Features/package rename

CODE_OF_CONDUCT.md

@@ -0,0 +1,122 @@
+# Contributor Covenant Code of Conduct
+
+## Our Pledge
+
+We as members, contributors, and leaders pledge to make participation in our
+community a harassment-free experience for everyone, regardless of age, body
+size, visible or invisible disability, ethnicity, sex characteristics, gender
+identity and expression, level of experience, education, socio-economic status,
+nationality, personal appearance, race, religion, or sexual identity
+and orientation.
+
+We pledge to act and interact in ways that are welcoming, inclusive,
+diverse, and equitable.
+
+## Our Standards
+
+Examples of behavior that contributes to a positive environment for our
+community include:
+
+*   Demonstrating empathy and kindness toward other people
+*   Being respectful of differing opinions, viewpoints, and experiences
+*   Giving and gracefully accepting constructive feedback
+*   Accepting responsibility and apologizing to those affected by our mistakes,
+    and learning from the experience
+*   Focusing on what is best not just for us as individuals, but for the
+    overall community
+
+Examples of unacceptable behavior include:
+
+*   The use of sexualized language or imagery, and sexual attention or
+    advances of any kind
+*   Trolling, insulting or derogatory comments, and personal or political attacks
+*   Public or private harassment
+*   Publishing others' private information, such as a physical or email
+    address, without their explicit permission
+*   Other conduct which could reasonably be considered inappropriate in a
+    professional setting
+
+## Enforcement Responsibilities
+
+Community leaders are responsible for clarifying and enforcing our standards of
+acceptable behavior and will take appropriate and fair corrective action in
+response to any behavior that they deem inappropriate, threatening, offensive,
+or harmful.
+
+Community leaders have the right and responsibility to remove, edit, or reject
+comments, commits, code, wiki edits, issues, and other contributions that are
+not aligned to this Code of Conduct, and will communicate reasons for moderation
+decisions when appropriate.
+
+## Scope
+
+This Code of Conduct applies within all community spaces, and also applies when
+an individual is officially representing the community in public spaces.
+Examples of representing our community include using an official e-mail address,
+posting via an official social media account, or acting as an appointed
+representative at an online or offline event.
+
+## Enforcement
+
+Instances of abusive, harassing, or otherwise unacceptable behavior may be
+reported to the community leaders responsible for enforcement at
+[email protected].
+All complaints will be reviewed and investigated promptly and fairly.
+
+All community leaders are obligated to respect the privacy and security of the
+reporter of any incident.
+
+## Enforcement Guidelines
+
+Community leaders will follow these Community Impact Guidelines in determining
+the consequences for any action they deem in violation of this Code of Conduct:
+
+### 1. Correction
+
+**Community Impact**: Use of inappropriate language or other behavior deemed
+unprofessional or unwelcome in the community.
+
+**Consequence**: A private, written warning from community leaders, providing
+clarity around the nature of the violation and an explanation of why the
+behavior was inappropriate. A public apology may be requested.
+
+### 2. Warning
+
+**Community Impact**: A violation through a single incident or series
+of actions.
+
+**Consequence**: A warning with consequences for continued behavior. No
+interaction with the people involved, including unsolicited interaction with
+those enforcing the Code of Conduct, for a specified period of time. This
+includes avoiding interaction in community spaces as well as external channels
+like social media. Violating these terms may lead to a temporary or
+permanent ban.
+
+### 3. Temporary Ban
+
+**Community Impact**: A serious violation of community standards, including
+sustained inappropriate behavior.
+
+**Consequence**: A temporary ban from any sort of interaction or public
+communication with the community for a specified period of time. No public or
+private interaction with the people involved, including unsolicited interaction
+with those enforcing the Code of Conduct, is allowed during this period.
+Violating these terms may lead to a permanent ban.
+
+### 4. Permanent Ban
+
+**Community Impact**: Demonstrating a pattern of violation of community
+standards, including sustained inappropriate behavior, harassment of an
+individual, or aggression toward or disparagement of classes of individuals.
+
+**Consequence**: A permanent ban from any sort of public interaction within
+the community.
+
+## Attribution
+
+This Code of Conduct is adapted from the [Contributor Covenant][homepage],
+version 2.1, available at
+[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
+
+[homepage]: https://www.contributor-covenant.org
+[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html

