scripts[minor]: Add toolkit template #6391
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "raw", | ||
| "id": "afaf8039", | ||
| "metadata": { | ||
| "vscode": { | ||
| "languageId": "raw" | ||
| } | ||
| }, | ||
| "source": [ | ||
| "---\n", | ||
| "sidebar_label: Sql Toolkit\n", | ||
| "---" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "e49f1e0d", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# SqlToolkit\n", | ||
| "\n", | ||
| "This will help you getting started with the [SqlToolkit](/docs/concepts/#toolkits). For detailed documentation of all SqlToolkit features and configurations head to the [API reference](https://api.js.langchain.com/classes/langchain_agents_toolkits_sql.SqlToolkit.html). You can also find the documentation for the Python equivalent [here](https://python.langchain.com/docs/integrations/toolkits/sql_database/)\n", | ||
| "\n", | ||
| "## Setup\n", | ||
| "\n", | ||
| "If you want to get automated tracing from runs of individual tools, you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:\n", | ||
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| "\n", | ||
| "```typescript\n", | ||
| "process.env.LANGCHAIN_TRACING_V2=\"true\"\n", | ||
| "process.env.LANGCHAIN_API_KEY=\"your-api-key\"\n", | ||
| "```\n", | ||
| "\n", | ||
| "### Installation\n", | ||
| "\n", | ||
| "This toolkit lives in the `langchain` package. You'll also need to install the `typeorm` peer dependency.\n", | ||
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| "\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 typeorm\n", | ||
| "</Npm2Yarn>\n", | ||
| "```" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "a38cde65-254d-4219-a441-068766c0d4b5", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Instantiation\n", | ||
| "\n", | ||
| "This example uses Chinook database, which is a sample database available for SQL Server, Oracle, MySQL, etc. To set it up, follow [these instructions](https://database.guide/2-sample-databases-sqlite/), placing the `.db` file in the directory where your code lives.\n", | ||
|
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| "\n", | ||
| "Next, we need to define our LLM to be used in the toolkit.\n", | ||
| "\n", | ||
| "```{=mdx}\n", | ||
| "import ChatModelTabs from \"@theme/ChatModelTabs\";\n", | ||
| "\n", | ||
| "<ChatModelTabs customVarName=\"llm\" />\n", | ||
| "```" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 8, | ||
| "id": "d1002b65", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "// @lc-docs-hide-cell\n", | ||
| "\n", | ||
| "import { ChatOpenAI } from \"@langchain/openai\";\n", | ||
| "\n", | ||
| "const llm = new ChatOpenAI({\n", | ||
| " model: \"gpt-4o-mini\",\n", | ||
| " temperature: 0,\n", | ||
| "})" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 20, | ||
| "id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import { SqlToolkit } from \"langchain/agents/toolkits/sql\"\n", | ||
| "import { DataSource } from \"typeorm\";\n", | ||
| "import { SqlDatabase } from \"langchain/sql_db\";\n", | ||
| "\n", | ||
| "const datasource = new DataSource({\n", | ||
| " type: \"sqlite\",\n", | ||
| " database: \"../../../../../../Chinook.db\", // Replace with the link to your database\n", | ||
| "});\n", | ||
| "const db = await SqlDatabase.fromDataSourceParams({\n", | ||
| " appDataSource: datasource,\n", | ||
| "});\n", | ||
| "\n", | ||
| "const toolkit = new SqlToolkit(db, llm);" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "5c5f2839-4020-424e-9fc9-07777eede442", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Tools\n", | ||
| "\n", | ||
| "View available tools:" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 21, | ||
| "id": "51a60dbe-9f2e-4e04-bb62-23968f17164a", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "[\n", | ||
| " {\n", | ||
| " name: 'query-sql',\n", | ||
| " description: 'Input to this tool is a detailed and correct SQL query, output is a result from the database.\\n' +\n", | ||
| " ' If the query is not correct, an error message will be returned.\\n' +\n", | ||
| " ' If an error is returned, rewrite the query, check the query, and try again.'\n", | ||
| " },\n", | ||
| " {\n", | ||
| " name: 'info-sql',\n", | ||
| " description: 'Input to this tool is a comma-separated list of tables, output is the schema and sample rows for those tables.\\n' +\n", | ||
| " ' Be sure that the tables actually exist by calling list-tables-sql first!\\n' +\n", | ||
| " '\\n' +\n", | ||
| " ' Example Input: \"table1, table2, table3.'\n", | ||
| " },\n", | ||
| " {\n", | ||
| " name: 'list-tables-sql',\n", | ||
| " description: 'Input is an empty string, output is a comma-separated list of tables in the database.'\n", | ||
