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Vadym Samoilenko 01bea84691 Add Azure AD SSO via MSAL.js SPA flow 
- Self-host msal-browser.min.js v5.6.3 (UMD, 244KB, no CDN dependency)
- login.html: SSO button + redirect callback handler + password form fallback
- config.js: MSAL config (tenant, client ID, redirect URI) + __SSO_ENABLED flag
- server.ts: POST /api/sso/token-exchange — validates Azure ID token using Node
  crypto (JWKS fetch + 24h cache + RSA-SHA256 sig verify), issues sl_session cookie
- server.ts: /api/auth now returns user name/email/authMethod from session
- server.ts: CSP updated with login.microsoftonline.com for connect-src + frame-src
- docker-compose.yml: pass AZURE_TENANT_ID + AZURE_CLIENT_ID to container
- deploy/setup.sh: add Azure AD vars to .env template

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-15 18:18:57 +01:00
agents/social-listening Add Azure AD SSO via MSAL.js SPA flow 2026-04-15 18:18:57 +01:00
db Initial commit: Social Listening Pipeline 2026-04-02 22:18:02 -04:00
deploy Add Azure AD SSO via MSAL.js SPA flow 2026-04-15 18:18:57 +01:00
frontend Add Azure AD SSO via MSAL.js SPA flow 2026-04-15 18:18:57 +01:00
.gitignore Initial commit: Social Listening Pipeline 2026-04-02 22:18:02 -04:00
DEVELOPER_BRIEF.md Initial commit: Social Listening Pipeline 2026-04-02 22:18:02 -04:00
docker-compose.prod.yml Security hardening: fix 17 audit findings (C2-C7, H1-H4, H6-H8, M1-M5, M7) 2026-04-08 10:59:48 -04:00
docker-compose.yml Add Azure AD SSO via MSAL.js SPA flow 2026-04-15 18:18:57 +01:00
Dockerfile Add per-brief Apify budget with platform splitting 2026-04-13 10:36:30 -04:00
package-lock.json Initial commit: Social Listening Pipeline 2026-04-02 22:18:02 -04:00
package.json Initial commit: Social Listening Pipeline 2026-04-02 22:18:02 -04:00
README.md Add project README with architecture, setup, and deployment docs 2026-04-07 14:13:24 -04:00
SECURITY_AUDIT.md Security hardening: fix 17 audit findings (C2-C7, H1-H4, H6-H8, M1-M5, M7) 2026-04-08 10:59:48 -04:00
tsconfig.json Initial commit: Social Listening Pipeline 2026-04-02 22:18:02 -04:00

README.md

Social Listening Pipeline

Automated social media research tool that scrapes TikTok, Instagram, and YouTube via Apify, analyses content with Claude AI, and generates client-ready HTML reports.

Architecture

frontend/          Static frontend (served by Apache)
agents/social-listening/
  dashboard/       Node.js backend (HTTP + SSE on port 3456)
  stages/          8-stage pipeline
  briefs/          Saved client briefs (JSON)
  outputs/         Generated reports
deploy/            Apache config + setup script

Pipeline Stages

Stage Name Description
1 Brief Validation Validates and normalises the client brief
2 Strategy Review AI reviews strategy, suggests up to 3 extra hashtags
3 Discovery Scrape Scrapes TikTok/Instagram/YouTube via Apify
4 Data Review AI analyses scraped content for trends
5 Enrichment Scrape Fetches transcripts and extra metadata
6 Pre-Report Review AI refines findings before report generation
7 Desk Research Web search for additional context
8 Report Generation Produces final HTML report with video embeds

Key Features

  • Real-time dashboard with SSE progress updates and live cost tracking
  • Apify budget control (APIFY_COST_LIMIT) — stops scraping when limit is reached
  • Saved briefs — save/load client briefs server-side with a dedicated tab
  • Run history — view, download, and delete past pipeline runs with cost breakdowns
  • Video embeds — YouTube iframes, Instagram native embeds, TikTok links in reports
  • Auth — cookie-based session auth with HMAC-signed tokens

Prerequisites

  • Docker & Docker Compose
  • Node.js 20+ (for local development)
  • Apify API token
  • Anthropic API key

Environment Variables

Copy .env.example or create .env in the project root:

APIFY_TOKEN=your_apify_token
ANTHROPIC_API_KEY=your_anthropic_key
APIFY_LIVE_APPROVED=true
APIFY_COST_LIMIT=5
TEST_MODE=false
DASHBOARD_PORT=3456
DATABASE_URL=postgres://social:social@db:5432/social_listening
DASH_USER=admin
DASH_PASS=changeme
SESSION_SECRET=random_secret_here

Running Locally

# Start PostgreSQL + app via Docker
docker compose up -d

# Dashboard available at http://localhost:3456

Or without Docker:

npm install

# Start the dashboard server
npm run dashboard

# Run pipeline directly (CLI)
npm run pipeline        # dry run
npm run pipeline:test   # test mode
npm run pipeline:live   # live Apify scraping

Production Deployment

The app is designed to run behind Apache on an Ubuntu server:

  • Backend: Docker containers at /opt/social-reporting
  • Frontend: Static files at /var/www/html/social-reporting
  • URL: https://your-domain.com/social-reports/
# On the server
cd /opt/social-reporting
git pull
cp frontend/* /var/www/html/social-reporting/
docker compose -f docker-compose.yml -f docker-compose.prod.yml up -d --build

See deploy/apache-social-reports.conf for the Apache reverse proxy config and deploy/setup.sh for first-time setup.

Tech Stack

  • Runtime: TypeScript (ESM) via tsx
  • Backend: Node.js HTTP server with SSE
  • Database: PostgreSQL (via postgres npm package)
  • Scraping: Apify REST API
  • AI: Anthropic Claude API (Messages API)
  • Frontend: Vanilla HTML/CSS/JS with Montserrat font
  • Deploy: Docker Compose + Apache reverse proxy