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meta-ai-sdk

v0.0.7

Published

A TypeScript SDK for interacting with the Meta AI, providing tools for AI agents, integrations, and utilities to enhance developer productivity.

Downloads

720

Readme


Overview

Meta AI SDK provides a unified TypeScript interface for building, integrating, and automating with Meta AI models. It includes:

  • SDK for agent orchestration, tool integration, and context management
  • Utilities for safe, context-aware automation
  • CLI for advanced developer workflows (coming soon)

Features

  • MetaAI Class: Simple interface for interacting with Meta AI models
  • Agent Framework: Compose multi-agent systems with planning, tool selection, and feedback loops
  • Safe Execution: Built-in guardrails to prevent destructive actions
  • Streaming & Context: Stream model outputs and manage working memory
  • Extensible Tools: Integrate your own tools, functions, and APIs
  • Beautiful Terminal Output: Colorful, structured, and readable logs

Installation

Add to your project:

npm install npm i meta-ai-sdk

Requires Node.js 18+ and TypeScript 5+ for SDK usage.


Usage

Basic Usage with MetaAI

import { MetaAI } from '@orello/meta-sdk';

const meta = new MetaAI({
  apiKey: 'YOUR_API_KEY',
  model: 'meta-llama/Llama-2-7b-chat-hf',
});

async function main() {
  const response = await meta.generateContent({
    prompt: 'Summarize the latest AI research trends.',
    maxTokens: 256,
    temperature: 0.7,
  });
  console.log(response.result);
}

main();

Streaming Responses

import { MetaAI } from '@orello/meta-sdk';

const meta = new MetaAI({ apiKey: 'YOUR_API_KEY' });

async function streamExample() {
  const stream = await meta.generateContentStream({
    prompt: 'Write a poem about the ocean.',
    maxTokens: 100,
  });
  for await (const chunk of stream) {
    process.stdout.write(chunk.text);
  }
}

streamExample();

Agentic Workflow Example

The SDK supports multi-agent orchestration:

  1. Information Gathering: Collect files, logs, docs, and context
  2. Planning: Generate a markdown implementation plan and decompose into tasks
  3. Tool Detection: Select tools/functions and create execution plans
  4. Execution & Feedback: Run plans, detect errors, and retry with feedback loops

Contributing

Contributions are welcome! Please open an issue or submit a pull request.


License

MIT License