Enterprise-grade conversational intelligence platform that ingests call transcripts, scores compliance against dynamic QSDD rubrics using LLMs, runs predictive machine learning models, and delivers real-time telemetry through a modern Liquid Glass React dashboard.
You can run CallIQ using Docker (Recommended) or Local Development.
Ensure Docker and Docker Compose are installed.
# 1. Clone the repository
git clone https://github.com/VedantPanchal23/CallIQ.git
cd CallIQ
# 2. Configure environment
cp .env.example .env
# 3. Build and launch all containers
docker compose up -d --build- Frontend Dashboard: http://localhost:3000
- Backend API & Swagger Docs: http://localhost:8000/docs
- API Health Check: http://localhost:8000/health
To view logs or stop containers:
docker compose logs -f # View live logs
docker compose down # Stop containers# 1. Clone the repository
git clone https://github.com/VedantPanchal23/CallIQ.git
cd CallIQ
# 2. Create and activate virtual environment
python -m venv venv
# Windows:
venv\Scripts\activate
# macOS / Linux:
# source venv/bin/activate
# 3. Install Python dependencies
pip install -r requirements.txt
# 4. Configure environment
cp .env.example .env
# Optional: Add your custom Groq API key in .env for live LLM chat/scoring
# 5. Run the end-to-end data pipeline (Ingestion -> ETL -> ML Models -> AI Scoring -> ChromaDB RAG)
python run_pipeline.py --force
# 6. Start FastAPI backend
python -m uvicorn backend.main:app --reload --port 8000cd dashboards/frontend
# Install dependencies (Node 18+)
npm install --legacy-peer-deps
# Start React development server
npm start
# Automatically opens at http://localhost:3000To verify the entire system, database tables, and ML/AI models locally:
# Run all 7 test suites
python -c "
import subprocess, sys
tests = [
'tests/test_ingestion.py',
'tests/test_etl.py',
'tests/test_scoring.py',
'tests/test_ml.py',
'tests/test_ml_unit.py',
'tests/test_rag.py',
'tests/test_qsdd_dynamic.py'
]
for t in tests:
res = subprocess.run([sys.executable, t])
if res.returncode != 0:
sys.exit(1)
print('\n*** ALL 7 TEST SUITES PASSED 100% ***')
" ┌──────────────────────────────────────────────┐
│ DATA INGESTION (Bronze) │
│ Real Calls JSON ──► data_loader.py │
│ Synthetic Data ──► synthetic_gen.py │
└──────────────────────┬───────────────────────┘
│
┌──────────────────────▼───────────────────────┐
│ ETL PIPELINE (Silver/Gold) │
│ Silver Cleaning ──► transform.py │
│ Dimensional Mart ──► dim_agents, dim_time │
└──────────────────────┬───────────────────────┘
│
┌──────────────────────▼───────────────────────┐
│ AI & MACHINE LEARNING │
│ LLM Dynamic Scorer (Groq / LangChain) │
│ Sentiment Classification (HuggingFace) │
│ K-Means Clustering & Random Forest Outcome │
│ Isolation Forest Anomaly Detection │
│ ChromaDB Vector Store + Hybrid RAG Chat │
└──────────────────────┬───────────────────────┘
│
┌──────────────────────▼───────────────────────┐
│ APPLICATION LAYER │
│ FastAPI Backend Server (Port 8000) │
│ React 18 Liquid Glass Dashboard (Port 3000)│
└──────────────────────────────────────────────┘
-
Executive Overview Dashboard:
- Live KPI cards with tabular figures (Total Calls, Duration, Resolution %, Quality Benchmark).
- Customer Sentiment Dynamics (Donut distribution + 30-day emotion area wave).
- Top Call Drivers (Ranked volume categories with progress bars).
- Agent Leaderboard with cluster classification and FCR rates.
- Live AI Insights and anomaly detection feed.
-
QSDD Quality Standards Manager:
- Fully dynamic rubrics (Greeting, Authentication, Assistance, Closing).
- In-app section and criteria CRUD with real-time weight adjustment.
- Asynchronous background re-scoring worker with live progress tracking.
-
Call Explorer & Transcript Analyzer:
- Paginated call table with search and sentiment filtering.
- Slide-out drawer with Speaker Diarization (Agent vs Customer bubbles).
- Granular criteria evaluation with PASS/FAIL badges and evidence quotes.
-
Conversational AI Copilot (⌘K):
- Natural Language to SQL query translation across DuckDB warehouse tables.
- RAG semantic vector search over call transcripts with source citations.
├── assets/ # Raw call details and transcripts
├── ingestion/ # Bronze data loader & synthetic call generator
├── etl/ # Medallion ETL (Bronze -> Silver -> Gold) & data quality
├── warehouse/ # DuckDB analytical warehouse & ChromaDB vector store
├── ai_engine/ # Dynamic QSDD scorer, summariser, RAG chatbot & ML models
│ └── ml/ # Sentiment, clustering, prediction & anomaly detection
├── backend/ # FastAPI backend & modular routers
│ ├── db.py # Centralized DuckDB connection manager
│ ├── main.py # App entrypoint with auto-initialization & CORS
│ └── routers/ # Dashboard, chat, QSDD, and ingestion endpoints
├── dashboards/frontend/ # React 18 frontend with Liquid Glass theme
│ ├── src/
│ │ ├── components/ # Topbar, KPIcards, SentimentChart, AIChatbot, etc.
│ │ ├── pages/ # Dashboard, QSDDManager, CallExplorer
│ │ └── api.js # Axios API client
│ └── Dockerfile # Multi-stage React + Nginx SPA container
├── tests/ # 7 automated test suites (100% pass rate)
├── run_pipeline.py # Master pipeline runner
├── Dockerfile # Backend container definition
├── docker-compose.yml # Full-stack Docker orchestration
├── requirements.txt # Python dependencies
└── .env.example # Environment variables template
MIT License. Built for enterprise call quality intelligence and analytics.