feat: improve agent workbench and digital human flows

This commit is contained in:
boos
2026-06-25 16:32:21 +08:00
parent 22e6c162b6
commit bc99c678f9
24 changed files with 4105 additions and 488 deletions
@@ -0,0 +1,13 @@
-- Restore the documented $1 starter credit for existing user default keys.
-- Keep explicit admin/recharge limits intact, and never leave default user keys
-- with NULL max_cost because NULL is treated as unlimited by the proxy path.
UPDATE downstream_api_keys
SET max_cost = 1.0,
updated_at = datetime('now')
WHERE user_id IS NOT NULL
AND (max_cost IS NULL OR max_cost <= 0.0)
AND (
name LIKE '% 的默认密钥'
OR name LIKE '% default key'
OR key LIKE 'sk-user-%'
);
@@ -0,0 +1,17 @@
CREATE INDEX IF NOT EXISTS proxy_logs_created_at_desc_idx
ON proxy_logs (created_at DESC, id DESC);
CREATE INDEX IF NOT EXISTS route_channels_route_enabled_cooldown_idx
ON route_channels (route_id, enabled, cooldown_until, account_id, token_id);
CREATE INDEX IF NOT EXISTS token_routes_enabled_id_idx
ON token_routes (enabled, id);
CREATE INDEX IF NOT EXISTS accounts_id_status_site_idx
ON accounts (id, status, site_id);
CREATE INDEX IF NOT EXISTS sites_id_status_url_idx
ON sites (id, status, url);
CREATE INDEX IF NOT EXISTS account_tokens_id_enabled_idx
ON account_tokens (id, enabled);
+12
View File
@@ -105,6 +105,8 @@ const SQLITE_COMPAT_DDL: &[&str] = &[
ON proxy_logs (downstream_api_key_id, created_at DESC, status)",
"CREATE INDEX IF NOT EXISTS proxy_logs_key_model_created_idx
ON proxy_logs (downstream_api_key_id, model_actual, created_at DESC)",
"CREATE INDEX IF NOT EXISTS proxy_logs_created_at_desc_idx
ON proxy_logs (created_at DESC, id DESC)",
"CREATE INDEX IF NOT EXISTS proxy_logs_content_summary_idx
ON proxy_logs (content_summary)",
"CREATE INDEX IF NOT EXISTS workspace_assets_user_output_created_idx
@@ -131,6 +133,16 @@ const SQLITE_COMPAT_DDL: &[&str] = &[
ON workspace_asset_daily (source, local_day DESC)",
"CREATE INDEX IF NOT EXISTS route_channels_oauth_route_unit_id_idx
ON route_channels (oauth_route_unit_id)",
"CREATE INDEX IF NOT EXISTS route_channels_route_enabled_cooldown_idx
ON route_channels (route_id, enabled, cooldown_until, account_id, token_id)",
"CREATE INDEX IF NOT EXISTS token_routes_enabled_id_idx
ON token_routes (enabled, id)",
"CREATE INDEX IF NOT EXISTS accounts_id_status_site_idx
ON accounts (id, status, site_id)",
"CREATE INDEX IF NOT EXISTS sites_id_status_url_idx
ON sites (id, status, url)",
"CREATE INDEX IF NOT EXISTS account_tokens_id_enabled_idx
ON account_tokens (id, enabled)",
"CREATE TABLE IF NOT EXISTS site_api_endpoints (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
site_id INTEGER NOT NULL,
+103 -3
View File
@@ -443,9 +443,21 @@ pub async fn delete_user(
Path(id): Path<i64>,
) -> AppResult<Json<Value>> {
info!("Deleting user: {}", id);
let mut tx = state.db.begin().await?;
sqlx::query("DELETE FROM downstream_api_keys WHERE user_id = ?")
.bind(id)
.execute(&mut *tx)
.await?;
sqlx::query("UPDATE invitations SET invited_by = NULL WHERE invited_by = ?")
.bind(id)
.execute(&mut *tx)
.await?;
let affected = sqlx::query("DELETE FROM users WHERE id = ?")
.bind(id)
.execute(&*state.db)
.execute(&mut *tx)
.await?
.rows_affected();
@@ -453,6 +465,8 @@ pub async fn delete_user(
return Err(AppError::NotFound(format!("User {} not found", id)));
}
tx.commit().await?;
Ok(Json(json!({ "data": { "deleted": true, "id": id } })))
}
@@ -953,6 +967,11 @@ mod tests {
.await
.expect("in-memory database");
sqlx::query("PRAGMA foreign_keys = ON")
.execute(&pool)
.await
.expect("enable foreign keys");
sqlx::query(
"CREATE TABLE users (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
@@ -989,7 +1008,7 @@ mod tests {
excluded_site_ids TEXT,
excluded_credential_refs TEXT,
last_used_at TEXT,
user_id INTEGER,
user_id INTEGER REFERENCES users(id),
created_at TEXT DEFAULT (datetime('now')),
updated_at TEXT DEFAULT (datetime('now'))
)",
@@ -998,6 +1017,23 @@ mod tests {
.await
.expect("downstream keys table");
sqlx::query(
"CREATE TABLE invitations (
id INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL,
org_id INTEGER NOT NULL,
email TEXT NOT NULL,
token TEXT NOT NULL UNIQUE,
role TEXT NOT NULL DEFAULT 'member',
invited_by INTEGER REFERENCES users(id),
status TEXT NOT NULL DEFAULT 'pending',
expires_at TEXT NOT NULL,
created_at TEXT DEFAULT (datetime('now'))
)",
)
.execute(&pool)
.await
.expect("invitations table");
AppState::new(
AppConfig {
server: ServerConfig {
@@ -1079,6 +1115,70 @@ mod tests {
assert_eq!(role, "admin");
}
#[tokio::test]
async fn delete_user_clears_owned_keys_and_nullable_references() {
let state = test_state().await;
let user_id = sqlx::query(
"INSERT INTO users (username, email, password_hash, role, status)
VALUES (?, ?, ?, 'user', 'active')",
)
.bind("Delete Me")
.bind("delete-me@example.test")
.bind("hash")
.execute(&*state.db)
.await
.expect("insert user")
.last_insert_rowid();
sqlx::query(
"INSERT INTO downstream_api_keys (name, key, user_id)
VALUES (?, ?, ?)",
)
.bind("default")
.bind("sk-delete-me")
.bind(user_id)
.execute(&*state.db)
.await
.expect("insert key");
sqlx::query(
"INSERT INTO invitations (org_id, email, token, invited_by, expires_at)
VALUES (1, 'invitee@example.test', 'tok-delete-me', ?, datetime('now', '+1 day'))",
)
.bind(user_id)
.execute(&*state.db)
.await
.expect("insert invitation");
let Json(value) = delete_user(State(state.clone()), Path(user_id))
.await
.expect("delete user");
assert_eq!(value["data"]["deleted"], true);
let user_count: i64 = sqlx::query_scalar("SELECT COUNT(*) FROM users WHERE id = ?")
.bind(user_id)
.fetch_one(&*state.db)
.await
.expect("count users");
assert_eq!(user_count, 0);
let key_count: i64 =
sqlx::query_scalar("SELECT COUNT(*) FROM downstream_api_keys WHERE user_id = ?")
.bind(user_id)
.fetch_one(&*state.db)
.await
.expect("count keys");
assert_eq!(key_count, 0);
let invited_by: Option<i64> =
sqlx::query_scalar("SELECT invited_by FROM invitations WHERE token = 'tok-delete-me'")
.fetch_one(&*state.db)
.await
.expect("read invitation");
assert_eq!(invited_by, None);
}
#[tokio::test]
async fn adjust_user_balance_writes_admin_adjust_ledger() {
let state = test_state().await;
@@ -1109,7 +1209,7 @@ mod tests {
.await
.expect("insert key");
adjust_user_balance(
let _ = adjust_user_balance(
State(state.clone()),
Path(user_id),
Json(AdjustBalanceRequest { delta: 5.0 }),
+132 -1
View File
@@ -32,7 +32,7 @@ use crate::services::agent_workbench::{
};
use crate::AppState;
use axum::{
extract::{DefaultBodyLimit, State},
extract::{DefaultBodyLimit, Path, Query, State},
http::{HeaderMap, StatusCode},
response::sse::{Event, Sse},
routing::{get, post},
@@ -73,6 +73,9 @@ pub fn routes() -> Router<AppState> {
.route("/api/agent/chat", post(chat_handler))
.route("/api/agent/approve", post(approve_handler))
.route("/api/agent/answer", post(answer_handler))
.route("/api/agent/models", get(models_handler))
.route("/api/agent/sessions", get(list_sessions_handler))
.route("/api/agent/sessions/{id}", get(get_session_handler))
.route("/api/agent/status", get(status_handler))
.layer(DefaultBodyLimit::max(AGENT_CHAT_BODY_LIMIT_BYTES))
}
@@ -105,6 +108,12 @@ struct AnswerRequest {
answer: String,
}
#[derive(Debug, Deserialize)]
struct SessionListQuery {
#[serde(default)]
limit: Option<i64>,
}
/// Resolved caller identity for an agent request.
#[derive(Debug, Clone)]
struct AgentAuth {
@@ -363,6 +372,16 @@ async fn chat_handler(
{
tracing::warn!(%e, "failed to ensure agent session row");
}
if let Err(e) = session_store::set_title_if_empty(
&state.db,
&session_id,
auth.user_id,
&body.message,
)
.await
{
tracing::warn!(%e, "failed to set agent session title");
}
// Load any prior conversation for this session so the agent sees the full
// multi-turn history (scoped to the caller — never another tenant's).
@@ -624,6 +643,118 @@ async fn answer_handler(
Ok(Json(json!({ "ok": delivered })))
}
async fn list_sessions_handler(
State(state): State<AppState>,
headers: HeaderMap,
Query(query): Query<SessionListQuery>,
) -> Result<Json<Value>, (StatusCode, Json<Value>)> {
let auth = resolve_auth(&headers, &state).await?;
let sessions = session_store::list_sessions(&state.db, auth.user_id, query.limit.unwrap_or(30))
.await
.map_err(|e| {
(
StatusCode::INTERNAL_SERVER_ERROR,
Json(json!({ "error": e.to_string() })),
)
})?;
Ok(Json(json!({ "ok": true, "sessions": sessions })))
}
async fn get_session_handler(
State(state): State<AppState>,
headers: HeaderMap,
Path(id): Path<String>,
) -> Result<Json<Value>, (StatusCode, Json<Value>)> {
let auth = resolve_auth(&headers, &state).await?;
let session = session_store::get_session(&state.db, &id, auth.user_id)
.await
.map_err(|e| {
(
StatusCode::INTERNAL_SERVER_ERROR,
Json(json!({ "error": e.to_string() })),
)
})?
.ok_or_else(|| {
(
StatusCode::NOT_FOUND,
Json(json!({ "error": "Agent session not found" })),
)
})?;
let transcript = session_store::load_transcript(&state.db, &id, auth.user_id)
.await
.map_err(|e| {
(
StatusCode::INTERNAL_SERVER_ERROR,
Json(json!({ "error": e.to_string() })),
)
})?
