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app.py

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+import gradio as gr
+import torch 
+import spacy
+import os
+import whisper
+os.system('pip install https://huggingface.co/Armandoliv/es_pipeline/resolve/main/es_pipeline-any-py3-none-any.whl')
+os.system('pip install git+https://github.com/openai/whisper.git')
+
+device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+
+nlp_ner = spacy.load("es_pipeline")
+
+def main_generator(youtube_id:str):
+  YouTubeID = youtube_id # ¿Qué es la enfermedad de Crohn y cómo detectarla?
+  OutputFile = 'test_audio_youtube_.m4a'
+
+  os.system(f"youtube-dl -o {OutputFile} {YouTubeID} --extract-audio --restrict-filenames -f 'bestaudio[ext=m4a]'")
+  model_whisper = whisper.load_model("small")
+  result = model_whisper.transcribe(OutputFile)
+  text = result['text']
+  output_list = []
+  for ent in doc.ents:
+      result_dict = {
+          'entity': ent.label_,
+          'word': ent.text,
+          'start':ent.start_char,
+          'end': ent.end_char
+      }
+      output_list.append(result_dict)
+
+  return {"text": text, "entities": output_list}      
+inputs = [gr.Textbox(lines=1, placeholder="Link of youtube video here...", label="Input")]
+outputs = gr.HighlightedText()
+title="ASR FOR MEDICAL RECORDS"
+description = "This demo uses AI Models to create an AUDIO ANNOTATION FOR MEDICAL RECORDS"
+examples = ['xOZM-1p-jAk']
+
+io = gr.Interface(fn=main_generator, inputs=inputs, outputs=outputs, title=title, description = description, examples = examples,
+
+                  css= """.gr-button-primary { background: -webkit-linear-gradient( 
+                    90deg, #355764 0%, #55a8a1 100% ) !important;     background: #355764;
+                        background: linear-gradient( 
+                    90deg, #355764 0%, #55a8a1 100% ) !important;
+                        background: -moz-linear-gradient( 90deg, #355764 0%, #55a8a1 100% ) !important;
+                        background: -webkit-linear-gradient( 
+                    90deg, #355764 0%, #55a8a1 100% ) !important;
+                    color:white !important}"""
+                  )
+  
+io.launch(debug=True)