CSV Splitter LangChain

This tool accepts a CSV payload in text form, a delimiter character, and optional chunking controls. It validates input, parses rows using a standards-compliant CSV parser, and produces one or more chunked CSV strings. If include_headers is true, the first line is treated as the header and replicated in every chunk; otherwise headers are not re-included. Output includes an array of chunk strings and a compact summary.
The core splitting algorithm counts rows, builds chunks up to max_rows_per_chunk, and handles quoted fields with embedded newlines. It preserves data integrity by not splitting within a single logical row. If max_rows_per_chunk is omitted, the entire CSV is returned as a single chunk. It supports common delimiters such as comma, semicolon, and tab.
Beneficiaries include data engineers preparing prompts for LangChain, ML researchers feeding dataset slices to evaluation workflows, and automation pipelines that require deterministic sub-CSV inputs. Typical use cases: feed each chunk to a LangChain chain as a separate input; batch processing to stay within token limits; generate reproducible iterations over a dataset.
Unique value comes from explicit LangChain suitability: chunked outputs with headers preserved, deterministic chunking, and optional quote-handling parameter. Core features include delimiter choice, include_headers flag, max_rows_per_chunk, and outputs that are ready for prompt ingestion or file export. Advanced users can integrate the outputs directly into LangChain workflows or orchestrate batch processing across multiple CSVs.