DocJev
LlamaIndex's open-source library that classifies a document against natural-language category rules or finds the boundaries between sub-documents, with swappable OCR backends (liteparse or LlamaParse) and a benchmark harness whose 40-document pilot classified 40/40 originals correctly at about 182 ms Jev decision p50.
OWNER
jerryjliu
INDUSTRY
Document pipelines
CATEGORY
Classification & Routing
KIND
REPO
HOST
github.com
WHAT IT DECIDES
CHOICE
Picks one option from a fixed set
SCORE
Rates against ordered levels
NOUL
Answers a yes / no question
Inferred from this project's own one-line summary in the community list — it reads as a CHOICE decision. Read the source to confirm.
THE SHAPE OF A CHOICE CALL
A generic skeleton for this question type, not this project's actual code.
from typesafe import TypeSafe
ts = TypeSafe() # reads TYPESAFE_API_KEY
result = ts.evaluate(
state=page_state,
questions={
"next_action": {
"type": "choice",
"options": ["click", "scroll", "type", "done"],
"instructions": "What should the agent do next?",
}
},
)
action = result["next_action"] # the chosen option
confidence = result["next_action_confidence"]MORE IN Classification & Routing
Notraproduction GEO platform whose `NOTRA_JEV_CLASSIFIERS` flag routes brand-visibility classifiers off an LLM and onto Jev `Boolean` decisions at a 0.5 threshold, targeting 300 ms p50.jev-routerroutes Claude Code tasks to the cheapest capable model by asking Jev to choose among candidates.jev-router (prismhq)open-source LiteLLM-based router where a Jev decision picks which model serves each request.pi-jev-routeradds automatic per-request model routing to the Pi coding agent through Jev decisions on Vercel AI Gateway.