<p align="center">
<a href="https://github.com/MAIF/melusine/actions?branch=master" target="_blank">
<img src="https://github.com/MAIF/melusine/actions/workflows/main.yml/badge.svg?branch=master" alt="Build & Test">
</a>
<a href="https://pypi.python.org/pypi/melusine" target="_blank">
<img src="https://img.shields.io/pypi/v/melusine.svg" alt="pypi">
</a>
<a href="https://opensource.org/licenses/Apache-2.0" target="_blank">
<img src="https://img.shields.io/badge/License-Apache%202.0-blue.svg" alt="Test">
</a>
<a href="https://shields.io/" target="_blank">
<img src="https://img.shields.io/badge/python-3.8+-blue.svg" alt="pypi">
</a>
</p>
<p align="center">🎉 **BREAKING** : New major version <b>Melusine 3.0</b> is available 🎉</p>
<p align="center">
<a href="https://maif.github.io/melusine" target="_blank">
<img src="docs/_static/melusine.png">
</a>
</p>
- **Free software**: Apache Software License 2.0
- **Documentation**: [maif.github.io/melusine](https://maif.github.io/melusine/)
- **Installation**: `pip install melusine`
- **Tutorials**: [Discover melusine](https://maif.github.io/melusine/tutorials/00_GettingStarted/)
## Overview
Discover Melusine, a comprehensive email processing library
designed to optimize your email workflow.
Leverage Melusine's advanced features to achieve:
- **Effortless Email Routing**: Ensure emails reach their intended destinations with high accuracy.
- **Smart Prioritization**: Prioritize urgent emails for timely handling and efficient task management.
- **Snippet Summaries**: Extract relevant information from lengthy emails, saving you precious time and effort.
- **Precision Filtering**: Eliminate unwanted emails from your inbox, maintaining focus and reducing clutter.
Melusine facilitates the integration of deep learning frameworks (HuggingFace, Pytorch, Tensorflow, etc),
deterministic rules (regex, keywords, heuristics) into a full email qualification workflow.
## Why Choose Melusine ?
Melusine stands out with its combination of features and advantages:
- **Pre-packaged Tools** : Melusine comes with out-of-the-box features such as
- Segmenting an email conversation into individual messages
- Tagging message parts (Email body, signatures, footers, etc)
- Transferred email handling
- **Streamlined Execution** : Focus on the core email qualification logic
while Melusine handles the boilerplate code, providing debug mode, pipeline execution, code parallelization, and more.
- **Flexible Integrations** : Melusine's modular architecture enables seamless integration with various AI frameworks,
ensuring compatibility with your preferred tools.
- **Production ready** : Proven in the MAIF production environment,
Melusine provides the robustness and stability you need.
## Email Segmentation Exemple
In the following example, an email is divided into two distinct messages
separated by a transition pattern.
Each message is then tagged line by line.
This email segmentation can later be leveraged to enhance the performance of machine learning models.
<p align="center">
<a href="https://maif.github.io/melusine" target="_blank">
<img src="docs/_static/segmentation.png">
</a>
</p>
## Getting started
Explore our comprehensive [documentation](https://maif.github.io/melusine/) and tested [tutorials](https://maif.github.io/melusine/tutorials/00_GettingStarted/) to get started.
Or dive into our minimal example to experience Melusine's simplicity and power:
``` Python
from melusine.data import load_email_data
from melusine.pipeline import MelusinePipeline
# Load an email dataset
df = load_email_data()
# Load a pipeline
pipeline = MelusinePipeline.from_config("demo_pipeline")
# Run the pipeline
df = pipeline.transform(df)
```
The code above executes a default pipeline and returns a qualified email dataset with columns such as:
- `messages`: List of individual messages present in each email.
- `emergency_result`: Flag to identify urgent emails.
With Melusine, you're well-equipped to transform your email handling, streamlining processes, maximizing efficiency,
and enhancing overall productivity.
