{
 "cells": [
  {
   "cell_type": "raw",
   "id": "71b5cfca",
   "metadata": {},
   "source": [
    "---\n",
    "sidebar_label: Llama API\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90a1faf2",
   "metadata": {},
   "source": [
    "# ChatLlamaAPI\n",
    "\n",
    "This notebook shows how to use LangChain with [LlamaAPI](https://llama-api.com/) - a hosted version of Llama2 that adds in support for function calling."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5b652cf",
   "metadata": {},
   "source": [
    "!pip install -U llamaapi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "bfd385fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "from llamaapi import LlamaAPI\n",
    "\n",
    "# Replace 'Your_API_Token' with your actual API token\n",
    "llama = LlamaAPI(\"Your_API_Token\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "632eb3e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/harrisonchase/.pyenv/versions/3.9.1/envs/langchain/lib/python3.9/site-packages/deeplake/util/check_latest_version.py:32: UserWarning: A newer version of deeplake (3.6.12) is available. It's recommended that you update to the latest version using `pip install -U deeplake`.\n",
      "  warnings.warn(\n"
     ]
    }
   ],
   "source": [
    "from langchain_experimental.llms import ChatLlamaAPI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6f850e82",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = ChatLlamaAPI(client=llama)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "975c2bf4",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.chains import create_tagging_chain\n",
    "\n",
    "schema = {\n",
    "    \"properties\": {\n",
    "        \"sentiment\": {\n",
    "            \"type\": \"string\",\n",
    "            \"description\": \"the sentiment encountered in the passage\",\n",
    "        },\n",
    "        \"aggressiveness\": {\n",
    "            \"type\": \"integer\",\n",
    "            \"description\": \"a 0-10 score of how aggressive the passage is\",\n",
    "        },\n",
    "        \"language\": {\"type\": \"string\", \"description\": \"the language of the passage\"},\n",
    "    }\n",
    "}\n",
    "\n",
    "chain = create_tagging_chain(schema, model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ef9638c3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'sentiment': 'aggressive', 'aggressiveness': 8, 'language': 'english'}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chain.run(\"give me your money\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "238b4f62",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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  "kernelspec": {
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.1"
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