undo semantic chunking

rag_system.py

@@ -199,6 +199,7 @@ class DocumentIngestion:
                 st.error("No embedding model available. Please install sentence-transformers or provide OpenAI API key.")
                 raise Exception("No embedding model available")
             
+        """""
         self.text_splitter = SemanticChunker(
             embeddings_model=self.embeddings,
             chunk_size=4,                    # 4 sentences per base chunk
@@ -207,9 +208,14 @@ class DocumentIngestion:
             min_chunk_size=150,             # Minimum 150 characters
             max_chunk_size=1500,            # Maximum 1500 characters
             debug=True                      # Show statistics in Streamlit
+        )"""
+        self.text_splitter = RecursiveCharacterTextSplitter(
+            chunk_size=1000,
+            chunk_overlap=200,
+            separators=["\n\n", "\n", ".", "!", "?", ",", " ", ""]
         )
         
-        st.info(f"🧠 Using semantic chunking with {self.embedding_type} embeddings")
+        """st.info(f"🧠 Using semantic chunking with {self.embedding_type} embeddings")"""
         self.persist_directory = os.getenv("CHROMA_PERSIST_DIRECTORY", "./chroma_db")
         os.makedirs(self.persist_directory, exist_ok=True)