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| import gradio as gr | |
| import openai | |
| import os | |
| from dotenv import load_dotenv | |
| from pydub import AudioSegment | |
| load_dotenv() | |
| #accessing openapi Key | |
| openai.api_key = os.getenv("OPENAI_API_KEY") | |
| audio_messages = [{"role": "system", "content": 'You are an AI assistant expert. Respond to all input in precise, crisp and easy to understand language.'}] | |
| text_messages = [{"role": "system", "content": 'You are an AI assistant expert. Respond to all input in precise, crisp and easy to understand language.'}] | |
| global user_text_input, text_output, user_audio_input, audio_output | |
| """ | |
| It seems like the gr.Audio source is not generating a WAV file, which is required for the openai.Audio.transcribe() method to work. | |
| To convert the audio file to WAV format, i have used a library like Pydub. | |
| """ | |
| def audio_transcribe(audio): | |
| global audio_messages | |
| audio_message = audio_messages | |
| #audio processing to whisper API. | |
| audio_file = AudioSegment.from_file(audio) | |
| audio_file.export("temp.wav", format="wav") | |
| final_audio_file = open("temp.wav", "rb") | |
| transcript = openai.Audio.transcribe("whisper-1", final_audio_file) | |
| os.remove("temp.wav") | |
| #transcripted input to chatGPT API for chatCompletion | |
| audio_message.append({"role": "user", "content": transcript["text"]}) # type: ignore | |
| response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=audio_message) | |
| system_message = response["choices"][0]["message"] # type: ignore | |
| audio_message.append(system_message) | |
| chat_transcript = "" | |
| for message in audio_message: | |
| if message['role'] != 'system': | |
| chat_transcript += message['role'] + ": " + message['content'] + "\n\n" | |
| return chat_transcript | |
| def text_transcribe(name): | |
| global text_messages | |
| text_message = text_messages | |
| user_text_input.update("") | |
| #transcripted input to chatGPT API | |
| text_message.append({"role": "user", "content": name}) # type: ignore | |
| response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=text_message) | |
| system_message = response["choices"][0]["message"] # type: ignore | |
| text_message.append(system_message) | |
| chat_transcript = "" | |
| for message in text_message: | |
| if message['role'] != 'system': | |
| chat_transcript += message['role'] + ": " + message['content'] + "\n\n" | |
| return chat_transcript | |
| title = """<h1 align="center">Your Chat-GPT AI Assistant at your Service!! 😎 </h1>""" | |
| with gr.Blocks(theme=gr.themes.Soft()) as demo: | |
| gr.HTML(title) | |
| with gr.Tab("Audio Input"): | |
| with gr.Row(): | |
| user_audio_input = (gr.Audio(source="microphone", type="filepath", label="Speak Here")) | |
| audio_input = user_audio_input | |
| audio_output = gr.Textbox(label="AI Response", lines=20, placeholder="AI Response will be displayed here...") | |
| with gr.Row(): | |
| audio_submit_button = gr.Button("Submit") | |
| with gr.Tab("Text Input"): | |
| with gr.Row(): | |
| user_text_input = (gr.Textbox(label="Type Here", lines=20, placeholder="Type your message here...")) | |
| text_input = user_text_input | |
| text_output = gr.Textbox(label="AI Response", lines=20, placeholder="AI Response will be displayed here...") | |
| with gr.Row(): | |
| text_submit_button = gr.Button("Submit") | |
| audio_submit_button.click(fn=audio_transcribe, inputs=audio_input, outputs=audio_output) | |
| text_submit_button.click(fn=text_transcribe, inputs=text_input, outputs=text_output) | |
| gr.Markdown("<center> Made with ❤️ by Tanish Gupta. Credits to 🤗 Spaces for Hosting this App </center>") | |
| demo.launch(share=True) | |