feat: added the main app

app.py

@@ -0,0 +1,61 @@
+import gradio as gr
+from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC, AutoTokenizer, BartForConditionalGeneration
+import torch
+import librosa
+
+# Load BART tokenizer and model for summarization
+tokenizer = AutoTokenizer.from_pretrained("facebook/bart-large-cnn")
+summarizer = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
+
+# Load Wav2Vec2 processor and model for transcription
+processor = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-base-960h")
+model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-base-960h")
+
+# Check if CUDA is available
+device = "cuda" if torch.cuda.is_available() else "cpu"
+model.to(device)
+summarizer.to(device)
+
+def transcribe_and_summarize(audioFile):
+    # Load audio as an array
+    audio, sampling_rate = librosa.load(audioFile, sr=16000)  # Ensure it's 16kHz for Wav2Vec2
+    values = processor(audio, sampling_rate=sampling_rate, return_tensors="pt").input_values
+
+    # Move tensors to GPU if available
+    values = values.to(device)
+
+    # Transcription
+    with torch.no_grad():  
+        logits = model(values).logits
+        predictedIDs = torch.argmax(logits, dim=-1)
+        transcription = processor.batch_decode(predictedIDs, skip_special_tokens=True)[0]
+
+    # Summarization
+    inputs = tokenizer(transcription, return_tensors="pt", truncation=True, max_length=1024)
+    inputs = inputs.to(device)  # Move inputs to GPU
+
+    result = summarizer.generate(
+        inputs["input_ids"],
+        min_length=10,
+        max_length=256,
+        no_repeat_ngram_size=2,
+        encoder_no_repeat_ngram_size=2,
+        repetition_penalty=2.0,
+        num_beams=4,
+        early_stopping=True,
+    )
+    summary = tokenizer.decode(result[0], skip_special_tokens=True)
+
+    return transcription, summary
+
+# Gradio interface
+iface = gr.Interface(
+    fn=transcribe_and_summarize,
+    inputs=gr.Audio(type="filepath", label="Upload Audio"),
+    outputs=[gr.Textbox(label="Transcription"), gr.Textbox(label="Summary")], 
+    title="Audio Transcription and Summarization",
+    description="Transcribe and summarize audio using Wav2Vec2 and BART.",
+)
+
+iface.launch()
+