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  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Metaphor Search"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Metaphor is a search engine fully designed to be used by LLMs. You can search and then get the contents for any page.\n",
    "\n",
    "This notebook goes over how to use Metaphor search.\n",
    "\n",
    "First, you need to set up the proper API keys and environment variables. Get 1000 free searches/month [here](https://platform.metaphor.systems/).\n",
    "\n",
    "Then enter your API key as an environment variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "\n",
    "os.environ[\"METAPHOR_API_KEY\"] = \"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.utilities import MetaphorSearchAPIWrapper"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "search = MetaphorSearchAPIWrapper()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Call the API\n",
    "`results` takes in a Metaphor-optimized search query and a number of results (up to 500). It returns a list of results with title, url, author, and creation date."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "search.results(\"The best blog post about AI safety is definitely this: \", 10)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Adding filters\n",
    "We can also add filters to our search. \n",
    "\n",
    "include_domains: Optional[List[str]] - List of domains to include in the search. If specified, results will only come from these domains. Only one of include_domains and exclude_domains should be specified.\n",
    "\n",
    "exclude_domains: Optional[List[str]] - List of domains to exclude in the search. If specified, results will only come from these domains. Only one of include_domains and exclude_domains should be specified.\n",
    "\n",
    "start_crawl_date: Optional[str] - \"Crawl date\" refers to the date that Metaphor discovered a link, which is more granular and can be more useful than published date. If start_crawl_date is specified, results will only include links that were crawled after start_crawl_date. Must be specified in ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ)\n",
    "\n",
    "end_crawl_date: Optional[str] - \"Crawl date\" refers to the date that Metaphor discovered a link, which is more granular and can be more useful than published date. If endCrawlDate is specified, results will only include links that were crawled before end_crawl_date. Must be specified in ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ)\n",
    "\n",
    "start_published_date: Optional[str] - If specified, only links with a published date after start_published_date will be returned. Must be specified in ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ). Note that for some links, we have no published date, and these links will be excluded from the results if start_published_date is specified.\n",
    "\n",
    "end_published_date: Optional[str] - If specified, only links with a published date before end_published_date will be returned. Must be specified in ISO 8601 format (YYYY-MM-DDTHH:MM:SSZ). Note that for some links, we have no published date, and these links will be excluded from the results if end_published_date is specified.\n",
    "\n",
    "See full docs [here](https://metaphorapi.readme.io/)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "search.results(\n",
    "    \"The best blog post about AI safety is definitely this: \",\n",
    "    10,\n",
    "    include_domains=[\"lesswrong.com\"],\n",
    "    start_published_date=\"2019-01-01\",\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Use Metaphor as a tool\n",
    "Metaphor can be used as a tool that gets URLs that other tools such as browsing tools."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install playwright\n",
    "from langchain.agents.agent_toolkits import PlayWrightBrowserToolkit\n",
    "from langchain.tools.playwright.utils import (\n",
    "    create_async_playwright_browser,  # A synchronous browser is available, though it isn't compatible with jupyter.\n",
    ")\n",
    "\n",
    "async_browser = create_async_playwright_browser()\n",
    "toolkit = PlayWrightBrowserToolkit.from_browser(async_browser=async_browser)\n",
    "tools = toolkit.get_tools()\n",
    "\n",
    "tools_by_name = {tool.name: tool for tool in tools}\n",
    "print(tools_by_name.keys())\n",
    "navigate_tool = tools_by_name[\"navigate_browser\"]\n",
    "extract_text = tools_by_name[\"extract_text\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain.agents import initialize_agent, AgentType\n",
    "from langchain.chat_models import ChatOpenAI\n",
    "from langchain.tools import MetaphorSearchResults\n",
    "\n",
    "llm = ChatOpenAI(model_name=\"gpt-4\", temperature=0.7)\n",
    "\n",
    "metaphor_tool = MetaphorSearchResults(api_wrapper=search)\n",
    "\n",
    "agent_chain = initialize_agent(\n",
    "    [metaphor_tool, extract_text, navigate_tool],\n",
    "    llm,\n",
    "    agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION,\n",
    "    verbose=True,\n",
    ")\n",
    "\n",
    "agent_chain.run(\n",
    "    \"find me an interesting tweet about AI safety using Metaphor, then tell me the first sentence in the post. Do not finish until able to retrieve the first sentence.\"\n",
    ")"
   ]
  }
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