Update app.py

app.py

@@ -5,7 +5,7 @@ import fitz
 from dotenv import load_dotenv
 from langchain_community.document_loaders import UnstructuredPDFLoader
 from langchain_community.vectorstores import FAISS
-from langchain_community.embeddings import HuggingFaceEmbeddings
+from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_text_splitters import CharacterTextSplitter
 from langchain_groq import ChatGroq
 from langchain.memory import ConversationBufferMemory
@@ -15,52 +15,15 @@ import sys
 import pytesseract
 from pdf2image import convert_from_path
 
-def check_installation(command):
-    try:
-        result = subprocess.run([command, '--version'], capture_output=True, text=True)
-        return result.returncode == 0, result.stdout
-    except FileNotFoundError:
-        return False, f"{command} not found"
-
-def check_dependencies():
-    dependencies = {
-        'tesseract': '/usr/bin/tesseract',
-        'pdftoppm': '/usr/bin/pdftoppm',  # Part of poppler-utils
-    }
-    
-    status = {}
-    for dep, path in dependencies.items():
-        installed, version = check_installation(path)
-        status[dep] = {
-            'installed': installed,
-            'path': path,
-            'version': version if installed else 'Not found'
-        }
-    
-    return status
-
-def log_dependency_status(status):
-    print("Dependency Status:")
-    for dep, info in status.items():
-        print(f"{dep}:")
-        print(f"  Installed: {info['installed']}")
-        print(f"  Path: {info['path']}")
-        print(f"  Version: {info['version']}")
-    print("\nEnvironment Variables:")
-    for key, value in os.environ.items():
-        if 'PATH' in key or 'PYTHONPATH' in key:
-            print(f"{key}: {value}")
-
-# Run dependency check
-dependency_status = check_dependencies()
-log_dependency_status(dependency_status)
 
 # Load environment variables
 load_dotenv()
 secret_key = os.getenv("GROQ_API_KEY")
 
 os.environ["GROQ_API_KEY"] = secret_key
+
 embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/paraphrase-multilingual-mpnet-base-v2")
+
 # Ensure the necessary folders exist
 UPLOAD_FOLDER = 'uploads/'
 AUDIO_FOLDER = 'audio/'
@@ -83,6 +46,7 @@ def prepare_vectorstore(data):
     texts = data
     vectorstore = FAISS.from_texts(texts, embeddings)
     vectorstore.save_local("faiss_index")
+    
     return vectorstore
 
 def load_vectorstore():