Files
ComfyUI-Lora-Manager/static/js/managers/AgentManager.js
Will Miao cf898da193 feat(agent): add LLM-powered metadata enrichment system with AgentCLI and PostProcessor
Introduce an agent skill framework for LLM-driven metadata enrichment:

- AgentCLI (py/agent_cli/): in-process wrappers around internal services
  using standard relative imports, eliminating the need for sys.path hacks
- LLMService: centralized BYOK (bring-your-own-key) LLM client supporting
  OpenAI, Ollama, and custom OpenAI-compatible endpoints
- PostProcessor: deterministic engine that applies LLM output via AgentCLI
  (replaces old handler.py + _BASE_MODEL_ALIASES approach)
- SkillRegistry: filesystem-based skill discovery (skill.yaml + prompt.md)
- AgentService: orchestrates skill execution with WebSocket progress
- Frontend AgentManager: WebSocket listeners, skill execution, config UI
- Context menu entries (single + bulk) for "Enrich Metadata (Agent)"
- Settings UI for AI Provider configuration (BYOK)
- Full i18n support across 9 locales

Bug fixes found during review:
- aiohttp.web.json_response: status_code= -> status=
- settings_modal cancelEditApiKey: wrong argument position
- AgentManager.isLlmConfigured: allow Ollama without API key
- PostProcessor._merge_tags: lowercase all tags to match TagUpdateService
2026-07-02 21:27:01 +08:00

197 lines
5.7 KiB
JavaScript

/**
* AgentManager — WebSocket listener for agent skill progress events.
*
* Connects to the generic WebSocket endpoint and filters for
* `type: "agent_progress"` messages. Dispatches progress and completion
* events to registered callbacks.
*/
class AgentManager {
constructor() {
this.websocket = null;
this.progressCallbacks = [];
this.completeCallbacks = [];
this.errorCallbacks = [];
this.connected = false;
}
/**
* Connect to the WebSocket endpoint for agent progress events.
* Safe to call multiple times — won't reconnect if already connected.
*/
connect() {
if (this.connected && this.websocket?.readyState === WebSocket.OPEN) {
return;
}
const wsProtocol = window.location.protocol === 'https:' ? 'wss://' : 'ws://';
try {
this.websocket = new WebSocket(
`${wsProtocol}${window.location.host}/ws/fetch-progress`
);
} catch (e) {
console.error('AgentManager: Failed to create WebSocket:', e);
return;
}
this.websocket.onopen = () => {
this.connected = true;
console.debug('AgentManager: WebSocket connected');
};
this.websocket.onmessage = (event) => {
try {
const data = JSON.parse(event.data);
if (data.type !== 'agent_progress') return;
this._dispatch(data);
} catch (e) {
// Not JSON or wrong format — ignore
}
};
this.websocket.onerror = (error) => {
console.error('AgentManager: WebSocket error:', error);
this.connected = false;
};
this.websocket.onclose = () => {
this.connected = false;
console.debug('AgentManager: WebSocket closed');
};
}
/**
* Dispatch a parsed agent event to the appropriate callbacks.
* @param {Object} data - The parsed WebSocket message
*/
_dispatch(data) {
const { status, skill } = data;
if (status === 'error') {
this.errorCallbacks.forEach((cb) => {
try {
cb(data);
} catch (e) {
console.error('AgentManager error callback failed:', e);
}
});
return;
}
if (status === 'completed') {
this.completeCallbacks.forEach((cb) => {
try {
cb(data);
} catch (e) {
console.error('AgentManager complete callback failed:', e);
}
});
return;
}
// started, processing — general progress
this.progressCallbacks.forEach((cb) => {
try {
cb(data);
} catch (e) {
console.error('AgentManager progress callback failed:', e);
}
});
}
/**
* Register a callback for progress events (started, processing).
* @param {Function} callback - Receives the event data
*/
onProgress(callback) {
this.progressCallbacks.push(callback);
}
/**
* Register a callback for completion events.
* @param {Function} callback - Receives the event data
*/
onComplete(callback) {
this.completeCallbacks.push(callback);
}
/**
* Register a callback for error events.
* @param {Function} callback - Receives the event data
*/
onError(callback) {
this.errorCallbacks.push(callback);
}
/**
* Clear all registered callbacks.
*/
clearCallbacks() {
this.progressCallbacks = [];
this.completeCallbacks = [];
this.errorCallbacks = [];
}
/**
* Execute an agent skill on the provided model paths.
*
* @param {string} skillName - The skill to execute
* @param {string[]} modelPaths - Model file paths to process
* @returns {Promise<Object>} The response JSON
*/
async executeSkill(skillName, modelPaths) {
const response = await fetch(
`/api/lm/agent/execute/${encodeURIComponent(skillName)}`,
{
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ model_paths: modelPaths }),
}
);
if (!response.ok) {
const errorData = await response.json().catch(() => ({}));
throw new Error(
errorData.error || `HTTP ${response.status}: ${response.statusText}`
);
}
return response.json();
}
/**
* Check if the LLM provider is configured.
*
* Returns true when both an API key and a model name are set.
*
* @returns {Promise<boolean>}
*/
async isLlmConfigured() {
try {
const response = await fetch('/api/lm/settings');
if (!response.ok) return false;
const data = await response.json();
const provider = data.settings?.llm_provider;
const hasModel = !!data.settings?.llm_model;
const hasKey = !!data.settings?.llm_api_key;
return hasModel && (hasKey || provider === 'ollama');
} catch {
return false;
}
}
/**
* Get the list of available agent skills.
*
* @returns {Promise<Array>}
*/
async listSkills() {
const response = await fetch('/api/lm/agent/skills');
if (!response.ok) return [];
const data = await response.json();
return data.skills || [];
}
}
// Export as singleton
export const agentManager = new AgentManager();