UPDATES

codePython/nlp1.py

@@ -0,0 +1,69 @@
+import torch
+from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor, pipeline
+from datasets import load_dataset
+import speech_recognition as sr
+import numpy as np
+import sys
+import json
+
+# Access command-line arguments
+arguments = sys.argv[1:]
+
+# Print the arguments passed from Java
+for arg in arguments:
+    print("Argument:", arg)
+
+# device = "cuda:0" if torch.cuda.is_available() else "cpu"
+device = "cpu"
+torch_dtype = torch.float16 if torch.cuda.is_available() else torch.float32
+
+model_id = "openai/whisper-large-v3"
+
+model = AutoModelForSpeechSeq2Seq.from_pretrained(
+    model_id, torch_dtype=torch_dtype, low_cpu_mem_usage=True, use_safetensors=True
+)
+model.to(device)
+
+processor = AutoProcessor.from_pretrained(model_id)
+
+pipe = pipeline(
+    "automatic-speech-recognition",
+    model=model,
+    tokenizer=processor.tokenizer,
+    feature_extractor=processor.feature_extractor,
+    max_new_tokens=128,
+    chunk_length_s=30,
+    batch_size=16,
+    return_timestamps=True,
+    torch_dtype=torch_dtype,
+    device=device,
+)
+
+
+resultTranscription = pipe("/home/anantha/PCF/AIML/SpeechToText/HIN_M_AbhishekS.mp3", generate_kwargs={"language": None})
+print("")
+print(resultTranscription["text"])
+
+
+resultTranslation = pipe("/home/anantha/PCF/AIML/SpeechToText/HIN_M_AbhishekS.mp3", generate_kwargs={"task": "translate"})
+print("")
+print(resultTranslation["text"])
+
+
+classifier = pipeline("sentiment-analysis",model="distilbert/distilbert-base-uncased-finetuned-sst-2-english",revision ="af0f99b")
+resultClassifier = classifier(resultTranslation["text"])
+print("")
+print(resultClassifier)
+
+# Create a Python dictionary
+data = {
+    "resultTranscription": resultTranscription,
+    "resultTranslation": resultTranslation,
+    "resultClassifier": resultClassifier
+}
+
+# Convert the dictionary to a JSON string
+json_string = json.dumps(data)
+
+# Print the JSON string
+print(json_string)