Raw data
{
"_id": null,
"home_page": null,
"name": "melusine",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": null,
"keywords": "nlp, email, courriel, text, data-science, machine-learning, natural-language-processing",
"author": "Tiphaine Fabre, Sacha Samama, Antoine Simoulin",
"author_email": "Hugo Perrier <hugorperrier@gmail.com>",
"download_url": "https://files.pythonhosted.org/packages/58/62/916d31e2a2404bfb2902ecf8ea21bb1763d71650ba54bb1867f218d6dfe4/melusine-3.1.0.tar.gz",
"platform": null,
"description": "<p align=\"center\">\n<a href=\"https://github.com/MAIF/melusine/actions?branch=master\" target=\"_blank\">\n<img src=\"https://github.com/MAIF/melusine/actions/workflows/main.yml/badge.svg?branch=master\" alt=\"Build & Test\">\n</a>\n<a href=\"https://pypi.python.org/pypi/melusine\" target=\"_blank\">\n<img src=\"https://img.shields.io/pypi/v/melusine.svg\" alt=\"pypi\">\n</a>\n<a href=\"https://opensource.org/licenses/Apache-2.0\" target=\"_blank\">\n<img src=\"https://img.shields.io/badge/License-Apache%202.0-blue.svg\" alt=\"Test\">\n</a>\n<a href=\"https://shields.io/\" target=\"_blank\">\n<img src=\"https://img.shields.io/badge/python-3.8+-blue.svg\" alt=\"pypi\">\n</a>\n</p>\n\n<p align=\"center\">\ud83c\udf89 **BREAKING** : New major version <b>Melusine 3.0</b> is available \ud83c\udf89</p>\n\n<p align=\"center\">\n<a href=\"https://maif.github.io/melusine\" target=\"_blank\">\n<img src=\"docs/_static/melusine.png\">\n</a>\n</p>\n\n- **Free software**: Apache Software License 2.0\n- **Documentation**: [maif.github.io/melusine](https://maif.github.io/melusine/)\n- **Installation**: `pip install melusine`\n- **Tutorials**: [Discover melusine](https://maif.github.io/melusine/tutorials/00_GettingStarted/)\n\n## Overview\n\nDiscover Melusine, a comprehensive email processing library\ndesigned to optimize your email workflow.\nLeverage Melusine's advanced features to achieve:\n\n- **Effortless Email Routing**: Ensure emails reach their intended destinations with high accuracy.\n- **Smart Prioritization**: Prioritize urgent emails for timely handling and efficient task management.\n- **Snippet Summaries**: Extract relevant information from lengthy emails, saving you precious time and effort.\n- **Precision Filtering**: Eliminate unwanted emails from your inbox, maintaining focus and reducing clutter.\n\nMelusine facilitates the integration of deep learning frameworks (HuggingFace, Pytorch, Tensorflow, etc),\ndeterministic rules (regex, keywords, heuristics) into a full email qualification workflow.\n\n## Why Choose Melusine ?\n\nMelusine stands out with its combination of features and advantages:\n\n- **Pre-packaged Tools** : Melusine comes with out-of-the-box features such as\n - Segmenting an email conversation into individual messages\n - Tagging message parts (Email body, signatures, footers, etc)\n - Transferred email handling\n- **Streamlined Execution** : Focus on the core email qualification logic\nwhile Melusine handles the boilerplate code, providing debug mode, pipeline execution, code parallelization, and more.\n- **Flexible Integrations** : Melusine's modular architecture enables seamless integration with various AI frameworks,\nensuring compatibility with your preferred tools.\n- **Production ready** : Proven in the MAIF production environment,\nMelusine provides the robustness and stability you need.\n\n## Email Segmentation Exemple\n\nIn the following example, an email is divided into two distinct messages\nseparated by a transition pattern.\nEach message is then tagged line by line.\nThis email segmentation can later be leveraged to enhance the performance of machine learning models.\n\n<p align=\"center\">\n<a href=\"https://maif.github.io/melusine\" target=\"_blank\">\n<img src=\"docs/_static/segmentation.png\">\n</a>\n</p>\n\n## Getting started\n\nExplore our comprehensive [documentation](https://maif.github.io/melusine/) and tested [tutorials](https://maif.github.io/melusine/tutorials/00_GettingStarted/) to get started.\nOr dive into our minimal example to experience Melusine's simplicity and power:\n\n``` Python\n from melusine.data import load_email_data\n from melusine.pipeline import MelusinePipeline\n\n # Load an email dataset\n df = load_email_data()\n\n # Load a pipeline\n pipeline = MelusinePipeline.from_config(\"demo_pipeline\")\n\n # Run the pipeline\n df = pipeline.transform(df)\n```\n\nThe code above executes a default pipeline and returns a qualified email dataset with columns such as:\n- `messages`: List of individual messages present in each email.\n- `emergency_result`: Flag to identify urgent emails.\n\n\nWith Melusine, you're well-equipped to transform your email handling, streamlining processes, maximizing efficiency,\nand enhancing overall productivity.\n",
"bugtrack_url": null,
"license": "Apache Software License 2.0",
"summary": "Melusine is a high-level library for emails processing",
"version": "3.1.0",
"project_urls": null,
"split_keywords": [
"nlp",
" email",
" courriel",
" text",
" data-science",
" machine-learning",
" natural-language-processing"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "79585be105830bcc4fc78127ec9956228543094b58370bfe2f0c0fce3083a56f",
"md5": "1f424351d9b624929a81cd42478a34e2",
"sha256": "fea8e60810341c91fb4d6718abf710b4da0f29d333d66ca8d37e634c38e67282"
},
"downloads": -1,
"filename": "melusine-3.1.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "1f424351d9b624929a81cd42478a34e2",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 302510,
"upload_time": "2024-11-04T10:28:07",
"upload_time_iso_8601": "2024-11-04T10:28:07.607105Z",
"url": "https://files.pythonhosted.org/packages/79/58/5be105830bcc4fc78127ec9956228543094b58370bfe2f0c0fce3083a56f/melusine-3.1.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "5862916d31e2a2404bfb2902ecf8ea21bb1763d71650ba54bb1867f218d6dfe4",
"md5": "c101e2ca9566a917c07443e81abfe9ab",
"sha256": "74d35e4cfda61dceed316a1a3debc90caf2e8c18e59ffda8f4ac11e4270aa5a4"
},
"downloads": -1,
"filename": "melusine-3.1.0.tar.gz",
"has_sig": false,
"md5_digest": "c101e2ca9566a917c07443e81abfe9ab",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 275036,
"upload_time": "2024-11-04T10:28:09",
"upload_time_iso_8601": "2024-11-04T10:28:09.523870Z",
"url": "https://files.pythonhosted.org/packages/58/62/916d31e2a2404bfb2902ecf8ea21bb1763d71650ba54bb1867f218d6dfe4/melusine-3.1.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-11-04 10:28:09",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "melusine"
}
JSON