.and_then(|raw| serde_json::from_str::<Value>(&raw).ok())
.unwrap_or_else(|| json!([]));
Ok(Json(json!({
"ok": true,
"session": session,
"transcript": transcript,
})))
}
async fn load_routable_models(state: &AppState) -> Result<Vec<Value>, sqlx::Error> {
let rows: Vec<(String, String)> = sqlx::query_as(
"SELECT
tr.model_pattern,
COALESCE(NULLIF(TRIM(tr.model_mapping), ''), tr.model_pattern)
FROM token_routes tr
WHERE tr.enabled = 1
AND EXISTS (
SELECT 1
FROM route_channels rc
JOIN accounts a ON a.id = rc.account_id
JOIN sites s ON s.id = a.site_id
LEFT JOIN account_tokens at ON at.id = rc.token_id AND at.enabled = 1
WHERE rc.route_id = tr.id
AND rc.enabled = 1
AND a.status = 'active'
AND s.status = 'active'
AND s.url IS NOT NULL
AND s.url <> ''
AND (rc.cooldown_until IS NULL OR rc.cooldown_until <= datetime('now'))
AND (rc.token_id IS NULL OR at.id IS NOT NULL)
)
ORDER BY tr.id",
)
.fetch_all(&*state.db)
.await?;
Ok(rows
.into_iter()
.map(|(name, model)| {
json!({
"id": model,
"object": "model",
"created": 0,
"owned_by": name,
})
})
.collect())
}
async fn models_handler(
State(state): State<AppState>,
headers: HeaderMap,
) -> Result<Json<Value>, (StatusCode, Json<Value>)> {
let _auth = resolve_auth(&headers, &state).await?;
let models = load_routable_models(&state).await.map_err(|e| {
(
StatusCode::INTERNAL_SERVER_ERROR,
Json(json!({ "error": e.to_string() })),
)
})?;
Ok(Json(json!({
"object": "list",
"data": models,
"default_model": state.config.comfyui.agent_model,
})))
}
async fn status_handler(
State(state): State<AppState>,
headers: HeaderMap,
+16 -12
View File
@@ -20,11 +20,10 @@ use std::net::{IpAddr, SocketAddr};
use tracing::{info, warn};
/// Default spending cap (USD) on a newly created user's auto-generated default
/// API key. Set to `0.0` so a freshly registered user has **zero** spend
/// allowance until they top up or an admin raises the cap. This must always be
/// bound explicitly on INSERT: a NULL `max_cost` is treated as *unlimited* by
/// the proxy, so leaving it unbound silently grants free unlimited usage.
pub const DEFAULT_NEW_USER_MAX_COST_USD: f64 = 0.0;
/// API key. This must always be bound explicitly on INSERT: a NULL `max_cost`
/// is treated as *unlimited* by the proxy, so leaving it unbound silently grants
/// free unlimited usage.
pub const DEFAULT_NEW_USER_MAX_COST_USD: f64 = 1.0;
// ── Request / Response types ─────────────────────────────────────────
@@ -1422,15 +1421,16 @@ mod tests {
}
#[test]
fn new_user_default_quota_is_zero() {
// New users must start with zero spend allowance, not unlimited.
assert_eq!(DEFAULT_NEW_USER_MAX_COST_USD, 0.0);
fn new_user_default_quota_matches_starter_credit() {
// New users receive a small starter credit, while still avoiding NULL
// (NULL means unlimited in the proxy path).
assert_eq!(DEFAULT_NEW_USER_MAX_COST_USD, 1.0);
}
#[tokio::test]
async fn registration_default_key_has_non_null_zero_max_cost() {
async fn registration_default_key_has_non_null_starter_max_cost() {
// Regression guard for the billing leak: the default downstream key
// created at registration must persist max_cost = 0.0, never NULL
// created at registration must persist a finite max_cost, never NULL
// (NULL is treated as unlimited by the proxy). This runs the exact
// INSERT the register handler uses.
let state = test_state().await;
@@ -1462,7 +1462,7 @@ mod tests {
.await
.expect("insert default key");
// max_cost must be present (non-NULL) and exactly zero.
// max_cost must be present (non-NULL) and match starter credit.
let max_cost: Option<f64> =
sqlx::query_scalar("SELECT max_cost FROM downstream_api_keys WHERE key = ?")
.bind("sk-user-quota-test")
@@ -1470,6 +1470,10 @@ mod tests {
.await
.expect("select max_cost");
assert!(max_cost.is_some(), "max_cost must not be NULL (NULL = unlimited)");
assert_eq!(max_cost.unwrap(), 0.0, "new user default key must have zero quota");
assert_eq!(
max_cost.unwrap(),
DEFAULT_NEW_USER_MAX_COST_USD,
"new user default key must receive starter quota",
);
}
}
+277 -17
View File
@@ -15,6 +15,7 @@ use axum::{
routing::{get, post},
Json, Router,
};
use mime_guess::MimeGuess;
use serde::Deserialize;
use serde_json::{json, Map, Value};
use std::{
@@ -140,6 +141,18 @@ fn pixelle_backend_label(state: &AppState, provider: &str) -> &'static str {
}
}
fn normalize_pixelle_media_workflow_for_api(value: &str) -> String {
let trimmed = value.trim();
let lower = trimmed.to_ascii_lowercase();
if lower == "runninghub/af_scail.json"
|| lower == "runninghub/af_scail_2_action_transfer.json"
{
"runninghub/video_SCAIL-2-_.json".to_string()
} else {
trimmed.to_string()
}
}
fn pixelle_base_url(state: &AppState) -> AppResult<String> {
state
.config
@@ -237,6 +250,36 @@ fn pixelle_project_root(state: &AppState) -> PathBuf {
PathBuf::from("/opt/Pixelle-Video")
}
fn workflow_media_prefix(media_type: &str) -> &'static str {
match media_type.trim().to_ascii_lowercase().as_str() {
"video" => "video_",
"action_transfer" | "action-transfer" | "af" => "af_",
_ => "image_",
}
}
fn normalize_pixelle_workflow_source(value: &str) -> Option<&'static str> {
match value.trim().to_ascii_lowercase().as_str() {
"runninghub" | "running_hub" | "rh" => Some("runninghub"),
"selfhost" | "self_host" | "comfy" | "comfyui" | "local" => Some("selfhost"),
_ => None,
}
}
fn normalize_workflow_filename(file_name: &str, media_type: &str) -> String {
let stem = FsPath::new(file_name)
.file_stem()
.and_then(|value| value.to_str())
.map(safe_pixelle_filename)
.unwrap_or_else(|| "custom".to_string());
let mut stem = stem.trim_end_matches(".json").to_string();
let prefix = workflow_media_prefix(media_type);
if !stem.starts_with("image_") && !stem.starts_with("video_") && !stem.starts_with("af_") {
stem = format!("{prefix}{stem}");
}
format!("{stem}.json")
}
async fn persist_pixelle_upload_resource(
state: &AppState,
file_name: &str,
@@ -357,6 +400,10 @@ pub fn routes() -> Router<AppState> {
"/api/digital-human/pixelle/workflows/media",
get(pixelle_list_media_workflows),
)
.route(
"/api/digital-human/pixelle/workflows/upload",
post(pixelle_upload_workflow),
)
.route(
"/api/digital-human/pixelle/templates",
get(pixelle_list_templates),
@@ -2031,7 +2078,35 @@ fn pixelle_request_body(state: &AppState, body: &Value) -> AppResult<(String, Va
"videoUrl",
"video_url",
],
);
)
.map(validate_pixelle_input_media_reference)
.transpose()?;
let reference_image_url = optional_string(
body,
&[
"referenceImageUrl",
"reference_image_url",
"imagePath",
"image_path",
"imageUrl",
"image_url",
],
)
.map(validate_pixelle_input_media_reference)
.transpose()?;
let reference_video_url = optional_string(
body,
&[
"referenceVideoUrl",
"reference_video_url",
"videoPath",
"video_path",
"videoUrl",
"video_url",
],
)
.map(validate_pixelle_input_media_reference)
.transpose()?;
let reference_audio_url = optional_string(
body,
&[
@@ -2049,6 +2124,16 @@ fn pixelle_request_body(state: &AppState, body: &Value) -> AppResult<(String, Va
let mut template_params = Map::new();
template_params.insert("source".to_string(), json!("boosapi-digital-human"));
template_params.insert("avatar_url".to_string(), json!(avatar_url.clone()));
template_params.insert("image_url".to_string(), json!(reference_image_url.clone()));
template_params.insert(
"reference_image_url".to_string(),
json!(reference_image_url.clone()),
);
template_params.insert("video_url".to_string(), json!(reference_video_url.clone()));
template_params.insert(
"reference_video_url".to_string(),
json!(reference_video_url.clone()),
);
template_params.insert(
"reference_audio_url".to_string(),
json!(reference_audio_url.clone()),
@@ -2076,6 +2161,15 @@ fn pixelle_request_body(state: &AppState, body: &Value) -> AppResult<(String, Va
let bgm_path = optional_string(body, &["bgmPath", "bgm_path"])
.map(validate_pixelle_input_media_reference)
.transpose()?;
let tts_inference_mode = optional_string(body, &["ttsInferenceMode", "tts_inference_mode", "inferenceMode", "inference_mode"])
.map(|value| {
if value.eq_ignore_ascii_case("comfyui") || value.eq_ignore_ascii_case("comfy") {
"comfyui".to_string()
} else {
"local".to_string()
}
})
.unwrap_or_else(|| "local".to_string());
let mut request_body = json!({
"text": script,
"mode": optional_string(body, &["pixelleMode", "pixelle_mode"]).unwrap_or_else(|| state.config.pixelle_video.mode.clone()),
@@ -2087,29 +2181,62 @@ fn pixelle_request_body(state: &AppState, body: &Value) -> AppResult<(String, Va
"frame_template": optional_string(body, &["frameTemplate", "frame_template"]).unwrap_or_else(|| state.config.pixelle_video.frame_template.clone()),
"template_params": Value::Object(template_params),
"prompt_prefix": prompt_text,
"bgm_volume": body.get("bgmVolume").or_else(|| body.get("bgm_volume")).and_then(Value::as_f64).unwrap_or(0.3).clamp(0.0, 1.0)
"bgm_volume": body.get("bgmVolume").or_else(|| body.get("bgm_volume")).and_then(Value::as_f64).unwrap_or(0.3).clamp(0.0, 1.0),
"tts_inference_mode": tts_inference_mode,
"inference_mode": tts_inference_mode
});
if let Some(value) = bgm_path {
request_body["bgm_path"] = json!(value);
}
if let Some(value) = avatar_url {
request_body["avatar_url"] = json!(value);
}
if let Some(value) = reference_image_url {
request_body["image_url"] = json!(value);
request_body["image_path"] = json!(value);
request_body["reference_image_url"] = json!(value);
}
if let Some(value) = reference_video_url {
request_body["video_url"] = json!(value);
request_body["video_path"] = json!(value);
request_body["reference_video_url"] = json!(value);
}
if let Some(value) = optional_string(body, &["mediaWorkflow", "media_workflow"])
.or_else(|| default_pixelle_media_workflow(state, backend_provider))
{
request_body["media_workflow"] = json!(value);
request_body["media_workflow"] = json!(normalize_pixelle_media_workflow_for_api(&value));
}
if let Some(value) = optional_string(body, &["ttsWorkflow", "tts_workflow"])
if tts_inference_mode == "local" {
request_body["tts_voice"] = json!(
optional_string(body, &["ttsVoice", "tts_voice", "voice"])
.unwrap_or_else(|| "zh-CN-YunjianNeural".to_string())
);
request_body["voice"] = request_body["tts_voice"].clone();
request_body["voice_id"] = request_body["tts_voice"].clone();
let speed = body
.get("ttsSpeed")
.or_else(|| body.get("tts_speed"))
.or_else(|| body.get("speed"))
.and_then(Value::as_f64)
.unwrap_or(1.2)
.clamp(0.5, 2.0);
request_body["tts_speed"] = json!(speed);
request_body["speed"] = json!(speed);
} else if let Some(value) = optional_string(body, &["ttsWorkflow", "tts_workflow"])
.or_else(|| default_pixelle_tts_workflow(state, backend_provider))
{
request_body["tts_workflow"] = json!(value);
}
if let Some(value) = optional_string(body, &["apiVideoWorkflow", "api_video_workflow"]) {
request_body["api_video_workflow"] = json!(value);
request_body["api_video_workflow"] = json!(normalize_pixelle_media_workflow_for_api(&value));
}
if let Some(value) = optional_string(body, &["llmModel", "llm_model"]) {
request_body["llm_model"] = json!(value);
}
if let Some(value) = reference_audio_url {
request_body["ref_audio"] = json!(value);
if tts_inference_mode == "comfyui" {
if let Some(value) = reference_audio_url {
request_body["ref_audio"] = json!(value);
}
}
Ok((
request_body
@@ -3145,6 +3272,83 @@ async fn upload_asset(
})))
}
async fn pixelle_upload_workflow(
State(state): State<AppState>,
headers: HeaderMap,
mut multipart: Multipart,
) -> AppResult<Json<Value>> {
resolve_auth(&headers, &state).await?;
let mut file_name = "workflow.json".to_string();
let mut source = "runninghub".to_string();
let mut media_type = "image".to_string();
let mut bytes: Option<Bytes> = None;
while let Some(field) = multipart
.next_field()
.await
.map_err(|err| AppError::BadRequest(err.to_string()))?
