Dharmiq

Open-source Indian legal information assistant for citizens. Dharmiq explains rights and obligations in plain language, grounded in statutory documents (IndiaCode corpus), with citations and clear disclaimers that it does not provide legal advice.

Alpha (v0.1) — actively under development. Landing page · App

Features

• RAG chat – multi-agent pipeline (clarify, retrieve, answer, validate) over indexed legal PDFs
• User uploads – private PDF/image indexing for contract and notice questions
• Citations – answers link back to source documents in the UI
• Corpus ingestion – daily scan, parse, chunk, embed pipeline for IndiaCode PDFs
• Evaluation – Ragas + LLM-judge scoring on curated Q&A datasets
• Observability – Prometheus metrics and Grafana dashboards

MVP scope covers fundamental rights, consumer issues, and employment (see docs/prd.md).

Repository layout

dharmiq/
  backend/          # FastAPI app, Celery workers, RAG pipeline
  frontend/         # React + assistant-ui chat client
  config/           # Environment YAML (dev, beta) + Grafana/Prometheus
  docs/             # PRD, TRD, implementation plan
  data/             # Local corpus, uploads, eval data (gitignored)
  docker-compose.yml

Path	Description
backend/README.md	API setup, endpoints, ingestion, eval, metrics
frontend/README.md	Vite dev server and build
docs/prd.md	Product requirements
docs/trd.md	Technical design
docs/plan.md	Implementation milestones

Prerequisites

• Docker – Postgres, Redis, Prometheus, Grafana
• uv – Python backend
• nvm – Node.js (see .nvmrc)
• OpenRouter API key – chat and eval LLM calls

Quick start

1. Infrastructure

cp .env.example .env
# Set OPENROUTER_API_KEY in .env

docker compose up -d

2. Backend

cd backend
uv sync --dev
uv run alembic upgrade head
mkdir -p ../data/corpus/india_code/raw ../data/eval/datasets ../data/eval/runs

uv run dharmiq-api

In another terminal (from backend/):

uv run celery -A celery_app worker --loglevel=info

3. Frontend

nvm install && nvm use
cd frontend
npm install
npm run dev

Open http://localhost:5173. The frontend proxies /api to the backend on port 8000.

4. Optional – observability

docker compose up -d prometheus grafana

Service	URL
App	http://localhost:5173
API	http://localhost:8000
API health	http://localhost:8000/api/health
Metrics	http://localhost:8000/metrics
Prometheus	http://localhost:9090
Grafana	http://localhost:3000 (admin / admin)

In Grafana: Dashboards → Dharmiq → Dharmiq Overview. The API must be running for Prometheus to scrape metrics.

Configuration

Non-secret settings live in config/config.dev.yaml (local) and config/config.beta.yaml (deployment). Secrets go in .env:

Variable	Description
DHARMIQ_ENV	Config profile (dev, beta)
DHARMIQ_DATABASE_PASSWORD	Postgres password (default: dharmiq)
DHARMIQ_JWT_SECRET	JWT signing secret
OPENROUTER_API_KEY	Required for chat and eval

Local Postgres is exposed on port 5433 via Docker Compose.

Data & ingestion

Legal PDFs go under data/corpus/india_code/raw/. After adding files:

cd backend
uv run celery -A celery_app call dharmiq.ingestion.sync_india_code_pdfs

User uploads are stored under data/uploads/{user_id}/. The data/ directory is gitignored.

Evaluation

See backend/dharmiq/eval/dataset_format.md. Requires an indexed corpus:

cd backend
uv run dharmiq-eval --dataset v1_fundamental_rights

Development

# Backend tests
cd backend && uv run pytest -m "not slow"

# Backend lint
cd backend && uv run ruff check .

# Frontend lint
cd frontend && npm run lint

Architecture (high level)

┌─────────────┐     REST/JWT      ┌──────────────────────────────────┐
│  Frontend   │ ────────────────► │  FastAPI (chat, auth, uploads)   │
│  (React)    │                   │  LangChain agents + pgvector RAG │
└─────────────┘                   └───────────────┬──────────────────┘
                                                  │
                    ┌─────────────────────────────┼─────────────────────┐
                    ▼                             ▼                     ▼
              PostgreSQL                      Redis                 OpenRouter
           (+ pgvector)                    (Celery broker)            (LLM API)
                    ▲
                    │ Celery workers: ingestion, eval
                    └────────────────────────────────────────────────────

Disclaimer

Dharmiq provides general legal information, not legal advice. Users should consult a qualified lawyer for decisions that matter to them.

License

MIT