923fa671fe
ContentGuardianAgent consolidation:
- Merge 3 duplicate classes into single source in specialized/content_guardian.py
- Watchdog audit_committee() with heuristic scoring, coverage gaps, overlaps, alerts
- Remove misleading rejection_rate() helper; use acceptance_rate directly
- Integrate audit + alerts + trend signals into today_workflow_service.py
Team Activity page:
- QualityAuditPanel: health ring, per-agent critiques, coverage gaps, overlaps
- TrendSignalsPanel: opportunity cards with urgency/impact/coverage bars
- AlertBanner: persistent dismiss via POST /alerts/{id}/mark-read
- AgentHelpModal: dialog showing all 8 agents with descriptions, tools, schedule
- QualityAuditPanel action buttons: Fill gap -> /content-planning, Resolve overlap, View CTA on alerts/issues
- TrendSignalsPanel action buttons: Create content from this trend -> /blog-writer with trend context state
Onboarding system:
- Step 4 validation: no auto-pass via basic_ready; requires persona data or explicit progression
- Step 5 validation: logs warning on auto-pass without integration data
- OnboardingCompletionService: single DB session, transactional task creation, upsert pattern
- Business-without-website: nullable website_url on SIFIndexingTask and MarketTrendsTask
- DeepCompetitorAnalysisExecutor: 5-min timeout, 10-competitor cap, asyncio.wait_for
- Persona generation: async with 30s timeout, falls back to scheduler
- OnboardingProgressService.reset_onboarding(): resets session + pauses all DB tasks
- OnboardingControlService.reset_onboarding(): also cancels APScheduler jobs
- FinalStep TaskSchedulingPanel: shows scheduled/failed tasks after completion, 8s auto-redirect
- onboarding_completed agent activity event logged to feed
Documentation:
- docs-site/features/onboarding/: overview, steps, scheduler-tasks, technical-reference (4 pages)
- docs-site/mkdocs.yml: added Onboarding System nav section
- docs-site/features/sif-agents/: overview, agent-directory, committee-system, content-guardian (4 pages)
- docs-site/features/team-activity/: overview, quality-audit, trend-signals, alert-system (4 pages)
- docs-site/features/todays-workflow/: updated overview, technical-architecture, workflow-guide, api-reference
97 lines
2.8 KiB
TypeScript
97 lines
2.8 KiB
TypeScript
import { useCallback, useState } from 'react';
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import { apiClient, aiApiClient } from '../../api/client';
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export interface ImageGenerationRequest {
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prompt: string;
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negative_prompt?: string;
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provider?: 'gemini' | 'huggingface' | 'stability' | 'wavespeed';
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model?: string;
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width?: number;
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height?: number;
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guidance_scale?: number;
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steps?: number;
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seed?: number;
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overlay_text?: string;
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}
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export interface ImageGenerationResponse {
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success: boolean;
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image_base64: string;
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width: number;
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height: number;
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provider: string;
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model?: string;
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seed?: number;
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}
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export function useImageGeneration() {
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const [isGenerating, setIsGenerating] = useState(false);
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const [error, setError] = useState<string | null>(null);
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const [result, setResult] = useState<ImageGenerationResponse | null>(null);
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const generate = useCallback(async (req: ImageGenerationRequest) => {
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setIsGenerating(true);
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setError(null);
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setResult(null);
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try {
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const response = await apiClient.post<ImageGenerationResponse>('/api/images/generate', req);
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const data = response.data;
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// Check if response has success field and image data
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if (data && (data.success !== false) && data.image_base64) {
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setResult(data);
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setError(null);
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return data;
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} else {
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// Response received but missing required data
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const message = 'Image generation completed but response is incomplete';
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setError(message);
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throw new Error(message);
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}
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} catch (e: any) {
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// Check if error response contains image data (partial success)
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if (e?.response?.data?.image_base64) {
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// Image was generated but there was an error in post-processing
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const data = e.response.data;
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console.warn('Image generation succeeded but post-processing had issues', data);
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setResult(data);
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setError(null);
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return data;
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}
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const message = e?.response?.data?.detail || e?.response?.data?.message || e?.message || 'Image generation failed';
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setError(message);
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throw new Error(message);
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} finally {
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setIsGenerating(false);
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}
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}, []);
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return { isGenerating, error, result, generate };
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}
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export interface PromptSuggestion {
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prompt: string;
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negative_prompt?: string;
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width?: number;
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height?: number;
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overlay_text?: string;
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}
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export async function fetchPromptSuggestions(payload: {
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provider?: string;
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model?: string;
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image_type?: string;
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title?: string;
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section?: any;
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research?: any;
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persona?: any;
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}): Promise<PromptSuggestion[]> {
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// Use aiApiClient (3-minute timeout) because suggest-prompts calls an LLM
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// which can take 30-60+ seconds to respond via WaveSpeed
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const response = await aiApiClient.post('/api/images/suggest-prompts', payload);
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return response.data.suggestions || [];
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}
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