Update app.py

app.py

@@ -469,30 +469,29 @@ def split_text_into_chunks(text):
     return splitter.create_documents([text])
 
 import os
-import tempfile
 import shutil
-from langchain.vectorstores import Chroma
-from langchain.embeddings import HuggingFaceEmbeddings
 from sentence_transformers import SentenceTransformer
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.vectorstores import Chroma
 
-# --- Create Vector DB ---
-def create_vectorstore(documents):
-    # Setup a writable directory for Chroma
-    chroma_dir = os.path.join(tempfile.gettempdir(), "chroma_db")
-    if os.path.exists(chroma_dir):
-        shutil.rmtree(chroma_dir)  # Clear any old data
-    os.makedirs(chroma_dir, exist_ok=True)
+# Setup a writable directory for Chroma
+chroma_dir = "/home/user/app/chroma_db"  # Change this to an absolute writable directory
+if os.path.exists(chroma_dir):
+    shutil.rmtree(chroma_dir)  # Clear any old data
+os.makedirs(chroma_dir, exist_ok=True)
 
-    # Initialize the model and embeddings
-    model = SentenceTransformer("all-MiniLM-L6-v2", device='cpu')
-    embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
-    
-    # Create the Chroma database
-    db = Chroma.from_documents(documents, embeddings, persist_directory=chroma_dir)
+# Initialize the model and embeddings
+model = SentenceTransformer("all-MiniLM-L6-v2", device='cpu')
+embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
 
-    # Persist the Chroma database
+# Create the Chroma database
+try:
+    db = Chroma.from_documents(splits, embeddings, persist_directory=chroma_dir)
     db.persist()
-    return db
+    print(f"Vectorstore created successfully at {chroma_dir}")
+except Exception as e:
+    print(f"Error creating vectorstore: {e}")
+
 
 # --- Setup QA Chain ---
 def setup_qa(db):