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

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{
"cells": [
{
"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",
"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 api_key is not passed, default behavior is to use the `MISTRAL_API_KEY` environment variable.\n",
"chat = ChatMistralAI(api_key=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\"})"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 5
}