Files
ImageApi/src/enhance/template.rs
T
Cameron CordesandClaude Opus 5.5 e2cf18678f feat(enhance): pick LoRAs from ComfyUI per job (#220)
Templates with `imageapi:lora-slot:<n>:high|low` nodes take LoRAs picked
per job from a catalog built live from ComfyUI.

- Catalog: ComfyUI's LoraLoaderModelOnly `lora_name` choices (cached
  60 s, re-read when a submit names an unknown id), paired by High/Low
  name tokens (StyleHigh/StyleLow, x-HIGH/x-LOW, x_high_noise/...). Files
  the workflow already loads outside the slots (lightx2v, switches) and
  `[template.catalog] exclude` substrings never show; ids derive from the
  names so they stay stable.
- POST /enhance `slots: [{lora, scale?}]` fills the slots in order: each
  pick sets the slot nodes' lora_name and scales their exported strength;
  unused slots run at 0, so the graph is never rewired. More picks than
  slots, duplicates or unknown ids are 400s.
- GET /enhance/templates gains `slots` and `catalog: {loras, strength,
  min, max}`; jobs store and return the picks (new enhance_jobs.lora_slots
  JSON column).

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-11-03 16:28:23 -05:00

1184 lines
43 KiB
Rust

//! Workflow templates (#192): load, validate, and fill in an API-format
//! ComfyUI workflow for one photo.
//!
//! Nodes are found by `_meta.title`, never by id, so re-exporting after
//! editing the graph keeps working.
use std::collections::BTreeMap;
use std::path::Path;
use anyhow::{Context as _, Result, bail};
use serde_json::{Map, Value, json};
use super::config::{LoraConfig, LoraRequest, PromptMode, TemplateConfig};
pub const TITLE_SOURCE: &str = "imageapi:source";
pub const TITLE_SAVE: &str = "imageapi:save";
pub const TITLE_PROMPT: &str = "imageapi:prompt";
pub const TITLE_REFERENCE: &str = "imageapi:reference";
/// `imageapi:lora:<id>`: a LoRA loader the app can switch off (#218).
pub const TITLE_LORA_PREFIX: &str = "imageapi:lora:";
/// `imageapi:lora-slot:<n>:high|low`: a LoRA loader the app fills with a
/// LoRA picked from the catalog (#220); unused slots run at strength 0.
pub const TITLE_SLOT_PREFIX: &str = "imageapi:lora-slot:";
/// LoRA loader inputs a switch scales (0 = off). `strength_model` is
/// required (LoraLoaderModelOnly); `strength_clip` is scaled when present
/// (LoraLoader).
const LORA_STRENGTH_INPUTS: &[&str] = &["strength_model", "strength_clip"];
/// Prompt-node inputs, in the order they are tried.
const PROMPT_INPUTS: &[&str] = &["text", "prompt", "value"];
/// What a template produces, from its `imageapi:save` node's class.
#[derive(Debug, Clone, Copy, PartialEq, Eq, serde::Serialize)]
#[serde(rename_all = "lowercase")]
pub enum OutputKind {
/// Save Image Version: PNG versions.
Image,
/// Save Video Version: an MP4 (e.g. a clip animated from the photo).
Video,
}
/// The save node class that makes a template's output a video.
pub const VIDEO_SAVE_CLASS: &str = "ImageApiSaveVideoVersion";
/// Output nodes that write into ComfyUI's output folder on every API run.
const STRAY_OUTPUT_CLASSES: &[&str] = &[
"SaveImage",
"SaveAnimatedWEBP",
"SaveAnimatedPNG",
"SaveWEBM",
"SaveVideo",
"SaveGLB",
];
#[derive(Debug, Clone)]
pub struct Template {
pub cfg: TemplateConfig,
workflow: Map<String, Value>,
source_id: String,
save_id: String,
/// `(node id, input name)` of the prompt text.
prompt: Option<(String, &'static str)>,
reference_id: Option<String>,
/// Declared LoRA switches that have nodes, in `enhance.toml` order.
loras: Vec<LoraSwitch>,
/// Pickable-LoRA slots, by slot number.
slots: Vec<Slot>,
/// `lora_name`s the workflow loads outside the slots (lightx2v, switch
/// LoRAs): never offered in the catalog.
fixed_loras: std::collections::HashSet<String>,
/// Image or video, from the save node's class.
pub output: OutputKind,
/// Startup warnings (stray output nodes).
pub warnings: Vec<String>,
}
#[derive(Debug, Clone)]
struct LoraSwitch {
cfg: LoraConfig,
/// Every node titled `imageapi:lora:<id>`, with its exported strengths
/// (`(input, value)`), which the switch's scale multiplies.
nodes: Vec<(String, Vec<(&'static str, f64)>)>,
}
/// One pickable-LoRA slot: its high- and low-noise loader nodes, each with
/// its exported strengths (a pick's scale multiplies them).
#[derive(Debug, Clone)]
struct Slot {
high: Vec<(String, Vec<(&'static str, f64)>)>,
low: Vec<(String, Vec<(&'static str, f64)>)>,
}
/// A LoRA picked for one slot: its two files and the resolved scale.
#[derive(Debug, Clone, PartialEq)]
pub struct SlotPick {
pub high: String,
pub low: String,
pub scale: f64,
}
/// Why a request can't be turned into a ComfyUI prompt. The message is for
/// the caller, so it names the problem in the user's terms.
