sydney-runkle

from langchain.tools import ToolRuntime
from typing_extensions import TypedDict
from langchain.agents import create_agent
from langchain.agents.middleware.model_call_limit import (
    ModelCallLimitMiddleware,
    ModelCallLimitExceededError,
)
from langchain_core.tools import tool

sydney-runkle

from langchain.agents import create_agent
from langchain.agents.middleware import SummarizationMiddleware
from langchain_community.retrievers import WikipediaRetriever
from langchain_core.tools import tool


retriever = WikipediaRetriever(  # type: ignore
    top_k_results=1,
    doc_content_chars_max=20_000,
)

sydney-runkle

from langchain.agents import create_agent
from langchain.agents.middleware import ModelFallbackMiddleware


agent = create_agent(
    # simulate model failure w/ a typo in the model name (404)
    model="anthropic:claude-sonnet-with-typo",
    middleware=[
        ModelFallbackMiddleware("openai:gpt-4o-with-typo", "openai:gpt-4o-mini")
    ],

sydney-runkle

import os
import subprocess
import tempfile

from langchain.agents import create_agent
from langchain.agents.middleware import TodoListMiddleware
from langchain_core.tools import tool


@tool(parse_docstring=True)

sydney-runkle

from langchain.agents import create_agent
from langchain.agents.middleware import ToolCallLimitMiddleware
from langchain_core.tools import tool


@tool(parse_docstring=True)
def search_items(query: str) -> str:
    """Search for items in the store.

    Args:

sydney-runkle

from langchain.agents import create_agent
from langchain_core.tools import tool
from langchain.agents.middleware import HumanInTheLoopMiddleware


@tool(parse_docstring=True)
def send_email(recipient: str, subject: str, body: str) -> str:
    """Send an email to a recipient.

    Args: