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Overview

Grupo de Anda projects use various Python libraries for AI, audio processing, GUI development, and more. This guide covers installing and managing these dependencies.
Ubuntu Users: Always activate your virtual environment before installing dependencies. See the Virtual Environments guide first.

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Required Dependencies

The Grupo de Anda projects use the following Python libraries: 
pip install customtkinter keyboard gpt4all requests llama-cpp-python gTTS pygame torch librosa numpy sounddevice pydub

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Library Overview

LibraryPurpose
customtkinterModern GUI framework for Python applications
keyboardKeyboard event handling and hotkeys
gpt4allLocal AI model integration
requestsHTTP requests for API calls
llama-cpp-pythonLlama model inference
gTTSGoogle Text-to-Speech
pygameAudio playback and game development
torchPyTorch deep learning framework
librosaAudio analysis and processing
numpyNumerical computing
sounddeviceAudio recording and playback
pydubAudio file manipulation

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Installation Steps

1

Activate Virtual Environment

Critical: Always activate your virtual environment first, especially on Ubuntu.
Windows:
.venv\Scripts\Activate.ps1
Linux/macOS:
source .venv/bin/activate
You should see (.venv) in your terminal prompt.
2

Update pip

Ensure you have the latest version of pip:
pip install --upgrade pip
3

Install All Dependencies

Install all required libraries at once:
pip install customtkinter keyboard gpt4all requests llama-cpp-python gTTS pygame torch librosa numpy sounddevice pydub
This may take several minutes as some packages (especially PyTorch) are quite large.
4

Verify Installation

Test that the packages installed correctly:
pip list
You should see all the installed packages listed.

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Installing Individual Packages

If you prefer to install packages one at a time or only need specific libraries:

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GUI Development

pip install customtkinter

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AI and Machine Learning

pip install gpt4all llama-cpp-python torch

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Audio Processing

pip install gTTS pygame librosa sounddevice pydub

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Utilities

pip install keyboard requests numpy

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API Configuration

Some features require API keys or external services:
If the code you want to run uses AI models that require an API, you’ll need to obtain the appropriate API key.

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Google Gemini API

  • Endpoint: https://generativelanguage.googleapis.com/
  • Use: AI model integration
  • Get your API key from Google AI Studio

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Google Text-to-Speech API

  • Endpoint: https://translate.google.com/translate_tts
  • Use: Text-to-speech conversion
  • Used by the gTTS library (no API key needed for basic usage)
API keys are typically configured in environment variables or configuration files:Environment Variable:
export GEMINI_API_KEY="your-api-key-here"
Configuration File: Create a .env file or config file as specified by the specific project.
Never commit API keys to version control. Add .env to your .gitignore file.

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Dependency Management

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Creating requirements.txt

To save your current dependencies: 
pip freeze > requirements.txt
This creates a file listing all installed packages and their versions.

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Installing from requirements.txt

If the project includes a requirements.txt file: 
pip install -r requirements.txt
This installs all dependencies with the exact versions specified.

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Platform-Specific Notes

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Ubuntu/Linux

Always use virtual environments on Ubuntu. Never use sudo pip to install packages.
Some packages may require system dependencies: 
# For audio libraries
sudo apt install portaudio19-dev python3-pyaudio

# For general development
sudo apt install python3-dev build-essential

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Windows

  • Most packages install without issues
  • PyTorch may require Visual C++ Redistributable
  • Some audio libraries may need additional setup

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macOS

  • Install Homebrew first for system dependencies
  • May need Xcode Command Line Tools: 
    xcode-select --install

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PyTorch Installation

PyTorch is a large package with different installation options:

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CPU-Only (Smaller, Faster Download)

pip install torch --index-url https://download.pytorch.org/whl/cpu

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GPU Support (CUDA)

For NVIDIA GPU acceleration: 
pip install torch --index-url https://download.pytorch.org/whl/cu118
The basic pip install torch command installs the CPU version. For GPU training and inference, use the CUDA version appropriate for your system.

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Updating Dependencies

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Update a Single Package

pip install --upgrade package-name

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Update All Packages

pip list --outdated
pip install --upgrade package-name1 package-name2
Be cautious when updating packages as new versions may introduce breaking changes. Test thoroughly after updates.

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Running the Code

After installing dependencies:
1

Ensure Virtual Environment is Active

Check for (.venv) in your terminal prompt.
2

Navigate to Project Directory

cd /path/to/your/project
3

Run the Program

In Terminal:
python your_script.py
In VS Code: Press F5 to execute in terminal or launch the visual interface.
Depending on the file, it will either run in the terminal or open a graphical user interface.

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Troubleshooting

The package isn’t installed. Install it:
pip install package-name
Make sure your virtual environment is activated.
Ubuntu: Never use sudo pip. Use a virtual environment instead.Windows: Run your terminal as administrator, or use virtual environments (recommended).
PyTorch is a large package (several GB). The download takes time depending on your internet connection.For a smaller install, use CPU-only:
pip install torch --index-url https://download.pytorch.org/whl/cpu
Try creating a fresh virtual environment:
# Deactivate current environment
deactivate

# Remove old environment
rm -rf .venv

# Create new environment
python3 -m venv .venv
source .venv/bin/activate

# Reinstall packages
pip install customtkinter keyboard gpt4all ...
Linux: Install system audio dependencies:
sudo apt install portaudio19-dev python3-pyaudio ffmpeg
Windows: Install Visual C++ Redistributable from Microsoft.macOS: Install portaudio via Homebrew:
brew install portaudio
These packages require compilation. Install build tools:Ubuntu:
sudo apt install build-essential cmake
Windows: Install Visual Studio Build ToolsmacOS: Install Xcode Command Line Tools:
xcode-select --install

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Next Steps

With dependencies installed, you can:
  1. Set up Arduino hardware (for hardware projects)
  2. Start running the Grupo de Anda projects
  3. Explore the AI model training in the ai creator folder

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Additional Resources

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AI Model Training

In the ai creator folder, you’ll find AI model training code. You can:
  • Use existing training data
  • Add your own data for training
  • Configure to use CPU, GPU, or both for improved performance

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Supported AI Commands

The trained models support these commands:
  • search=[tema] - AI searches the internet for a topic
  • clma=[lugar] - AI provides climate data for a specific region
  • ubicacion=[] - Provides location data to the AI

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Intent Detection

The intent detection model recognizes:
  • investigar (research)
  • clima (weather/climate)
  • conversacion_ai (AI conversation)

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