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct FillError(pub String);
impl std::fmt::Display for FillError {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
f.write_str(&self.0)
}
}
/// A filled-in prompt plus whether the reference node had to be removed
/// (so a ComfyUI rejection can be reported as "needs a reference photo").
#[derive(Debug)]
pub struct Filled {
pub prompt: Value,
pub dropped_reference: bool,
/// Every switch's resolved scale (0 = off; request, else its default);
/// stored on the job so a retry repeats it. Empty without switches.
pub loras: BTreeMap<String, f64>,
}
impl Template {
pub fn load(cfg: &TemplateConfig, base_dir: &Path) -> Result<Template> {
let path = if cfg.file.is_absolute() {
cfg.file.clone()
} else {
base_dir.join(&cfg.file)
};
let text = std::fs::read_to_string(&path)
.with_context(|| format!("reading workflow {}", path.display()))?;
let value: Value = serde_json::from_str(&text)
.with_context(|| format!("parsing workflow {}", path.display()))?;
Self::from_value(cfg.clone(), value)
}
pub fn from_value(cfg: TemplateConfig, value: Value) -> Result<Template> {
let Value::Object(workflow) = value else {
bail!("workflow is not a JSON object (is it the API-format export?)");
};
for (id, node) in &workflow {
if node.get("class_type").and_then(Value::as_str).is_none()
|| !node.get("inputs").is_some_and(Value::is_object)
{
bail!(
"node {id} has no class_type/inputs: this looks like a UI-format workflow, \
export with Workflow -> Export (API)"
);
}
}
let find = |title: &str| -> Result<Option<String>> {
let ids: Vec<&String> = workflow
.iter()
.filter(|(_, n)| title_of(n) == Some(title))
.map(|(id, _)| id)
.collect();
match ids.len() {
0 => Ok(None),
1 => Ok(Some(ids[0].clone())),
_ => bail!("more than one node is titled {title:?}"),
}
};
let Some(source_id) = find(TITLE_SOURCE)? else {
bail!("no node titled {TITLE_SOURCE:?} (the Load Image From Path that gets the photo)");
};
let Some(save_id) = find(TITLE_SAVE)? else {
bail!("no node titled {TITLE_SAVE:?} (the Save Image Version node)");
};
require_input(&workflow, &source_id, "path", TITLE_SOURCE)?;
let prompt = match find(TITLE_PROMPT)? {
None => None,
Some(id) => {
let inputs = inputs_of(&workflow, &id);
let Some(name) = PROMPT_INPUTS
.iter()
.copied()
.find(|n| inputs.get(*n).is_some_and(Value::is_string))
else {
bail!(
"node {TITLE_PROMPT:?} has none of the inputs {PROMPT_INPUTS:?} \
as a plain string (a linked input can't take the user's text)"
);
};
Some((id, name))
}
};
if cfg.prompt_mode == PromptMode::Replace && prompt.is_none() {
bail!("prompt_mode = \"replace\" needs a node titled {TITLE_PROMPT:?}");
}
let reference_id = find(TITLE_REFERENCE)?;
if let Some(id) = &reference_id {
require_input(&workflow, id, "path", TITLE_REFERENCE)?;
}
let mut warnings = Vec::new();
// LoRA switches: declared ids collect their nodes; a declared id with
// none is skipped (not offered), an undeclared node keeps its strength.
let mut lora_nodes: BTreeMap<&str, Vec<String>> = BTreeMap::new();
for (id, node) in &workflow {
if let Some(lora) = title_of(node).and_then(|t| t.strip_prefix(TITLE_LORA_PREFIX)) {
if !inputs_of(&workflow, id)
.get("strength_model")
.is_some_and(Value::is_number)
{
bail!(
"node {id} titled {:?} has no numeric strength_model input \
(use a LoraLoaderModelOnly or LoraLoader)",
format!("{TITLE_LORA_PREFIX}{lora}")
);
}
lora_nodes.entry(lora).or_default().push(id.clone());
}
}
let mut loras = Vec::new();
for l in &cfg.loras {
match lora_nodes.remove(l.id.as_str()) {
Some(mut ids) => {
ids.sort();
let nodes = ids
.into_iter()
.map(|id| {
let inputs = inputs_of(&workflow, &id);
let exported = LORA_STRENGTH_INPUTS
.iter()
.filter_map(|k| {
inputs.get(*k).and_then(Value::as_f64).map(|v| (*k, v))
})
.collect();
(id, exported)
})
.collect();
loras.push(LoraSwitch {
cfg: l.clone(),
nodes,
});
}
None => warnings.push(format!(
"lora {:?} has no node titled {:?}, so it isn't offered",
l.id,
format!("{TITLE_LORA_PREFIX}{}", l.id)
)),
}
}
for lora in lora_nodes.keys() {
warnings.push(format!(
"node titled {:?} has no [[template.lora]] entry, so it stays at its exported strength",
format!("{TITLE_LORA_PREFIX}{lora}")
));
}
// Pickable-LoRA slots, and the LoRAs loaded outside them.
