Gradio will launch a web-based interface that allows users to speak into their microphone and receive AI-generated responses in real-time and it will then look like this: To run the chatbot, simply run the Python script gradio app.py or python app.py incase gradio app.py doesn't work and it will run on. Finally, we launch the interface using the "launch()" method. We specify that the input type is a microphone audio source and the output type is text. This code creates a Gradio interface object and sets the "fn" parameter to our "transcribe" function. Now that we have our chatbot function defined, we can create a Gradio interface to capture audio input from the user and display the chat history. Finally, we add the AI-generated response to the "messages" list and format the conversation history as a string that can be returned to the user. We then use the "pyttsx3" library to convert the text to speech and play it back to the user. The "AImessage" variable stores the generated response text.The "()" method sends the conversation history to GPT-3 for processing and generates a response based on the previous messages.It then transcribes the audio using OpenAI's anscribe() method and adds the user's message to the "message" list. The "transcribe" function takes an audio file path as input and reads it using the "open()" function.It is initialized with a system message telling the user that they are a teacher. The "messages" list stores the conversation history between the user and the chatbot.Let's go over the key components of this function: It also converts the response to speech using the pyttsx3 library. This function takes an audio input from a microphone, transcribes it using OpenAI's Audio API, sends it to GPT-3 for processing, and returns the AI-generated response as text. launch ()Įnter fullscreen mode Exit fullscreen mode Audio ( source = 'microphone', type = 'filepath' ), outputs = 'text' ) ui. Interface ( fn = transcribe, inputs = gr. getenv ( "OPENAI_API_KEY" ) messages = != 'system' : chat += message + ':' + message + " \n\n " return chat ui = gr. Import gradio as gr import openai import pyttsx3 from dotenv import load_dotenv import os load_dotenv () openai. You can install these libraries using pip, like this:
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