{
let name = field.name().unwrap_or_default().to_string();
match name.as_str() {
"file" => {
file_name = field.file_name().unwrap_or(&file_name).to_string();
bytes = Some(
field
.bytes()
.await
.map_err(|err| AppError::BadRequest(err.to_string()))?,
);
}
"source" => source = field.text().await.unwrap_or_else(|_| source.clone()),
"media_type" | "mediaType" => {
media_type = field.text().await.unwrap_or_else(|_| media_type.clone())
}
_ => {}
}
}
let Some(bytes) = bytes else {
return Err(AppError::BadRequest("file is required".into()));
};
if filename_extension(&file_name).as_deref() != Some("json") {
return Err(AppError::BadRequest("工作流文件必须是 .json".into()));
}
let json_value: Value = serde_json::from_slice(&bytes)
.map_err(|err| AppError::BadRequest(format!("工作流 JSON 无效: {err}")))?;
if !json_value.is_object() {
return Err(AppError::BadRequest("工作流 JSON 必须是对象".into()));
}
let Some(source) = normalize_pixelle_workflow_source(&source) else {
return Err(AppError::BadRequest("source must be runninghub or selfhost".into()));
};
let file_name = normalize_workflow_filename(&file_name, &media_type);
let relative_path = format!("data/workflows/{source}/{file_name}");
let absolute_path = pixelle_project_root(&state).join(&relative_path);
if let Some(parent) = absolute_path.parent() {
tokio::fs::create_dir_all(parent).await.map_err(|err| {
AppError::Internal(anyhow::anyhow!("Failed to create Pixelle workflow dir: {err}"))
})?;
}
tokio::fs::write(&absolute_path, &bytes).await.map_err(|err| {
AppError::Internal(anyhow::anyhow!("Failed to persist Pixelle workflow: {err}"))
})?;
let _ = crate::services::pixelle_connection::restart_pixelle(&state.config.pixelle_video.compose_dir).await;
let key = format!("{source}/{file_name}");
Ok(Json(json!({
"success": true,
"workflow": {
"name": file_name,
"display_name": format!("{} - {}", file_name, source_label(source)),
"source": source,
"path": absolute_path.to_string_lossy(),
"key": key,
"media_type": if workflow_media_prefix(&media_type) == "image_" { "image" } else { "video" }
}
})))
}
// ── Pixelle WebUI parity: thin proxy + auth wrapper ─────────────────────
#[derive(Debug, Deserialize)]
@@ -3180,15 +3384,23 @@ async fn pixelle_list_media_workflows(
headers: HeaderMap,
) -> AppResult<Json<Value>> {
resolve_auth(&headers, &state).await?;
Ok(Json(
pixelle_json(
&state,
Method::GET,
"/api/resources/workflows/media",
None,
)
.await?,
))
let value = pixelle_json(
&state,
Method::GET,
"/api/resources/workflows/media",
None,
)
.await?;
Ok(Json(value))
}
fn source_label(source: &str) -> &'static str {
match source {
"runninghub" => "Runninghub",
"selfhost" => "Selfhost",
"comfy" => "Comfy",
_ => "Workflow",
}
}
async fn pixelle_list_templates(
@@ -3254,9 +3466,40 @@ async fn pixelle_preview_image(
async fn pixelle_preview_tts(
State(state): State<AppState>,
headers: HeaderMap,
Json(body): Json<Value>,
Json(mut body): Json<Value>,
) -> AppResult<Json<Value>> {
resolve_auth(&headers, &state).await?;
if let Some(object) = body.as_object_mut() {
if !object.contains_key("inference_mode") {
if let Some(value) = object.get("tts_inference_mode").cloned() {
object.insert("inference_mode".to_string(), value);
}
}
if !object.contains_key("voice") {
if let Some(value) = object.get("tts_voice").cloned() {
object.insert("voice".to_string(), value);
}
}
if !object.contains_key("voice_id") {
if let Some(value) = object.get("voice").or_else(|| object.get("tts_voice")).cloned() {
object.insert("voice_id".to_string(), value);
}
}
if object
.get("inference_mode")
.and_then(Value::as_str)
.is_some_and(|value| value.eq_ignore_ascii_case("local"))
{
object.remove("workflow");
object.remove("tts_workflow");
object.remove("ref_audio");
}
if !object.contains_key("speed") {
if let Some(value) = object.get("tts_speed").cloned() {
object.insert("speed".to_string(), value);
}
}
}
Ok(Json(
pixelle_json(&state, Method::POST, "/api/tts/synthesize", Some(&body)).await?,
))
@@ -3303,6 +3546,23 @@ async fn pixelle_proxy_file(
if trimmed.is_empty() {
return Err(AppError::BadRequest("file path is required".into()));
}
let project_root = pixelle_project_root(&state);
let local_path = project_root.join(trimmed);
if local_path.starts_with(&project_root) && local_path.is_file() {
let bytes = tokio::fs::read(&local_path).await.map_err(|err| {
AppError::Internal(anyhow::anyhow!("Failed to read Pixelle local file: {err}"))
})?;
let content_type = MimeGuess::from_path(&local_path)
.first_or_octet_stream()
.essence_str()
.to_string();
return Ok((
StatusCode::OK,
[(header::CONTENT_TYPE, content_type)],
bytes,
)
.into_response());
}
// Pixelle path-encodes segments separately; rebuild safely.
let encoded = trimmed
.split('/')
+7 -3
View File
@@ -219,11 +219,15 @@ async fn load_proxy_log_events(state: &AppState, limit: i64) -> AppResult<Vec<Ev
l.id AS related_id,
'proxy_log' AS related_type,
l.created_at AS created_at
FROM proxy_logs l
FROM (
SELECT *
FROM proxy_logs
ORDER BY created_at DESC, id DESC
LIMIT ?
) l
LEFT JOIN accounts a ON a.id = l.account_id
LEFT JOIN sites s ON s.id = a.site_id
ORDER BY l.created_at DESC
LIMIT ?
ORDER BY l.created_at DESC, l.id DESC
"#,
)
.bind(limit)
+85 -17
View File
@@ -248,12 +248,22 @@ async fn is_job_cancelled(state: &AppState, id: &str) -> bool {
struct ImageJobRequest {
prompt: String,
#[serde(default)]
model: Option<String>,
#[serde(default)]
image_urls: Vec<String>,
#[serde(default)]
width: Option<i64>,
#[serde(default)]
height: Option<i64>,
#[serde(default)]
size: Option<i64>,
#[serde(default)]
scale: Option<f64>,
#[serde(default)]
min_ratio: Option<f64>,
#[serde(default)]
max_ratio: Option<f64>,
#[serde(default)]
force_single: Option<bool>,
}
@@ -262,6 +272,8 @@ struct VideoJobRequest {
#[serde(default)]
prompt: Option<String>,
#[serde(default)]
model: Option<String>,
#[serde(default)]
image_urls: Vec<String>,
#[serde(default = "default_video_frames")]
frames: i64,
@@ -285,9 +297,14 @@ async fn create_image_job(
let image_req = ImageRequest {
prompt: req.prompt,
model: req.model,
image_urls: req.image_urls,
width: req.width,
height: req.height,
size: req.size,
scale: req.scale,
min_ratio: req.min_ratio,
max_ratio: req.max_ratio,
force_single: req.force_single,
};
// Validate eagerly so the caller gets a 400 instead of a failed job.
@@ -301,7 +318,17 @@ async fn create_image_job(
JimengCapability::Image,
body,
title,
json!({ "prompt": image_req.prompt }),
json!({
"prompt": image_req.prompt,
"model": image_req.model,
"imageUrls": image_req.image_urls,
"width": image_req.width,
"height": image_req.height,
"size": image_req.size,
"scale": image_req.scale,
"minRatio": image_req.min_ratio,
"maxRatio": image_req.max_ratio,
}),
)
.await?;
@@ -319,6 +346,7 @@ async fn create_video_job(
let video_req = VideoRequest {
prompt: req.prompt,
model: req.model,
image_urls: req.image_urls,
frames: req.frames,
aspect_ratio: req.aspect_ratio,
@@ -342,8 +370,10 @@ async fn create_video_job(
title,
json!({
"prompt": video_req.prompt,
"model": video_req.model,
"imageUrls": video_req.image_urls,
"frames": video_req.frames,
"aspectRatio": video_req.aspect_ratio,
}),
)
.await?;
@@ -432,12 +462,17 @@ async fn spawn_job(
) -> AppResult<String> {
let task_id = format!("{}_{}", capability.id_prefix(), uuid::Uuid::new_v4().simple());
let task_type = capability.task_type();
let model = body
.get("req_key")
.and_then(Value::as_str)
.unwrap_or_else(|| capability.req_key())
.to_string();
let initial_result = json!({
"userId": auth.user_id,
"role": auth.role,
"keyId": auth.key_id,
"keyName": auth.key_name,
"capability": capability.req_key(),
"capability": model,
"request": request_snapshot,
});
sqlx::query(
@@ -450,7 +485,7 @@ async fn spawn_job(
.bind(if title.trim().is_empty() { "即梦生成任务" } else { title.trim() })
.bind(format!(
"jimeng:{}:{}",
capability.req_key(),
model,
auth.user_id.map(|id| id.to_string()).unwrap_or_else(|| "admin".into())
))
.bind(initial_result.to_string())
@@ -488,17 +523,38 @@ async fn run_worker(
task_id: String,
base_result: Value,
) {
let model = capability.req_key().to_string();
let model = body
.get("req_key")
.and_then(Value::as_str)
.unwrap_or_else(|| capability.req_key())
.to_string();
let outcome = drive(&state, &provider, capability, &body, &task_id).await;
match outcome {
Ok(output) => {
update_job_progress(&state, &task_id, 3, "生成完成,正在转存到工作空间").await;
let assets = store_outputs(&state, &auth, capability, &output).await;
let assets = store_outputs(&state, &auth, capability, &model, &output).await;
let mut final_result = base_result.clone();
if let Some(obj) = final_result.as_object_mut() {
obj.insert("assets".into(), json!(assets));
}
if !assets_have_completed(&assets) {
let error = "产物转存失败,未生成可用工作空间文件";
let _ = sqlx::query(
"UPDATE background_tasks
SET status = 'failed', message = '生成完成但转存失败', error = ?,
result_json = ?, updated_at = datetime('now'), finished_at = datetime('now')
WHERE id = ? AND status IN ('pending', 'running')",
)
.bind(error)
.bind(final_result.to_string())
.bind(&task_id)
.execute(&*state.db)
.await;
record_billing(&state, &auth, capability, &model, false, Some(error.to_string()))
.await;
return;
}
let _ = sqlx::query(
"UPDATE background_tasks
SET status = 'succeeded', message = '生成完成', result_json = ?, progress = 4,
@@ -583,29 +639,29 @@ async fn store_outputs(
state: &AppState,
auth: &JimengAuth,
capability: JimengCapability,
model: &str,
output: &JimengOutput,
) -> Vec<Value> {
let model = capability.req_key().to_string();
let mut assets = Vec::new();
match output {
JimengOutput::Image { urls, base64 } => {
for url in urls {
let input = asset_input(auth, capability, &model, Some(url.clone()));
let input = asset_input(auth, capability, model, Some(url.clone()));
let stored = record_remote_asset(state, input).await;
assets.push(asset_to_json(stored));
assets.push(asset_to_json(stored, auth.user_id.is_some()));
}
for data in base64 {
let input = asset_input(auth, capability, &model, None);
let input = asset_input(auth, capability, model, None);
match record_base64_asset(state, input, data).await {
Ok(stored) => assets.push(asset_to_json(Ok(stored))),
Ok(stored) => assets.push(asset_to_json(Ok(stored), auth.user_id.is_some())),
Err(err) => assets.push(json!({ "status": "failed", "error": err.to_string() })),
}
}
}
JimengOutput::Video { url } => {
let input = asset_input(auth, capability, &model, Some(url.clone()));
let input = asset_input(auth, capability, model, Some(url.clone()));
let stored = record_remote_asset(state, input).await;
assets.push(asset_to_json(stored));
assets.push(asset_to_json(stored, auth.user_id.is_some()));
}
}
assets
@@ -625,19 +681,34 @@ fn asset_input(
prompt: None,
model: Some(model.to_string()),
