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decidr

Typed decisions from local LLMs in one forward pass, via Ollama. No generation loop, no JSON parsing.

Details

External ID
1380755098
Source
GITHUB
Company
—
Product
decider
Website domain
github.com
Launched
Sept. 22, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.05976172175249808
Tags
classification, llm, local-llm, logprobs, nlp, ollama, python, routing
Fetched at
Sept. 26, 2026, 1:03 a.m.
Updated at
Sept. 26, 2026, 1:03 a.m.

Enrichment

Theme
decision model runtimes and tools
Vertical
Horizontal
Function
Dev tools
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
typed decision engine for local llms in one forward pass
Manually corrected
False

Could you build this?

Partial Extracting typed decisions in a single forward pass without autoregressive generation requires manipulating LLM logit probabilities or integrating deeply with llama.cpp/Ollama internal sampling endpoints.

What it would actually take: Instead of prompting the model to output JSON tokens sequentially, the engine submits the input prompt, evaluates the forward pass logits for the very next token, and restricts probability distribution specifically to predefined category token IDs (e.g., true/false or enum choices). This requires interacting with llama.cpp or custom Ollama engine hooks via C++/Go bindings to intercept the raw logit vector rather than standard HTTP completion streams. A vibe coder can use the standard API, but building genuine single-forward-pass logit classification bypasses standard generation loops and demands familiarity with transformer inference internals.

Competitors

Other products that read as similar to this one — 407 launches clear the similarity bar, closest 8 shown.

Attention rank: #384 of 408 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 325 days after the earliest competitor.

Other launches for this product

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