README.md

metadata

title: Citizen Navigator AI Portal
emoji: ⚖️
colorFrom: indigo
colorTo: blue
sdk: docker
app_port: 7860
pinned: false

Citizen Navigator AI Portal

A dual-dashboard Flask + LangGraph application for Indian citizen assistance:

• ⚖️ Legal Resolution Dashboard: upload a notice/document or describe a case and get official-step guidance.
• 🎓 Opportunity Finder Dashboard: submit a detailed profile and get personalized schemes, jobs, innovation grants, missed opportunities, and a practical roadmap.

The system uses hybrid retrieval for profile intelligence:

• Live web search (official domains via Tavily)
• Offline policy RAG (FAISS over local policy PDFs)

---

Features

• Two independent pipelines (no cross-contamination of legal/profile workflows)
• Stage-aware legal analysis (legal_category, case_status)
• Deep profile filtering (gender, income, status, skills, goal)
• Structured profile outputs:
  • opportunities_json
  • missed_opportunities_json
  • guiding_roadmap
• Dark-mode, dual-tab frontend with async API calls
• OCR fallback for scanned PDF/image documents

---

Project Structure

legal/
├── README.md
├── .gitignore
├── legal_agentic_system/
│   ├── app.py
│   ├── main_graph.py
│   ├── state.py
│   ├── requirements.txt
│   ├── templates/
│   │   └── index.html
│   ├── agents/
│   │   ├── data_agent.py
│   │   ├── legal_pipeline.py
│   │   ├── profile_pipeline.py
│   │   ├── policy_rag.py
│   │   └── search_tool.py
│   └── ...
└── venv/ (local)

---

Architecture Overview

1) Legal Graph

data_extraction -> legal_analysis -> END

• data_extraction: reads raw text / text file / PDF / image OCR
• legal_analysis: summarizes issue, performs official procedure search, returns legal action plan

2) Profile Graph

profile_analysis -> END

• profile_analysis: combines policy RAG + live search, ranks opportunities, flags missed windows, builds roadmap

---

Requirements

• Python 3.10+
• Poppler installed (required by pdf2image)
• API keys for Groq and Tavily

Install dependencies:

cd legal_agentic_system
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

---

Environment Variables

Create legal_agentic_system/.env:

GROQ_API_KEY=your_groq_key
TAVILY_API_KEY=your_tavily_key
HF_TOKEN=your_huggingface_token

Optional policy-RAG corpus:

• Put policy PDFs in: legal_agentic_system/policy_docs/
• FAISS index is auto-created in: legal_agentic_system/policy_faiss_index/

---

Run Locally

cd legal_agentic_system
python app.py

Open: http://localhost:5000

---

API Endpoints

• POST /api/analyze_legal

  • Inputs: raw_text or file, plus optional legal_category, case_status
  • Output: solution

• POST /api/analyze_profile

  • Inputs: profile fields (user_age, user_state, user_education, user_specialization, user_gender, annual_income, current_status, extracurriculars, user_goal)
  • Output: opportunities, missed_opportunities, roadmap, report

---

Why Files May Not Have Appeared on GitHub

This repository previously had legal_agentic_system tracked as a nested git link instead of normal files. That setup was converted so the folder contents are now tracked directly by this repo.

After pulling these changes, run:

git add -A
git commit -m "Fix tracking + add README"
git push

---

Notes

• Large/generated directories are intentionally gitignored by default:
  • legal_agentic_system/data/
  • legal_agentic_system/faiss_index/
  • legal_agentic_system/policy_faiss_index/
• If you want these committed, remove those lines from .gitignore.

---

License

Use according to your organization/course requirements.