Token Splitter llamaindex

The token splitter analyzes input text and returns a list of tokens and a token count based on a chosen mode. It supports delimiter-based tokenization and whitespace-based tokenization to cover structured data and free-form text. The system is deterministic, ensuring reproducible token lists for embeddings and indexing. Outputs include tokens, token_count, and optional sample_tokens for quick inspection.
The underlying logic selects a split strategy, applies language rules if provided, and enforces optional constraints such as max_tokens or case normalization. When delimiter is provided, splitting uses the exact delimiter; otherwise whitespace rules apply. Unicode and multi-byte characters are preserved, making the tool suitable for multilingual preprocessing.
This tool is valuable for data scientists, ML engineers, and content teams preparing data for LlamaIndex pipelines, embeddings, or search indexing, where precise token counts influence model cost and retrieval behavior. Its deterministic behavior and simple integration points support automated ETL and preprocessing scripts.