Vaayu: Small Language Machine Model (SLMM)

Vaayu is an ultra-lightweight, embeddable Small Language Machine Model (SLMM) family designed specifically for local machine execution, application integration, and native Model Context Protocol (MCP) tool calling.

Key Features

• Embedded & Local: Runs entirely locally on consumer hardware and CPUs/GPUs with low memory footprint (~245M to 492M parameters).
• Native MCP Support: Direct, first-class connection to Model Context Protocol servers over stdio and SSE.
• Structured Tool Calling: Emits precise tool calls in structured JSON formats with built-in schema compliance.
• Fast KV-Cache Inference: Optimized autoregressive generation with Grouped Query Attention (GQA).
• Zero Heavy Dependencies: Clean Python API designed to be embedded directly into existing applications, IDE extensions, or agentic frameworks.

Installation

pip install vaayu

Quickstart

1. Load Pretrained Model from Hugging Face

You can load official weights directly from the Hugging Face Hub:

from vaayu import Vaayu

# Load official Vaayu-Base directly from Hugging Face Hub
ai = Vaayu.from_pretrained("meetmendapara/Vaayu-Base")

# Generate response
response = ai.chat("Explain the purpose of Model Context Protocol (MCP) in one paragraph.")
print(response)

2. Connect to Local MCP Tools

Vaayu natively discovers and invokes tools provided by MCP servers:

from vaayu import Vaayu

ai = Vaayu.from_pretrained("meetmendapara/Vaayu-Base")

# Connect to any local MCP server (e.g. filesystem or custom service)
ai.attach_mcp_server(
    command="npx",
    args=["-y", "@modelcontextprotocol/server-filesystem", "./workspace"]
)

# Run an agentic prompt with tool execution
result = ai.agent_step("Read the file config.json and list all defined settings.")
print(result)

3. Load Local Checkpoints

If you have trained or downloaded local weights:

from vaayu import Vaayu

ai = Vaayu.load_local("checkpoints/vaayu_base/vaayu_final.pt")
print(ai.chat("Hello, Vaayu!"))

Command Line Interface (CLI)

Vaayu comes with an interactive CLI for chatting, testing tools, and inspecting weights:

# Start an interactive chat session with Hugging Face weights
vaayu chat --repo meetmendapara/Vaayu-Base

# Or chat with a local checkpoint
vaayu chat --weights checkpoints/vaayu_base/vaayu_final.pt

Architecture Variants

Resources & Links

• Hugging Face Model: meetmendapara/Vaayu-Base
• Source Code & Documentation: GitHub: Meetmendapara09/Vaayu-SLMM
• Model Context Protocol (MCP): modelcontextprotocol.io

License

MIT License. Free for academic research and commercial applications.