
Trimwise
Exact-budget, source-faithful context selection for prompts
Trimwise launched on August 4, 2026 with 3 votes, #2,940 of 23,273 launches that month and more than 50% of that year's launches.
What it does
Trimwise is an open-source Python library for selecting the most relevant, verbatim passages from a known source under exact token, word, or character budgets. It preserves source order and returns original character spans for auditability, with lexical, semantic, and hybrid selection modes. Built for RAG, agents, and prompt pipelines, with reproducible benchmarks and a public research artifact.
Create compact, high-signal excerpts for LLM prompts without rewriting the source. Trimwise is an extractive Python library for the step between collecting text and assembling a prompt. Give it a document, a maximum size, and optionally the task you care about. It selects useful fragments from across the document, returns them in source order, and guarantees that the measured result stays within your token, word, or character limit. This is especially useful when an agent has several sources but cannot place every source in the context window. Instead of taking the first N characters from each article, report, note, or search result, Trimwise gives each source a smarter evidence budget…from trimwise.readthedocs.io
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