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Wayfinder Router: deterministic routing of queries between local and hosted LLM

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Wayfinder Router: deterministic routing of queries between local and hosted LLM
TL;DR · WeSearch summary

The Wayfinder Router is a deterministic routing system that sends queries to either local or cloud models based on the prompt's structure and wording. It decides in microseconds, runs offline, and never calls another model to make the call, reducing latency, cost, and randomness. The system is designed to be self-hosted and calibrated on the user's own data, allowing for a score and recommendation to be provided for each prompt.

Key facts
About this source

Hacker News (AI / LLM) files mainly under ai. We currently carry 3,266 of its stories.

Original article
GitHub
Read full at GitHub →

Story provenance

Source · retrieval · rights · ranking — open for full record
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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 publisherGitHub
Canonical URLhttps://github.com/itsthelore/wayfinder-router
Publication timeSun, 28 Jun 2026 04:31:18 +0000
Retrieval time2026-06-28T09:26:46.953Z
Last seen2026-06-28T09:26:46.953Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
Clusteroucbackk9BaJ
Cluster logicGrouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

Rights status (four layers)

Publisher-declared
No publisher-confirmed rights record for this source yet.
Machine-readable
No source-specific machine-readable restriction detected beyond the public feed.
WeSearch interpretation
WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
Retrieval and training permissions are not asserted unless the publisher confirms them.

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

Deterministic prompt-complexity routing — send each prompt to your local or cloud model, offline, with no model call to decide. Quickstart · Benchmark · How it compares · Explainer · Changelog No model callto decide the route Deterministicand fully offline Calibrateon your own data Bring your own keyself-hosted Wayfinder looks at a prompt's structure (length, headings, lists, code) and its wording (proofs, math, hard constraints), then tells you whether to send it to your small local model or your big cloud one. It decides in microseconds, runs offline, and never calls another model to make the call: no API key, no network, no model call to decide. You get a score and a recommendation, and what you do with it is up to you.

Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.

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