Building a Decentralized AI Chatbot with MimirLLM: A Step-by-Step Tutorial

Explore the Decentralized Chatbot Landscape with MimirLLM

This tutorial guides you through building a decentralized chatbot using MimirLLM, a peer-to-peer communication library for AI language models. You'll create a system where nodes host and interact with Large Language Models (LLMs) across a decentralized network.

Key Learning Objectives:

• Setting up MimirLLM in Node and Client modes.
• Utilizing the /mimirllm/1.0.0 protocol for peer discovery and LLM communication.
• Integrating OpenAI or custom models like Ollama.

Prerequisites:

• Node.js v22.13.0 (LTS) or later (download from nodejs.org).
• Optional: Ollama or OpenAI API Key (for OpenAI or Ollama model integration).

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Step 1: Repository Cloning and Dependency Installation

Clone the MimirLLM repository and install its dependencies:

<code class="language-bash">git clone https://github.com/your-repo/mimirllm.git
cd mimirllm
npm install</code>

This installs libp2p (for peer-to-peer communication) and openai (for OpenAI model interaction).

Step 2: Setting Up an LLM Hosting Node

Configure a node to host an LLM and make it discoverable on the network.

Creating the Node Script (node.ts):

<code class="language-typescript">import { createLibp2p } from './createNode';
import libp2pConfig from '../../shared/libp2p';
import { MimirP2PClient } from '../../shared/mimir';

createLibp2p(libp2pConfig).then(async (node) => {
    console.log('Node listening on:');
    node.getMultiaddrs().forEach((ma) => console.log(ma.toString()));

    const mimir = new MimirP2PClient(node, {
        mode: "node",
        openaiConfig: {
            baseUrl: process.env.OLLAMA_ENDPOINT || "https://api.openai.com/v1",
            apiKey: process.env.OPENAI_API_KEY || null
        }
    });
    await mimir.start();
}).catch((e) => {
    console.error(e);
});</code>

Running the Node:

<code class="language-bash">tsx node.ts</code>

The node will begin listening and advertise its hosted LLMs. The output will show its listening address (e.g., /ip4/127.0.0.1/tcp/12345/p2p/QmPeerId).

Step 3: Building an LLM Interaction Client

Create a client to discover and interact with the hosted LLM.

Creating the Client Script (client.ts):

<code class="language-typescript">import { createLibp2p } from "libp2p";
import libp2pConfig from "../../shared/libp2p";
import { MimirP2PClient } from "../../shared/mimir";
import { createInterface } from "readline";
import { streamToConsole } from "../utils/stream";

// ... (rest of the client.ts code remains the same)</code>

Running the Client:

<code class="language-bash">tsx client.ts</code>

The client prompts for messages, discovers the node, sends messages, and streams responses.

Step 4: Protocol Overview

MimirLLM uses:

• Discovery Protocol (/mimirllm/1.0.0/identify): For peer discovery and initial communication. Clients query for LLMs; nodes respond with their hosted models.
• LLM Interaction Protocol (/mimirllm/1.0.0): For message exchange. Clients send messages; nodes forward them to the LLM and stream back responses.

Step 5: LLM Customization

MimirLLM supports OpenAI and Ollama. Configure the MimirP2PClient to use your preferred LLM. For Ollama, set the baseUrl to your endpoint; for OpenAI, provide your API key.

Step 6: Future Enhancements

Potential future improvements include robust discovery mechanisms, blockchain integration for incentivizing node participation, and support for additional LLMs.

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MimirLLM empowers decentralized AI. Explore its capabilities, contribute to its development, and share your decentralized AI applications. Happy coding! ?

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