let exported = |id: &str| -> Vec<(&'static str, f64)> {
let inputs = inputs_of(&workflow, id);
LORA_STRENGTH_INPUTS
.iter()
.filter_map(|k| inputs.get(*k).and_then(Value::as_f64).map(|v| (*k, v)))
.collect()
};
let mut slot_map: BTreeMap<u32, Slot> = BTreeMap::new();
let mut fixed_loras = std::collections::HashSet::new();
for (id, node) in &workflow {
let Some(rest) = title_of(node).and_then(|t| t.strip_prefix(TITLE_SLOT_PREFIX)) else {
if let Some(name) = inputs_of(&workflow, id)
.get("lora_name")
.and_then(Value::as_str)
{
fixed_loras.insert(name.to_string());
}
continue;
};
let title = format!("{TITLE_SLOT_PREFIX}{rest}");
let (n, role) = rest
.split_once(':')
.and_then(|(n, role)| Some((n.parse::<u32>().ok().filter(|n| *n > 0)?, role)))
.ok_or_else(|| {
anyhow::anyhow!(
"node {id} titled {title:?}: expected {TITLE_SLOT_PREFIX}<n>:high or :low (n from 1)"
)
})?;
let inputs = inputs_of(&workflow, id);
if !inputs.get("lora_name").is_some_and(Value::is_string)
|| !inputs.get("strength_model").is_some_and(Value::is_number)
{
bail!(
"node {id} titled {title:?} needs a lora_name and a numeric strength_model \
(use a LoraLoaderModelOnly or LoraLoader)"
);
}
let slot = slot_map.entry(n).or_insert(Slot {
high: Vec::new(),
low: Vec::new(),
});
match role {
"high" => slot.high.push((id.clone(), exported(id))),
"low" => slot.low.push((id.clone(), exported(id))),
_ => bail!("node {id} titled {title:?}: the role must be high or low"),
}
}
for (n, slot) in &slot_map {
if slot.high.is_empty() || slot.low.is_empty() {
bail!("LoRA slot {n} needs both a :high and a :low node");
}
}
if let Some((last, _)) = slot_map.last_key_value()
&& *last as usize != slot_map.len()
{
bail!(
"LoRA slots must be numbered 1..{} without gaps",
slot_map.len()
);
}
let slots: Vec<Slot> = slot_map.into_values().collect();
for (id, node) in &workflow {
let class = node["class_type"].as_str().unwrap_or_default();
if STRAY_OUTPUT_CLASSES.contains(&class) {
warnings.push(format!(
"node {id} ({class}) also writes into ComfyUI's output folder on every run"
));
}
}
let output = if workflow[&save_id]["class_type"].as_str() == Some(VIDEO_SAVE_CLASS) {
OutputKind::Video
} else {
OutputKind::Image
};
Ok(Template {
cfg,
workflow,
source_id,
save_id,
prompt,
reference_id,
loras,
slots,
fixed_loras,
output,
warnings,
})
}
pub fn accepts_prompt(&self) -> bool {
self.prompt.is_some()
}
pub fn accepts_reference(&self) -> bool {
self.reference_id.is_some()
}
pub fn prompt_required(&self) -> bool {
self.cfg.prompt_mode == PromptMode::Replace
}
/// How many pickable-LoRA slots the workflow has (#220).
pub fn slot_count(&self) -> usize {
self.slots.len()
}
/// `lora_name`s loaded outside the slots; kept out of the catalog.
pub fn fixed_loras(&self) -> &std::collections::HashSet<String> {
&self.fixed_loras
}
/// The LoRA switches clients can offer (declared and present in the
/// workflow), in `enhance.toml` order.
pub fn lora_switches(&self) -> impl Iterator<Item = &LoraConfig> {
self.loras.iter().map(|l| &l.cfg)
}
/// Fill the workflow for one photo.
///
/// - `source` / `reference` are paths as ComfyUI sees them.
/// - Without a reference the reference node and every link to it are
/// removed: its leftover export path must never be used.
/// - Every `seed` / `noise_seed` / `*.seed` input gets a fresh value
/// (ComfyUI's "randomize after generate" only exists in its page), or a
/// retry would return the cached result.
/// - `loras` sets each switch (missing = its default; see
/// [`LoraConfig::resolve`]): the resolved scale multiplies the node's
/// exported strengths, 0 being off, so the graph is never rewired.
