Skip to content

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.

License

Notifications You must be signed in to change notification settings

goPluto-ai/llm-tools-orchestration

Repository files navigation

🛠️ @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

About

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.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published