remote_url,
metadata: json!({ "jimeng": { "reqKey": model } }),
metadata: json!({
"workspaceAsset": { "role": "output" },
"jimeng": { "reqKey": model },
}),
}
}
fn assets_have_completed(assets: &[Value]) -> bool {
assets
.iter()
.any(|asset| asset.get("status").and_then(Value::as_str) == Some("completed"))
}
fn asset_to_json(
stored: Result<crate::services::workspace::StoredWorkspaceAsset, AppError>,
is_user_asset: bool,
) -> Value {
match stored {
Ok(asset) => json!({
Ok(asset) if is_user_asset => json!({
"publicId": asset.public_id,
"status": asset.status,
"fileUrl": format!("/api/user/workspace/assets/{}/file", asset.public_id),
}),
Ok(asset) => json!({
"publicId": asset.public_id,
"status": asset.status,
"fileUrl": format!("/api/workspace/assets/{}/file", asset.public_id),
}),
Err(err) => json!({ "status": "failed", "error": err.to_string() }),
}
}
@@ -680,6 +751,3 @@ async fn record_billing(
tracing::warn!(%err, "jimeng billing record failed");
}
}
+32 -22
View File
@@ -281,21 +281,26 @@ async fn gemini_list_models(
let _ = check_gemini_auth(&state, &headers, &query).await?;
let rows: Vec<(String, String)> = sqlx::query_as(
"SELECT DISTINCT
"SELECT
tr.model_pattern,
COALESCE(NULLIF(TRIM(tr.model_mapping), ''), tr.model_pattern)
FROM token_routes tr
JOIN route_channels rc ON rc.route_id = tr.id
JOIN accounts a ON a.id = rc.account_id
JOIN sites s ON s.id = a.site_id
LEFT JOIN account_tokens at ON at.id = rc.token_id AND at.enabled = 1
WHERE tr.enabled = 1
AND rc.enabled = 1
AND a.status = 'active'
AND s.status = 'active'
AND TRIM(COALESCE(s.url, '')) <> ''
AND (rc.cooldown_until IS NULL OR rc.cooldown_until <= datetime('now'))
AND (rc.token_id IS NULL OR at.id IS NOT NULL)
AND EXISTS (
SELECT 1
FROM route_channels rc
JOIN accounts a ON a.id = rc.account_id
JOIN sites s ON s.id = a.site_id
LEFT JOIN account_tokens at ON at.id = rc.token_id AND at.enabled = 1
WHERE rc.route_id = tr.id
AND rc.enabled = 1
AND a.status = 'active'
AND s.status = 'active'
AND s.url IS NOT NULL
AND s.url <> ''
AND (rc.cooldown_until IS NULL OR rc.cooldown_until <= datetime('now'))
AND (rc.token_id IS NULL OR at.id IS NOT NULL)
)
ORDER BY tr.id",
)
.fetch_all(&*state.db)
@@ -775,21 +780,26 @@ async fn list_models(State(state): State<AppState>, headers: HeaderMap) -> AppRe
let _ = check_auth(&state, &headers).await?;
let rows: Vec<(String, String)> = sqlx::query_as(
"SELECT DISTINCT
"SELECT
tr.model_pattern,
COALESCE(NULLIF(TRIM(tr.model_mapping), ''), tr.model_pattern)
FROM token_routes tr
JOIN route_channels rc ON rc.route_id = tr.id
JOIN accounts a ON a.id = rc.account_id
JOIN sites s ON s.id = a.site_id
LEFT JOIN account_tokens at ON at.id = rc.token_id AND at.enabled = 1
WHERE tr.enabled = 1
AND rc.enabled = 1
AND a.status = 'active'
AND s.status = 'active'
AND TRIM(COALESCE(s.url, '')) <> ''
AND (rc.cooldown_until IS NULL OR rc.cooldown_until <= datetime('now'))
AND (rc.token_id IS NULL OR at.id IS NOT NULL)
AND EXISTS (
SELECT 1
FROM route_channels rc
JOIN accounts a ON a.id = rc.account_id
JOIN sites s ON s.id = a.site_id
LEFT JOIN account_tokens at ON at.id = rc.token_id AND at.enabled = 1
WHERE rc.route_id = tr.id
AND rc.enabled = 1
AND a.status = 'active'
AND s.status = 'active'
AND s.url IS NOT NULL
AND s.url <> ''
AND (rc.cooldown_until IS NULL OR rc.cooldown_until <= datetime('now'))
AND (rc.token_id IS NULL OR at.id IS NOT NULL)
)
ORDER BY tr.id",
)
.fetch_all(&*state.db)
@@ -27,6 +27,22 @@ pub struct AgentSession {
pub updated_at: String,
}
/// Lightweight row for the session history list.
#[derive(Debug, Clone, Serialize, sqlx::FromRow)]
pub struct AgentSessionSummary {
pub id: String,
pub user_id: Option<i64>,
pub title: Option<String>,
pub model: String,
pub permission_mode: String,
pub total_tokens: i64,
pub cost_usd: f64,
pub num_turns: i64,
pub message_count: i64,
pub created_at: String,
pub updated_at: String,
}
/// Token/cost delta produced by one completed agent turn.
#[derive(Debug, Clone, Copy, Default)]
pub struct UsageDelta {
@@ -93,6 +109,33 @@ pub async fn record_turn(
Ok(())
}
/// Set a human-readable title once, preserving any existing title.
pub async fn set_title_if_empty(
db: &SqlitePool,
session_id: &str,
user_id: Option<i64>,
title: &str,
) -> AppResult<()> {
let trimmed = title.trim();
if trimmed.is_empty() {
return Ok(());
}
sqlx::query(
"UPDATE agent_sessions
SET title = ?
WHERE id = ?
AND user_id IS ?
AND (title IS NULL OR trim(title) = '')",
)
.bind(trimmed.chars().take(80).collect::<String>())
.bind(session_id)
.bind(user_id)
.execute(db)
.await
.map_err(AppError::Database)?;
Ok(())
}
/// Whether `user_id` may use `session_id` for a new turn.
///
/// Returns `Ok(true)` when the id is free (no row yet) or already owned by this
@@ -185,6 +228,32 @@ pub async fn get_session(
Ok(row)
}
/// List recent sessions scoped to the caller. Admin/global-token callers pass
/// `None` and see only admin-owned sessions (`user_id IS NULL`), matching the
/// ownership semantics used by chat resume.
pub async fn list_sessions(
db: &SqlitePool,
user_id: Option<i64>,
limit: i64,
) -> AppResult<Vec<AgentSessionSummary>> {
let limit = limit.clamp(1, 100);
let rows = sqlx::query_as::<_, AgentSessionSummary>(
"SELECT id, user_id, title, model, permission_mode, total_tokens, cost_usd,
num_turns, message_count, created_at, updated_at
FROM agent_sessions
WHERE ((? IS NULL AND user_id IS NULL) OR user_id = ?)
ORDER BY datetime(updated_at) DESC, datetime(created_at) DESC
LIMIT ?",
)
.bind(user_id)
.bind(user_id)
.bind(limit)
.fetch_all(db)
.await
.map_err(AppError::Database)?;
Ok(rows)
}
#[cfg(test)]
mod tests {
use super::*;
@@ -259,6 +328,25 @@ mod tests {
assert_eq!(s.message_count, 6);
}
#[tokio::test]
async fn title_is_set_once_and_session_list_is_scoped() {
let db = pool().await;
ensure_session(&db, "s-user", Some(7), "m", "default").await.unwrap();
ensure_session(&db, "s-admin", None, "m", "default").await.unwrap();
set_title_if_empty(&db, "s-user", Some(7), " first title ").await.unwrap();
set_title_if_empty(&db, "s-user", Some(7), "second title").await.unwrap();
let owned = list_sessions(&db, Some(7), 20).await.unwrap();
assert_eq!(owned.len(), 1);
assert_eq!(owned[0].id, "s-user");
assert_eq!(owned[0].title.as_deref(), Some("first title"));
let admin = list_sessions(&db, None, 20).await.unwrap();
assert_eq!(admin.len(), 1);
assert_eq!(admin[0].id, "s-admin");
}
#[tokio::test]
async fn get_session_is_user_scoped() {
let db = pool().await;
+50 -6
View File
@@ -187,6 +187,7 @@ impl UsageTracker {
event: ComfyTaskBillingEvent,
) -> AppResult<Value> {
Self::ensure_schema(&self.db).await?;
crate::services::billing::ledger::ensure_ledger_schema(&self.db).await?;
Self::ensure_proxy_log_task_columns(&self.db).await?;
let prompt_tokens = event.prompt_tokens.max(0);
let completion_tokens = event.completion_tokens.max(0);
@@ -222,6 +223,33 @@ impl UsageTracker {
.bind(key_id)
.execute(&mut *tx)
.await?;
let owner: Option<(Option<i64>, Option<f64>, Option<f64>)> = sqlx::query_as(
"SELECT user_id, max_cost, used_cost FROM downstream_api_keys WHERE id = ?",
)
.bind(key_id)
.fetch_optional(&mut *tx)
.await?;
if let Some((Some(user_id), max_cost, used_cost)) = owner {
let used = used_cost.unwrap_or(0.0);
let remaining = max_cost.map(|m| (m - used).max(0.0)).unwrap_or(used);
crate::services::billing::ledger::record_ledger_entry(
&mut tx,
crate::services::billing::ledger::LedgerEntry {
user_id,
track: "usd",
entry_type: "consume",
amount: -cost,
balance_after: remaining,
ref_type: Some("usage_log"),
ref_id: None,
model: Some(&event.model),
operator: Some("system"),
note: Some("comfy_task"),
},
)
.await?;
}
}
sqlx::query(
@@ -1077,12 +1105,14 @@ mod tests {
#[tokio::test]
async fn records_comfy_task_success_as_usage_and_proxy_log() {
let pool = pool().await;
let pool = billing_test_pool().await;
create_proxy_logs(&pool).await;
let tracker = UsageTracker::new(Arc::new(pool));
let mut event = test_comfy_event(0.35);
event.key_id = Some(7);
let billing = tracker
.record_comfy_task_success(test_comfy_event(0.35))
.record_comfy_task_success(event)
.await
.unwrap();
@@ -1091,7 +1121,7 @@ mod tests {
assert_eq!(billing["totalCost"], 0.35);
let usage: (i64, f64) = sqlx::query_as(
"SELECT COUNT(*), COALESCE(SUM(cost), 0.0) FROM usage_logs WHERE downstream_key_id = 1",
"SELECT COUNT(*), COALESCE(SUM(cost), 0.0) FROM usage_logs WHERE downstream_key_id = 7",
)
.fetch_one(&*tracker.db)
.await
@@ -1099,14 +1129,28 @@ mod tests {
assert_eq!(usage, (1, 0.35));
let key_usage: (i64, f64) =
sqlx::query_as("SELECT used_requests, used_cost FROM downstream_api_keys WHERE id = 1")
sqlx::query_as("SELECT used_requests, used_cost FROM downstream_api_keys WHERE id = 7")
.fetch_one(&*tracker.db)
.await
.unwrap();
assert_eq!(key_usage, (1, 0.35));
assert_eq!(key_usage, (1, 2.35));
let ledger: (String, String, f64, f64, Option<String>, Option<String>) = sqlx::query_as(
"SELECT track, entry_type, amount, balance_after, model, note
FROM credit_ledger WHERE user_id = 9 ORDER BY id DESC LIMIT 1",
)
.fetch_one(&*tracker.db)
.await
.unwrap();
assert_eq!(ledger.0, "usd");
assert_eq!(ledger.1, "consume");
assert_eq!(ledger.2, -0.35);
assert_eq!(ledger.3, 7.65);
assert_eq!(ledger.4.as_deref(), Some("seedance-comfy"));
assert_eq!(ledger.5.as_deref(), Some("comfy_task"));
let proxy_log: (String, f64, String, String) = sqlx::query_as(
"SELECT status, estimated_cost, client_app_id, billing_details FROM proxy_logs WHERE downstream_api_key_id = 1",
"SELECT status, estimated_cost, client_app_id, billing_details FROM proxy_logs WHERE downstream_api_key_id = 7",
)
.fetch_one(&*tracker.db)
.await
+87 -4
View File
@@ -343,20 +343,54 @@ pub fn build_image_body(req: &ImageRequest) -> Result<Value, JimengError> {
if req.prompt.trim().is_empty() {
return Err(JimengError::Invalid("prompt is required".into()));
}
let image_urls = req
.image_urls
.iter()
.map(|url| url.trim())
.filter(|url| !url.is_empty())
.collect::<Vec<_>>();
if image_urls.len() > 10 {
return Err(JimengError::Invalid(
"image_urls supports at most 10 images".into(),
));
}
if req.size.is_some_and(|size| size <= 0) {
return Err(JimengError::Invalid("size must be greater than 0".into()));
}
for (name, ratio) in [("min_ratio", req.min_ratio), ("max_ratio", req.max_ratio)] {
if ratio.is_some_and(|value| value <= 0.0) {
return Err(JimengError::Invalid(format!(
"{name} must be greater than 0"
)));
}
}
let req_key = types::normalize_req_key(JimengCapability::Image, req.model.as_deref());
let mut body = json!({
"req_key": JimengCapability::Image.req_key(),
"req_key": req_key,
"prompt": req.prompt,
});
let obj = body.as_object_mut().expect("object");
