging",
  contextSchema,
  beforeModel: (state, runtime) => {  
    console.log(`Processing request for user: ${runtime.context?.userName}`);  
    return;
  },
  afterModel: (state, runtime) => {  
    console.log(`Completed request for user: ${runtime.context?.userName}`);  
    return;
  },
});

const agent = createAgent({
  model: "gpt-4.1",
  tools: [
    /* ... */
  ],
  middleware: [dynamicPromptMiddleware, loggingMiddleware],  
  contextSchema,
});

const result = await agent.invoke(
  { messages: [{ role: "user", content: "What's my name?" }] },
  { context: { userName: "John Smith" } }
);