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A scalable functions or tools orchestration SDK for LLM agents, built on OpenAI’s /v1/responses API. Supports dynamic tool planning, memory lifecycle hooks, and multi-modal agent workflows.

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goPluto-ai/llm-tools-orchestration

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🛠️ @gopluto_ai/llm-tools-orchestration

Scalable LLM tool orchestration SDK with memory hooks, parallel Multi function execution, and GPT-4o (or any model) planning — built for production AI agents. Alternative of MCP for AI or LLM Parallel multi tool calling which is easy to understand.


🚀 Features

  • ✅ Register tools with full JSON schema
  • 🧠 Pre/post tool memory lifecycle hooks
  • 🔍 Plans tools dynamically using OpenAI /v1/responses API (⚠️ not chat completion)
  • 🛠️ Parallel tool execution with context-rich synthesis
  • 🔄 ESM + CommonJS ready for Node.js and serverless
  • 🔌 Works with any GPT model (gpt-4o, gpt-4-turbo, etc.) — dynamic model control

📦 Installation

npm install @gopluto_ai/llm-tools-orchestration
Set in .env
OPENAI_API_KEY = xxxxxxxxxxxx

⚡ Quick Example

import {
  registerTool,
  planTools,
  executeParallelTools,
  synthesizeFinalReply,
  registerHookProcessor
} from "@gopluto_ai/llm-tools-orchestration";
import { getOpenAIResData } from "@gopluto_ai/llm-tools-orchestration/dist/openaiHelpers";

registerHookProcessor("logStart", async (memory) => {
  console.log("🧠 Memory:", memory);
  return memory;
});

registerTool({
  type: "function",
  name: "get_stock_price",
  description: "Returns dummy stock price",
  parameters: {
    type: "object",
    required: ["ticker", "currency"],
    properties: {
      ticker: { type: "string" },
      currency: { type: "string" }
    }
  },
  preHooks: ["logStart"],
  handler: async ({ ticker, currency }) => {
    return { ticker, currency, price: 999.99 };
  }
});

const messages = {
  sysprompt: "You are a stock price assistant.",
  userMessage: "What's the price of TSLA in USD?",
  conversationHistory: [],
  agentMemory: {},
  imageUrl:'',
  fileUrl:''
};

(async () => {
  const plan = await planTools(messages, getOpenAIResData, "gpt-4o");
  const results = await executeParallelTools(plan.neededTools, plan.args, { userId: "xyz" });
  const reply = await synthesizeFinalReply(messages.userMessage, results, messages, plan.tools, getOpenAIResData, "gpt-4o");

  console.log("🧠 Final AI Reply:", reply);
})();

📁 Structure

src/
├── index.ts                  # Entry point
├── toolOrchestrator.ts       # Tool registration + planning
├── openaiHelpers.ts          # Handles OpenAI /v1/responses payloads
examples/
└── index.js                  # CLI-ready use case

🔒 This SDK Uses OpenAI's /v1/responses Endpoint

Unlike typical chat/completions, this SDK uses the new /v1/responses API to support multi-modal inputs (text, file, image) and tool usage natively.

This gives you:

  • Context-rich messages (system + memory)
  • Native tool calling structure
  • Easy agent memory injection
  • Full control over function outputs

🤝 Contributing

  1. Clone this repo
  2. Run npm install && npm run build
  3. Edit tools in src/toolOrchestrator.ts
  4. Submit PRs!

Contact

 Email: shubham@e2ecapital.com
 Contact: +91 9110035665
 Whatsapp: https://wa.me/919110035665

📝 License

MIT © GoPluto.ai

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A scalable functions or tools orchestration SDK for LLM agents, built on OpenAI’s /v1/responses API. Supports dynamic tool planning, memory lifecycle hooks, and multi-modal agent workflows.

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