.. image:: _static/emotion_detective.png
   :alt: Emotion Detective Logo
   :width: 500
   :align: center

Overview
--------

This NLP project provides functions to analyze emotions in video or audio files. It offers a comprehensive set of tools to detect and analyze emotions at a sentence level, producing valuable insights into the emotional content of multimedia sources. It includes a package with all necessary functions, two pipelines -- one for training the NLP model and one for inference, and Sphinx documentation.

.. toctree::
   :maxdepth: 3
   :caption: Contents:

   data_preparation_inference
   data_preparation_training
   logger
   models
   pipelines
   

Installation
------------

To install the package and its dependencies, use the following pip command:

.. code-block:: bash

   pip install emotion_detective

Dependencies
------------

The emotion_detective package requires the following dependencies:
- python ^3.9
- pandas ^2.0.0
- nltk:
- Version ^3.6.3 for win32 platforms
- Version 3.8.1 for linux platforms
- regex 2024.5.10
- moviepy 1.0.3
- pydub 0.25.1
- imageio 2.34.1
- imageio-ffmpeg 0.4.9
- scikit-learn ^1.0
- transformers ^4.30.0
- gensim ^4.3.2
- torch ^2.1.2
- numpy 1.23.2
- torchvision ^0.16.2
- setuptools-rust 1.9.0
- scipy 1.12
- pyspellchecker ^0.8.1
- accelerate >=0.20.1
- fastapi >=0.111.0
- uvicorn ^0.22.0
- typer >=0.12.3
- tokenizers:
- Version 0.19 for win32 platforms
- Version 0.11.1 for linux platforms
- safetensors 0.4.2
- wordninja ^2.0.0
- textblob ^0.18.0.post0
- azureml-core ^1.56.0
- azureml-fsspec ^1.3.1
- sphinx-rtd-theme ^2.0.0
- h5py ^3.11.0
- matplotlib ^3.9.0
- mlflow ^2.13.2
- colorama ^0.4.6
- datasets ^2.20.0
- azureml-mlflow ^1.56.0
- azure-ai-ml ^1.17.0


Additional Dependencies
------------------------

The package also requires to have the following dependencies installed on your system. To install the additional dependencies, refer to the installation documentation linked below:

   - `Rust <https://www.rust-lang.org/tools/install>`_
   - `Cuda Toolkit <https://developer.nvidia.com/cuda-downloads>`_


Using the API
-------------

The Emotion Detective package also offers an API for the training and inference pipeline. 

To use the API, create a simple POST request containing the arguments for the specific pipeline.

Here is an example using the python library 'requests':

.. code-block:: python
   
   import requests
   import json

   url = ""194.171.191.226:3950/train"

   payload = json.dumps({
   "train_data_path": "./data/CSV/5000_sampled_emotions_neutral.csv",
   "test_data_path": "./data/CSV/val_set_5000.csv",
   "text_column": "text",
   "emotion_column": "label",
   "num_epochs": 1,
   "model_type": "rnn",
   "model_dir": "./models",
   "model_name": "rnn_test_api",
   "learning_rate": 0.001,
   "train_batch_size": 4,
   "eval_batch_size": 8,
   "cloud_logging": False
   })
   headers = {
   'Content-Type': 'application/json'
   }

   response = requests.request("POST", url, headers=headers, data=payload)

   print(response.text)

.. code-block:: python

   import requests
   import json
   
   url = "194.171.191.226:3950/inference"
   
   payload = json.dumps({
     "input_media_path": "./data/EmotionsforKids.mp3",
     "model_path": "./models/rnn.pth",
     "model_type": "rnn",
     "emotion_mapping_path": "./models/mapping_emotions_rnn.json"
   })
   headers = {
     'Content-Type': 'application/json'
   }
   
   response = requests.request("POST", url, headers=headers, data=payload)
   
   print(response.text)


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`
* :ref:`search`