Bindu - A2A Protocol Compliant AI Agent Framework

TypeScript agent using LangChain.js with Bindu SDK.

Code

/**
 * TypeScript LangChain Agent — Bindufied
 *
 * Demonstrates using the Bindu TypeScript SDK with LangChain.js.
 * The developer writes their agent using any TS framework — Bindu handles
 * the conversion to a microservice with DID, auth, x402, and A2A protocol.
 *
 * Usage:
 *   1. Set OPENAI_API_KEY in .env or environment
 *   2. npx tsx index.ts
 *
 * The SDK will:
 *   - Start the Bindu Python core in the background
 *   - Register this agent with DID identity and A2A endpoints
 *   - Listen for tasks via gRPC and execute them with LangChain
 */

import { bindufy, ChatMessage } from "@bindu/sdk";
import { ChatOpenAI } from "@langchain/openai";
import * as dotenv from "dotenv";

dotenv.config();

// Create LangChain agent — this is the developer's choice
const llm = new ChatOpenAI({
  model: "gpt-4o",
  temperature: 0.7,
});

// bindufy — one call, full microservice
bindufy(
  {
    author: "dev@example.com",
    name: "langchain-research-agent",
    description: "A research assistant built with LangChain.js and Bindu",
    version: "1.0.0",
    deployment: {
      url: "http://localhost:3773",
      expose: true,
      cors_origins: ["http://localhost:5173"],
    },
    skills: ["skills/typescript-langchain-skill"],
    capabilities: {
      streaming: false,
      push_notifications: false,
    },
  },
  async (messages: ChatMessage[]) => {
    // Convert Bindu messages to LangChain format
    const langchainMessages = messages.map((m) => ({
      role: m.role as "user" | "assistant" | "system",
      content: m.content,
    }));

    // Invoke LangChain
    const response = await llm.invoke(langchainMessages);

    // Return the content — Bindu handles the rest
    return typeof response.content === "string"
      ? response.content
      : JSON.stringify(response.content);
  }
);

Skill Configuration

Create skills/typescript-langchain-skill/skill.yaml:

# TypeScript LangChain Agent Skill
# TypeScript-based AI agent using LangChain.js framework

id: typescript-langchain-skill
name: TypeScript LangChain Agent Skill
version: 1.0.0
author: typescript-developer@example.com

description: |
  TypeScript agent that demonstrates Bindu SDK integration with LangChain.js.
  Built with modern TypeScript practices and LangChain framework for AI agent development.

  Features:
  - Direct LangChain.js integration
  - TypeScript type safety and modern ES features
  - OpenAI API integration through LangChain
  - Environment-based configuration
  - CORS-enabled for frontend integration

tags:
  - typescript
  - langchain
  - openai
  - bindu-sdk
  - agent-development
  - es2022
  - nodejs

input_modes:
  - application/json
output_modes:
  - application/json

examples:
  - "Research the latest developments in quantum computing and provide a summary"
  - "What are the main benefits of using LangChain with TypeScript?"
  - "How do I integrate LangChain with OpenAI in a TypeScript application?"
  - "Create a TypeScript agent that can analyze documents"
  - "What are the best practices for TypeScript agent development?"

capabilities_detail:
  langchain_integration:
    supported: true
    description: "Direct integration with LangChain.js framework"
    features:
      - chain_composition
      - memory_management
      - prompt_templates

  typescript_support:
    supported: true
    description: "Full TypeScript support with type safety"
    features:
      - es2022_target
      - strict_typing
      - modern_syntax

  openai_backend:
    supported: true
    description: "OpenAI API integration through LangChain"
    models_supported: ["gpt-4o", "gpt-4o-mini"]

  bindu_sdk:
    supported: true
    description: "Full Bindu SDK integration for protocol compliance"
    features:
      - did_support
      - x402_payments
      - a2a_protocol
      - cors_enabled