| " },\n", | ||
| " {\n", | ||
| " name: 'query-checker',\n", | ||
| " description: 'Use this tool to double check if your query is correct before executing it.\\n' +\n", | ||
| " ' Always use this tool before executing a query with query-sql!'\n", | ||
| " }\n", | ||
| "]\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "const tools = toolkit.getTools();\n", | ||
| "\n", | ||
| "console.log(tools.map((tool) => ({\n", | ||
| " name: tool.name,\n", | ||
| " description: tool.description,\n", | ||
| "})))" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "dfe8aad4-8626-4330-98a9-7ea1ca5d2e0e", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Use within an agent\n", | ||
| "\n", | ||
| "First, ensure you have LangGraph installed:\n", | ||
| "\n", | ||
| "```{=mdx}\n", | ||
| "<Npm2Yarn>\n", | ||
| " @langchain/langgraph\n", | ||
| "</Npm2Yarn>\n", | ||
| "```" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 22, | ||
| "id": "310bf18e-6c9a-4072-b86e-47bc1fcca29d", | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import { createReactAgent } from \"@langchain/langgraph/prebuilt\"\n", | ||
| "\n", | ||
| "const agentExecutor = createReactAgent({ llm, tools });" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 26, | ||
| "id": "23e11cc9-abd6-4855-a7eb-799f45ca01ae", | ||
| "metadata": {}, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "[\n", | ||
| " {\n", | ||
| " name: 'list-tables-sql',\n", | ||
| " args: {},\n", | ||
| " type: 'tool_call',\n", | ||
| " id: 'call_LqsRA86SsKmzhRfSRekIQtff'\n", | ||
| " }\n", | ||
| "]\n", | ||
| "Album, Artist, Customer, Employee, Genre, Invoice, InvoiceLine, MediaType, Playlist, PlaylistTrack, Track\n", | ||
| "[\n", | ||
| " {\n", | ||
| " name: 'query-checker',\n", | ||
| " args: { input: 'SELECT * FROM Artist LIMIT 10;' },\n", | ||
| " type: 'tool_call',\n", | ||
| " id: 'call_MKBCjt4gKhl5UpnjsMHmDrBH'\n", | ||
| " }\n", | ||
| "]\n", | ||
| "The SQL query you provided is:\n", | ||
| "\n", | ||
| "```sql\n", | ||
| "SELECT * FROM Artist LIMIT 10;\n", | ||
| "```\n", | ||
| "\n", | ||
| "This query is straightforward and does not contain any of the common mistakes listed. It simply selects all columns from the `Artist` table and limits the result to 10 rows. \n", | ||
| "\n", | ||
| "Therefore, there are no mistakes to correct, and the original query can be reproduced as is:\n", | ||
| "\n", | ||
| "```sql\n", | ||
| "SELECT * FROM Artist LIMIT 10;\n", | ||
| "```\n", | ||
| "[\n", | ||
| " {\n", | ||
| " name: 'query-sql',\n", | ||
| " args: { input: 'SELECT * FROM Artist LIMIT 10;' },\n", | ||
| " type: 'tool_call',\n", | ||
| " id: 'call_a8MPiqXPMaN6yjN9i7rJctJo'\n", | ||
| " }\n", | ||
| "]\n", | ||
| "[{\"ArtistId\":1,\"Name\":\"AC/DC\"},{\"ArtistId\":2,\"Name\":\"Accept\"},{\"ArtistId\":3,\"Name\":\"Aerosmith\"},{\"ArtistId\":4,\"Name\":\"Alanis Morissette\"},{\"ArtistId\":5,\"Name\":\"Alice In Chains\"},{\"ArtistId\":6,\"Name\":\"Antônio Carlos Jobim\"},{\"ArtistId\":7,\"Name\":\"Apocalyptica\"},{\"ArtistId\":8,\"Name\":\"Audioslave\"},{\"ArtistId\":9,\"Name\":\"BackBeat\"},{\"ArtistId\":10,\"Name\":\"Billy Cobham\"}]\n", | ||
| "Here are 10 artists from your database:\n", | ||
| "\n", | ||
| "1. AC/DC\n", | ||
| "2. Accept\n", | ||
| "3. Aerosmith\n", | ||
| "4. Alanis Morissette\n", | ||
| "5. Alice In Chains\n", | ||
| "6. Antônio Carlos Jobim\n", | ||
| "7. Apocalyptica\n", | ||
| "8. Audioslave\n", | ||
| "9. BackBeat\n", | ||
| "10. Billy Cobham\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "const exampleQuery = \"Can you list 10 artists from my database?\"\n", | ||
| "\n", | ||
| "const events = await agentExecutor.stream(\n", | ||
| " { messages: [[\"user\", exampleQuery]]},\n", | ||
| " { streamMode: \"values\", }\n", | ||
| ")\n", | ||
| "\n", | ||
| "for await (const event of events) {\n", | ||
| " const lastMsg = event.messages[event.messages.length - 1];\n", | ||
| " if (lastMsg.tool_calls?.length) {\n", | ||
| " console.dir(lastMsg.tool_calls, { depth: null });\n", | ||
| " } else if (lastMsg.content) {\n", | ||
| " console.log(lastMsg.content);\n", | ||
| " }\n", | ||
| "}" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## API reference\n", | ||
| "\n", | ||
| "For detailed documentation of all SqlToolkit features and configurations head to the [API reference](https://api.js.langchain.com/classes/langchain_agents_toolkits_sql.SqlToolkit.html)." | ||
| ] | ||
| } | ||
| ], | ||
| "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": 5 | ||
| } | ||
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Should add something up here - what does this do? Why is it useful?