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| import json | |
| import gradio as gr | |
| import requests | |
| import os | |
| def is_file_larger_than_30mb(file_path): | |
| try: | |
| file_size = os.path.getsize(file_path) | |
| return file_size > (30 * 1024 * 1024) | |
| except FileNotFoundError: | |
| return False | |
| except PermissionError: | |
| return False | |
| except Exception as e: | |
| return False | |
| def upload_audio(audio_path): | |
| try: | |
| size = is_file_larger_than_30mb(audio_path) | |
| if size == True: | |
| return 'size' | |
| with open(audio_path, 'rb') as audio_file: | |
| response = requests.post('http://sls-titan-6.csail.mit.edu:8080/upload/', files={'audio_file': audio_file}) | |
| if response.status_code == 200: | |
| return response.json()["path"] | |
| except: | |
| return None | |
| def upload_audio_13b(audio_path): | |
| try: | |
| size = is_file_larger_than_30mb(audio_path) | |
| if size == True: | |
| return 'size' | |
| with open(audio_path, 'rb') as audio_file: | |
| response = requests.post('http://sls-titan-5.csail.mit.edu:8080/upload/', files={'audio_file': audio_file}) | |
| if response.status_code == 200: | |
| return response.json()["path"] | |
| except: | |
| return None | |
| def predict(audio_path, question, model): | |
| if model == '7B (Default)': | |
| upload_statues = upload_audio(audio_path) | |
| if upload_statues == None: | |
| return 'Please upload an audio file.' | |
| if upload_statues == 'size': | |
| return 'This demo does not support audio file size larger than 30MB.' | |
| if question == '': | |
| return 'Please ask a question.' | |
| print(audio_path, question) | |
| response = requests.put('http://sls-titan-6.csail.mit.edu:8080/items/0', json={ | |
| 'audio_path': audio_path, 'question': question | |
| }) | |
| answer_7b = json.loads(response.content) | |
| ans_str_7b = answer_7b['output'] | |
| return ans_str_7b | |
| if model == '13B (Beta)': | |
| upload_statues = upload_audio_13b(audio_path) | |
| if upload_statues == None: | |
| return 'Please upload an audio file.' | |
| if upload_statues == 'size': | |
| return 'This demo does not support audio file size larger than 30MB.' | |
| if question == '': | |
| return 'Please ask a question.' | |
| print(audio_path, question) | |
| response = requests.put('http://sls-titan-5.csail.mit.edu:8080/items/0', json={ | |
| 'audio_path': audio_path, 'question': question | |
| }) | |
| answer_13b = json.loads(response.content) | |
| ans_str_13b = answer_13b['output'] | |
| return ans_str_13b | |
| if __name__ == '__main__': | |
| link = "https://github.com/YuanGongND/ltu" | |
| text = "[Github]" | |
| paper_link = "https://arxiv.org/pdf/2309.14405.pdf" | |
| paper_text = "[ASRU Paper]" | |
| sample_audio_link = "https://drive.google.com/drive/folders/17yeBevX0LIS1ugt0DZDOoJolwxvncMja?usp=sharing" | |
| sample_audio_text = "[sample audios from AudioSet evaluation set]" | |
| demo = gr.Interface(fn=predict, | |
| inputs=[gr.Audio(type="filepath"), | |
| gr.Textbox(value='What can be inferred from the spoken text and sounds? Why?', label='Edit the textbox to ask your own questions!'), | |
| gr.Radio(["7B (Default)", "13B (Beta)"], value='7B (Default)', label="LLM size", info="All experiments in the ASRU paper are 7B LLM.")], | |
| outputs=[gr.Textbox(label="LTU-AS-Output")], | |
| cache_examples=True, | |
| title="Demo of LTU-AS", | |
| description="LTU-AS an improved version of LTU. LTU-AS is stronger in spoken text understanding and music understanding. " + f"<a href='{paper_link}'>{paper_text}</a> <br>" + | |
| "LTU-AS is authored by Yuan Gong, Alexander H. Liu, Hongyin Luo, Leonid Karlinsky, and James Glass (MIT & MIT-IBM Watson AI Lab). <br>" + | |
| "Input should be wav file sampled at 16kHz. This demo trims input audio to 10 seconds. <br>" + | |
| "Code of LTU-AS will be available soon at " + f"<a href='{link}'>{text}</a> <br>" + | |
| "**Research Demo, Not for Commercial Use (Due to license of LLaMA).**") | |
| demo.launch(debug=False, share=False) |