larkintuckerllc

import asyncio

from langchain.agents import create_agent
from langchain.messages import HumanMessage
from langchain_mcp_adapters.client import MultiServerMCPClient

QUESTION = HumanMessage(content="What's the weather in San Francisco?")

client = MultiServerMCPClient(
    {

larkintuckerllc

from langchain.agents import create_agent
from langgraph.checkpoint.memory import InMemorySaver
from langchain.messages import HumanMessage
from langchain.tools import tool
from tavily import TavilyClient

tavily_client = TavilyClient();

CONFIG = {"configurable": {"thread_id": "1"}}
QUESTION = HumanMessage(content="I have some leftover chicken and rice in my fridge. What can I make?")

larkintuckerllc

from langchain.agents import create_agent
from langgraph.checkpoint.memory import InMemorySaver
from langchain.messages import HumanMessage
from langchain.tools import tool

CONFIG = {"configurable": {"thread_id": "1"}}
QUESTION_1 = HumanMessage(content="Hello my name is Sean and my favorite color is green.")
QUESTION_2 = HumanMessage(content="What is my favorite color?")

agent = create_agent(

larkintuckerllc

from langchain.agents import create_agent
from langchain.messages import HumanMessage
from langchain.tools import tool
from tavily import TavilyClient

tavily_client = TavilyClient();

QUESTION = HumanMessage(content="Who is the current mayor of San Francisco?")

@tool

larkintuckerllc

from langchain.agents import create_agent
from langchain.messages import HumanMessage
from langchain.tools import tool

QUESTION = HumanMessage(content="What's the square root of 467?")
SYSTEM_PROMPT = "You are an arithmetic wizard."

@tool
def square_root(x: float) -> float:
    """

larkintuckerllc

from langchain.agents import create_agent
from langchain.messages import HumanMessage
from pydantic import BaseModel

QUESTION = HumanMessage(content="What's the capital of the Moon?")
SYSTEM_PROMPT = "You are a science fiction writer, create a capital city at the users request."

class CapitalCity(BaseModel):
    name: str
    location: str

larkintuckerllc

from langchain.agents import create_agent
from langchain.messages import HumanMessage

SYSTEM_PROMPT = """"
You are a science fiction writer, create a capital city at the users request.

User: What is the capital of Mars?
Agent: Marsialias

User: What is the capital of Venus?

larkintuckerllc

from langchain.agents import create_agent
from langchain.messages import HumanMessage

agent = create_agent(model="gpt-5-nano")
response = agent.invoke({
    "messages": [HumanMessage(content="What's the capital of the Moon?")],
})
print(response["messages"][-1].content)

larkintuckerllc

from pprint import pprint

from langchain.chat_models import init_chat_model

def main():
    model = init_chat_model(model="gpt-5-nano")
    response = model.invoke("What's the capital of the Moon?")
    print(response.content)
    pprint(response.response_metadata)

larkintuckerllc

package com.example;

import io.grpc.ManagedChannel;
import io.grpc.ManagedChannelBuilder;
import io.grpc.StatusRuntimeException;

public class GreeterClient {
    public static void main(String[] args) {
        String host = "localhost";
        int port = 50051;