pub fn fill(
&self,
source: &str,
prompt: Option<&str>,
reference: Option<&str>,
loras: &BTreeMap<String, LoraRequest>,
picks: &[SlotPick],
next_seed: &mut dyn FnMut() -> u64,
) -> Result<Filled, FillError> {
if picks.len() > self.slots.len() {
return Err(FillError(if self.slots.is_empty() {
"this template doesn't take picked LoRAs".to_string()
} else {
format!(
"this template takes at most {} picked LoRAs",
self.slots.len()
)
}));
}
if let Some(unknown) = loras
.keys()
.find(|id| !self.loras.iter().any(|l| &l.cfg.id == *id))
{
return Err(FillError(format!(
"this template has no LoRA switch {unknown:?}"
)));
}
let user_text = prompt.map(str::trim).filter(|t| !t.is_empty());
match (&self.prompt, user_text) {
(None, Some(_)) => {
return Err(FillError("this template doesn't take a prompt".to_string()));
}
(Some(_), None) if self.prompt_required() => {
return Err(FillError(
"this template needs an instruction (the prompt can't be empty)".to_string(),
));
}
_ => {}
}
if reference.is_some() && self.reference_id.is_none() {
return Err(FillError(
"this template doesn't take a reference photo".to_string(),
));
}
let mut wf = self.workflow.clone();
set_input(&mut wf, &self.source_id, "path", json!(source));
set_input(&mut wf, &self.save_id, "require_approval", json!(true));
if let (Some((id, input)), Some(text)) = (&self.prompt, user_text) {
let base = inputs_of(&wf, id)
.get(*input)
.and_then(Value::as_str)
.unwrap_or_default()
.to_string();
let combined = match self.cfg.prompt_mode {
PromptMode::Replace => text.to_string(),
PromptMode::Append if base.trim().is_empty() => text.to_string(),
PromptMode::Append => format!("{base}{}{text}", self.cfg.prompt_join),
};
set_input(&mut wf, id, input, json!(combined));
}
let mut dropped_reference = false;
if let Some(ref_id) = &self.reference_id {
match reference {
Some(path) => set_input(&mut wf, ref_id, "path", json!(path)),
None => {
wf.remove(ref_id);
for node in wf.values_mut() {
if let Some(inputs) = node.get_mut("inputs").and_then(Value::as_object_mut)
{
inputs.retain(|_, v| !links_to(v, ref_id));
}
}
dropped_reference = true;
}
}
}
let mut resolved = BTreeMap::new();
for switch in &self.loras {
let scale = switch.cfg.resolve(loras.get(&switch.cfg.id).copied());
resolved.insert(switch.cfg.id.clone(), scale);
for (id, exported) in &switch.nodes {
for (input, value) in exported {
set_input(&mut wf, id, input, json!(value * scale));
}
}
}
// Picked LoRAs fill the slots in order; the rest run at 0 (their
// exported lora_name stays, a file ComfyUI knows).
for (i, slot) in self.slots.iter().enumerate() {
let pick = picks.get(i).filter(|p| p.scale > 0.0);
for (nodes, file) in [
(&slot.high, pick.map(|p| p.high.as_str())),
(&slot.low, pick.map(|p| p.low.as_str())),
] {
for (id, exported) in nodes {
if let Some(file) = file {
set_input(&mut wf, id, "lora_name", json!(file));
}
let scale = pick.map_or(0.0, |p| p.scale);
for (input, value) in exported {
set_input(&mut wf, id, input, json!(value * scale));
}
}
}
}
for node in wf.values_mut() {
let Some(inputs) = node.get_mut("inputs").and_then(Value::as_object_mut) else {
continue;
};
for (key, value) in inputs.iter_mut() {
if is_seed_input(key) && value.is_number() {
*value = json!(next_seed());
}
}
}
Ok(Filled {
prompt: Value::Object(wf),
dropped_reference,
loras: resolved,
})
}
}
fn title_of(node: &Value) -> Option<&str> {
node.get("_meta")?.get("title")?.as_str()
}
fn inputs_of<'a>(wf: &'a Map<String, Value>, id: &str) -> &'a Map<String, Value> {
static EMPTY: std::sync::LazyLock<Map<String, Value>> = std::sync::LazyLock::new(Map::new);
wf.get(id)
.and_then(|n| n.get("inputs"))
.and_then(Value::as_object)
.unwrap_or(&EMPTY)
}
fn require_input(wf: &Map<String, Value>, id: &str, input: &str, title: &str) -> Result<()> {
if !inputs_of(wf, id).get(input).is_some_and(Value::is_string) {
bail!("node {title:?} has no string input {input:?}");
}
Ok(())
}
fn set_input(wf: &mut Map<String, Value>, id: &str, input: &str, value: Value) {
if let Some(inputs) = wf
.get_mut(id)
.and_then(|n| n.get_mut("inputs"))
.and_then(Value::as_object_mut)
{
inputs.insert(input.to_string(), value);
}
}
/// `["<id>", n]`: a link to output `n` of node `id`.
fn links_to(v: &Value, id: &str) -> bool {
matches!(v.as_array().map(Vec::as_slice), Some([Value::String(s), Value::Number(_)]) if s == id)
}
/// A fresh seed for one job. 32 bits: some nodes cap their seed there
/// (SeedVR2VideoUpscaler's max is 2^32 - 1), and it's plenty of variety for
/// the ones that take 64.
pub fn random_seed() -> u64 {
u64::from(rand::random::<u32>())
}
fn is_seed_input(key: &str) -> bool {
key == "seed" || key == "noise_seed" || key.ends_with(".seed")
}
#[cfg(test)]
mod tests {
use super::*;
pub const RESTORE: &str = include_str!("../../tests/fixtures/enhance/restore_turbo.json");
pub const EDIT: &str = include_str!("../../tests/fixtures/enhance/edit_turbo.json");
pub const DEV: &str = include_str!("../../tests/fixtures/enhance/restore_dev.json");
/// The Animate template plus a Style pair titled `imageapi:lora:style`
/// (nodes 50 high, 51 low).
pub const ANIMATE_LORAS: &str = include_str!("../../tests/fixtures/enhance/animate_loras.json");
/// ANIMATE_LORAS plus two pickable slots chained after the switch:
/// 60/61 (slot 1 high/low), 62/63 (slot 2).
