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chatbot

in this project, we not only get the weather and location API, we call the openai API so that we can ask whenever we want to get a chatbot. Also we add to the voice control.

Setting Up the Environment To begin building our voice-responsive OpenAI chatbot, it's essential to set up the right development environment. This involves installing necessary libraries and configuring API access. Here's how you can get started:

  1. Install Required Libraries Your chatbot relies on several Python libraries, as listed in the requirements.txt file. These libraries include Streamlit for the web interface, OpenAI for accessing speech processing services, and others for specific functionalities like audio recording. Install them by running the following command in your project directory: pip install -r requirements.txt Here's a quick breakdown of the key libraries:

streamlit: For building and running the web app.

openai: To access OpenAI's API for speech-to-text and text-to-speech services.

audio_recorder_streamlit: To record audio within the Streamlit app.

streamlit-float: Provides floating elements in the Streamlit interface.

  1. Set Up the .env File Sensitive information such as your OpenAI API key should be stored in a .env file. This approach keeps your credentials secure. Create a .env file in the root of your project and include your OpenAI API key like this:

#OPENAI_API_KEY='your_openai_api_key_here'

The audio_recorder() function captures audio input from the user. Once the audio is recorded, it's processed to extract the spoken text:

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