Citizen Voice AI - Government Accountability System AI Agent That Never Lets Government Ignore You

Project ID: T3:315-Citizen Voice AI MultiAgent Government Accountability System-vinay-vinayb1021

Complete AI-Powered Government Complaint Processing System with Dual Deployment Modes

Project Overview

A comprehensive AI system that automates government complaint processing from citizen submission to resolution tracking. Features 6 intelligent agents working together to ensure transparency, accountability, and efficient resolution of citizen grievances.

6-Agent Workflow:

Citizen Complaint → Chat Agent → Router Agent → Tracker Agent
                                                    ├→ Follow Agent
                                                    ├→ Analytics Agent  
                                                    └→ Escalate Agent

Status Progression:

🔴 RED: New complaint received
🟠 ORANGE: Routed to department with deadline
🔵 BLUE: Acknowledged by department
🟢 GREEN: Under resolution/progress
⚫ BLACK: Resolved and closed

Dual Deployment Architecture

Mode 1: Standalone FastAPI Demo

Perfect for: Development, demos, local testing
Features: Instant setup, no API keys needed, full web interface
Deployment: Single command - python main.py

Mode 2: IBM Watsonx Orchestrate Production

Perfect for: Government deployment, enterprise scale
Features: Professional AI orchestration, cloud scalability
Deployment: Import ready-made agents, flows, and tools

Prerequisites

Python 3.9+
Git (for cloning repository)
Web Browser (Chrome/Firefox recommended)
IBM Watsonx Account (for Mode 2 only)

Installation Steps

1. Clone Repository

git clone https://github.com/vinay1359/citizen-voice-ai.git
cd citizen-voice-ai

2. Create Virtual Environment

# Windows
python -m venv venv
venv\Scripts\activate

# Mac/Linux  
python3 -m venv venv
source venv/bin/activate

3. Install Dependencies

pip install -r requirements.txt

4. Environment Setup (Optional for Mode 1)

# Copy environment template
copy ".env sample" .env

# Edit .env file with your credentials (only needed for Mode 2)

Build & Deployment

Mode 1: FastAPI Standalone Demo

Quick Start (30 seconds):

python main.py

Access Points:

Citizen Interface: http://localhost:8000
Government Dashboard: http://localhost:8000/dashboard.html
API Documentation: http://localhost:8000/docs

Features Available:

Real-time complaint submission
6-agent processing simulation
WebSocket live updates
Department routing and tracking
Status progression visualization
Government dashboard for officials

Mode 2: IBM Watsonx Orchestrate Production

Prerequisites:

IBM Watsonx Orchestrate account
CLI tool installed: npm install -g @ibm/watsonx-orchestrate-cli

Deployment Steps:

Import Tools:

orchestrate tools import -k python -f "tools/language_detector.py"
orchestrate tools import -k python -f "tools/text_classifier.py"
orchestrate tools import -k python -f "tools/urgency_analyzer.py"
orchestrate tools import -k python -f "tools/department_mapper.py"
orchestrate tools import -k python -f "tools/deadline_calculator.py"
orchestrate tools import -k python -f "tools/status_monitor.py"
orchestrate tools import -k python -f "tools/reminder_scheduler.py"
orchestrate tools import -k python -f "tools/data_analyzer.py"
orchestrate tools import -k python -f "tools/deadline_tracker.py"

Import Knowledge Base:

orchestrate knowledge import -f "knowledge/knowledge_base_config.yaml"

Import Agents:

orchestrate agents import -f "agents/chat-agent.yaml"
orchestrate agents import -f "agents/router-agent.yaml"
orchestrate agents import -f "agents/tracker-agent.yaml"
orchestrate agents import -f "agents/follow-agent.yaml"
orchestrate agents import -f "agents/analytics-agent.yaml"
orchestrate agents import -f "agents/escalate-agent.yaml"

Deploy Agents:

orchestrate agents deploy --name "Chat_Agent"
orchestrate agents deploy --name "Router_Agent"
orchestrate agents deploy --name "Tracker_Agent"
orchestrate agents deploy --name "Follow_Agent"
orchestrate agents deploy --name "Analytics_Agent"
orchestrate agents deploy --name "Escalate_Agent"

Import Workflow:

orchestrate flows import -f "flows/complaint-processing-flow.py"

Demo Instructions

Mode 1 Demo Walkthrough

Start the Application:
```
python main.py
```
Wait for: Server started on http://localhost:8000
Citizen Interface Demo:
- Open: http://localhost:8000
- Submit a complaint: "There has been no electricity in my area for 2 days"
- Expected Output:
  - Complaint ID generated (e.g., abc123def)
  - Status changes: RED → ORANGE
  - Agent activities displayed in real-time
  - Department assignment shown
Government Dashboard Demo:
- Open: http://localhost:8000/dashboard.html
- View complaint in department queue
- Change status from ORANGE → BLUE → GREEN → BLACK
- Expected Output:
  - Real-time status updates
  - Deadline tracking
  - Department workload display
Agent Workflow Observation:
- Chat Agent: Processes complaint → categorizes as "electricity"
- Router Agent: Routes to "Delhi Electricity Board" → sets 48hr deadline
- Tracker Agent: Monitors status → sets up tracking
- Follow Agent: Schedules reminders
- Analytics Agent: Generates insights
- Escalate Agent: Monitors for delays

