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| # Import the required libraries | |
| import gradio as gr | |
| import openai | |
| from gtts import gTTS | |
| from pydub import AudioSegment | |
| import os | |
| messages = [{"role": "system", "content": 'You are the Anishinaabe hero Nanaboozhoo. Not only do you answer with profound wisdom but you will continue the conversation by answering like this, Boozhoo: (your answer)'}] | |
| full_transcript = [] | |
| openai.api_key = "" | |
| audio_file = 'response.mp3' | |
| def set_api(my_key): | |
| openai.api_key = my_key | |
| def create_image(response): | |
| # Send text to be summarized | |
| dalle_prompt = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=[ | |
| {"role": "user", "content": f'Summarize this text "{response["choices"][0]["message"]["content"]}" into a short and concise Dall-E 2 prompt starting with "A Professional photograph of an Anishinaabe person saying :(summarization)".'} | |
| ] | |
| ) | |
| # Use summary as prompt for pic | |
| dalle_summary = openai.Image.create( | |
| prompt = dalle_prompt["choices"][0]["message"]["content"], | |
| size="512x512" | |
| ) | |
| image_url = dalle_summary['data'][0]['url'] | |
| return image_url | |
| def speak(system_message): | |
| global audio_file | |
| content = system_message['content'] | |
| tts = gTTS(content, lang='en', slow=False) | |
| tts.save("response.mp3") | |
| return "response.mp3" | |
| def transcribe(gradio_input, api_key): | |
| global messages | |
| global full_transcript | |
| global audio_file | |
| set_api(api_key) | |
| #Transcribe audio | |
| input_audio = AudioSegment.from_file(gradio_input) | |
| input_audio.export("input_audio.wav", format="wav") | |
| with open("input_audio.wav", "rb") as audio_file: | |
| print(f"Audio file format: {os.path.splitext(audio_file.name)[1]}\n") | |
| transcript = openai.Audio.transcribe("whisper-1", audio_file) | |
| #Append content to messages | |
| full_transcript.append(transcript["text"]) | |
| messages.append({"role": "user", "content": transcript["text"]}) | |
| #Send the latest set of messages to OpenAI to get a response | |
| response = openai.ChatCompletion.create( | |
| model="gpt-3.5-turbo", | |
| messages=messages | |
| ) | |
| # Extract the latest system message from the response and add it as a new message to the messages list | |
| system_message = response["choices"][0]["message"] | |
| messages.append(system_message) | |
| pic_url = create_image(response) | |
| speech = speak(system_message) | |
| # Combine all messages in the messages list to create a chat transcript | |
| chat_transcript = "" | |
| for message in messages: | |
| if message['role'] != 'system': | |
| chat_transcript += message['role'] + ": " + message['content'] + "\n\n" | |
| return speech, chat_transcript, pic_url | |
| MY_INFO = '\nSupport me at my [Linktree](https://linktr.ee/Nbiish).' | |
| API_INFO = 'Get your api key at [platform.openai.com/account/api-keys](https://platform.openai.com/account/api-keys)' | |
| # Create a Gradio interface | |
| demo = gr.Interface( | |
| fn=transcribe, | |
| inputs=[ | |
| gr.Audio(source="microphone", type="filepath", show_label=False), | |
| gr.Textbox( | |
| label="OpenAI API Key", | |
| lines=1, | |
| placeholder="Enter your OpenAI API key", | |
| default=None, | |
| type="password", | |
| fn=set_api, | |
| ), | |
| ], | |
| outputs=[ | |
| gr.Audio(show_label=False), | |
| gr.Textbox(label="Transcript:"), | |
| gr.Image(show_label=False), | |
| ], | |
| title="Boozhoo Bot", | |
| description=f""" | |
| Anishinaabe Chatbot | |
| Applies OpenAI's Whisper to transcribe audio input. | |
| GPT-3.5 Turbo to generate a response. | |
| Dall-E 2.0 to generate an image. | |
| gTTS to generate audio response. | |
| 1) Record to get started | |
| 2) Press X near recording to keep going | |
| 3) Refresh page to restart | |
| {MY_INFO} | |
| {API_INFO} | |
| """, | |
| ) | |
| if __name__ == "__main__": | |
| demo.queue().launch() |