{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4ae4b789",
   "metadata": {},
   "source": [
    "## Document Loading\n",
    "\n",
    "Load a blog post on agents."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5d6bd62e",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.document_loaders import WebBaseLoader\n",
    "\n",
    "loader = WebBaseLoader(\"https://lilianweng.github.io/posts/2023-06-23-agent/\")\n",
    "text = loader.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e21575d",
   "metadata": {},
   "source": [
    "## Run Template\n",
    "\n",
    "As shown in the README, add template and start server:\n",
    "```\n",
    "langchain app add extraction-anthropic-functions\n",
    "langchain serve\n",
    "```\n",
    "\n",
    "We can now look at the endpoints:\n",
    "\n",
    "http://127.0.0.1:8000/docs#\n",
    "\n",
    "And specifically at our loaded template:\n",
    "\n",
    "http://127.0.0.1:8000/docs#/default/invoke_extraction-anthropic-functions_invoke_post\n",
    " \n",
    "We can also use remote runnable to call it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "92edba86",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langserve.client import RemoteRunnable\n",
    "\n",
    "anthropic_function_model = RemoteRunnable(\n",
    "    \"http://localhost:8000/extraction-anthropic-functions\"\n",
    ")\n",
    "anthropic_function_model.invoke(text[0].page_content[0:1500])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "langserve",
   "language": "python",
   "name": "langserve"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}