CONTRIBUTING.md

@@ -0,0 +1,97 @@
+# Contributing to Intugle
+
+First off, thank you for considering contributing to Intugle! It's people like you that make Intugle such a great tool.
+
+Intugle is an open source project and we love to receive contributions from our community — you!
+
+There are many ways to contribute, from writing tutorials or blog posts, improving the documentation, submitting bug reports and feature requests or writing code which can be incorporated into Intugle itself.
+
+## How to Contribute
+
+### Reporting Bugs
+
+If you find a bug, please open an issue on our [GitHub repository](https://github.com/Intugle/data-tools/issues). Please include a clear and concise description of the bug, as well as steps to reproduce it.
+
+### Submitting Feature Requests
+
+If you have an idea for a new feature, please open an issue on our [GitHub repository](https://github.com/Intugle/data-tools/issues). Please include a clear and concise description of the feature, as well as a justification for why it would be a good addition to the project.
+
+### Writing Code
+
+If you want to contribute code to the project, please follow the steps below.
+
+## Getting Started
+
+1.  Fork the repository on GitHub.
+2.  Clone your fork locally:
+
+    ```bash
+    git clone https://github.com/your-username/intugle.git
+    ```
+
+3.  Set up a virtual environment and install the dependencies:
+
+    ```bash
+    cd intugle
+    python -m venv venv
+    source venv/bin/activate
+    pip install -r requirements.txt
+    ```
+
+## Development Workflow
+
+1.  Create a new branch for your changes:
+
+    ```bash
+    git checkout -b my-new-feature
+    ```
+
+2.  Make your changes to the code.
+
+3.  Run the tests to make sure that your changes don't break anything:
+
+    ```bash
+    pytest
+    ```
+
+4.  Commit your changes:
+
+    ```bash
+    git commit -m "Add some feature"
+    ```
+
+5.  Push your changes to your fork:
+
+    ```bash
+    git push origin my-new-feature
+    ```
+
+6.  Open a pull request on the [Intugle repository](https://github.com/Intugle/data-tools/pulls).
+
+## Coding Style
+
+This project uses `ruff` for linting and code formatting. Before submitting a pull request, please make sure that your code conforms to the project's coding style by running the following command:
+
+```bash
+ruff check .
+```
+
+## Testing
+
+This project uses `pytest` for testing. To run the tests, use the following command:
+
+```bash
+pytest
+```
+
+## Submitting a Pull Request
+
+When you submit a pull request, please include the following:
+
+*   A clear and concise title for the pull request.
+*   A clear and concise description of the changes that you made.
+*   A link to the issue that the pull request addresses (if applicable).
+
+## Code of Conduct
+
+Please note that this project is released with a [Contributor Code of Conduct](CODE_OF_CONDUCT.md). By participating in this project you agree to abide by its terms.

README.md

@@ -1,4 +1,7 @@
-# Data-Tools
+<p align="center">
+      <img src="https://intugle.ai/assets/Icons/intugle.png" alt="Intugle Logo" width="350">
+ <h3 align="center"><i>The GenAI-powered toolkit for automated data intelligence.</i></h3>
+</p>
 
 [![Release](https://img.shields.io/github/release/Intugle/data-tools)](https://github.com/Intugle/data-tools/releases/tag/v0.1.0)     
 [![Made with Python](https://img.shields.io/badge/Made_with-Python-blue?logo=python&logoColor=white)](https://www.python.org/)
@@ -11,7 +14,7 @@
 
 ## Overview
 
-Intugle's Data-Tools is a GenAI-powered Python library that simplifies and accelerates the journey from raw data to insights. It empowers data and business teams to build an intelligent semantic layer over their data, enabling self-serve analytics and natural language queries. By automating data profiling, link prediction, and SQL generation, Data-Tools helps you build data products faster and more efficiently than traditional methods.
+Intugle provides a set of GenAI-powered Python tools to simplify and accelerate the journey from raw data to insights. This library empowers data and business teams to build an intelligent semantic layer over their data, enabling self-serve analytics and natural language queries. By automating data profiling, link prediction, and SQL generation, Intugle helps you build data products faster and more efficiently than traditional methods.
 
 ## Who is this for?
 
@@ -35,7 +38,7 @@ This tool is designed for both **data teams** and **business teams**.
 ### Installation
 
 ```bash
-pip install data-tools
+pip install intugle
 ```
 
 ### Configuration
@@ -67,7 +70,7 @@ The core workflow of the project involves the following steps:
 3.  **Predict links:** Use the `LinkPredictor` to discover relationships between your tables.
 
