Spaces:
Runtime error
Runtime error
| import gradio as gr | |
| from output_beautify import * | |
| import pandas as pd | |
| from load_data import * | |
| import os | |
| from gingerit import * | |
| #os.system("pip install git+https://github.com/openai/whisper.git") | |
| #import whisper | |
| #model = whisper.load_model("small") | |
| #current_size = 'small' | |
| hf_writer = gr.HuggingFaceDatasetSaver('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', "Pavankalyan/chitti_data") | |
| ''' | |
| def inference(audio): | |
| audio = whisper.load_audio(audio) | |
| audio = whisper.pad_or_trim(audio) | |
| mel = whisper.log_mel_spectrogram(audio).to(model.device) | |
| _, probs = model.detect_language(mel) | |
| options = whisper.DecodingOptions(fp16 = False) | |
| result = whisper.decode(model, mel, options) | |
| return result.text | |
| ''' | |
| def chitti(query): | |
| re_table = search(query) | |
| answers_re_table = [re_table[i][0] for i in range(0,5)] | |
| answer_links = [re_table[i][3] for i in range(0,5)] | |
| sorted_indices = sorted(range(len(answers_re_table)), key=lambda k: len(answers_re_table[k])) | |
| repeated_answers_indices =list() | |
| for i in range(4): | |
| if answers_re_table[sorted_indices[i]] in answers_re_table[sorted_indices[i+1]]: | |
| repeated_answers_indices.append(sorted_indices[i]) | |
| for idx in repeated_answers_indices: | |
| answers_re_table.pop(idx) | |
| answer_links.pop(idx) | |
| #return [res1,answers_re_table[0],res2,answers_re_table[1]] | |
| return [runGinger(answers_re_table[0]),answer_links[0],runGinger(answers_re_table[1]),answer_links[1]] | |
| #return [re_table[0][0],re_table[0][3],re_table[1][0],re_table[1][3]] | |
| demo = gr.Interface( | |
| fn=chitti, | |
| inputs=["text"], | |
| #inputs=[gr.inputs.Audio(source="microphone", type="filepath", label="Record your audio")], | |
| outputs=["text","text","text","text"], | |
| allow_flagging = "manual", | |
| flagging_options = ["0","1","None"], | |
| flagging_callback=hf_writer | |
| ) | |
| demo.launch() | |