if !image_urls.is_empty() {
obj.insert("image_urls".into(), json!(image_urls));
}
if let Some(width) = req.width {
obj.insert("width".into(), json!(width));
}
if let Some(height) = req.height {
obj.insert("height".into(), json!(height));
}
if let Some(size) = req.size {
obj.insert("size".into(), json!(size));
}
if let Some(scale) = req.scale {
obj.insert("scale".into(), json!(scale));
}
if let Some(min_ratio) = req.min_ratio {
obj.insert("min_ratio".into(), json!(min_ratio));
}
if let Some(max_ratio) = req.max_ratio {
obj.insert("max_ratio".into(), json!(max_ratio));
}
if let Some(force_single) = req.force_single {
obj.insert("force_single".into(), json!(force_single));
}
@@ -390,8 +424,9 @@ pub fn build_video_body(req: &VideoRequest) -> Result<Value, JimengError> {
}
}
let req_key = types::normalize_req_key(JimengCapability::Video, req.model.as_deref());
let mut body = json!({
"req_key": JimengCapability::Video.req_key(),
"req_key": req_key,
"frames": req.frames,
});
let obj = body.as_object_mut().expect("object");
@@ -417,10 +452,15 @@ mod tests {
#[test]
fn image_body_requires_prompt() {
let req = ImageRequest {
model: None,
prompt: " ".into(),
image_urls: vec![],
width: None,
height: None,
size: None,
scale: None,
min_ratio: None,
max_ratio: None,
force_single: None,
};
assert!(matches!(build_image_body(&req), Err(JimengError::Invalid(_))));
@@ -429,39 +469,73 @@ mod tests {
#[test]
fn image_body_includes_optional_fields() {
let req = ImageRequest {
model: None,
prompt: "a cat".into(),
image_urls: vec!["https://x/ref.png".into()],
width: Some(2048),
height: Some(2048),
size: Some(4096),
scale: Some(0.5),
min_ratio: Some(0.33),
max_ratio: Some(3.0),
force_single: Some(true),
};
let body = build_image_body(&req).unwrap();
assert_eq!(body["req_key"], "jimeng_t2i_v40");
assert_eq!(body["prompt"], "a cat");
assert_eq!(body["image_urls"][0], "https://x/ref.png");
assert_eq!(body["width"], 2048);
assert_eq!(body["height"], 2048);
assert_eq!(body["size"], 4096);
assert_eq!(body["scale"], 0.5);
assert_eq!(body["min_ratio"], 0.33);
assert_eq!(body["max_ratio"], 3.0);
assert_eq!(body["force_single"], true);
}
#[test]
fn image_body_omits_absent_optional_fields() {
let req = ImageRequest {
model: None,
prompt: "a cat".into(),
image_urls: vec![],
width: None,
height: None,
size: None,
scale: None,
min_ratio: None,
max_ratio: None,
force_single: None,
};
let body = build_image_body(&req).unwrap();
let obj = body.as_object().unwrap();
assert!(!obj.contains_key("width"));
assert!(!obj.contains_key("image_urls"));
assert!(!obj.contains_key("size"));
assert!(!obj.contains_key("scale"));
}
#[test]
fn image_body_rejects_too_many_reference_images() {
let req = ImageRequest {
model: None,
prompt: "a cat".into(),
image_urls: (0..11).map(|idx| format!("https://x/{idx}.png")).collect(),
width: None,
height: None,
size: None,
scale: None,
min_ratio: None,
max_ratio: None,
force_single: None,
};
assert!(matches!(build_image_body(&req), Err(JimengError::Invalid(_))));
}
#[test]
fn video_body_requires_prompt_or_image() {
let req = VideoRequest {
model: None,
prompt: None,
image_urls: vec![],
frames: 121,
@@ -474,6 +548,7 @@ mod tests {
#[test]
fn video_body_accepts_prompt_only() {
let req = VideoRequest {
model: None,
prompt: Some("horses".into()),
image_urls: vec![],
frames: 121,
@@ -492,6 +567,7 @@ mod tests {
#[test]
fn video_body_accepts_image_only() {
let req = VideoRequest {
model: None,
prompt: None,
image_urls: vec!["https://x/a.jpg".into()],
frames: 241,
@@ -507,6 +583,7 @@ mod tests {
#[test]
fn video_body_rejects_bad_frames() {
let req = VideoRequest {
model: None,
prompt: Some("x".into()),
image_urls: vec![],
frames: 100,
@@ -519,6 +596,7 @@ mod tests {
#[test]
fn video_body_rejects_bad_aspect_ratio() {
let req = VideoRequest {
model: None,
prompt: Some("x".into()),
image_urls: vec![],
frames: 121,
@@ -551,7 +629,8 @@ mod tests {
fn video_body_accepts_all_allowed_aspect_ratios() {
for ratio in ALLOWED_ASPECT_RATIOS {
let req = VideoRequest {
prompt: Some("x".into()),
model: None,
prompt: Some("x".into()),
image_urls: vec![],
frames: 121,
aspect_ratio: Some(ratio.to_string()),
@@ -592,7 +671,8 @@ mod tests {
fn video_body_accepts_both_frame_counts() {
for frames in ALLOWED_FRAMES {
let req = VideoRequest {
prompt: Some("x".into()),
model: None,
prompt: Some("x".into()),
image_urls: vec![],
frames,
aspect_ratio: None,
@@ -609,6 +689,7 @@ mod tests {
// Both inputs supplied (image-to-video with a guiding prompt): both end
// up in the body.
let req = VideoRequest {
model: None,
prompt: Some("a dragon".into()),
image_urls: vec!["https://x/a.jpg".into(), "https://x/b.jpg".into()],
frames: 241,
@@ -627,6 +708,7 @@ mod tests {
// A whitespace-only prompt is not a real prompt: it must not be written
// to the body, yet the image alone satisfies the "one of" requirement.
let req = VideoRequest {
model: None,
prompt: Some(" ".into()),
image_urls: vec!["https://x/a.jpg".into()],
frames: 121,
@@ -642,6 +724,7 @@ mod tests {
#[test]
fn video_body_omits_absent_optional_fields() {
let req = VideoRequest {
model: None,
prompt: Some("x".into()),
image_urls: vec![],
frames: 121,
+21
View File
@@ -63,6 +63,14 @@ impl JimengCapability {
}
}
pub fn normalize_req_key(capability: JimengCapability, raw: Option<&str>) -> String {
let value = raw.unwrap_or("").trim();
if value.is_empty() {
return capability.req_key().to_string();
}
value.to_string()
}
/// The `data.status` field returned by the GetResult action.
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum TaskStatus {
@@ -217,12 +225,23 @@ pub enum JimengOutput {
pub struct ImageRequest {
pub prompt: String,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub model: Option<String>,
/// Optional reference images for image-to-image / multi-image generation.
#[serde(default, skip_serializing_if = "Vec::is_empty")]
pub image_urls: Vec<String>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub width: Option<i64>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub height: Option<i64>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub size: Option<i64>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub scale: Option<f64>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub min_ratio: Option<f64>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub max_ratio: Option<f64>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub force_single: Option<bool>,
}
@@ -231,6 +250,8 @@ pub struct ImageRequest {
pub struct VideoRequest {
#[serde(default, skip_serializing_if = "Option::is_none")]
pub prompt: Option<String>,
#[serde(default, skip_serializing_if = "Option::is_none")]
pub model: Option<String>,
/// First-frame image URLs for image-to-video (public URLs only in v1).
#[serde(default, skip_serializing_if = "Vec::is_empty")]
pub image_urls: Vec<String>,
+19 -1
View File
@@ -2048,6 +2048,24 @@ export const api = {
},
);
},
uploadWorkflow: (file: File, data?: { source?: string; mediaType?: string }) => {
const formData = new FormData();
formData.set("file", file);
formData.set("source", data?.source || "runninghub");
formData.set("media_type", data?.mediaType || "image");
return request<{
success: boolean;
workflow: { name: string; display_name?: string; source?: string; path?: string; key?: string; media_type?: string };
}>(
"/api/digital-human/pixelle/workflows/upload",
{
method: "POST",
body: formData,
preserveAuthErrors: true,
timeoutMs: 120_000,
},
);
},
getTemplateParams: (template: string) =>
request<{ template: string; media_width?: number; media_height?: number; params?: any }>(
`/api/digital-human/pixelle/template-params?template=${encodeURIComponent(template)}`,
@@ -2071,7 +2089,7 @@ export const api = {
timeoutMs: 180_000,
},
),
previewTts: (data: { text: string; workflow?: string; ref_audio?: string }) =>
previewTts: (data: { text: string; inference_mode?: string; workflow?: string; voice?: string; speed?: number; ref_audio?: string }) =>
request<any>(
"/api/digital-human/pixelle/preview-tts",
{
+1278
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File diff suppressed because it is too large Load Diff
File diff suppressed because it is too large Load Diff
+8 -7
View File
@@ -595,8 +595,9 @@ export default function Dashboard({
const siteAvailability = showInactiveSites
? [...activeSites, ...inactiveSites]
: activeSites;
const proxyFailed24h = Math.max(0, proxy24hTotal - proxy24hSuccess);
const proxySuccessRate =
proxy24hTotal > 0 ? (proxy24hSuccess / proxy24hTotal) * 100 : 0;
proxy24hTotal > 0 ? (proxy24hSuccess / proxy24hTotal) * 100 : 100;
const activeAccountRate =
totalAccounts > 0 ? (activeAccounts / totalAccounts) * 100 : 0;
const siteRiskCount = activeSites.filter((site) => {
@@ -643,15 +644,16 @@ export default function Dashboard({
(item) => item.health.tone === "danger" || item.health.tone === "warning",
);
const routeRiskCount = routeRiskItems.length;
const hasDangerRoute = routeHealthCounts.danger > 0;
const overallHealthTone =
proxySuccessRate >= 99 && siteRiskCount === 0 && routeRiskCount === 0
? "success"
: proxySuccessRate >= 95 && siteRiskCount <= 2 && routeHealthCounts.danger === 0
proxyFailed24h > 0 || hasDangerRoute
? "danger"
: proxySuccessRate < 99 || siteRiskCount > 0 || routeRiskCount > 0
? "warning"
: "danger";
: "success";
const overallHealthLabel =
overallHealthTone === "success"
? t("稳定")
? t("健康")
: overallHealthTone === "warning"
? t("需关注")
: t("异常");
@@ -665,7 +667,6 @@ export default function Dashboard({
requestsPerMinute > 0
? `${Math.round(requestsPerMinute).toLocaleString()} RPM`
: t("暂无流量");
const proxyFailed24h = Math.max(0, proxy24hTotal - proxy24hSuccess);
const avgActiveSiteLatency = activeSites.length > 0
? Math.round(
activeSites.reduce(
+460 -96
View File
@@ -29,11 +29,16 @@ type DigitalHumanDraft = {
nScenes?: number;
bgmPath?: string;
bgmVolume?: number;
ttsInferenceMode?: TtsInferenceMode;
ttsVoice?: string;
ttsSpeed?: number;
ttsWorkflow?: string;
refAudioPath?: string;
previewTtsText?: string;
imageWorkflow?: string;
apiVideoWorkflow?: string;
referenceImagePath?: string;
referenceVideoPath?: string;
llmModel?: string;
imageWidth?: number;
imageHeight?: number;
@@ -46,6 +51,19 @@ type DigitalHumanDraft = {
const DEFAULT_PROMPT_PREFIX =
'Minimalist black-and-white matchstick figure style illustration, clean lines, simple sketch style';
const DIGITAL_HUMAN_DRAFT_KEY = 'boosapi:digital-human:draft:v1';
type TtsInferenceMode = 'local' | 'comfyui';
const EDGE_TTS_VOICES = [
{ id: 'zh-CN-YunjianNeural', label: '男声-专业(云健)' },
{ id: 'zh-CN-XiaoxiaoNeural', label: '女声-自然(晓晓)' },
{ id: 'zh-CN-YunxiNeural', label: '男声-活力(云希)' },
{ id: 'zh-CN-XiaoyiNeural', label: '女声-明亮(晓伊)' },
