langchain/docs/docs/integrations/chat/mistralai.ipynb

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  {
   "cell_type": "raw",
   "id": "53fbf15f",
   "metadata": {},
   "source": [
    "---\n",
    "sidebar_label: MistralAI\n",
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf733a38-db84-4363-89e2-de6735c37230",
   "metadata": {},
   "source": [
    "# MistralAI\n",
    "\n",
    "This notebook covers how to get started with MistralAI chat models, via their [API](https://docs.mistral.ai/api/).\n",
    "\n",
    "A valid [API key](https://console.mistral.ai/users/api-keys/) is needed to communicate with the API.\n",
    "\n",
    "Head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_mistralai.chat_models.ChatMistralAI.html) for detailed documentation of all attributes and methods."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc686b8f",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "You will need the `langchain-core` and `langchain-mistralai` package to use the API. You can install these with:\n",
    "\n",
    "```bash\n",
    "pip install -U langchain-core langchain-mistralai\n",
    "\n",
    "We'll also need to get a [Mistral API key](https://console.mistral.ai/users/api-keys/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c3fd4184",
   "metadata": {},
   "outputs": [],
   "source": [
    "import getpass\n",
    "\n",
    "mistral_api_key = getpass.getpass()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "502127fd",
   "metadata": {},
   "source": [
    "## Usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d4a7c55d-b235-4ca4-a579-c90cc9570da9",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from langchain_core.messages import HumanMessage\n",
    "from langchain_mistralai.chat_models import ChatMistralAI"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "70cf04e8-423a-4ff6-8b09-f11fb711c817",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "# If mistral_api_key is not passed, default behavior is to use the `MISTRAL_API_KEY` environment variable.\n",
    "chat = ChatMistralAI(mistral_api_key=mistral_api_key)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8199ef8f-eb8b-4253-9ea0-6c24a013ca4c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content=\"Who's there? I was just about to ask the same thing! How can I assist you today?\")"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "messages = [HumanMessage(content=\"knock knock\")]\n",
    "chat.invoke(messages)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c361ab1e-8c0c-4206-9e3c-9d1424a12b9c",
   "metadata": {},
   "source": [
    "### Async"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c5fac0e9-05a4-4fc1-a3b3-e5bbb24b971b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content='Who\\'s there?\\n\\n(You can then continue the \"knock knock\" joke by saying the name of the person or character who should be responding. For example, if I say \"Banana,\" you could respond with \"Banana who?\" and I would say \"Banana bunch! Get it? Because a group of bananas is called a \\'bunch\\'!\" and then we would both laugh and have a great time. But really, you can put anything you want in the spot where I put \"Banana\" and it will still technically be a \"knock knock\" joke. The possibilities are endless!)')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "await chat.ainvoke(messages)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "86ccef97",
   "metadata": {},
   "source": [
    "### Streaming\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "025be980-e50d-4a68-93dc-c9c7b500ce34",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Who's there?\n",
      "\n",
      "(After this, the conversation can continue as a call and response \"who's there\" joke. Here is an example of how it could go:\n",
      "\n",
      "You say: Orange.\n",
      "I say: Orange who?\n",
      "You say: Orange you glad I didn't say banana!?)\n",
      "\n",
      "But since you asked for a knock knock joke specifically, here's one for you:\n",
      "\n",
      "Knock knock.\n",
      "\n",
      "Me: Who's there?\n",
      "\n",
      "You: Lettuce.\n",
      "\n",
      "Me: Lettuce who?\n",
      "\n",
      "You: Lettuce in, it's too cold out here!\n",
      "\n",
      "I hope this brings a smile to your face! Do you have a favorite knock knock joke you'd like to share? I'd love to hear it."
     ]
    }
   ],
   "source": [
    "for chunk in chat.stream(messages):\n",
    "    print(chunk.content, end=\"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f6189577",
   "metadata": {},
   "source": [
    "### Batch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e63aebcb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[AIMessage(content=\"Who's there? I was just about to ask the same thing! Go ahead and tell me who's there. I love a good knock-knock joke.\")]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chat.batch([messages])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38e39e71",
   "metadata": {},
   "source": [
    "## Chaining\n",
    "\n",
    "You can also easily combine with a prompt template for easy structuring of user input. We can do this using [LCEL](/docs/expression_language)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "ee43a1ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "\n",
    "prompt = ChatPromptTemplate.from_template(\"Tell me a joke about {topic}\")\n",
    "chain = prompt | chat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "0dc49212",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AIMessage(content='Why do bears hate shoes so much? They like to run around in their bear feet.')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "chain.invoke({\"topic\": \"bears\"})"
   ]
  }
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