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| import gradio as gr | |
| import openai | |
| import requests | |
| from gtts import gTTS | |
| from moviepy.editor import * | |
| from io import BytesIO | |
| from tempfile import NamedTemporaryFile | |
| from base64 import b64encode | |
| from pydub import AudioSegment | |
| input_gif_path = "https://i.imgur.com/ork8hoP.gif" | |
| #Lucy https://i.imgur.com/RLMkj1P.gif | |
| #Lisa "https://i.imgur.com/ork8hoP.gif" | |
| def get_text_response(prompt,openAI_key): | |
| openai.api_key = openAI_key | |
| completions = openai.Completion.create(engine="text-davinci-003",prompt=prompt,max_tokens=600,n=1,stop=None,temperature=0.5,) | |
| message = completions.choices[0].text.strip() | |
| return message | |
| def text_to_speech(text, output_file): | |
| tts = gTTS(text=text, lang='en', tld='co.uk') | |
| tts.save(output_file) | |
| def chat_and_animate(output_file, user_prompt,openAI_key): | |
| # Get audio response from OpenAI API | |
| text_response = get_text_response(user_prompt,openAI_key) | |
| text_to_speech(text_response, "response.mp3") | |
| # Get audio duration in milliseconds | |
| audio = AudioSegment.from_file("response.mp3") | |
| audio_duration = len(audio) | |
| # Download the input GIF | |
| response = requests.get(input_gif_path) | |
| # Save the input GIF to a temporary file | |
| with NamedTemporaryFile(delete=False, suffix=".gif") as temp_gif: | |
| temp_gif.write(response.content) | |
| # Load the input GIF | |
| gif_clip = VideoFileClip(temp_gif.name) | |
| # Calculate the number of loops required to match the audio duration | |
| num_loops = audio_duration / (gif_clip.duration * 1000) | |
| # Duplicate the animated GIF to match the audio duration | |
| final_gif = gif_clip.loop(n=int(num_loops)) | |
| # Set the audio to the animated GIF | |
| final_video = final_gif.set_audio(AudioFileClip("response.mp3")) | |
| # Save the final video | |
| final_video.write_videofile(output_file, codec="libx264", audio_codec="aac") | |
| # Clean up the temporary GIF file | |
| os.unlink(temp_gif.name) | |
| # Set up the input and output components for the Gradio app | |
| user_prompt = gr.inputs.Textbox(label="Ask me anything", default="Welcome") | |
| output_video = gr.outputs.Video() | |
| def chatbot(user_prompt,openAI_key): | |
| if user_prompt.strip() == '': | |
| return '[ERROR]: Blank input not allowed.' | |
| if openAI_key.strip() == '': | |
| return '[ERROR]: Please enter your Open AI Key. Get your key here : https://platform.openai.com/account/api-keys' | |
| if user_prompt.lower() == "welcome": | |
| output_file = "preloaded.mp4" | |
| else: | |
| output_file = "output.mp4" | |
| chat_and_animate(output_file, user_prompt,openAI_key) | |
| return output_file | |
| with gr.Blocks() as demo: | |
| gr.Markdown(f'<center><h1>Ask Lisa !</h1></center>') | |
| gr.Markdown(f'<center><p>Ask Lisa is an AI powered chatbot experiment that provides users with animated video responses to their questions. Ask anything, from general knowledge, advice, to fun facts and play the video responses.</p></center>') | |
| gr.Markdown(f'<center><p>Powered by <a href="https://www.bhaskartripathi.com">www.bhaskartripathi.com</a></p></center>') | |
| gr.Markdown(f'<span><img src="https://i.imgur.com/ork8hoP.gif" width="100" height="100"></span>') | |
| with gr.Row(): | |
| with gr.Group(): | |
| gr.Markdown(f'<p style="text-align:center">Get your Open AI API key <a href="https://platform.openai.com/account/api-keys">here</a></p>') | |
| openAI_key=gr.Textbox(label='Enter your OpenAI API key here') | |
| question = gr.Textbox(label='Ask me anything, and I will give you an animated response! Enteryour question here') | |
| btn = gr.Button(value='Talk') | |
| btn.style(full_width=True) | |
| with gr.Group(): | |
| output_video = gr.outputs.Video() | |
| btn.click(chatbot, inputs=[question,openAI_key], outputs=[output_video]) | |
| # openai.api_key = os.getenv('Your_Key_Here') | |
| demo.launch() | |