{ id: 'zh-CN-YunyangNeural', label: '男声-新闻(云扬)' },
{ id: 'zh-CN-liaoning-XiaobeiNeural', label: '东北女声(晓北)' },
{ id: 'zh-CN-shaanxi-XiaoniNeural', label: '陕西女声(晓妮)' },
{ id: 'en-US-JennyNeural', label: 'English - Jenny' },
{ id: 'en-US-GuyNeural', label: 'English - Guy' },
];
function getErrorMessage(error: unknown, fallback: string): string {
if (error instanceof Error && error.message) return error.message;
@@ -62,6 +80,50 @@ function workflowValue(item: WorkflowItem): string {
return item.key?.trim() || item.name;
}
function isVideoWorkflow(item: WorkflowItem): boolean {
const key = workflowValue(item).toLowerCase();
const name = item.name.toLowerCase();
return key.includes('video_') || name.includes('video_') || basename(key).startsWith('af_');
}
function workflowSource(value: string): string {
return value.includes('/') ? value.split('/')[0].toLowerCase() : '';
}
function isSameWorkflowValue(value: string, item: WorkflowItem): boolean {
const normalized = value.trim().toLowerCase();
if (!normalized) return false;
return [workflowValue(item), item.name, item.display_name]
.filter(Boolean)
.some((candidate) => String(candidate).trim().toLowerCase() === normalized);
}
function resolveAvailableWorkflow(
value: string,
workflows: WorkflowItem[],
predicate?: (item: WorkflowItem) => boolean,
): string {
const trimmed = value.trim();
if (!trimmed) return '';
const candidates = predicate ? workflows.filter(predicate) : workflows;
const exact = candidates.find((item) => isSameWorkflowValue(trimmed, item));
if (exact) return workflowValue(exact);
const source = workflowSource(trimmed);
const lowerBase = basename(trimmed).toLowerCase();
const sourceCandidates = source
? candidates.filter((item) => workflowSource(workflowValue(item)) === source || item.source?.toLowerCase() === source)
: candidates;
const pool = sourceCandidates.length > 0 ? sourceCandidates : candidates;
if (lowerBase.includes('scail')) {
const scail = pool.find((item) => workflowValue(item).toLowerCase().includes('scail') || item.name.toLowerCase().includes('scail'));
if (scail) return workflowValue(scail);
}
return '';
}
function templateValue(item: TemplateItem): string {
return item.key?.trim() || item.name;
}
@@ -96,6 +158,10 @@ function writeDigitalHumanDraft(draft: DigitalHumanDraft) {
} catch {}
}
function wait(ms: number): Promise<void> {
return new Promise((resolve) => window.setTimeout(resolve, ms));
}
function normalizeNumber(value: unknown, fallback: number, min?: number, max?: number): number {
const numeric = Number(value);
if (!Number.isFinite(numeric)) return fallback;
@@ -397,11 +463,16 @@ export default function DigitalHuman() {
const [bgmVolume, setBgmVolume] = useState(() => normalizeNumber(draftRef.current.bgmVolume, 0.3, 0, 1));
// Middle column — voice & visual
const [ttsInferenceMode, setTtsInferenceMode] = useState<TtsInferenceMode>(draftRef.current.ttsInferenceMode === 'comfyui' ? 'comfyui' : 'local');
const [ttsVoice, setTtsVoice] = useState(draftRef.current.ttsVoice || 'zh-CN-YunjianNeural');
const [ttsSpeed, setTtsSpeed] = useState(() => normalizeNumber(draftRef.current.ttsSpeed, 1.2, 0.5, 2));
const [ttsWorkflow, setTtsWorkflow] = useState(draftRef.current.ttsWorkflow || '');
const [refAudioPath, setRefAudioPath] = useState(isPrivateWorkspaceMediaUrl(draftRef.current.refAudioPath) ? '' : draftRef.current.refAudioPath || '');
const [previewTtsText, setPreviewTtsText] = useState(draftRef.current.previewTtsText || '你好,欢迎使用 BoosAPI 数字人。');
const [imageWorkflow, setImageWorkflow] = useState(draftRef.current.imageWorkflow || '');
const [apiVideoWorkflow, setApiVideoWorkflow] = useState(draftRef.current.apiVideoWorkflow || '');
const [referenceImagePath, setReferenceImagePath] = useState(isPrivateWorkspaceMediaUrl(draftRef.current.referenceImagePath) ? '' : draftRef.current.referenceImagePath || '');
const [referenceVideoPath, setReferenceVideoPath] = useState(isPrivateWorkspaceMediaUrl(draftRef.current.referenceVideoPath) ? '' : draftRef.current.referenceVideoPath || '');
const [llmModel, setLlmModel] = useState(draftRef.current.llmModel || '');
const [llmModels, setLlmModels] = useState<MarketplaceModel[]>([]);
const [imageWidth, setImageWidth] = useState(() => normalizeNumber(draftRef.current.imageWidth, 1024, 64));
@@ -418,8 +489,15 @@ export default function DigitalHuman() {
const [previewError, setPreviewError] = useState('');
const [uploadingAudio, setUploadingAudio] = useState(false);
const [uploadingBgm, setUploadingBgm] = useState(false);
const [uploadingImage, setUploadingImage] = useState(false);
const [uploadingVideo, setUploadingVideo] = useState(false);
const [uploadingWorkflow, setUploadingWorkflow] = useState(false);
const [workflowUploadSource, setWorkflowUploadSource] = useState<'runninghub' | 'selfhost'>('runninghub');
const [uploadMessage, setUploadMessage] = useState('');
const [bgmUploadMessage, setBgmUploadMessage] = useState('');
const [imageUploadMessage, setImageUploadMessage] = useState('');
const [videoUploadMessage, setVideoUploadMessage] = useState('');
const [workflowUploadMessage, setWorkflowUploadMessage] = useState('');
const [generating, setGenerating] = useState(false);
const [generateError, setGenerateError] = useState('');
@@ -479,6 +557,22 @@ export default function DigitalHuman() {
setImageWorkflow(workflowValue(imageOne || mediaWorkflows[0]));
}
}, [imageWorkflow, mediaWorkflows]);
useEffect(() => {
if (!mediaWorkflows.length) return;
if (imageWorkflow && !resolveAvailableWorkflow(imageWorkflow, mediaWorkflows)) {
const imageOne = mediaWorkflows.find((w) => !isVideoWorkflow(w) && w.name.toLowerCase().includes('image'));
if (imageOne) setImageWorkflow(workflowValue(imageOne));
}
if (apiVideoWorkflow) {
const resolved = resolveAvailableWorkflow(apiVideoWorkflow, mediaWorkflows, isVideoWorkflow);
if (resolved && resolved !== apiVideoWorkflow) {
setApiVideoWorkflow(resolved);
} else if (!resolved) {
setApiVideoWorkflow('');
setWorkflowUploadMessage(`已清除不存在的视频工作流:${apiVideoWorkflow}`);
}
}
}, [imageWorkflow, apiVideoWorkflow, mediaWorkflows]);
useEffect(() => {
if (!frameTemplate && templates.length > 0) setFrameTemplate(templateValue(templates[0]));
}, [frameTemplate, templates]);
@@ -502,11 +596,16 @@ export default function DigitalHuman() {
nScenes,
bgmPath,
bgmVolume,
ttsInferenceMode,
ttsVoice,
ttsSpeed,
ttsWorkflow,
refAudioPath,
previewTtsText,
imageWorkflow,
apiVideoWorkflow,
referenceImagePath,
referenceVideoPath,
llmModel,
imageWidth,
imageHeight,
@@ -522,11 +621,16 @@ export default function DigitalHuman() {
nScenes,
bgmPath,
bgmVolume,
ttsInferenceMode,
ttsVoice,
ttsSpeed,
ttsWorkflow,
refAudioPath,
previewTtsText,
imageWorkflow,
apiVideoWorkflow,
referenceImagePath,
referenceVideoPath,
llmModel,
imageWidth,
imageHeight,
@@ -617,17 +721,32 @@ export default function DigitalHuman() {
stopPolling();
setTask(null);
try {
const resolvedImageWorkflow = resolveAvailableWorkflow(imageWorkflow, mediaWorkflows);
const resolvedVideoWorkflow = resolveAvailableWorkflow(apiVideoWorkflow, mediaWorkflows, isVideoWorkflow);
const payload: Record<string, unknown> = {
text: text.trim(),
prompt: text.trim(),
mode,
title: title.trim() || undefined,
n_scenes: nScenes,
media_workflow: imageWorkflow || undefined,
api_video_workflow: apiVideoWorkflow || undefined,
media_workflow: resolvedImageWorkflow || undefined,
api_video_workflow: resolvedVideoWorkflow || undefined,
llm_model: llmModel || undefined,
tts_workflow: ttsWorkflow || undefined,
tts_inference_mode: ttsInferenceMode,
inference_mode: ttsInferenceMode,
tts_voice: ttsInferenceMode === 'local' ? ttsVoice : undefined,
voice: ttsInferenceMode === 'local' ? ttsVoice : undefined,
tts_speed: ttsInferenceMode === 'local' ? ttsSpeed : undefined,
speed: ttsInferenceMode === 'local' ? ttsSpeed : undefined,
tts_workflow: ttsInferenceMode === 'comfyui' ? (ttsWorkflow || undefined) : undefined,
frame_template: frameTemplate,
avatar_url: referenceVideoPath.trim() || referenceImagePath.trim() || undefined,
image_url: referenceImagePath.trim() || undefined,
image_path: referenceImagePath.trim() || undefined,
reference_image_url: referenceImagePath.trim() || undefined,
video_url: referenceVideoPath.trim() || undefined,
video_path: referenceVideoPath.trim() || undefined,
reference_video_url: referenceVideoPath.trim() || undefined,
ratio: selectedTemplateSize.ratio,
resolution: selectedTemplateSize.resolution,
prompt_prefix: promptPrefix.trim() || undefined,
@@ -661,8 +780,15 @@ export default function DigitalHuman() {
title,
nScenes,
imageWorkflow,
apiVideoWorkflow,
mediaWorkflows,
llmModel,
ttsInferenceMode,
ttsVoice,
ttsSpeed,
ttsWorkflow,
referenceImagePath,
referenceVideoPath,
promptPrefix,
videoFps,
bgmPath,
@@ -681,8 +807,14 @@ export default function DigitalHuman() {
setTitle(firstString(payload.title) || '');
setNScenes(normalizeNumber(payload.n_scenes ?? payload.nScenes, 5, 1, 20));
setImageWorkflow(firstString(payload.media_workflow, payload.mediaWorkflow, payload.workflow, payload.workflow_key) || '');
setApiVideoWorkflow(firstString(payload.api_video_workflow, payload.apiVideoWorkflow) || '');
setTtsInferenceMode(firstString(payload.tts_inference_mode, payload.inference_mode, payload.ttsInferenceMode) === 'comfyui' ? 'comfyui' : 'local');
setTtsVoice(firstString(payload.tts_voice, payload.voice, payload.ttsVoice) || 'zh-CN-YunjianNeural');
setTtsSpeed(normalizeNumber(payload.tts_speed ?? payload.speed ?? payload.ttsSpeed, 1.2, 0.5, 2));
setTtsWorkflow(firstString(payload.tts_workflow, payload.ttsWorkflow) || '');
setFrameTemplate(firstString(payload.frame_template, payload.frameTemplate) || '');
setReferenceImagePath(firstString(payload.reference_image_url, payload.image_url, payload.image_path, payload.imagePath, payload.referenceImagePath) || '');
setReferenceVideoPath(firstString(payload.reference_video_url, payload.video_url, payload.video_path, payload.videoPath, payload.referenceVideoPath) || '');
setPromptPrefix(firstString(payload.prompt_prefix, payload.promptPrefix) || DEFAULT_PROMPT_PREFIX);
setVideoFps(normalizeNumber(payload.video_fps ?? payload.videoFps, 30, 12, 60));
setBgmPath(firstString(payload.bgm_path, payload.bgmPath) || '');
@@ -787,8 +919,11 @@ export default function DigitalHuman() {
try {
const data = await api.pixelle.previewTts({
text: previewTtsText.trim(),
workflow: ttsWorkflow || undefined,
ref_audio: refAudioPath.trim() || undefined,
inference_mode: ttsInferenceMode,
workflow: ttsInferenceMode === 'comfyui' ? (ttsWorkflow || undefined) : undefined,
voice: ttsInferenceMode === 'local' ? ttsVoice : undefined,
speed: ttsInferenceMode === 'local' ? ttsSpeed : undefined,
