A Python library enhancing conversational AI with emotion detection, using computer vision and NLP. It tags emotions from facial expressions in real-time and integrates them with a Large Language Model for empathetic responses.
Reason this release was yanked:
Can only be used with environment variable
Project description
Boosting CV-LLM sentiment
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:
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
Find Your API Key: First, locate your API key from your OpenAI account under API settings.
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:
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:
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:
echo $OPENAI_API_KEY
Windows:
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:
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.
History
0.1.0 (2024-03-24)
First release on PyPI.
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