---
title: Gov Env - Government Service Assistant
colorFrom: blue
colorTo: green
sdk: docker
app_file: server/app.py
pinned: false
---

# 🇮🇳 Government Service Application Assistant Environment

A production-quality OpenEnv environment that simulates an AI assistant helping users navigate Indian government service applications, with a focus on document validation and correction workflows.

## 🎯 Problem Statement & Motivation

### The Challenge
Every year, **~1.3-1.4 crore (13-14 million)** Indian citizens apply for passports alone. With **138+ crore Aadhaar holders** and **2.5-3 crore PAN applications**, the scale is massive.

### The Pain Point
**70-80% of government service rejections** are due to:
- Document confusion and missing requirements
- Name mismatches across documents
- Invalid or expired proof documents

### Our Solution
An AI agent environment that trains models to:
1. **Identify** required documents for any government service
2. **Validate** submitted documents for completeness and validity
3. **Suggest** corrections for rejected applications

---

## 📋 Action Space

```json
{
  "action_type": "validate_documents",
  "service_type": "passport_new",
  "documents": [{"type": "Aadhaar Card", "details": "Valid"}]
}
```

| Action | Description |
|--------|-------------|
| `select_service` | Choose a government service |
| `list_required_documents` | Get document requirements |
| `validate_documents` | Check submitted documents |
| `suggest_corrections` | Get fix suggestions |
| `submit_application` | Finalize application |

---

## 📝 Task Descriptions

| Task ID | Difficulty | Description | Optimal Steps |
|---------|------------|-------------|----------------|
| `passport_new_easy` | Easy | Identify required documents | 2 |
| `passport_new_medium` | Medium | Validate submitted docs | 3 |
| `passport_new_hard` | Hard | Fix incorrect application | 4 |

---

## 💰 Grading System

- **Range**: [0.0, 1.0]
- **Deterministic**: Same input → same output
- **Components**: Document accuracy (0-0.3) + Validation quality (0-0.3) + Efficiency (+/- 0.1)

---

## 🚀 Endpoints

| Endpoint | Method | Description |
|----------|--------|-------------|
| `/reset` | POST | Initialize environment |
| `/step` | POST | Execute action |
| `/state` | GET | Get current state |
| `/tasks` | GET | Get available tasks |
| `/health` | GET | Health check |

---

## 🤖 Running Inference

```bash
export HF_TOKEN=your_groq_api_key
export ENV_URL=https://dharunkkk-gov-env.hf.space
python3 inference.py passport_new_easy
```

### Output Format
```
[START] task=passport_new_easy env=gov_env model=llama-3.3-70b-versatile
[STEP] step=1 action=... reward=1.00 done=false
[END] success=true steps=10 score=10.00
```

---

## ✅ Validation Checklist

- [x] HF Space deploys (HTTP 200)
- [x] OpenEnv spec compliance
- [x] Dockerfile builds
- [x] Baseline runs without errors
- [x] 3+ tasks with graders
- [x] Grader outputs in [0.0, 1.0]

---

## 📁 Project Structure

```
├── inference.py
├── Dockerfile
├── requirements.txt
├── openenv.yaml
├── models.py
├── tasks.py
├── grader.py
├── client.py
└── server/
    ├── app.py
    └── gov_env_environment.py
```

---

**Live Space**: https://dharunkkk-gov-env.hf.space