how to make chunks in langchain rag databases

from langchain.text_splitter import RecursiveCharacterTextSplitter

# Example: Recursive chunking with overlap
text_splitter = RecursiveCharacterTextSplitter(
    chunk_size=500,      # tokens per chunk
    chunk_overlap=50,    # overlap to preserve context
    separators=["\n\n", "\n", " ", ""]
)

chunks = text_splitter.split_text(long_document)
print(f"Created {len(chunks)} chunks")

• Chunk size: Typically 300–1000 tokens.

• Overlap: 10–20% of chunk size helps preserve context across boundaries.

• Storage: Chunks are embedded and stored in a vector DB (e.g., FAISS, Pinecone).