Show HN: Solvi 1.0 – an LLM proposes, checks decide, every decision replays
You describe what to compute with plain Python functions and checks; a model — an LLM, your own classifier or a small local one — proposes where judgement is needed; solvi's checks decide. Every answer comes with a confidence, a reason you can check (the rule's inputs, a formula over computed facts, or a quote with character offsets in the source) and a hash-chained trace that can be re-executed later to confirm the answer or pinpoint the step that was altered. When something cannot be computed or checked, solvi abstains or hands the case to a person instead of guessing; a failed hard check always overrides any model's confidence. solvi 1.0 has two levels.
- ▪You describe what to compute with plain Python functions and checks; a model — an LLM, your own classifier or a small local one — proposes where judgement is needed; solvi's checks decide.
- ▪Every answer comes with a confidence, a reason you can check (the rule's inputs, a formula over computed facts, or a quote with character offsets in the source) and a hash-chained trace that can be re-executed later to confirm the answer or
- ▪When something cannot be computed or checked, solvi abstains or hands the case to a person instead of guessing; a failed hard check always overrides any model's confidence. solvi 1.0 has two levels.
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Story provenance
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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/solvi-ai/solvi |
| Publication time | Sun, 04 Oct 2026 07:50:57 +0000 |
| Retrieval time | 2026-10-04T08:02:56.292Z |
| Last seen | 2026-10-04T08:02:56.292Z |
| 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 | 7qtOOBgpWbTt · 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
solvi Decision systems you can check. You describe what to compute with plain Python functions and checks; a model — an LLM, your own classifier or a small local one — proposes where judgement is needed; solvi's checks decide. Every answer comes with a confidence, a reason you can check (the rule's inputs, a formula over computed facts, or a quote with character offsets in the source) and a hash-chained trace that can be re-executed later to confirm the answer or pinpoint the step that was altered. When something cannot be computed or checked, solvi abstains or hands the case to a person instead of guessing; a failed hard check always overrides any model's confidence. solvi 1.0 has two levels.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.