Mode 2 Demo Walkthrough

Access IBM Watsonx Orchestrate Interface

Start Chat with Chat_Agent:

{
  "complaint_text": "Water pressure is very low in our building",
  "citizen_name": "John Doe",
  "phone": "+91-9876543210",
  "location": "Mumbai, Maharashtra"
}

Expected Agent Flow:
- Chat_Agent → processes and returns complaint_id
- Router_Agent → routes to Mumbai Water Board
- Tracker_Agent → sets up monitoring
- Follow/Analytics/Escalate Agents → work in background

Project Structure

citizen-voice-ai/
├── 📄 main.py                 # FastAPI application (Mode 1)
├── 🌐 index.html             # Citizen interface
├── 🏛️ dashboard.html         # Government dashboard
├── 📋 requirements.txt       # Python dependencies
├── ⚙️ .env                   # Configuration file
├── 🤖 agents/                # IBM Watsonx agent configs (Mode 2)
│   ├── chat-agent.yaml
│   ├── router-agent.yaml
│   ├── tracker-agent.yaml
│   ├── follow-agent.yaml
│   ├── analytics-agent.yaml
│   └── escalate-agent.yaml
├── 🔄 flows/                 # Workflow definitions (Mode 2)
│   ├── complaint-processing-flow.py
│   └── complaint-processing-flow.yaml
├── 🛠️ tools/                 # Processing tools (Mode 2)
│   ├── language_detector.py
│   ├── text_classifier.py
│   ├── urgency_analyzer.py
│   └── [6 more tools]
└── 📚 knowledge/             # Knowledge base (Mode 2)
    ├── complaint-categories.json
    ├── department-contacts.json
    └── [configuration files]

Configuration

Environment Variables (.env)

# IBM Watsonx Configuration (Mode 2 only)
WATSON_JWT_TOKEN=your_jwt_token_here
WATSON_INSTANCE_ID=your_instance_id
WATSON_REGION_CODE=us-south
WATSON_MODE=auto

Key Features

Citizen Experience

Multilingual complaint submission (English, Hindi, regional languages)
Real-time status tracking with visual indicators
SMS/Email notifications for updates
Community visibility for public complaints
Upvoting system for community issues

Government Experience

Centralized complaint dashboard
Department-wise workload distribution
Automated deadline management
Escalation alerts and workflows
Performance analytics and insights

AI Capabilities

Automatic complaint categorization
Department routing based on complaint type
Urgency assessment and prioritization
Deadline calculation with government SLAs
Pattern recognition for systemic issues
Automated escalation for delays

Expected Demo Outputs

Successful Complaint Processing:

✅ Complaint ID: GVT2024001
✅ Category: Electricity
✅ Urgency: HIGH  
✅ Department: Delhi Electricity Regulatory Commission
✅ Acknowledgment Deadline: 24 hours
✅ Resolution Deadline: 5 days
✅ Status: ORANGE → Routed to Department
✅ Tracking: ACTIVE
✅ Reminders: SCHEDULED

Real-time Updates:

Agent status indicators in UI
WebSocket notifications
Status progression visualization
Department workload updates
Escalation alerts when needed

Deployment Options

Local Development

python main.py  # Runs on localhost:8000

Troubleshooting

Common Issues:

"Module not found" error:

pip install -r requirements.txt

Port 8000 in use:

# Change port in main.py or kill existing process
netstat -ano | findstr :8000

WebSocket connection failed:

Refresh browser
Check firewall settings
Ensure main.py is running

License

MIT License - Open for educational and government use

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Citizen Voice AI - Government Accountability System AI Agent That Never Lets Government Ignore You

Project Overview

6-Agent Workflow:

Status Progression:

Dual Deployment Architecture

Mode 1: Standalone FastAPI Demo

Mode 2: IBM Watsonx Orchestrate Production

Prerequisites

Installation Steps

1. Clone Repository

2. Create Virtual Environment

3. Install Dependencies

4. Environment Setup (Optional for Mode 1)

Build & Deployment

Mode 1: FastAPI Standalone Demo

Mode 2: IBM Watsonx Orchestrate Production

Demo Instructions

Mode 1 Demo Walkthrough

Mode 2 Demo Walkthrough

Project Structure

Configuration

Environment Variables (.env)

Key Features

Citizen Experience

Government Experience

AI Capabilities

Expected Demo Outputs

Successful Complaint Processing:

Real-time Updates:

Deployment Options

Local Development

Troubleshooting

Common Issues:

License

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Citizen Voice AI - Government Accountability System AI Agent That Never Lets Government Ignore You

Project Overview

6-Agent Workflow:

Status Progression:

Dual Deployment Architecture

Mode 1: Standalone FastAPI Demo

Mode 2: IBM Watsonx Orchestrate Production

Prerequisites

Installation Steps

1. Clone Repository

2. Create Virtual Environment

3. Install Dependencies

4. Environment Setup (Optional for Mode 1)

Build & Deployment

Mode 1: FastAPI Standalone Demo

Mode 2: IBM Watsonx Orchestrate Production

Demo Instructions

Mode 1 Demo Walkthrough

Mode 2 Demo Walkthrough

Project Structure

Configuration

Environment Variables (.env)

Key Features

Citizen Experience

Government Experience

AI Capabilities

Expected Demo Outputs

Successful Complaint Processing:

Real-time Updates:

Deployment Options

Local Development

Troubleshooting

Common Issues:

License