This project involves building a bot that predicts the likelihood of a wildfire based on flame sensors, temperature, and humidity data using OpenAI's GPT-3 architecture. The bot takes in data as input and generates a prediction based on the input. The prediction generated is one of three categories: High, Medium, or Low, and the bot provides a recommendation for action based on the prediction.
To use this project, you need to have Python 3 installed on your system. You also need an OpenAI API key. You can get an API key by signing up for OpenAI at https://beta.openai.com/signup/.
Clone the repository to your local machine using the following command:
git clone https://github.com/<username>/WildFire-Predictor-Using-GPT-3.git
- Enter the location for which you want to predict the likelihood of a wildfire.
location_var = input("Enter the location of the wildfire prediction: ")
- Call the
predict_wildfire()function by providing the flame sensors, temperature, humidity, and location data.
percentage, simple_text, text_output = predict_wildfire(0.75, 90, 50, location_var)
- The function will return three values:
- The percentage likelihood of a wildfire.
- The simple text prediction, which is one of High, Medium, or Low.
- The detailed prediction generated by the GPT-3 architecture.
- Print the output values.
if percentage is not None:
print(f"Percentage likelihood: {percentage}%")
print(f"Simple Text: {simple_text}")
print(f"AI Prediction: {text_output}")
Contributions are always welcome! If you have any ideas, suggestions, or improvements, please feel free to raise an issue or submit a pull request. I hope to make this project much more advanced.
This project is licensed under the MIT License. See the LICENSE file for details.
- OpenAI for providing the GPT-3 architecture and API.
- The developers of the openai library for creating an easy-to-use Python interface for the OpenAI API.