{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "49ec4bd8",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://pip.repos.neuron.amazonaws.com\n",
      "Collecting huggingface_hub\n",
      "  Downloading huggingface_hub-0.13.4-py3-none-any.whl (200 kB)\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m200.1/200.1 kB\u001b[0m \u001b[31m11.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
      "\u001b[?25hRequirement already satisfied: requests in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from huggingface_hub) (2.28.1)\n",
      "Requirement already satisfied: filelock in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from huggingface_hub) (3.9.0)\n",
      "Requirement already satisfied: tqdm>=4.42.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from huggingface_hub) (4.64.1)\n",
      "Requirement already satisfied: packaging>=20.9 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from huggingface_hub) (21.3)\n",
      "Requirement already satisfied: pyyaml>=5.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from huggingface_hub) (5.4.1)\n",
      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from huggingface_hub) (4.4.0)\n",
      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from packaging>=20.9->huggingface_hub) (3.0.9)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from requests->huggingface_hub) (1.26.8)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from requests->huggingface_hub) (2022.12.7)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from requests->huggingface_hub) (3.4)\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from requests->huggingface_hub) (2.1.1)\n",
      "Installing collected packages: huggingface_hub\n",
      "Successfully installed huggingface_hub-0.13.4\n"
     ]
    }
   ],
   "source": [
    "!pip install langchain --quiet\n",
    "!pip install huggingface_hub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d32f24b8",
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Looking in indexes: https://pypi.org/simple, https://pip.repos.neuron.amazonaws.com\n",
      "Requirement already satisfied: openai in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (0.27.4)\n",
      "Requirement already satisfied: requests>=2.20 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from openai) (2.28.1)\n",
      "Requirement already satisfied: aiohttp in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from openai) (3.8.3)\n",
      "Requirement already satisfied: tqdm in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from openai) (4.64.1)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from requests>=2.20->openai) (3.4)\n",
      "Requirement already satisfied: charset-normalizer<3,>=2 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from requests>=2.20->openai) (2.1.1)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from requests>=2.20->openai) (2022.12.7)\n",
      "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from requests>=2.20->openai) (1.26.8)\n",
      "Requirement already satisfied: multidict<7.0,>=4.5 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from aiohttp->openai) (6.0.4)\n",
      "Requirement already satisfied: attrs>=17.3.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from aiohttp->openai) (22.2.0)\n",
      "Requirement already satisfied: yarl<2.0,>=1.0 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from aiohttp->openai) (1.8.2)\n",
      "Requirement already satisfied: frozenlist>=1.1.1 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from aiohttp->openai) (1.3.3)\n",
      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from aiohttp->openai) (4.0.2)\n",
      "Requirement already satisfied: aiosignal>=1.1.2 in /home/ec2-user/anaconda3/envs/python3/lib/python3.10/site-packages (from aiohttp->openai) (1.3.1)\n"
     ]
    }
   ],
   "source": [
    "!pip install openai"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08560f8b",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "bc4c618e",
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "#os.environ[\"OPENAI_API_KEY\"]= \"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\"\n",
    "#import os\n",
    "os.environ[\"HUGGINGFACEHUB_API_TOKEN\"]= \"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\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "733e776b",
   "metadata": {},
   "source": [
    "# 1 LLM说明"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "aca39ebd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#from langchain.llms import OpenAI\n",
    "from langchain import PromptTemplate, HuggingFaceHub, LLMChain\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "4d2de07b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#llm = OpenAI(temperature = 0.9)\n",
    "llm=HuggingFaceHub(repo_id=\"bigscience/bloomz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "52c90bdc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "，然后 click on the name of the service you want to use.\n"
     ]
    }
   ],
   "source": [
    "text = \"列举AWS的服务名称\"\n",
    "print(llm(text))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6e7b89ac",
   "metadata": {},
   "source": [
    "chatGPT输出\n",
    "\n",
    "1、Amazon EC2（Elastic Compute Cloud）\n",
    "2、Amazon S3（Simple Storage Service）\n",
    "3、Amazon RDS（Relational Database Service）\n",
    "4、Amazon VPC（Virtual Private Cloud）\n",
    "5、Amazon CloudFront（Content Delivery Network）\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efe14a57",
   "metadata": {},
   "source": [
    "# 2 Prompt说明"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "a8312234",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.prompts import PromptTemplate\n",