     ```python
-    from data_tools import LinkPredictor
+    from intugle import LinkPredictor
 
     # Initialize the predictor
     predictor = LinkPredictor(datasets)
@@ -80,7 +83,7 @@ The core workflow of the project involves the following steps:
 5.  **Generate SQL:** Use the `SqlGenerator` to generate SQL queries from the semantic layer.
 
     ```python
-    from data_tools import SqlGenerator
+    from intugle import SqlGenerator
 
     # Create a SqlGenerator
     sql_generator = SqlGenerator()

notebooks/quickstart_content.txt

@@ -3,7 +3,7 @@ type: markdown
 ---
 # Quickstart: Building a Semantic Layer with Data-Tools
 
-This notebook provides a quick introduction to the `data-tools` project. You'll learn how to use its key features to automatically build a semantic layer over your data.
+This notebook provides a quick introduction to the `intugle` project. You'll learn how to use its key features to automatically build a semantic layer over your data.
 
 **What is a Semantic Layer?**
 
@@ -67,12 +67,12 @@ type: markdown
 ---
 ## 3. Data Profiling
 
-The first step in building a semantic layer is to profile your data. This involves analyzing your data sources to understand their structure, data types, and other characteristics. The `data-tools` project provides a pipeline for this purpose.
+The first step in building a semantic layer is to profile your data. This involves analyzing your data sources to understand their structure, data types, and other characteristics. The `intugle` project provides a pipeline for this purpose.
 ---
 type: code
 ---
 import pandas as pd
-from data_tools.analysis.models import DataSet
+from intugle.analysis.models import DataSet
 ---
 type: code
 ---
@@ -109,7 +109,7 @@ type: markdown
 ---
 ## 4. Automated Link Prediction
 
-Now that we've profiled our data, let's discover the relationships between tables. The `data-tools` project uses a Large Language Model (LLM) to predict links (foreign keys) between tables.
+Now that we've profiled our data, let's discover the relationships between tables. The `intugle` project uses a Large Language Model (LLM) to predict links (foreign keys) between tables.
 
 First, we'll load a few more tables from the sample dataset.
 ---
@@ -130,7 +130,7 @@ Now, let's run the link prediction pipeline.
 ---
 type: code
 ---
-from data_tools.link_predictor import LinkPredictor
+from intugle.link_predictor import LinkPredictor
 
 # Initialize the predictor
 predictor = LinkPredictor(datasets)
@@ -168,7 +168,7 @@ Now, we can load the YAML files and create a manifest.
 ---
 type: code
 ---
-from data_tools.parser.manifest import ManifestLoader
+from intugle.parser.manifest import ManifestLoader
 
 # Load the manifest
 manifest_loader = ManifestLoader('.')
@@ -188,7 +188,7 @@ Let's create an ETL model to define the query we want to generate.
 ---
 type: code
 ---
-from data_tools.libs.smart_query_generator.models.models import ETLModel, FieldModel
+from intugle.libs.smart_query_generator.models.models import ETLModel, FieldModel
 
 # Create an ETL model
 etl_model = ETLModel(
@@ -205,7 +205,7 @@ Now, let's use the `SqlGenerator` to generate the SQL query.
 ---
 type: code
 ---
-from data_tools.sql_generator import SqlGenerator
+from intugle.sql_generator import SqlGenerator
 
 # Create a SqlGenerator
 sql_generator = SqlGenerator('.')
@@ -220,12 +220,12 @@ type: markdown
 ---
 ## Conclusion
 
-This notebook has provided a brief overview of the `data-tools` project. You've learned how to:
+This notebook has provided a brief overview of the `intugle` project. You've learned how to:
 
 * Configure your LLM provider.
 * Profile your data to understand its characteristics.
 * Use an LLM to automatically predict links between tables.
 * Generate a semantic layer (`manifest.json`).
 * Use the semantic layer to generate SQL queries.
 
-This is just a starting point. The `data-tools` project has many other features to explore. We encourage you to try it with your own data and see how it can help you build a powerful semantic layer.
+This is just a starting point. The `intugle` project has many other features to explore. We encourage you to try it with your own data and see how it can help you build a powerful semantic layer.