@truto/langchain-toolset

Truto's SuperAI Toolset for Langchain.js

A powerful toolset for integrating Truto's Proxy APIs with Langchain.js applications. This package provides all the Proxy APIs configured to be used as a tool on Truto as tools to Langchain. Read more about configuring tools on Truto here.

Installation

npm install @truto/langchain-toolset
# or
yarn add @truto/langchain-toolset

Prerequisites

• Node.js 22.14.0 or higher
• Yarn 1.22.19 or higher
• Truto API credentials
• Bun (for running examples)
• OpenAI API key (only needed for running examples)

Environment Setup

Create a .env file in your project root with the following variables:

TRUTO_API_TOKEN=your_truto_api_token

#OPTIONAL
OPENAI_API_KEY=your_openai_api_key # if you are using OpenAI models
TRUTO_API_BASE_URL=your_truto_api_base_url

Usage

Here's a complete example showing how to use the toolset with Langchain.js, including handling multiple tool executions:

To create or modify tools, please refer this Truto guide.

import { ChatOpenAI } from '@langchain/openai';
import { HumanMessage, SystemMessage } from '@langchain/core/messages';
import { isEmpty, values } from 'lodash-es';
import { ToolCall } from '@langchain/core/dist/messages/tool';
import { getTools } from '@truto/langchain-toolset';

// Initialize the LLM
const llm = new ChatOpenAI({
  model: 'o3-mini',
});

const INTEGRATED_ACCOUNT_ID = 'your_account_id';

async function main() {
  // Get all available tools for a customer connection
  const tools = await getTools(INTEGRATED_ACCOUNT_ID, {
    truto: {
      baseUrl: process.env.TRUTO_API_BASE_URL,
      token: process.env.TRUTO_API_TOKEN as string,
    },
    // Optional: Filter tools by specific methods
    methods: ['list', 'get', 'create', 'update', 'delete', 'read', 'write', 'custom', 'your_custom_method_name']
  });

  // Bind tools to the LLM
  const llmWithTools = llm.bindTools(values(tools));

  // Create your messages
  const messages = [
    new SystemMessage(
      'You are an assistant who uses the available tools to give the user an answer. Make sure you respect the arguments required for a tool call, use them to filter down the results wherever necessary. All the tools return a JSON string response, so parse the output correctly and use them in the arguments.'
    ),
    new HumanMessage('Your question here'),
  ];

  let toolCalls: ToolCall[] = [];
  do {
    // Execute any pending tool calls
    for (const toolCall of toolCalls) {
      const toolResponse = await tools[toolCall.name].invoke(toolCall);
      console.log('\n===================\n');
      console.log(
        'Called tool',
        toolCall.name,
        toolCall.args,
        toolResponse.content
      );
      messages.push(toolResponse);
    }

    // Get the next AI response
    const aiMessage = await llmWithTools.invoke(messages);
    messages.push(aiMessage);

    // Check if there are more tool calls to execute
    if (isEmpty(aiMessage.tool_calls)) {
      console.log('\n\n===================\n\n');
      console.log(aiMessage.content);
      break;
    }
    toolCalls = aiMessage.tool_calls || [];
  } while (!isEmpty(toolCalls));
}

main();

This example demonstrates:

• How to initialize the tools with Truto credentials
• How to bind tools to a Langchain.js LLM
• How to handle multiple tool calls in sequence
• How to process tool responses and continue the conversation
• How to properly handle the conversation flow until all tool calls are complete

API Reference

getTools

getTools(
  integratedAccountId: string,
  config: {
    truto: {
      baseUrl?: string;
      token: string;
    };
    methods?: Array<'list' | 'get' | 'create' | 'update' | 'delete' | 'read' | 'write' | 'custom' | string>;
  }
): Promise<Record<string, Tool>>

Returns a promise that resolves to an object containing all available tools for the specified integrated account. Each tool is a Langchain.js Tool instance that can be used with Langchain.js supported LLMs.

Parameters

• integratedAccountId (string): The ID of the integrated account to get tools for
• config (object): Configuration object
  • truto (object): Truto API configuration
    • baseUrl (string, optional): Custom base URL for the Truto API
    • token (string): Truto API token
  • methods (array, optional): Array of method names to filter tools by. Can include:
    • Standard CRUD operations: 'list', 'get', 'create', 'update', 'delete'
    • Permission-based methods: 'read', 'write'
    • Custom methods: 'custom'
    • Specific custom method names (string)

Returns

A promise that resolves to a Record<string, Tool> where each key is the tool name and the value is a Langchain.js Tool instance.

Running Examples

The repository includes example code in the examples directory. To run the examples:

1. First, install Bun if you haven't already:

   • Visit bun.sh to install Bun for your platform
   • Or use the following command:

   curl -fsSL https://bun.sh/install | bash

2. Install dependencies:

bun install

3. Set up your environment variables in .env as described above.

4. Run the example:

bun run examples/index.ts

The example demonstrates how to:

• Initialize the tools with Truto credentials
• Bind tools to a Langchain.js LLM
• Make tool calls and handle responses
• Process multi-turn conversations with tool usage

Development

To build the package locally:

yarn build

To run type checking:

yarn check

License

MIT

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.