https://github.com/n-t-raghava/natquery

natquery is a Python package that enables users to interact with relational databases using natural language via a secure, performance-aware command-line interface along with database driven machine learning analytics.
https://github.com/n-t-raghava/natquery

Last synced: 2 months ago
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natquery is a Python package that enables users to interact with relational databases using natural language via a secure, performance-aware command-line interface along with database driven machine learning analytics.

• Host: GitHub
• URL: https://github.com/n-t-raghava/natquery
• Owner: N-T-Raghava
• License: mit
• Created: 2026-03-13T13:26:56.000Z (3 months ago)
• Default Branch: main
• Last Pushed: 2026-04-14T11:31:50.000Z (2 months ago)
• Last Synced: 2026-04-14T12:24:43.507Z (2 months ago)
• Language: Python
• Size: 104 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# NatQuery

[![PyPI Version](https://img.shields.io/pypi/v/natquery)](https://pypi.org/project/natquery/)

[![codecov](https://codecov.io/gh/N-T-Raghava/natquery/graph/badge.svg?token=KZIEXD9ALC)](https://codecov.io/gh/N-T-Raghava/natquery)

[![Type Checked](https://img.shields.io/badge/mypy-checked-blue)](https://github.com/python/mypy)

[![Code Style: Black](https://img.shields.io/badge/code%20style-black-000000)](https://github.com/psf/black)

[![license](https://img.shields.io/github/license/mashape/apistatus.svg)]((https://img.shields.io/github/license/mashape/apistatus.svg))

natquery is a Python package that enables users to interact with relational databases using natural language via a secure, performance-aware command-line interface along with database driven machine learning analytics.

```

natquery/

│

├── pyproject.toml

├── README.md

├── requirements.txt

│── src/

├   ├── natquery/

│       ├── __init__.py

│

│       # =========================

│       # 1. CLI LAYER

│       # =========================

│       ├── cli/

│       │   ├── __init__.py

│       │   ├── main.py              # Entry point

│       │   ├── shell.py             # Interactive REPL

│       │   ├── commands.py          # CLI command registry

│

│       # =========================

│       # 2. CONFIG LAYER

│       # =========================

│       ├── config/

│       │   ├── __init__.py

│       │   ├── settings.py          # API keys, DB config

│       │   ├── connection.py        # PostgreSQL connection manager

│

│       # =========================

│       # 3. ORCHESTRATION LAYER

│       # =========================

│       ├── orchestration/

│       │   ├── __init__.py

│       │   ├── pipeline.py          # End-to-end coordinator

│       │   ├── error_handler.py

│

│       # =========================

│       # 4. SCHEMA MODULE

│       # =========================

│       ├── schema/

│       │   ├── __init__.py

│       │   ├── extractor.py         # Dynamic schema extraction

│       │   ├── formatter.py         # Convert schema to prompt-friendly text

│

│       # =========================

│       # 5. PROMPT BUILDER

│       # =========================

│       ├── prompt/

│       │   ├── __init__.py

│       │   ├── builder.py           # Structured prompt construction

│

│       # =========================

│       # 6. LLM CLIENT

│       # =========================

│       ├── llm/

│       │   ├── __init__.py

│       │   ├── client.py            # LLM API calls

│       │   ├── self_corrector.py    # Retry & correction mechanism

│

│       # =========================

│       # 7. SECURITY + VALIDATION

│       # =========================

│       ├── security/

│       │   ├── __init__.py

│       │   ├── validator.py         # SELECT-only enforcement

│       │   ├── limiter.py           # LIMIT enforcement

│

│       # =========================

│       # 8. EXECUTION ENGINE

│       # =========================

│       ├── execution/

│       │   ├── __init__.py

│       │   ├── engine.py            # SQL execution

│       │   ├── explain.py           # EXPLAIN / ANALYZE

│

│       # =========================

│       # 9. MACHINE LEARNING

│       # =========================

│       ├── ml/

│       │   ├── __init__.py

│       │   ├── preprocessing.py

│       │   ├── trainer.py

│       │   ├── inference.py

│       │

│       # =========================

│       # 10. PERFORMANCE + LOGGING

│       # =========================

│       ├── observability/

│          ├── __init__.py

│          ├── logger.py

│          ├── cost_analyzer.py

│          ├── index_recommender.py

│

│

├── database/

│   ├── schema.sql

│   ├── seed.py

│   ├── synthetic_data.py

│

├── tests/

│   ├── test_pipeline.py

│   ├── test_security.py

│   ├── test_ml.py

│

└── benchmarks/

    ├── nl_queries.json