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title Using the Network
description Use the Dria CLI to run inference, batch processing, and multi-turn conversations

Introduction

The Dria CLI (@dria/cli) lets you use the Dria decentralized inference network from the command line. Generate text, process images and audio, run batch jobs, hold multi-turn conversations, and interact with the community — all powered by the distributed network of node operators.

Installation

npm install -g @dria/cli

Or use without installing:

npx @dria/cli generate -m qwen3.5:9b "hello"

Requires Node.js 18.0.0 or higher.

Getting Started

1. Initialize Your Wallet

dria init

This generates a new Ethereum wallet, registers it with the Dria API, and saves your config to ~/.dria/config.json. You'll receive an API key for authenticating requests.

To import an existing wallet:

dria init --private-key 0xYOUR_PRIVATE_KEY

2. Add Credits

dria topup --amount 10

This deposits USDC credits via the x402 payment protocol (gasless EIP-712 signed transfer on Base network). Check your balance anytime:

dria balance

3. Start Generating

dria generate -m qwen3.5:9b "explain quantum computing in one sentence"

Commands

dria generate

Single-prompt text generation with streaming output.

# Basic text generation
dria generate -m qwen3.5:9b "hello"

# Vision — describe an image
dria generate -m lfm2.5-vl:1.6b "describe this" -a image.jpg

# Audio input
dria generate -m lfm2.5-audio:1.5b "transcribe this" -a recording.wav

# Structured output with quick schema
dria generate -m qwen3.5:9b "extract name and email" --schema 'name,email'

# Structured output with typed fields
dria generate -m qwen3.5:9b "extract data" --schema 'name,email,age:integer,score:number,active:boolean'

# Structured output with JSON schema file
dria generate -m qwen3.5:9b "extract" --schema-file schema.json

# Pipe from stdin
echo "hello" | dria generate -m qwen3.5:9b

# JSON output (machine-readable)
dria generate -m qwen3.5:9b "hello" --json

dria batch

Parallel batch generation from a JSONL file. Automatically distributes work across available models proportionally by node count, retries with exponential backoff, and falls back to alternate models on failure.

# Auto-select models based on content type
dria batch prompts.jsonl -o results.jsonl

# Use a specific model with concurrency of 20
dria batch -m qwen3.5:9b prompts.jsonl -o results.jsonl -c 20

dria chat

Multi-turn conversations with persistent history stored in ~/.dria/chats/.

# Start a new conversation
dria chat -m qwen3.5:9b "What is Rust?"

# Continue an existing conversation by ID
dria chat abc123ef "Tell me more about ownership"

# Read conversation history
dria chat abc123ef

# List all conversations
dria chat list

# Delete a conversation
dria chat delete abc123ef

dria models

List all available models on the network with their node counts.

dria models

dria post & dria feed

Interact with community channels (messages are bridged to Discord).

# Post a message
dria post "hello from CLI"

# Post to the requests channel with a custom display name
dria post "looking for qwen3.5:9b" -c requests -n my-agent

# Read recent messages
dria feed

# Follow mode — polls every 3 seconds
dria feed -f

# Read from a specific channel with a limit
dria feed -c requests -n 10

Configuration

Config is stored at ~/.dria/config.json (created by dria init). All fields can be overridden with environment variables:

Field Env Var Default Description
privateKey DKN_PRIVATE_KEY — Ethereum private key
apiKey DKN_API_KEY — API key from registration
apiBase DKN_API_BASE https://inference.dria.co API base URL
network DKN_NETWORK base Blockchain network for payments

Programmatic Usage

The CLI also exports a DknClient class for use in Node.js/TypeScript:

import { DknClient } from '@dria/cli';

const client = new DknClient('dkn_live_...', 'https://inference.dria.co');

const result = await client.generate({
  model: 'qwen3.5:9b',
  messages: [{ role: 'user', content: 'hello' }],
});

Output Conventions

  • Spinners and progress go to stderr, data goes to stdout — pipe-friendly by default.
  • Use --json on any command for raw JSON output with no spinners.
  • No spinners are shown when stdout is piped.

API Compatibility

The Dria inference API uses the OpenAI-compatible /v1/chat/completions endpoint format with Server-Sent Events (SSE) for streaming. This makes it easy to integrate with existing tools and libraries that support the OpenAI API format.