=========================
Boosting CV-LLM sentiment
=========================


.. image:: https://img.shields.io/pypi/v/boosting_cv_llm_sentiment.svg
        :target: https://pypi.python.org/pypi/boosting_cv_llm_sentiment

.. image:: https://img.shields.io/travis/ToroData/boosting_cv_llm_sentiment.svg
        :target: https://travis-ci.com/ToroData/boosting_cv_llm_sentiment

.. image:: https://readthedocs.org/projects/boosting-cv-llm-sentiment/badge/?version=latest
        :target: https://boosting-cv-llm-sentiment.readthedocs.io/en/latest/?version=latest
        :alt: Documentation Status




Boosting CV-LLM Sentiment is a Python library that fuses computer vision and natural language processing capabilities to enhance human-computer interactions with language model systems. Leveraging OpenCV, the framework detects emotions and facial expressions in real-time, tagging the identified sentiments. These sentiment tags are then fed as metadata into a Large Language Model (LLM) to inform and shape text generation, enabling conversational empathy adaptability. This innovative approach enhances LLMs' ability to produce more meaningful and context-aware responses, fostering more natural and human-like interactions across various applications, from virtual assistants to customer feedback analysis.


* Free software: Apache Software License
* Documentation: https://boosting-cv-llm-sentiment.readthedocs.io.


Features
--------

- Real-time facial emotion detection using OpenCV.
- Integration with Large Language Models for context-aware text generation.
- Enhances conversational AI with a layer of emotional intelligence.
- Easy to integrate into existing Python projects with language model requirements.

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

To install Boosting CV-LLM Sentiment, run this command in your terminal:

.. code-block:: bash

    pip install boosting_cv_llm_sentiment

This is the preferred method to install Boosting CV-LLM Sentiment, as it will always install the most recent stable release.

Setting up the OpenAI API Key
-----------------------------

1. **Find Your API Key**: First, locate your API key from your OpenAI account under API settings.

2. **Configure the Key in Your Environment**:

   - **On Unix/Linux/macOS**:
     Open your terminal and run the following command, replacing ``YOUR_API_KEY`` with your actual OpenAI API key:

     .. code-block:: bash

        export OPENAI_API_KEY="YOUR_API_KEY"

     To make this change permanent, you can add the command to your ``~/.bashrc``, ``~/.zshrc``, or the configuration file of your shell.

   - **On Windows**:
     Open Command Prompt as an administrator and run:

     .. code-block:: cmd

        setx OPENAI_API_KEY "YOUR_API_KEY"

     Alternatively, you can set the environment variable through the System Properties. Search for "Edit the system environment variables" in the Start menu, click on "Environment Variables", and then add a new variable under "User variables" with the name ``OPENAI_API_KEY`` and your actual key as the value.

Verifying the Configuration
---------------------------

You can verify that your API key is set up correctly by running the following command in your terminal or Command Prompt:

- **Unix/Linux/macOS**:

  .. code-block:: bash

     echo $OPENAI_API_KEY

- **Windows**:

  .. code-block:: cmd

     echo %OPENAI_API_KEY%

If the command prints your API key, then you're all set.

Please ensure you keep your API key secure and do not share it publicly.

Usage
-----

After installation, you can start using Boosting CV-LLM Sentiment by importing it and initializing the main classes:

.. code-block:: python

    from boosting_cv_llm_sentiment.emoboostllm import EmoBoostLLM

    # Initialize and run the application
    app = EmoBoostLLM(webcam_index=0)
    app.run()

Refer to the documentation for more detailed usage instructions.


Credits
-------

This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