ref_audio: ttsInferenceMode === 'comfyui' ? (refAudioPath.trim() || undefined) : undefined,
});
const audioPath = firstMediaPath(data, ['audio_path', 'audioPath', 'audio_url', 'audioUrl', 'url', 'file_url', 'fileUrl', 'path']);
if (audioPath) {
@@ -801,7 +936,7 @@ export default function DigitalHuman() {
} finally {
setPreviewing(null);
}
}, [previewTtsText, ttsWorkflow, refAudioPath]);
}, [previewTtsText, ttsInferenceMode, ttsWorkflow, ttsVoice, ttsSpeed, refAudioPath]);
const previewBgm = useMemo(() => {
if (!bgmPath) return '';
@@ -853,7 +988,79 @@ export default function DigitalHuman() {
}
}, []);
const uploadReferenceImage = useCallback(async (file?: File | null) => {
if (!file) return;
setPreviewError('');
setImageUploadMessage('');
if (!file.type.startsWith('image/')) {
setPreviewError('请上传图片文件作为图片工作流输入。');
return;
}
setUploadingImage(true);
try {
const result = await api.pixelle.uploadAsset(file, 'reference_image');
const fileUrl = result?.asset?.pixellePath || result?.asset?.fileUrl;
if (!fileUrl) throw new Error('上传成功但未返回文件地址');
setReferenceImagePath(fileUrl);
setPreviewImageUrl(resolvePixelleMediaUrl(fileUrl));
setImageUploadMessage(`已上传 ${file.name}`);
} catch (error) {
setPreviewError(getErrorMessage(error, '参考图片上传失败'));
} finally {
setUploadingImage(false);
}
}, []);
const uploadReferenceVideo = useCallback(async (file?: File | null) => {
if (!file) return;
setPreviewError('');
setVideoUploadMessage('');
if (!file.type.startsWith('video/')) {
setPreviewError('请上传视频文件作为视频工作流输入。');
return;
}
setUploadingVideo(true);
try {
const result = await api.pixelle.uploadAsset(file, 'reference_video');
const fileUrl = result?.asset?.pixellePath || result?.asset?.fileUrl;
if (!fileUrl) throw new Error('上传成功但未返回文件地址');
setReferenceVideoPath(fileUrl);
setVideoUploadMessage(`已上传 ${file.name}`);
} catch (error) {
setPreviewError(getErrorMessage(error, '参考视频上传失败'));
} finally {
setUploadingVideo(false);
}
}, []);
const uploadWorkflow = useCallback(async (mediaType: 'image' | 'video', file?: File | null) => {
if (!file) return;
setPreviewError('');
setWorkflowUploadMessage('');
if (!file.name.toLowerCase().endsWith('.json')) {
setWorkflowUploadMessage('请选择 JSON 工作流文件');
return;
}
setUploadingWorkflow(true);
try {
const result = await api.pixelle.uploadWorkflow(file, {
source: workflowUploadSource,
mediaType,
});
const workflow = result.workflow;
const key = workflowValue(workflow);
setWorkflowUploadMessage(`已上传 ${key}`);
await wait(1500);
const refreshed = await api.pixelle.listMediaWorkflows();
setMediaWorkflows(Array.isArray(refreshed?.workflows) ? refreshed.workflows : []);
if (mediaType === 'image') setImageWorkflow(key);
else setApiVideoWorkflow(key);
} catch (error) {
setWorkflowUploadMessage(getErrorMessage(error, '工作流上传失败'));
} finally {
setUploadingWorkflow(false);
}
}, [workflowUploadSource]);
const taskBadgeTone = task ? statusTone(task.status) : 'neutral';
@@ -1017,109 +1224,266 @@ export default function DigitalHuman() {
</label>
</section>
<section className="digital-human-panel">
<section className="digital-human-panel digital-human-pipeline-panel">
<div className="digital-human-section-head">
<div>
<h2>语音与画面</h2>
<p>选择 TTS、图像工作流、模板,并试听试看样片。</p>
<h2>配置合成</h2>
<p>参考 Pixelle 原版,将配音、分镜、插图和素材输入拆开配置。</p>
</div>
</div>
<label className="digital-human-field">
<span>TTS 工作流</span>
<select value={ttsWorkflow} onChange={(event) => setTtsWorkflow(event.target.value)}>
<option value="">默认</option>
{ttsWorkflows.map((wf) => (
<option key={workflowValue(wf)} value={workflowValue(wf)}>{pickItemLabel(wf)}{wf.source ? ` · ${wf.source}` : ''}</option>
))}
</select>
</label>
<label className="digital-human-field">
<span>参考音频路径(可选,用于音色克隆)</span>
<input value={refAudioPath} onChange={(event) => setRefAudioPath(event.target.value)} placeholder="例如 resources/voice/sample.wav" />
</label>
<label className="digital-human-field">
<span>上传参考音频</span>
<div className="digital-human-file-picker">
<input
id="digital-human-reference-upload"
type="file"
accept="audio/*"
disabled={uploadingAudio}
onChange={(event) => void uploadReferenceAudio(event.target.files?.[0])}
/>
<label htmlFor="digital-human-reference-upload">
{uploadingAudio ? '上传中...' : '选择音频文件'}
</label>
<span>{uploadMessage ? basename(uploadMessage.replace(/^已上传\s*/, '')) : '用于音色克隆,可选'}</span>
<div className="digital-human-subpanel">
<div className="digital-human-subpanel-head">
<h3>配音合成</h3>
<p>{ttsInferenceMode === 'local' ? '本地 Edge TTS 开箱即用,可调音色和语速。' : 'ComfyUI/RunningHub TTS 支持工作流和音色克隆。'}</p>
</div>
</label>
{uploadMessage && <div className="digital-human-upload-note">{uploadMessage}</div>}
<label className="digital-human-field">
<span>语音试听文本</span>
<input value={previewTtsText} onChange={(event) => setPreviewTtsText(event.target.value)} />
</label>
<div style={{ display: 'flex', gap: 8, flexWrap: 'wrap', marginBottom: 12 }}>
<button type="button" className="btn btn-ghost" onClick={() => void previewTts()} disabled={previewing === 'tts'}>
{previewing === 'tts' ? '合成中...' : '试听语音'}
</button>
</div>
{previewAudioUrl && <PreviewAudio src={previewAudioUrl} />}
<label className="digital-human-field">
<span>图片工作流</span>
<select value={imageWorkflow} onChange={(event) => setImageWorkflow(event.target.value)}>
<option value="">默认</option>
{mediaWorkflows.map((wf) => (
<option key={workflowValue(wf)} value={workflowValue(wf)}>{pickItemLabel(wf)}{wf.source ? ` · ${wf.source}` : ''}</option>
))}
</select>
</label>
<label className="digital-human-field">
<span>视频工作流(可选,生成说话视频)</span>
<select value={apiVideoWorkflow} onChange={(event) => setApiVideoWorkflow(event.target.value)}>
<option value="">不生成视频(仅图片合成)</option>
{mediaWorkflows
.filter((wf) => wf.name.toLowerCase().includes('video'))
.map((wf) => (
<div className="digital-human-mode-grid">
<button
type="button"
className={`digital-human-mode${ttsInferenceMode === 'local' ? ' is-active' : ''}`}
onClick={() => setTtsInferenceMode('local')}
>
<strong>本地合成</strong>
<span>Edge TTS,无需工作流;适合快速生成旁白。</span>
</button>
<button
type="button"
className={`digital-human-mode${ttsInferenceMode === 'comfyui' ? ' is-active' : ''}`}
onClick={() => setTtsInferenceMode('comfyui')}
>
<strong>ComfyUI 合成</strong>
<span>使用 TTS 工作流;可上传参考音频做音色克隆。</span>
</button>
</div>
{ttsInferenceMode === 'local' ? (
<>
<div className="digital-human-form-grid">
<label className="digital-human-field">
<span>音色选择</span>
<select value={ttsVoice} onChange={(event) => setTtsVoice(event.target.value)}>
{EDGE_TTS_VOICES.map((voice) => (
<option key={voice.id} value={voice.id}>{voice.label}</option>
))}
</select>
</label>
<label className="digital-human-field">
<span>语速 {ttsSpeed.toFixed(1)}x</span>
<input
type="range"
min={0.5}
max={2}
step={0.1}
value={ttsSpeed}
onChange={(event) => setTtsSpeed(normalizeNumber(event.target.value, 1.2, 0.5, 2))}
/>
</label>
</div>
</>
) : (
<>
<label className="digital-human-field">
<span>TTS 工作流</span>
<select value={ttsWorkflow} onChange={(event) => setTtsWorkflow(event.target.value)}>
<option value="">默认</option>
{ttsWorkflows.map((wf) => (
<option key={workflowValue(wf)} value={workflowValue(wf)}>{pickItemLabel(wf)}{wf.source ? ` · ${wf.source}` : ''}</option>
))}
</select>
</label>
<div className="digital-human-form-grid">
<label className="digital-human-field">
<span>宽度</span>
<input type="number" min={64} step={64} value={imageWidth} onChange={(event) => setImageWidth(Math.max(64, Number(event.target.value) || 1024))} />
</select>
</label>
<label className="digital-human-field">
<span>高度</span>
<input type="number" min={64} step={64} value={imageHeight} onChange={(event) => setImageHeight(Math.max(64, Number(event.target.value) || 1024))} />
<span>参考音频路径(可选,用于音色克隆)</span>
<input value={refAudioPath} onChange={(event) => setRefAudioPath(event.target.value)} placeholder="例如 resources/voice/sample.wav" />
</label>
<label className="digital-human-field">
<span>上传参考音频</span>
<div className="digital-human-file-picker">
<input
id="digital-human-reference-upload"
type="file"
accept="audio/*"
disabled={uploadingAudio}
onChange={(event) => void uploadReferenceAudio(event.target.files?.[0])}
/>
<label htmlFor="digital-human-reference-upload">
{uploadingAudio ? '上传中...' : '选择音频文件'}
</label>
<span>{uploadMessage ? basename(uploadMessage.replace(/^已上传\s*/, '')) : '用于音色克隆,可选'}</span>
</div>
</label>
{uploadMessage && <div className="digital-human-upload-note">{uploadMessage}</div>}
</>
)}
<label className="digital-human-field">
<span>语音试听文本</span>
<input value={previewTtsText} onChange={(event) => setPreviewTtsText(event.target.value)} />
</label>
<div className="digital-human-inline-actions">
<button type="button" className="btn btn-ghost" onClick={() => void previewTts()} disabled={previewing === 'tts'}>
{previewing === 'tts' ? '合成中...' : '试听语音'}
</button>
</div>
{previewAudioUrl && <PreviewAudio src={previewAudioUrl} />}
</div>
<label className="digital-human-field">
<span>风格 prompt prefix</span>
<textarea rows={2} value={promptPrefix} onChange={(event) => setPromptPrefix(event.target.value)} />
</label>
<label className="digital-human-field">
<span>预览镜头描述</span>
<input value={previewImagePrompt} onChange={(event) => setPreviewImagePrompt(event.target.value)} />
</label>
<div style={{ display: 'flex', gap: 8, flexWrap: 'wrap', marginBottom: 12 }}>
<button type="button" className="btn btn-ghost" onClick={() => void previewImage()} disabled={previewing === 'image'}>
{previewing === 'image' ? '生成中...' : '预览风格'}
</button>
</div>
{previewImageUrl && <PreviewImage src={previewImageUrl} />}
<label className="digital-human-field">
<span>视频模板</span>
<select value={frameTemplate} onChange={(event) => setFrameTemplate(event.target.value)}>
<option value="">请选择</option>
{templates.map((tpl) => (
<option key={templateValue(tpl)} value={templateValue(tpl)}>{pickItemLabel(tpl)}{tpl.size ? ` (${tpl.size})` : ''}</option>
))}
</select>
</label>
<div className="digital-human-subpanel">
<div className="digital-human-subpanel-head">
<h3>分镜模板</h3>
<p>模板决定最终画面排版,尺寸会传给 Pixelle 合成链路。</p>
</div>
<label className="digital-human-field">
<span>视频模板</span>
<select value={frameTemplate} onChange={(event) => setFrameTemplate(event.target.value)}>
<option value="">请选择</option>
{templates.map((tpl) => (
<option key={templateValue(tpl)} value={templateValue(tpl)}>{pickItemLabel(tpl)}{tpl.size ? ` (${tpl.size})` : ''}</option>
))}
</select>
</label>
<div className="digital-human-dimension-strip">
<span>最终视频尺寸</span>
<strong>{imageWidth} x {imageHeight}</strong>
</div>
</div>
<div className="digital-human-subpanel">
<div className="digital-human-subpanel-head">
<h3>插图生成</h3>
