Update app.py

app.py

@@ -1,54 +1,67 @@
-# app.py
+# Standard Libraries
 import os
 import json
-import keras
-from datasets import load_dataset
-import tensorflow as tf
-from huggingface_hub import login
+import time
+import asyncio
+import logging
+import gc
+import re
+import traceback
+from pathlib import Path
+from datetime import datetime
+from typing import List, Dict, Union, Tuple, Optional, Any
+from dataclasses import dataclass, field
+
+# Machine Learning and Deep Learning Libraries
 import torch
-from transformers import ( AutoTokenizer, AutoModelForCausalLM, TrainingArguments, Trainer)
-from sentence_transformers import SentenceTransformer
-from typing import List, Dict, Union, Tuple
-import faiss
-import numpy as np
-from datasets import Dataset
+import torch.nn as nn
 import torch.nn.functional as F
 from torch.cuda.amp import autocast
-import gc
-from peft import ( LoraConfig, get_peft_model, prepare_model_for_kbit_training, TaskType, PeftModel)
-from tqdm.auto import tqdm
 from torch.utils.data import DataLoader
-import logging
-import wandb
-from pathlib import Path
-from typing import List, Dict, Union, Optional, Any
-import torch.nn as nn
-from dataclasses import dataclass, field
-import time
-import asyncio
-import pytest
-from unittest.mock import Mock, patch
-from sklearn.metrics import classification_report, confusion_matrix
-import gradio as gr
-import matplotlib.pyplot as plt
-from datetime import datetime
-import requests
+import tensorflow as tf
+import keras
+import numpy as np
+
+# Hugging Face and Transformers
+from transformers import AutoTokenizer, AutoModelForCausalLM, TrainingArguments, Trainer
+from sentence_transformers import SentenceTransformer
+from datasets import load_dataset, Dataset, concatenate_datasets
+from huggingface_hub import login
+
+# FAISS and PEFT
+import faiss
+from peft import LoraConfig, get_peft_model, prepare_model_for_kbit_training, TaskType, PeftModel
+
+# LangChain - updated imports as per recent deprecations
+from langchain_community.vectorstores import FAISS  # Updated import
+from langchain_community.embeddings import HuggingFaceEmbeddings  # Updated import
+from langchain_community.document_loaders import TextLoader  # Updated import
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+
+# Data Science and Visualization Libraries
 import pandas as pd
 import seaborn as sns
-import traceback
+import matplotlib.pyplot as plt
 from matplotlib.gridspec import GridSpec
-from datasets import load_dataset, concatenate_datasets
-from langchain.vectorstores import FAISS
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.embeddings import HuggingFaceEmbeddings
-from langchain.document_loaders import TextLoader
-import IPython.display as display
-from peft import get_peft_model, LoraConfig, prepare_model_for_kbit_training
-import warnings
-import re
+from sklearn.metrics import classification_report, confusion_matrix
+
+# Development and Testing
+import pytest
+from unittest.mock import Mock, patch
+
+# External Tools and APIs
+import wandb
+import requests
+import gradio as gr
+import IPython.display as display  # Required for IPython display functionality
 from dotenv import load_dotenv
+from tqdm.auto import tqdm
+
+# Suppress Warnings
+import warnings
 warnings.filterwarnings('ignore')
 
+
 # Ensure Hugging Face login
 try:
     hf_token = os.getenv("HF_TOKEN")
@@ -58,13 +71,12 @@ try:
 except Exception as e:
     print("Hugging Face Login failed:", e)
 
-# CUDA and Memory Configurations
-torch.backends.cuda.matmul.allow_tf32 = False
-torch.backends.cudnn.allow_tf32 = False
+
 os.environ['PYTORCH_CUDA_ALLOC_CONF'] = 'max_split_size_mb:64,garbage_collection_threshold:0.8,expandable_segments:True'
 os.environ['CUDA_LAUNCH_BLOCKING'] = '1'
 
 
+
 # Setup logging
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)