pub const ANIMATE_SLOTS: &str = include_str!("../../tests/fixtures/enhance/animate_slots.json");
fn pick(name: &str, scale: f64) -> SlotPick {
SlotPick {
high: format!("{name}_high.safetensors"),
low: format!("{name}_low.safetensors"),
scale,
}
}
fn lora(id: &str, default: bool) -> LoraConfig {
LoraConfig {
id: id.into(),
label: id.into(),
default,
strength: 1.0,
min: 0.0,
max: 1.5,
}
}
fn load_with_loras(json: &str, loras: Vec<LoraConfig>) -> Result<Template> {
let mut c = cfg("animate", PromptMode::Append);
c.loras = loras;
Template::from_value(c, serde_json::from_str(json).unwrap())
}
fn reqs(pairs: &[(&str, LoraRequest)]) -> BTreeMap<String, LoraRequest> {
pairs.iter().map(|(k, v)| (k.to_string(), *v)).collect()
}
fn scales(pairs: &[(&str, f64)]) -> BTreeMap<String, f64> {
pairs.iter().map(|(k, v)| (k.to_string(), *v)).collect()
}
fn none() -> BTreeMap<String, LoraRequest> {
BTreeMap::new()
}
fn cfg(name: &str, mode: PromptMode) -> TemplateConfig {
TemplateConfig {
name: name.into(),
label: name.into(),
description: String::new(),
file: "x.json".into(),
prompt_mode: mode,
prompt_join: " ".into(),
output_megapixels: 1.0,
loras: Vec::new(),
catalog: Default::default(),
}
}
fn load(json: &str, mode: PromptMode) -> Result<Template> {
Template::from_value(cfg("t", mode), serde_json::from_str(json).unwrap())
}
fn seeds() -> impl FnMut() -> u64 {
let mut n = 1000;
move || {
n += 1;
n
}
}
fn input<'a>(p: &'a Value, id: &str, name: &str) -> &'a Value {
&p[id]["inputs"][name]
}
#[test]
fn real_templates_load() {
let restore = load(RESTORE, PromptMode::Append).unwrap();
assert!(restore.accepts_prompt());
assert!(!restore.accepts_reference());
assert!(!restore.prompt_required());
let edit = load(EDIT, PromptMode::Replace).unwrap();
assert!(edit.accepts_prompt() && edit.accepts_reference() && edit.prompt_required());
assert!(load(DEV, PromptMode::Append).is_ok());
// The prompt node is a String Multiline primitive: input `value`.
assert_eq!(restore.prompt.as_ref().unwrap().1, "value");
assert!(restore.warnings.is_empty());
}
#[test]
fn missing_required_titles_are_rejected_with_a_clear_message() {
let no_source = RESTORE.replace("imageapi:source", "something else");
let err = load(&no_source, PromptMode::Append)
.unwrap_err()
.to_string();
assert!(err.contains("imageapi:source"), "{err}");
let no_save = RESTORE.replace("imageapi:save", "something else");
let err = load(&no_save, PromptMode::Append).unwrap_err().to_string();
assert!(err.contains("imageapi:save"), "{err}");
}
#[test]
fn rejects_ui_format_duplicates_and_bad_prompt_nodes() {
let ui = r#"{"nodes": [], "links": []}"#;
assert!(load(ui, PromptMode::Append).is_err());
let dup = RESTORE.replace("\"Load CLIP\"", "\"imageapi:source\"");
assert!(load(&dup, PromptMode::Append).is_err());
// Prompt node with none of text / prompt / value.
let mut v: Value = serde_json::from_str(RESTORE).unwrap();
v["13"]["inputs"] = json!({"other": "x"});
assert!(Template::from_value(cfg("t", PromptMode::Append), v).is_err());
// replace without a prompt node
let no_prompt = RESTORE.replace("imageapi:prompt", "nope");
assert!(load(&no_prompt, PromptMode::Replace).is_err());
assert!(load(&no_prompt, PromptMode::Append).is_ok());
}
#[test]
fn prompt_node_accepts_text_or_prompt_inputs() {
let mut v: Value = serde_json::from_str(RESTORE).unwrap();
v["13"]["inputs"] = json!({"prompt": "base"});
let t = Template::from_value(cfg("t", PromptMode::Append), v).unwrap();
let f = t
.fill(
"Z:\\a.jpg",
Some("more"),
None,
&BTreeMap::new(),
&[],
&mut seeds(),
)
.unwrap();
assert_eq!(input(&f.prompt, "13", "prompt"), "base more");
}
#[test]
fn stray_save_image_is_a_warning_not_an_error() {
let mut v: Value = serde_json::from_str(RESTORE).unwrap();
v["99"] = json!({"class_type": "SaveImage", "inputs": {"images": ["6", 0]}});
let t = Template::from_value(cfg("t", PromptMode::Append), v).unwrap();
assert_eq!(t.warnings.len(), 1);
assert!(t.warnings[0].contains("SaveImage"));
}
#[test]
fn fill_sets_path_forces_approval_and_randomises_every_seed() {
let t = load(RESTORE, PromptMode::Append).unwrap();
let f = t
.fill("Z:\\p\\a.jpg", None, None, &none(), &[], &mut seeds())
.unwrap();
assert_eq!(input(&f.prompt, "37", "path"), "Z:\\p\\a.jpg");
assert_eq!(input(&f.prompt, "36", "require_approval"), true);
// KSampler.seed and TextGenerate's sampling_mode.seed, both fresh.
let a = input(&f.prompt, "5", "seed").as_u64().unwrap();
let b = input(&f.prompt, "14", "sampling_mode.seed")
.as_u64()
.unwrap();
assert!(a > 1000 && b > 1000 && a != b);
assert_ne!(a, 774744764437710);
// Two fills with a real RNG differ.
let mut rng = random_seed;
let x = t.fill("p", None, None, &none(), &[], &mut rng).unwrap();
let y = t.fill("p", None, None, &none(), &[], &mut rng).unwrap();
assert_ne!(input(&x.prompt, "5", "seed"), input(&y.prompt, "5", "seed"));
}
#[test]
fn output_kind_follows_the_save_node() {
assert_eq!(
load(RESTORE, PromptMode::Append).unwrap().output,
OutputKind::Image
);
let video = RESTORE.replace(
"\"ImageApiSaveImageVersion\"",
"\"ImageApiSaveVideoVersion\"",
);
assert_ne!(video, RESTORE);
assert_eq!(
load(&video, PromptMode::Append).unwrap().output,
OutputKind::Video
);
}
#[test]
fn random_seeds_fit_seedvr2s_u32_limit() {
// SeedVR2VideoUpscaler rejects seeds above 2^32 - 1 at validation.
let t = load(RESTORE, PromptMode::Append).unwrap();
for _ in 0..200 {
let f = t
.fill("p", None, None, &none(), &[], &mut random_seed)
.unwrap();
assert!(input(&f.prompt, "5", "seed").as_u64().unwrap() <= u64::from(u32::MAX));
}
}
#[test]
fn force_approval_even_if_the_export_had_it_off() {
let off = RESTORE.replace("\"require_approval\": true", "\"require_approval\": false");
let t = load(&off, PromptMode::Append).unwrap();
let f = t.fill("p", None, None, &none(), &[], &mut seeds()).unwrap();
assert_eq!(input(&f.prompt, "36", "require_approval"), true);
}
#[test]
fn append_uses_the_join_text_and_empty_leaves_the_base() {
let base = "Increase the clarity";
let mut c = cfg("t", PromptMode::Append);
c.prompt_join = "\n\nAdditional instructions: ".into();
let mut v: Value = serde_json::from_str(RESTORE).unwrap();
v["13"]["inputs"]["value"] = json!(base);
let t = Template::from_value(c, v).unwrap();
let f = t
.fill(
"p",
Some(" warmer "),
None,
&BTreeMap::new(),
&[],
&mut seeds(),
)
.unwrap();
assert_eq!(
input(&f.prompt, "13", "value"),
"Increase the clarity\n\nAdditional instructions: warmer"
);
let f = t
.fill("p", Some(" "), None, &none(), &[], &mut seeds())
.unwrap();
assert_eq!(input(&f.prompt, "13", "value"), base);
let f = t.fill("p", None, None, &none(), &[], &mut seeds()).unwrap();
assert_eq!(input(&f.prompt, "13", "value"), base);
}
#[test]
fn default_join_is_a_single_space_sentence() {
let t = load(RESTORE, PromptMode::Append).unwrap();
let f = t
.fill(
"p",
Some("Make it warmer."),
None,
&BTreeMap::new(),
&[],
&mut seeds(),
)
.unwrap();
let text = input(&f.prompt, "13", "value").as_str().unwrap();
assert!(text.ends_with("Remove any phone interface overlays. Make it warmer."));
}
#[test]
fn replace_mode_requires_and_uses_the_instruction() {
let t = load(EDIT, PromptMode::Replace).unwrap();
let err = t
.fill("p", None, None, &none(), &[], &mut seeds())
.unwrap_err();
assert!(err.0.contains("instruction"));
assert!(
t.fill("p", Some(" "), None, &none(), &[], &mut seeds())
.is_err()
);
let f = t
.fill(
"p",
Some("make it black and white"),
None,
&BTreeMap::new(),
&[],
&mut seeds(),
)
.unwrap();
assert_eq!(input(&f.prompt, "13", "value"), "make it black and white");
}
#[test]
fn prompt_or_reference_the_template_cant_take_are_refused() {
let mut v: Value = serde_json::from_str(RESTORE).unwrap();
v.as_object_mut().unwrap().remove("13");
// 14 links to 13; drop that link so the graph stays plausible.
v["14"]["inputs"].as_object_mut().unwrap().remove("prompt");
let t = Template::from_value(cfg("t", PromptMode::Append), v).unwrap();
assert!(
t.fill("p", Some("x"), None, &none(), &[], &mut seeds())
.is_err()
);
assert!(t.fill("p", None, None, &none(), &[], &mut seeds()).is_ok());
let restore = load(RESTORE, PromptMode::Append).unwrap();
assert!(
restore
.fill("p", None, Some("r"), &none(), &[], &mut seeds())
.is_err()
);
}
#[test]
fn reference_given_sets_its_path_and_keeps_links() {
let t = load(EDIT, PromptMode::Replace).unwrap();
let f = t
.fill(
"src",
Some("x"),
Some("Z:\\ref.jpg"),
&BTreeMap::new(),
&[],
&mut seeds(),
)
.unwrap();
assert!(!f.dropped_reference);
assert_eq!(input(&f.prompt, "38", "path"), "Z:\\ref.jpg");
assert_eq!(input(&f.prompt, "36", "reference_1"), &json!(["38", 1]));
}
#[test]
fn no_reference_removes_the_node_and_every_link_to_it() {
let t = load(EDIT, PromptMode::Replace).unwrap();
let f = t
.fill("src", Some("x"), None, &none(), &[], &mut seeds())
.unwrap();
assert!(f.dropped_reference);
let wf = f.prompt.as_object().unwrap();
assert!(!wf.contains_key("38"));
// No input anywhere still links to node 38, and the leftover export
// path can't leak.
assert!(
!serde_json::to_string(&f.prompt)
.unwrap()
.contains("[\"38\"")
);
assert!(wf["36"]["inputs"].get("reference_1").is_none());
// Links to other nodes survive.
assert_eq!(input(&f.prompt, "36", "source"), &json!(["37", 1]));
}
#[test]
fn lora_switch_drives_every_node_with_its_id() {
let t = load_with_loras(ANIMATE_LORAS, vec![lora("style", false)]).unwrap();
assert_eq!(
t.lora_switches().map(|l| l.id.as_str()).collect::<Vec<_>>(),
["style"]
);
assert!(t.warnings.is_empty(), "{:?}", t.warnings);
// Default off: both the high and the low node go to 0.
let off = t.fill("p", None, None, &none(), &[], &mut seeds()).unwrap();
assert_eq!(off.loras, scales(&[("style", 0.0)]));
for id in ["50", "51"] {
assert_eq!(input(&off.prompt, id, "strength_model"), &json!(0.0));
}
// The graph isn't rewired, and the fixed lightx2v LoRAs are untouched.
assert_eq!(input(&off.prompt, "14", "model"), &json!(["50", 0]));
assert_eq!(input(&off.prompt, "12", "strength_model"), &json!(1.0));
// On: the configured strength (1.0 = as exported).
let on = t
.fill(
"p",
None,
None,
&reqs(&[("style", LoraRequest::On(true))]),
&[],
&mut seeds(),
)
.unwrap();
assert_eq!(on.loras, scales(&[("style", 1.0)]));
for id in ["50", "51"] {
assert_eq!(input(&on.prompt, id, "strength_model"), &json!(1.0));
}
}
#[test]
fn a_scale_multiplies_each_nodes_exported_strength() {
// A pair exported at different strengths keeps its ratio.
let mut v: Value = serde_json::from_str(ANIMATE_LORAS).unwrap();
v["51"]["inputs"]["strength_model"] = json!(0.8);
let mut c = cfg("animate", PromptMode::Append);
c.loras = vec![lora("style", false)];
let t = Template::from_value(c, v).unwrap();
let f = t
.fill(
"p",
None,
None,
&reqs(&[("style", LoraRequest::Scale(0.5))]),
&[],
&mut seeds(),
)
.unwrap();
assert_eq!(f.loras, scales(&[("style", 0.5)]));
assert_eq!(input(&f.prompt, "50", "strength_model"), &json!(0.5));
assert_eq!(input(&f.prompt, "51", "strength_model"), &json!(0.4));
// Clamped to the switch's max; 0 is off.
let f = t
.fill(
"p",
None,
None,
&reqs(&[("style", LoraRequest::Scale(9.0))]),
&[],
&mut seeds(),
)
.unwrap();
assert_eq!(f.loras, scales(&[("style", 1.5)]));
let f = t
.fill(
"p",
None,
None,
&reqs(&[("style", LoraRequest::Scale(0.0))]),
&[],
&mut seeds(),
)
.unwrap();
assert_eq!(input(&f.prompt, "51", "strength_model"), &json!(0.0));
}
#[test]
fn lora_default_on_and_unknown_ids_refused() {
let mut l = lora("style", true);
l.strength = 0.7;
let t = load_with_loras(ANIMATE_LORAS, vec![l]).unwrap();
let f = t.fill("p", None, None, &none(), &[], &mut seeds()).unwrap();
assert_eq!(f.loras, scales(&[("style", 0.7)]));
assert_eq!(input(&f.prompt, "50", "strength_model"), &json!(0.7));
let err = t
.fill(
"p",
None,
None,
&reqs(&[("nope", LoraRequest::On(true))]),
&[],
&mut seeds(),
)
.unwrap_err();
assert!(err.0.contains("nope"), "{err}");
}
#[test]
fn lora_clip_strength_is_scaled_too() {
let mut v: Value = serde_json::from_str(ANIMATE_LORAS).unwrap();
v["50"]["class_type"] = json!("LoraLoader");
v["50"]["inputs"]["strength_clip"] = json!(0.8);
let mut c = cfg("animate", PromptMode::Append);
c.loras = vec![lora("style", false)];
let t = Template::from_value(c, v).unwrap();
let off = t.fill("p", None, None, &none(), &[], &mut seeds()).unwrap();
assert_eq!(input(&off.prompt, "50", "strength_clip"), &json!(0.0));
let half = t
.fill(
"p",
None,
None,
&reqs(&[("style", LoraRequest::Scale(0.5))]),
&[],
&mut seeds(),
)
.unwrap();
assert_eq!(input(&half.prompt, "50", "strength_clip"), &json!(0.4));
}
#[test]
fn undeclared_or_missing_lora_switches_are_warnings() {
// Nodes but no [[template.lora]]: fixed at their strength, not offered.
let t = load_with_loras(ANIMATE_LORAS, Vec::new()).unwrap();
assert_eq!(t.lora_switches().count(), 0);
assert!(
t.warnings.iter().any(|w| w.contains("imageapi:lora:style")),
"{:?}",
t.warnings
);
let f = t.fill("p", None, None, &none(), &[], &mut seeds()).unwrap();
assert!(f.loras.is_empty());
assert_eq!(input(&f.prompt, "50", "strength_model"), &json!(1.0));
assert!(
t.fill(
"p",
None,
None,
&reqs(&[("style", LoraRequest::On(false))]),
&[],
&mut seeds(),
)
.is_err()
);
// Declared but no node: skipped with a warning, the rest load.
let t = load_with_loras(
ANIMATE_LORAS,
vec![lora("style", false), lora("detail", true)],
)
.unwrap();
assert_eq!(
t.lora_switches().map(|l| l.id.as_str()).collect::<Vec<_>>(),
["style"]
);
assert!(
t.warnings.iter().any(|w| w.contains("\"detail\"")),
"{:?}",
t.warnings
);
}
#[test]
fn a_lora_node_without_strength_model_is_rejected() {
let bad = ANIMATE_LORAS.replace(
"\"strength_model\": 1.0,\n \"model\": [\n \"12\"",
"\"weight\": 1.0,\n \"model\": [\n \"12\"",
);
assert_ne!(bad, ANIMATE_LORAS, "fixture layout changed");
let err = load_with_loras(&bad, vec![lora("style", false)])
.unwrap_err()
.to_string();
assert!(err.contains("strength_model"), "{err}");
}
#[test]
fn slots_are_found_and_fixed_loras_listed() {
let t = load(ANIMATE_SLOTS, PromptMode::Append).unwrap();
assert_eq!(t.slot_count(), 2);
let mut fixed: Vec<_> = t.fixed_loras().iter().cloned().collect();
fixed.sort();
assert_eq!(
fixed,
[
"example_style_high.safetensors",
"example_style_low.safetensors",
"wan2.2_i2v_lightx2v_4steps_lora_v1_high_noise.safetensors",
"wan2.2_i2v_lightx2v_4steps_lora_v1_low_noise.safetensors",
]
);
assert_eq!(
load(ANIMATE_LORAS, PromptMode::Append)
.unwrap()
.slot_count(),
0
);
}
#[test]
fn picks_fill_slots_in_order_and_unused_slots_run_at_zero() {
let t = load(ANIMATE_SLOTS, PromptMode::Append).unwrap();
let f = t
.fill(
"p",
None,
None,
&none(),
&[pick("motion", 0.5)],
&mut seeds(),
)
.unwrap();
assert_eq!(
input(&f.prompt, "60", "lora_name"),
&json!("motion_high.safetensors")
);
assert_eq!(
input(&f.prompt, "61", "lora_name"),
&json!("motion_low.safetensors")
);
assert_eq!(input(&f.prompt, "60", "strength_model"), &json!(0.5));
assert_eq!(input(&f.prompt, "61", "strength_model"), &json!(0.5));
// Slot 2 unused: its exported file stays, at strength 0.
assert_eq!(
input(&f.prompt, "62", "lora_name"),
&json!("example_slot_high.safetensors")
);
assert_eq!(input(&f.prompt, "62", "strength_model"), &json!(0.0));
assert_eq!(input(&f.prompt, "63", "strength_model"), &json!(0.0));
// The chain isn't rewired.
assert_eq!(input(&f.prompt, "14", "model"), &json!(["62", 0]));
// No picks at all: every slot off.
let f = t.fill("p", None, None, &none(), &[], &mut seeds()).unwrap();
assert_eq!(input(&f.prompt, "60", "strength_model"), &json!(0.0));
let err = t
.fill(
"p",
None,
None,
&none(),
&[pick("a", 1.0), pick("b", 1.0), pick("c", 1.0)],
&mut seeds(),
)
.unwrap_err();
assert!(err.0.contains("at most 2"), "{err}");
let plain = load(ANIMATE_LORAS, PromptMode::Append).unwrap();
assert!(
plain
.fill("p", None, None, &none(), &[pick("a", 1.0)], &mut seeds())
.is_err()
);
}
#[test]
fn malformed_slots_are_rejected() {
let only_high = ANIMATE_SLOTS.replace("imageapi:lora-slot:2:low", "something else");
let err = load(&only_high, PromptMode::Append)
.unwrap_err()
.to_string();
assert!(err.contains("slot 2 needs both"), "{err}");
let gap = ANIMATE_SLOTS
.replace("imageapi:lora-slot:2:high", "imageapi:lora-slot:3:high")
.replace("imageapi:lora-slot:2:low", "imageapi:lora-slot:3:low");
let err = load(&gap, PromptMode::Append).unwrap_err().to_string();
assert!(err.contains("without gaps"), "{err}");
let role = ANIMATE_SLOTS.replace("imageapi:lora-slot:1:high", "imageapi:lora-slot:1:mid");
assert!(
load(&role, PromptMode::Append)
.unwrap_err()
.to_string()
.contains("high or low")
);
let no_n = ANIMATE_SLOTS.replace("imageapi:lora-slot:1:high", "imageapi:lora-slot:x:high");
assert!(load(&no_n, PromptMode::Append).is_err());
}
}