Jtoken – lossless JSON compression for LLM prompts
jtoken Compress JSON for LLM prompts — same data, fewer tokens. Author: Hermann Samimi PyPI · Repository · Issues jtoken strips JSON syntactic noise, collapses repeated booleans and nulls into summary lines, flattens nested dicts with dot notation, and supports normalization for Elasticsearch hits and MongoDB JSON. The package ships as a stdlib-first library with an optional tiktoken extra and a jtoken CLI.
- ▪jtoken Compress JSON for LLM prompts — same data, fewer tokens.
- ▪Author: Hermann Samimi PyPI · Repository · Issues jtoken strips JSON syntactic noise, collapses repeated booleans and nulls into summary lines, flattens nested dicts with dot notation, and supports normalization for Elasticsearch hits and M
- ▪The package ships as a stdlib-first library with an optional tiktoken extra and a jtoken CLI.
Hacker News (AI / LLM) files mainly under ai. We currently carry 6,867 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | GitHub |
| Canonical URL | https://github.com/HermannSamimi/jtoken |
| Publication time | Tue, 29 Sep 2026 16:21:55 +0000 |
| Retrieval time | 2026-09-29T16:27:02.792Z |
| Last seen | 2026-09-29T16:27:02.792Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | diOYOrZiGCJ9 · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
jtoken Compress JSON for LLM prompts — same data, fewer tokens. Author: Hermann Samimi PyPI · Repository · Issues jtoken strips JSON syntactic noise, collapses repeated booleans and nulls into summary lines, flattens nested dicts with dot notation, and supports normalization for Elasticsearch hits and MongoDB JSON. The package ships as a stdlib-first library with an optional tiktoken extra and a jtoken CLI. Table of contents Installation Quick start What the format looks like Normalization and denormalization CLI Token savings API reference Development Contributing Security License Installation TipInstall jtoken[tiktoken] when you want OpenAI-compatible token counts from the real tokenizer.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.