Metadata-Version: 2.1
Name: intellihub
Version: 1.4.0
Summary: Python Client for INTELLIHUB.
Home-page: https://github.com/Spotflock/intellihub-sdk-python
Author: INTELLIHUB
Author-email: connect@spotflock.com
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
License-File: LICENSE

# INTELLIHUB SDK
[![Python 3.8](https://img.shields.io/badge/python-3.8-blue.svg)](https://www.python.org/downloads/release/python-380/)


[![INTELLIHUB Logo](https://intellihub.ai/static/img/logo-high1.png)](https://intellihub.ai)

## About

Our philosophy is to create a Deep Technologies platform with ethical AI for enterprises that offers meaningful insights and actions. 

INTELLIHUB Unified Deep Learning platform can be leveraged to build solutions that are Application-Specific and Industry-Specific where AI opportunity found by using INTELLIHUB SDKs, APIs and Microservices. With best of the breed AI Services from platform pioneers like H2O, Google's TensorFlow, WEKA and a few trusted open-sources models and libraries, we offer custom AI algorithms with co-innovation support. 

## Getting Started

### Pre-requisite

1. INTELLIHUB : INTELLIHUB is collection of open-source docker images, where processing of images, text or structured tabular data is done using state-of-the-art AI models.

Please follow the below link for instructions on [INTELLIHUB Installation](https://docs.intellihub.ai/getting_started/INTELLIHUB_setup.html)

---

**Note**: To use third party AI engines please provide your credentials. Instructions on getting credentials and configuring are provided below.

---


### Installation

**Installing through pip**
```sh
    pip install intellihub
```

**Installing from Source**

a. Clone the repo

```sh
   git clone https://github.com/Spotflock/intellihub-sdk-python.git
``` 
b. Set working directory to intellihub folder

c. Install requirements from requirements.txt file

```sh
    pip install -r requirements.txt
```

Choose any one of the above options for Installation

---

### Usage

```python
import intellihub
client = intellihub.IntellihubClient("YOUR_API_KEY",base_url='http://localhost:8000')

text = "The product is very easy to use and has got a really good life expectancy."

sentiment_analysis_response = client.sentiment_analysis(text)

print(sentiment_analysis_response)
```

Important Parameters:

**1. API key:**
Login to [https://intellihub.ai]() and Go to console and click on Apps and then click on Create App, fill the details and Click submit. The App will be created and an API Key is generated in the App.

**2. base_url:**
The base_url is the url for the machine where base service is installed by _default_ its localhost, so base_url needs to be [http://localhost:8000]()

_Expected Output_
```json
{
  'nltk_vader': {'emotion': 'POSITIVE', 'scores': {'compound': 0.7496, 'negative': 0.0, 'positive': 0.347, 'neutral': 0.653}}
}
```

---
## Services

**1. Machine Learning**

* ML Wrapper - It parse user request parameters

* ML Scikit - This Microservice uses widely used Scikit package for training and evaluating classification, regression, clustering models and other ML related tasks on dataset provided by user.

* ML H2O - This Microservice uses H2O.ai python SDK for training and evaluating classification, regression, clustering models and other ML related tasks on dataset provided by user.

* ML Weka - This Microservice uses WEKA for training and evaluating classification, regression, clustering models and other ML related tasks on dataset provided by user.

**2. NLP**

* This microservice provides features like Sentiment analysis, Name Entity Recognition, Tag Extraction using widely used ``Spacy`` and `NLTK` package. It also provide support for various AI engines like Azure & IBM.

**3. Computer Vision**

* CV Wrapper - This microservice receives images provided by user and route to right service based on the feature requested by them.

* Image Classification - This microservice classify images into various classes using pretrained model and also using supported AI Engines.

* Object Detection - This microservice detect objects in Images provided by user using pretrained model and using supported AI Engines.


## Reference

For more detail on INTELLIHUB features & usage please refer [INTELLIHUB SDK Client Documentation](https://docs.intellihub.ai)

## License

The content of this project itself is licensed under [GNU LGPL, Version 3 (LGPL-3)](https://github.com/Spotflock/intellihub-sdk-python/blob/master/LICENSE)

## Contact

Spotflock Email-ID - connect@spotflock.com


