mistralai[minor]: Add llms entrypoint, update chat model integration

docs/core_docs/docs/integrations/chat/mistral.mdx

@@ -7,21 +7,16 @@ import CodeBlock from "@theme/CodeBlock";
 # ChatMistralAI
 
 [Mistral AI](https://mistral.ai/) is a research organization and hosting platform for LLMs.
-They're most known for their family of 7B models ([`mistral7b` // `mistral-tiny`](https://mistral.ai/news/announcing-mistral-7b/), [`mixtral8x7b` // `mistral-small`](https://mistral.ai/news/mixtral-of-experts/)).
-
 The LangChain implementation of Mistral's models uses their hosted generation API, making it easier to access their models without needing to run them locally.
 
-## Models
-
-Mistral's API offers access to two of their open source, and proprietary models:
+:::tip
+Want to run Mistral's models locally? Check out our [Ollama integration](/docs/integrations/chat/ollama).
+:::
 
-- `open-mistral-7b` (aka `mistral-tiny-2312`)
-- `open-mixtral-8x7b` (aka `mistral-small-2312`)
-- `mistral-small-latest` (aka `mistral-small-2402`) (default)
-- `mistral-medium-latest` (aka `mistral-medium-2312`)
-- `mistral-large-latest` (aka `mistral-large-2402`)
+## Models
 
-See [this page](https://docs.mistral.ai/guides/model-selection/) for an up to date list.
+Mistral's API offers access to two of their open source, and proprietary models.
+See [this page](https://docs.mistral.ai/getting-started/models/) for an up to date list.
 
 ## Setup
 

docs/core_docs/docs/integrations/llms/mistral.ipynb

@@ -0,0 +1,160 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# MistralAI\n",
+    "\n",
+    "```{=mdx}\n",
+    ":::tip\n",
+    "Want to run Mistral's models locally? Check out our [Ollama integration](/docs/integrations/chat/ollama).\n",
+    ":::\n",
+    "```\n",
+    "\n",
+    "Here's how you can initialize an `MistralAI` LLM instance:\n",
+    "\n",
+    "```{=mdx}\n",
+    "import IntegrationInstallTooltip from \"@mdx_components/integration_install_tooltip.mdx\";\n",
+    "import Npm2Yarn from \"@theme/Npm2Yarn\";\n",
+    "\n",
+    "<IntegrationInstallTooltip></IntegrationInstallTooltip>\n",
+    "\n",
+    "<Npm2Yarn>\n",
+    "  @langchain/mistralai\n",
+    "</Npm2Yarn>\n",
+    "```\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "console.log('hello world');\n",
+      "```\n",
+      "This will output 'hello world' to the console.\n"
+     ]
+    }
+   ],
+   "source": [
+    "import { MistralAI } from \"@langchain/mistralai\";\n",
+    "\n",
+    "const model = new MistralAI({\n",
+    "  model: \"codestral-latest\", // Defaults to \"codestral-latest\" if no model provided.\n",
+    "  temperature: 0,\n",
+    "  apiKey: \"YOUR-API-KEY\", // In Node.js defaults to process.env.MISTRAL_API_KEY\n",
+    "});\n",
+    "const res = await model.invoke(\n",
+    "  \"You can print 'hello world' to the console in javascript like this:\\n```javascript\"\n",
+    ");\n",
+    "console.log(res);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Since the Mistral LLM is a completions model, they also allow you to insert a `suffix` to the prompt. Suffixes can be passed via the call options when invoking a model like so:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "console.log('hello world');\n",
+      "```\n"
+     ]
+    }
+   ],
+   "source": [
+    "const res = await model.invoke(\n",
+    "  \"You can print 'hello world' to the console in javascript like this:\\n```javascript\", {\n",
+    "    suffix: \"```\"\n",
+    "  }\n",
+    ");\n",
+    "console.log(res);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "As seen in the first example, the model generated the requested `console.log('hello world')` code snippet, but also included extra unwanted text. By adding a suffix, we can constrain the model to only complete the prompt up to the suffix (in this case, three backticks). This allows us to easily parse the completion and extract only the desired response without the suffix using a custom output parser."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "console.log('hello world');\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "import { MistralAI } from \"@langchain/mistralai\";\n",
+    "\n",
+    "const model = new MistralAI({\n",
+    "  model: \"codestral-latest\",\n",
+    "  temperature: 0,\n",
+    "  apiKey: \"YOUR-API-KEY\",\n",
+    "});\n",
+    "\n",
+    "const suffix = \"```\";\n",
+    "\n",
+    "const customOutputParser = (input: string) => {\n",
+    "  if (input.includes(suffix)) {\n",
+    "    return input.split(suffix)[0];\n",
+    "  }\n",
+    "  throw new Error(\"Input does not contain suffix.\")\n",
+    "};\n",
+    "\n",
+    "const res = await model.invoke(\n",
+    "  \"You can print 'hello world' to the console in javascript like this:\\n```javascript\", {\n",
+    "    suffix,\n",
+    "  }\n",
+    ");\n",
+    "\n",
+    "console.log(customOutputParser(res));"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "TypeScript",
+   "language": "typescript",
+   "name": "tslab"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "mode": "typescript",
+    "name": "javascript",
+    "typescript": true
+   },
+   "file_extension": ".ts",
+   "mimetype": "text/typescript",
+   "name": "typescript",
+   "version": "3.7.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

examples/src/models/chat/chat_mistralai_tools.ts

@@ -33,7 +33,7 @@ class CalculatorTool extends StructuredTool {
 
 const model = new ChatMistralAI({
   apiKey: process.env.MISTRAL_API_KEY,
-  model: "mistral-large",
+  model: "mistral-large-latest",
 });
 
 // Bind the tool to the model

examples/src/models/chat/chat_mistralai_wsa.ts

@@ -14,7 +14,7 @@ const calculatorSchema = z
 
 const model = new ChatMistralAI({
   apiKey: process.env.MISTRAL_API_KEY,
-  model: "mistral-large",
+  model: "mistral-large-latest",
 });
 
 // Pass the schema and tool name to the withStructuredOutput method

examples/src/models/chat/chat_mistralai_wsa_json.ts

@@ -21,7 +21,7 @@ const calculatorJsonSchema = {
 
 const model = new ChatMistralAI({
   apiKey: process.env.MISTRAL_API_KEY,
-  model: "mistral-large",
+  model: "mistral-large-latest",
 });
 
 // Pass the schema and tool name to the withStructuredOutput method

libs/langchain-mistralai/package.json

@@ -41,7 +41,7 @@
   "license": "MIT",
   "dependencies": {
     "@langchain/core": ">0.1.56 <0.3.0",
-    "@mistralai/mistralai": "^0.1.3",
+    "@mistralai/mistralai": "^0.4.0",
     "uuid": "^9.0.0",
     "zod": "^3.22.4",
     "zod-to-json-schema": "^3.22.4"