Metadata-Version: 2.4
Name: urimai
Version: 0.1.0
Summary: AI-powered SQL answer engine - ask questions about your databases
Author: Shiva
License: Elastic License 2.0 (ELv2)
        
        Licensor: Shiva
        Licensed Work: urimai
        
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Project-URL: Homepage, https://github.com/shivakharbanda/urimAI
Project-URL: Source, https://github.com/shivakharbanda/urimAI
Keywords: sql,ai,llm,database,natural-language,query
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Database
Requires-Python: >=3.11.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: dq-db-manager>=0.2.0
Requires-Dist: pydantic>=2.12.3
Requires-Dist: pydantic-ai>=0.0.14
Requires-Dist: typer>=0.12.0
Requires-Dist: rich>=13.0.0
Requires-Dist: keyring>=25.0.0
Requires-Dist: tomli-w>=1.0.0
Requires-Dist: aiosqlite>=0.20.0
Requires-Dist: prompt-toolkit>=3.0.0
Requires-Dist: numpy>=2.3.4
Requires-Dist: scipy>=1.16.3
Requires-Dist: pandas>=2.0.0
Requires-Dist: openai>=1.0.0
Requires-Dist: openpyxl>=3.1.0
Dynamic: license-file

# SQL Answer Engine

Ask natural-language questions about SQLite databases and CSV files using AI.

## Prerequisites

- Python >= 3.11.6
- [uv](https://docs.astral.sh/uv/) package manager
- A Google API key (Gemini)

## Installation

```bash
git clone <repo-url>
cd sql_answer_engine
uv sync
```

Create a `.env` file in the project root:

```
GOOGLE_API_KEY=your-google-api-key
```

## Environment Variables

| Variable | Required | Default | Description |
|---|---|---|---|
| `GOOGLE_API_KEY` | Yes | — | Google Gemini API key |
| `MODEL_NAME` | No | `gemini-2.5-flash` | Model to use for AI queries |
| `METADATA_DB_PATH` | No | `./metadata.db` | Path to the internal metadata database |
| `DEFAULT_SAMPLE_ROWS` | No | `5` | Number of sample rows extracted per table during init/sync |

## CLI Commands

### `sql-engine init <path>`

Register a SQLite database or CSV file.

```bash
sql-engine init ./my_database.db
sql-engine init ./data.csv --name my_data --table-name sales --delimiter "," --encoding utf-8
```

| Option | Description |
|---|---|
| `--name` | Custom name for the database (default: filename) |
| `--table-name` | Table name for CSV import (default: LLM-suggested) |
| `--delimiter` | CSV delimiter character (default: `,`) |
| `--encoding` | CSV file encoding (default: `utf-8`) |

CSV files are automatically converted to SQLite with LLM-powered schema inference.

### `sql-engine list`

List all registered databases.

```bash
sql-engine list
```

### `sql-engine chat <db_name>`

Start an interactive chat session with a registered database.

```bash
sql-engine chat my_database
```

### `sql-engine sync <db_name>`

Re-sync schema metadata for a registered database. Useful after the source data changes.

```bash
sql-engine sync my_database
```

### `sql-engine config`

View or modify settings.

```bash
sql-engine config --show
sql-engine config --sample-rows 10
```

| Option | Description |
|---|---|
| `--show` | Show current settings |
| `--sample-rows` | Set number of sample rows extracted per table |

## Quick Start

```bash
# Register a database
sql-engine init ./chinook.db

# Start chatting
sql-engine chat chinook
```
