I got around to getting uploaded a current video of the much improved offline/online voice assistance.  The arm is not in it's final resting place it is just clamped down for testing.  The robot is no longer hearing itself (huge milestone), the microphone does randomly hear a huh or ah in the background noise. (may end up reducing sensitivity).

So, because of these improvements I can leave the voice assistance on for much longer, possibly no need to close it/restart. Need to have it run when the robot first powers on however, as I'm still manually running the program from the terminal.

Major refactoring of the code to including:

voice_assist.py

• -Made the time function more natural sounding and state am/pm
• Refactored code, reduce main down and add dictionary for the offline phrases
• Lots of additional descriptions made for easier understanding 
• Turned weather function into a class, it was getting quite large

Created a whole new weather class as that function was getting very long

weather_service.py

This class retrieves the current weather report for a specified city using the OpenWeather API. It constructs
and sends a request to the API with the city name, desired units (imperial or metric), and the API key. After
receiving the response, the function parses the JSON data to extract key weather details such as temperature,
humidity, and weather description.

Based on the weather data, it formulates a user-friendly weather report which includes temperature, feels-like
temperature, humidity, and a general description of the weather conditions. Additionally, the function provides
attire recommendations based on the current weather (e.g., suggesting a raincoat for rainy weather, or warm
clothing for cold temperatures). This function enhances the robot's interactive capabilities by providing useful
and practical information to the user in a conversational manner.

reading_module.py

It can now read fine print from a book held about 12" away. It does this by scaling the image up after boxing text. 

- Changed to Python text-to-speech.
- Heavily modified the pipeline to scale the image and box the text to help OCR be faster and more accurate, it also arranges the bounding boxes from left to right and top to bottom, so that it reads in the correct order.
- You need to hold a book/text ~12 inches from the camera, this may be improved by upping the scale factor but it is working well at that distance for now.
- More optimization is needed in the pipeline...