GT AI OS Community Edition v2.0.33
Security hardening release addressing CodeQL and Dependabot alerts: - Fix stack trace exposure in error responses - Add SSRF protection with DNS resolution checking - Implement proper URL hostname validation (replaces substring matching) - Add centralized path sanitization to prevent path traversal - Fix ReDoS vulnerability in email validation regex - Improve HTML sanitization in validation utilities - Fix capability wildcard matching in auth utilities - Update glob dependency to address CVE - Add CodeQL suppression comments for verified false positives 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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HackWeasel
270
apps/tenant-app/src/services/orchestrator.ts
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270
apps/tenant-app/src/services/orchestrator.ts
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/**
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* GT 2.0 Task Orchestrator Service
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*
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* DeepAgent-inspired intelligent orchestration layer that analyzes user intent
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* and selects optimal resources (datasets, history, or direct LLM) for responses.
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*/
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import { searchDocuments, searchConversationHistory, ConversationHistoryResult, SearchResult } from './documents';
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import { api } from './api';
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export interface TaskContext {
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conversationId: string;
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userId: string;
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availableDatasets: string[];
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selectedDatasets: string[];
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historySearchEnabled: boolean;
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agentId?: string;
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}
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export interface IntentAnalysis {
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intent: 'question' | 'task' | 'creative' | 'analysis';
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complexity: 'simple' | 'moderate' | 'complex';
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needsContext: boolean;
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needsHistory: boolean;
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confidence: number;
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reasoning: string;
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}
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export interface ResourceSelection {
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useDatasets: boolean;
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useHistory: boolean;
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searchMethod: 'vector' | 'hybrid' | 'keyword';
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datasetIds: string[];
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historyParams?: {
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days_back: number;
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agent_filter?: string[];
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};
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}
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export interface OrchestrationResult {
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intent: IntentAnalysis;
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resources: ResourceSelection;
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contextSources: ContextSource[];
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historyResults?: ConversationHistoryResult[];
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searchResults?: SearchResult[];
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}
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export interface ContextSource {
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id: string;
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type: 'dataset' | 'history' | 'direct';
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name: string;
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relevance: number;
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content?: string;
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}
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export class TaskOrchestrator {
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private readonly INTENT_KEYWORDS = {
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question: ['what', 'how', 'why', 'when', 'where', 'explain', 'tell me about'],
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task: ['create', 'build', 'generate', 'write', 'make', 'develop', 'implement'],
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creative: ['imagine', 'story', 'poem', 'creative', 'artistic', 'design'],
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analysis: ['analyze', 'compare', 'evaluate', 'review', 'assess', 'study']
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};
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private readonly CONTEXT_INDICATORS = [
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'based on', 'according to', 'in the document', 'from the data',
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'previously', 'earlier', 'last time', 'before'
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];
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private readonly HISTORY_INDICATORS = [
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'previously', 'earlier', 'last time', 'before', 'remember when',
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'what did we discuss', 'go back to', 'from our conversation'
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];
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async orchestrate(query: string, context: TaskContext): Promise<OrchestrationResult> {
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// Step 1: Analyze user intent
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const intent = this.analyzeIntent(query);
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// Step 2: Determine resource needs
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const resources = await this.selectResources(query, intent, context);
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// Step 3: Gather context from selected resources
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const contextSources: ContextSource[] = [];
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let historyResults: ConversationHistoryResult[] = [];
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let searchResults: SearchResult[] = [];
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// Execute dataset search if needed
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if (resources.useDatasets && resources.datasetIds.length > 0) {
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try {
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const searchResponse = await searchDocuments({
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query,
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dataset_ids: resources.datasetIds,
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search_method: resources.searchMethod,
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top_k: 5,
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similarity_threshold: 0.7
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});
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if (searchResponse.success) {
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searchResults = searchResponse.data.results;
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searchResults.forEach(result => {
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contextSources.push({
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id: result.chunk_id,
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type: 'dataset',
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name: `Document: ${result.document}`,
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relevance: result.similarity,
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content: result.metadata?.content || result.document
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});
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});
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}
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} catch (error) {
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console.error('Dataset search failed:', error);
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}
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}
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// Execute history search if needed
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if (resources.useHistory) {
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try {
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const historyResponse = await searchConversationHistory({
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query,
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...resources.historyParams,
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limit: 5
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});
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if (historyResponse.success) {
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historyResults = historyResponse.data;
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historyResults.forEach(result => {
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contextSources.push({
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id: result.message_id,
