Oneiro

Discord bot for image generation using Hugging Face Diffusers with Civitai integration.

Installation

pip install -e ".[dev]"

Usage

export TOKEN="your-discord-bot-token"
python -m oneiro

Or after installation:

oneiro

Configuration

Config uses layered TOML with hot-reload:

• Base config: Required, primary settings (config.toml)
• Overlay config: Optional, overrides base values
• State file: JSON, runtime-persisted values

Environment Variables

Variable	Required	Description
TOKEN	Yes	Discord bot token
CONFIG_PATH	No	Base config path (default: config.toml)
CONFIG_OVERLAY_PATH	No	Overlay config for overrides
STATE_PATH	No	Runtime state persistence (JSON)
HF_HOME	No	Hugging Face cache directory
CIVITAI_API_KEY	No	Civitai API key for downloading restricted models
CIVITAI_CACHE_DIR	No	Civitai cache directory (default: ~/.cache/civitai)
ENABLE_PROGRESS_BARS	No	Set to 1 to enable tqdm progress bars (disabled by default)

Discord Commands

Command	Description
/dream	Generate an image from a text prompt
/model	Switch the active model
/queue	Check your queue status
/config	Show current configuration
/fetch	Fetch and auto-configure a model from Civitai URL

/dream Parameters

Parameter	Description
prompt	Text prompt for generation (required)
negative_prompt	What to avoid in the image
image	Reference image for img2img
strength	img2img strength (0.0-1.0, higher = more change)
width	Image width (512, 768, 1024)
height	Image height (512, 768, 1024)
seed	Random seed (-1 for random)
lora	LoRA(s) to apply (see below)

LoRA Usage

The lora parameter supports multiple formats:

# Named LoRA from config
/dream prompt:"a portrait" lora:my-lora

# Named LoRA with custom weight
/dream prompt:"a portrait" lora:my-lora:0.8

# Direct Civitai reference (downloads on-demand)
/dream prompt:"a portrait" lora:civitai:12345

# Civitai reference with weight
/dream prompt:"a portrait" lora:civitai:12345:0.7

# Multiple LoRAs
/dream prompt:"a portrait" lora:my-lora:0.8,civitai:12345:0.5

Civitai Integration

Oneiro supports downloading and using models from Civitai:

• LoRAs: Use in /dream via lora:civitai:<id> or fetch with /fetch
• Checkpoints: Fetch with /fetch and switch with /model
• Embeddings: Fetch with /fetch for textual inversions

/fetch Command

Download and auto-configure resources from Civitai:

/fetch url:https://civitai.com/models/12345
/fetch url:https://civitai.com/models/12345 name:my-custom-name

The command automatically:

• Detects resource type (LoRA, Checkpoint, Embedding)
• Downloads to the cache directory
• Configures the resource in the state file
• Shows usage instructions

API Key

Some Civitai models require authentication. Set CIVITAI_API_KEY to download restricted content:

1. Go to https://civitai.com/user/account
2. Generate an API key
3. Set the environment variable

See config.toml for full configuration options with examples.

License

MIT - see LICENSE