<p>选择图片工作流,也可以上传人物或参考图给工作流使用。</p>
</div>
<label className="digital-human-field">
<span>图片工作流</span>
<select value={imageWorkflow} onChange={(event) => setImageWorkflow(event.target.value)}>
<option value="">默认</option>
{mediaWorkflows.map((wf) => (
<option key={workflowValue(wf)} value={workflowValue(wf)}>{pickItemLabel(wf)}{wf.source ? ` · ${wf.source}` : ''}</option>
))}
</select>
</label>
<div className="digital-human-form-grid">
<label className="digital-human-field">
<span>宽度</span>
<input type="number" min={64} step={64} value={imageWidth} onChange={(event) => setImageWidth(Math.max(64, Number(event.target.value) || 1024))} />
</label>
<label className="digital-human-field">
<span>高度</span>
<input type="number" min={64} step={64} value={imageHeight} onChange={(event) => setImageHeight(Math.max(64, Number(event.target.value) || 1024))} />
</label>
</div>
<label className="digital-human-field">
<span>图片工作流输入图(可选)</span>
<input
value={referenceImagePath}
onChange={(event) => setReferenceImagePath(event.target.value)}
placeholder="例如 resources/boosapi-uploads/avatar.png"
/>
</label>
<label className="digital-human-field">
<span>上传图片素材</span>
<div className="digital-human-file-picker">
<input
id="digital-human-image-asset-upload"
type="file"
accept="image/*"
disabled={uploadingImage}
onChange={(event) => void uploadReferenceImage(event.target.files?.[0])}
/>
<label htmlFor="digital-human-image-asset-upload">
{uploadingImage ? '上传中...' : '选择图片文件'}
</label>
<span>{imageUploadMessage ? basename(imageUploadMessage.replace(/^已上传\s*/, '')) : '用于图片/人物参考,可选'}</span>
</div>
</label>
{imageUploadMessage && <div className="digital-human-upload-note">{imageUploadMessage}</div>}
<label className="digital-human-field">
<span>风格 prompt prefix</span>
<textarea rows={2} value={promptPrefix} onChange={(event) => setPromptPrefix(event.target.value)} />
</label>
<label className="digital-human-field">
<span>预览镜头描述</span>
<input value={previewImagePrompt} onChange={(event) => setPreviewImagePrompt(event.target.value)} />
</label>
<div className="digital-human-inline-actions">
<button type="button" className="btn btn-ghost" onClick={() => void previewImage()} disabled={previewing === 'image'}>
{previewing === 'image' ? '生成中...' : '预览风格'}
</button>
</div>
{previewImageUrl && <PreviewImage src={previewImageUrl} />}
</div>
<div className="digital-human-subpanel">
<div className="digital-human-subpanel-head">
<h3>视频素材与工作流</h3>
<p>用于说话视频、动作迁移或图生视频,RunningHub 与 Selfhost 都可以上传。</p>
</div>
<label className="digital-human-field">
<span>视频工作流(可选,生成说话视频)</span>
<select value={apiVideoWorkflow} onChange={(event) => setApiVideoWorkflow(event.target.value)}>
<option value="">不生成视频(仅图片合成)</option>
{mediaWorkflows
.filter(isVideoWorkflow)
.map((wf) => (
<option key={workflowValue(wf)} value={workflowValue(wf)}>{pickItemLabel(wf)}{wf.source ? ` · ${wf.source}` : ''}</option>
))}
</select>
</label>
<label className="digital-human-field">
<span>视频工作流输入视频(可选)</span>
<input
value={referenceVideoPath}
onChange={(event) => setReferenceVideoPath(event.target.value)}
placeholder="例如 resources/boosapi-uploads/action.mp4"
/>
</label>
<label className="digital-human-field">
<span>上传视频素材</span>
<div className="digital-human-file-picker">
<input
id="digital-human-video-asset-upload"
type="file"
accept="video/*"
disabled={uploadingVideo}
onChange={(event) => void uploadReferenceVideo(event.target.files?.[0])}
/>
<label htmlFor="digital-human-video-asset-upload">
{uploadingVideo ? '上传中...' : '选择视频文件'}
</label>
<span>{videoUploadMessage ? basename(videoUploadMessage.replace(/^已上传\s*/, '')) : '用于动作迁移/视频参考,可选'}</span>
</div>
</label>
{videoUploadMessage && <div className="digital-human-upload-note">{videoUploadMessage}</div>}
<div className="digital-human-field">
<span>上传自定义图片/视频工作流</span>
<div className="digital-human-workflow-upload-grid">
<select value={workflowUploadSource} onChange={(event) => setWorkflowUploadSource(event.target.value as 'runninghub' | 'selfhost')}>
<option value="runninghub">RunningHub</option>
<option value="selfhost">Selfhost</option>
</select>
<div className="digital-human-file-picker">
<input
id="digital-human-image-workflow-upload"
type="file"
accept="application/json,.json"
disabled={uploadingWorkflow}
onChange={(event) => void uploadWorkflow('image', event.target.files?.[0])}
/>
<label htmlFor="digital-human-image-workflow-upload">
{uploadingWorkflow ? '上传中...' : '上传图片工作流'}
</label>
<input
id="digital-human-video-workflow-upload"
type="file"
accept="application/json,.json"
disabled={uploadingWorkflow}
onChange={(event) => void uploadWorkflow('video', event.target.files?.[0])}
/>
<label htmlFor="digital-human-video-workflow-upload">
{uploadingWorkflow ? '上传中...' : '上传视频工作流'}
</label>
<span>{workflowUploadMessage || '自动保存到 Pixelle 工作流目录并刷新列表'}</span>
</div>
</div>
</div>
</div>
</section>
<section className="digital-human-panel">
@@ -16,6 +16,11 @@ describe('Dashboard mobile layout', () => {
expect(source).toMatch(/className="dashboard-hero-topline"[\s\S]*?className="dashboard-hero-status"[\s\S]*?className="dashboard-hero-maincopy"/);
expect(css).toContain('.dashboard-hero-topline {');
expect(css).toContain('.dashboard-hero-maincopy {');
expect(css).toMatch(/@media \(max-width: 1200px\) \{[\s\S]*?\.dashboard-hero\.console-hero \{[\s\S]*?grid-template-columns: 1fr;/);
expect(css).toMatch(/@media \(max-width: 1200px\) \{[\s\S]*?\.dashboard-hero \.console-hero-rail \{[\s\S]*?width: 100%;[\s\S]*?grid-template-columns: repeat\(3, minmax\(0, 1fr\)\);/);
expect(css).toMatch(/@media \(max-width: 1100px\) \{[\s\S]*?\.dashboard-hero-topline \{[\s\S]*?flex-direction: column;/);
expect(css).toMatch(/@media \(max-width: 1100px\) \{[\s\S]*?\.dashboard-hero-status \{[\s\S]*?width: 100%;/);
expect(css).toMatch(/@media \(max-width: 1100px\) \{[\s\S]*?\.dashboard-hero-signals \{[\s\S]*?grid-template-columns: repeat\(2, minmax\(0, 1fr\)\);/);
expect(css).toMatch(/@media \(max-width: 860px\) \{[\s\S]*?\.dashboard-hero-topline \{[\s\S]*?flex-direction: column;/);
expect(css).toMatch(/@media \(max-width: 860px\) \{[\s\S]*?\.dashboard-hero-status \{[\s\S]*?width: 100%;/);
expect(css).toMatch(/@media \(max-width: 860px\) \{[\s\S]*?\.dashboard-hero-signals \{[\s\S]*?grid-template-columns: repeat\(2, minmax\(0, 1fr\)\);/);
@@ -209,4 +209,108 @@ describe('Dashboard and ops log placement', () => {
root?.unmount();
}
});
it('treats an idle healthy platform as healthy on Dashboard', async () => {
apiMock.getDashboard.mockResolvedValue({
totalBalance: 0,
totalUsed: 0,
todaySpend: 0,
todayReward: 0,
activeAccounts: 1,
totalAccounts: 1,
todayCheckin: { success: 0, total: 0 },
proxy24h: { success: 0, total: 0, totalTokens: 0 },
performance: { windowSeconds: 60, requestsPerMinute: 0, tokensPerMinute: 0 },
siteAvailability: [],
modelAnalysis: null,
});
apiMock.getRoutesSummary.mockResolvedValue([]);
let root!: WebTestRenderer;
try {
await act(async () => {
root = create(
<MemoryRouter initialEntries={['/dashboard']}>
<ToastProvider>
<Dashboard />
</ToastProvider>
</MemoryRouter>,
);
});
await flushMicrotasks();
const dashboardText = collectText(root.root);
expect(dashboardText).toContain('健康');
expect(dashboardText).toContain('100.0% 成功率');
expect(dashboardText).toContain('平台运行平稳,可以继续观察吞吐和成本变化。');
expect(dashboardText).not.toContain('平台存在明显异常');
} finally {
root?.unmount();
}
});
it('does not keep Ops Monitor abnormal after logs are cleared when routes only lack snapshots', async () => {
apiMock.getDashboard.mockResolvedValue({
totalBalance: 0,
totalUsed: 0,
todaySpend: 0,
todayReward: 0,
activeAccounts: 5,
totalAccounts: 5,
todayCheckin: { success: 0, total: 0 },
proxy24h: { success: 0, total: 0, totalTokens: 0 },
performance: { windowSeconds: 60, requestsPerMinute: 0, tokensPerMinute: 0 },
siteAvailability: [],
modelAnalysis: null,
});
apiMock.getDashboardInsights.mockResolvedValue({ siteAvailability: [] });
apiMock.getRoutesSummary.mockResolvedValue([{
id: 101,
modelPattern: 'gpt-5.2-codex',
displayName: 'Codex Route',
displayIcon: null,
modelMapping: null,
enabled: true,
channelCount: 3,
enabledChannelCount: 3,
siteNames: ['Main Site'],
decisionSnapshot: null,
decisionRefreshedAt: null,
}]);
apiMock.getEvents.mockResolvedValue({ data: [] });
apiMock.getTasks.mockResolvedValue({ tasks: [] });
let root!: WebTestRenderer;
try {
await act(async () => {
root = create(
<MemoryRouter initialEntries={['/ops']}>
<ToastProvider>
<OpsMonitor />
</ToastProvider>
</MemoryRouter>,
);
});
await flushMicrotasks();
const statusCard = root.root.find((node) => (
node.type === 'article'
&& node.props.className === 'ops-monitor-kpi'
&& collectText(node).includes('运行状态')
));
expect(statusCard.props['data-tone']).toBe('success');
expect(collectText(statusCard)).toContain('健康');
expect(collectText(statusCard)).toContain('成功率 100.0%');
const routeRiskCard = root.root.find((node) => (
node.type === 'article'
&& node.props.className === 'ops-monitor-kpi'
&& collectText(node).includes('路由风险')
));
expect(routeRiskCard.props['data-tone']).toBe('success');
expect(collectText(routeRiskCard)).toContain('路由风险0');
} finally {
root?.unmount();
}
});
});
@@ -183,7 +183,7 @@ describe('RouteCard', () => {
);
expect(collectText(root.root)).toContain('m.');
expect(collectText(root.root)).toContain('注意 76');
expect(collectText(root.root)).toContain('健康 90');
const regexBadge = root.root.find((node) => (
node.type === 'span'
@@ -88,6 +88,33 @@ describe('routeHealth', () => {
expect(empty.reasons).toContain('没有通道');
});
it('does not mark fully routed routes without decision snapshots as risky', () => {
const health = buildRouteHealthScore(buildRoute({
channelCount: 3,
enabledChannelCount: 3,
decisionSnapshot: null,
}));
expect(health.label).toBe('健康');
expect(health.tone).toBe('good');
expect(health.score).toBeGreaterThanOrEqual(80);
expect(health.reasons).toContain('3/3 通道可用');
expect(health.reasons).toContain('暂无选择概率快照');
});
it('keeps partial channel coverage without decision snapshots in attention state', () => {
const health = buildRouteHealthScore(buildRoute({
channelCount: 4,
enabledChannelCount: 2,
decisionSnapshot: null,
}));
expect(health.label).toBe('注意');
expect(health.tone).toBe('warning');
expect(health.reasons).toContain('2/4 通道可用');
expect(health.reasons).toContain('暂无选择概率快照');
});
it('penalizes candidate snapshots with recent failures and low eligibility', () => {
const health = buildRouteHealthScore(buildRoute({
channelCount: 3,
@@ -103,6 +103,9 @@ export function buildRouteHealthScore(
reasons.push(`最高选择概率 ${Math.round(topProbability)}%`);
}
} else {
if (enabledChannelCount > 0 && channelRatio === 1) {
score += 14;
}
reasons.push('暂无选择概率快照');
}