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type: 'history',
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name: `${result.conversation_title} - ${result.agent_name}`,
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relevance: result.relevance_score,
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content: result.content
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});
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});
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}
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} catch (error) {
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console.error('History search failed:', error);
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}
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}
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// Sort context sources by relevance
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contextSources.sort((a, b) => b.relevance - a.relevance);
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return {
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intent,
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resources,
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contextSources: contextSources.slice(0, 8), // Limit to top 8 sources
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historyResults,
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searchResults
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};
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}
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private analyzeIntent(query: string): IntentAnalysis {
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const lowerQuery = query.toLowerCase();
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const words = lowerQuery.split(/\s+/);
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// Determine primary intent
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let intent: IntentAnalysis['intent'] = 'question';
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let maxScore = 0;
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for (const [intentType, keywords] of Object.entries(this.INTENT_KEYWORDS)) {
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const score = keywords.reduce((acc, keyword) => {
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return acc + (lowerQuery.includes(keyword) ? 1 : 0);
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}, 0);
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if (score > maxScore) {
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maxScore = score;
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intent = intentType as IntentAnalysis['intent'];
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}
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}
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// Determine complexity based on query length and structure
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const complexity: IntentAnalysis['complexity'] =
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words.length < 5 ? 'simple' :
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words.length < 15 ? 'moderate' : 'complex';
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// Check if context is needed
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const needsContext = this.CONTEXT_INDICATORS.some(indicator =>
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lowerQuery.includes(indicator)
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);
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// Check if history is needed
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const needsHistory = this.HISTORY_INDICATORS.some(indicator =>
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lowerQuery.includes(indicator)
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);
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const confidence = Math.min(0.9, 0.5 + (maxScore * 0.1));
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return {
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intent,
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complexity,
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needsContext: needsContext || intent === 'analysis',
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needsHistory,
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confidence,
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reasoning: `Intent: ${intent}, Keywords found: ${maxScore}, Length: ${words.length} words`
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};
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}
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private async selectResources(
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query: string,
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intent: IntentAnalysis,
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context: TaskContext
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): Promise<ResourceSelection> {
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const resources: ResourceSelection = {
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useDatasets: false,
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useHistory: false,
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searchMethod: 'hybrid',
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datasetIds: []
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};
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// Use datasets if context is needed and datasets are available
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if ((intent.needsContext || intent.intent === 'analysis') && context.selectedDatasets.length > 0) {
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resources.useDatasets = true;
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resources.datasetIds = context.selectedDatasets;
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// Choose search method based on intent and complexity
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if (intent.intent === 'creative') {
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resources.searchMethod = 'vector'; // Better for semantic similarity
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} else if (intent.complexity === 'simple') {
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resources.searchMethod = 'keyword'; // Faster for simple queries
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} else {
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resources.searchMethod = 'hybrid'; // Best overall performance
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}
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}
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// Use history if explicitly requested or if pattern suggests it
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if (context.historySearchEnabled && (intent.needsHistory || intent.complexity === 'complex')) {
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resources.useHistory = true;
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resources.historyParams = {
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days_back: intent.complexity === 'complex' ? 60 : 30,
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agent_filter: context.agentId ? [context.agentId] : undefined
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};
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}
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return resources;
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}
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/**
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* Generate a prompt with context for the LLM
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*/
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generateContextualPrompt(
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originalQuery: string,
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orchestrationResult: OrchestrationResult
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): string {
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let prompt = originalQuery;
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if (orchestrationResult.contextSources.length === 0) {
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return prompt;
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}
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// Add context header
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prompt += '\n\n--- CONTEXT ---\n';
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// Add relevant sources
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orchestrationResult.contextSources.forEach((source, index) => {
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prompt += `\n${index + 1}. [${source.type.toUpperCase()}] ${source.name}\n`;
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if (source.content) {
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prompt += ` ${source.content.substring(0, 500)}${source.content.length > 500 ? '...' : ''}\n`;
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}
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});
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prompt += '\n--- END CONTEXT ---\n\n';
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prompt += 'Please answer based on the provided context when relevant. ';
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prompt += 'If the context doesn\'t contain relevant information, please indicate that and provide a general response.';
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return prompt;
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}
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}
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// Singleton instance
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export const taskOrchestrator = new TaskOrchestrator();
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