added Whisper model api

app.py

@@ -7,7 +7,7 @@ from langchain.vectorstores import FAISS
 from langchain.chains import RetrievalQA
 from langchain.prompts import PromptTemplate
 from langchain.docstore.document import Document
-from whisper_app import WHISPERModel
+import whisper_app
 import llm_ops
 
 FILE_EXT = ['wav','mp3']
@@ -55,7 +55,7 @@ def process_documents(documents,data_chunk=1500,chunk_overlap=100):
 def audio_processor(wav_file,API_key,wav_model='small',llm='HuggingFace',temperature=0.1,max_tokens=4096):
     device='cpu'
     logger.info("Loading Whsiper Model || Model size:{}".format(wav_model))
-    whisper = WHISPERModel(model_name=wav_model,device=device)
+    whisper = whisper_app.WHISPERModel(model_name=wav_model,device=device)
     text_info = whisper.speech_to_text(audio_path=wav_file)
     
     metadata = {"source": f"{wav_file}","duration":text_info['duration'],"language":text_info['language']}

whisper_app.py

@@ -5,7 +5,6 @@ from whisper.audio import SAMPLE_RATE
 from tenacity import retry, wait_random
 import openai
 import requests
-import time
 # os.environ['OPENAI_API_KEY'] = "sk-<API KEY>"
 
 class WHISPERModel: