> ## Documentation Index
> Fetch the complete documentation index at: https://node-guide.dria.co/llms.txt
> Use this file to discover all available pages before exploring further.

# Using the Network

> 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

```bash theme={null}
npm install -g @dria/cli
```

Or use without installing:

```bash theme={null}
npx @dria/cli generate -m qwen3.5:9b "hello"
```

<Info>Requires Node.js 18.0.0 or higher.</Info>

## Getting Started

### 1. Initialize Your Wallet

```bash theme={null}
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:

```bash theme={null}
dria init --private-key 0xYOUR_PRIVATE_KEY
```

### 2. Add Credits

```bash theme={null}
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:

```bash theme={null}
dria balance
```

### 3. Start Generating

```bash theme={null}
dria generate -m qwen3.5:9b "explain quantum computing in one sentence"
```

## Commands

### `dria generate`

Single-prompt text generation with streaming output.

```bash theme={null}
# 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.

```bash theme={null}
# 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/`.

```bash theme={null}
# 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.

```bash theme={null}
dria models
```

### `dria post` & `dria feed`

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

```bash theme={null}
# 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:

```typescript theme={null}
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.