    "prompt = PromptTemplate(\n",
    "    input_variables=[\"food\"],\n",
    "    template=\"推荐一个以{food}闻名的旅游城市?\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "4038e113",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "推荐一个以意大利面闻名的旅游城市?\n"
     ]
    }
   ],
   "source": [
    "print(prompt.format(food=\"意大利面\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "219e2da4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 巴黎\n"
     ]
    }
   ],
   "source": [
    "print(llm(prompt.format(food=\"dessert\")))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13f38472",
   "metadata": {},
   "source": [
    " # 3 Chain说明"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "9b43c123",
   "metadata": {},
   "outputs": [],
   "source": [
    "chain = LLMChain(llm=llm, prompt=prompt)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "1a9fd565",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " 泰国\n"
     ]
    }
   ],
   "source": [
    "print(chain.run(\"榴莲\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a84fe9aa",
   "metadata": {},
   "source": [
    "# 4 agent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a457d6a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "pip install google-search-results\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "33cfcb45",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.agents import load_tools\n",
    "from langchain.agents import initialize_agent\n",
    "\n",
    "# Load the model\n",
    "#llm=HuggingFaceHub(repo_id=\"bigscience/bloomz\")\n",
    "llm = OpenAI(temperature=0)\n",
    "\n",
    "# Load in some tools to use\n",
    "\n",
    "os.environ[\"SERPAPI_API_KEY\"] = \"e919f6e0e7667fce51d670860d33089dae3393d9090c660c933b5dca9b0200e9\"\n",
    "\n",
    "tools = load_tools([\"serpapi\", \"llm-math\"], llm=llm)\n",
    "\n",
    "# Finally, let's initialize an agent with:\n",
    "# 1. The tools\n",
    "# 2. The language model\n",
    "# 3. The type of agent we want to use.\n",
    "\n",
    "agent = initialize_agent(tools, llm, agent=\"zero-shot-react-description\", verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "498fa3e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.agents import ZeroShotAgent, Tool, AgentExecutor\n",
    "from langchain import OpenAI, SerpAPIWrapper, LLMChain\n",
    "from langchain import PromptTemplate, HuggingFaceHub, LLMChain"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "97989bb3",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.agents import ZeroShotAgent, Tool, AgentExecutor\n",
    "from langchain import OpenAI, SerpAPIWrapper, LLMChain\n",
    "\n",
    "search = SerpAPIWrapper()\n",
    "tools = [\n",
    "    Tool(\n",
    "        name = \"Search\",\n",
    "        func=search.run,\n",
    "        description=\"useful for when you need to answer questions about current events\"\n",
    "    )\n",
    "]\n",
    "\n",
    "prefix = \"\"\"Answer the following questions as best you can, but speaking as a pirate might speak. You have access to the following tools:\"\"\"\n",
    "suffix = \"\"\"Begin! Remember to speak as a pirate when giving your final answer. Use lots of \"Args\"\n",
    "\n",
    "Question: {input}\n",
    "{agent_scratchpad}\"\"\"\n",
    "\n",
    "prompt = ZeroShotAgent.create_prompt(\n",
    "    tools, \n",
    "    prefix=prefix, \n",
    "    suffix=suffix, \n",
    "    input_variables=[\"input\", \"agent_scratchpad\"]\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e06c53ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "#llm_chain = LLMChain(llm=OpenAI(temperature=0), prompt=prompt)\n",
    "\n",
    "llm_chain = LLMChain(llm=HuggingFaceHub(repo_id=\"bigscience/bloomz\"), prompt=prompt)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "77363f05",
   "metadata": {},
   "outputs": [],
   "source": [
    "tool_names = [tool.name for tool in tools]\n",
    "agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8ba9972e",
   "metadata": {},
   "outputs": [],
   "source": [
    "agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=tools, verbose=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e6e50071",
   "metadata": {},
   "outputs": [],
   "source": [
    "agent_executor.run(\"How many people live in canada as of 2023?\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "edeec7fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "#agent.run(\"谁是中国的国家主席\")\n",
    "agent.run(\"Who is the current leader of Japan? What is the largest prime number that is smaller than their age?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2aff6b23",
   "metadata": {},
   "source": [
    "# 5 Memory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1aa6575a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain import OpenAI, ConversationChain\n",
    "\n",
    "#llm = OpenAI(temperature=0)\n",
    "conversation = ConversationChain(llm=llm, verbose=True)\n",
    "\n",
    "conversation.predict(input=\"你好!\")\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "529b3dbf",
   "metadata": {},
   "outputs": [],
   "source": [
    "conversation.predict(input=\"很高兴认识你\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4116d7db",
   "metadata": {},
   "outputs": [],
   "source": [
    "conversation.predict(input=\"你给我说的第一句话是什么？\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "094eac07",
   "metadata": {},
   "outputs": [],
   "source": [
    "conversation.predict(input=\"我对你说的第一句话的另一个说法是什么？\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2f7c824f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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