Update app.py

app.py

@@ -169,13 +169,23 @@ Answer:
 )
 
 # Load PDF and split into chunks
+
+from langchain_community.document_loaders import PyPDFLoader
+import tempfile
+
 def load_and_split_pdf(uploaded_file):
-    loader = PyPDFLoader(uploaded_file.name)
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
+        tmp_file.write(uploaded_file.read())
+        tmp_file_path = tmp_file.name
+
+    loader = PyPDFLoader(tmp_file_path)
     documents = loader.load()
-    text_splitter = RecursiveCharacterTextSplitter(chunk_size=800, chunk_overlap=100)
+
+    # Then your text splitting logic follows
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)
     chunks = text_splitter.split_documents(documents)
     return chunks
-
+    
 # Build vectorstore from document chunks
 def build_vectorstore(chunks):
     embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")