requirements:
  packages:
    - "@bindu/sdk"
    - "@langchain/openai"
    - "dotenv"
    - "@types/node"
    - "tsx"
  system:
    - node_18_or_higher
    - typescript_5_or_higher
  api_keys:
    - OPENAI_API_KEY

performance:
  avg_response_time_ms: 3000
  max_concurrent_requests: 5
  memory_usage_mb: 256
  scalability: vertical

assessment:
  keywords:
    - typescript
    - langchain
    - openai
    - agent
    - bindu
    - nodejs
    - es2022

  specializations:
    - domain: typescript-development
      confidence_boost: 0.4
    - domain: langchain-integration
      confidence_boost: 0.5
    - domain: openai-integration
      confidence_boost: 0.3

  anti_patterns:
    - "blocking operations"
    - "callback hell"
    - "type_any_usage"
    - "legacy_syntax"

  complexity_indicators:
    simple:
      - "research"
      - "explain"
      - "what is"
    medium:
      - "how to integrate"
      - "best practices for"
    complex:
      - "create agent that"
      - "comprehensive guide"
      - "production-ready"

How It Works

TypeScript SDK Integration

@bindu/sdk: TypeScript Bindu SDK for agent development
Automatic microservice generation with DID and auth
gRPC communication with Bindu Python core
A2A protocol compliance handled by SDK

LangChain.js Integration

ChatOpenAI: LangChain’s OpenAI integration
Message format conversion between Bindu and LangChain
Async/await pattern for response handling
Flexible content type handling

Message Processing

ChatMessage[]: Bindu message format with role and content
Role mapping (user/assistant/system) for LangChain compatibility
Content extraction and type checking
Response formatting for Bindu protocol

Configuration

Environment-based API key management
Standard Bindu deployment configuration
Skills and capabilities declaration
CORS origins for frontend integration

Dependencies

npm install @bindu/sdk @langchain/openai dotenv
npm install -D @types/node tsx

Environment Setup

Create .env file:

OPENAI_API_KEY=your_openai_api_key_here

Run

npx tsx index.ts

Examples:

“Research the latest developments in quantum computing and provide a summary”
“What are the main benefits of using LangChain with TypeScript?”
“How do I integrate LangChain with OpenAI in a TypeScript application?”

Example API Calls

Message Send Request

{
  "jsonrpc": "2.0",
  "method": "message/send",
  "params": {
    "message": {
      "role": "user",
      "kind": "message",
      "messageId": "9f11c870-5616-49ad-b187-d93cbb100001",
      "contextId": "9f11c870-5616-49ad-b187-d93cbb100002",
      "taskId": "9f11c870-5616-49ad-b187-d93cbb100003",
      "parts": [
        {
          "kind": "text",
          "text": "Research the latest developments in quantum computing and provide a summary"
        }
      ]
    },
     "skillId": "typescript-langchain-skill",
    "configuration": {
      "acceptedOutputModes": ["application/json"]
    }
  },
  "id": "9f11c870-5616-49ad-b187-d93cbb100003"
}

Task get Request

{
  "jsonrpc": "2.0",
  "method": "tasks/get",
  "params": {
    "taskId": "9f11c870-5616-49ad-b187-d93cbb100003"
  },
  "id": "9f11c870-5616-49ad-b187-d93cbb100004"
}

Frontend Setup

# Clone the Bindu repository
git clone https://github.com/GetBindu/Bindu

# Navigate to frontend directory
cd frontend

# Install dependencies
npm install

# Start frontend development server
npm run dev

Open http://localhost:5173 and try to chat with the TypeScript LangChain agent

Beginner

Specialized

Advanced

3.6 TypeScript LangChain Agent

Code

Skill Configuration

How It Works

Dependencies

Environment Setup

Run

Example API Calls

Frontend Setup

​Code

​Skill Configuration

​How It Works

​Dependencies

​Environment Setup

​Run

​Example API Calls

​Frontend Setup

Code

Skill Configuration

How It Works

Dependencies

Environment Setup

Run

Example API Calls

Frontend Setup