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R client for the TypeSafe Jev System One API
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CommunityJev Repos & SDKs
JevR
R client for TypeSafe Jev that asks typed noul, choice, and score questions about text or structured rows and returns probabilities ready for code and aggregation.
- Stars
- 5
- Language
- R
- Published by
- Community
- Author
- mountainMath
- Last verified
- Oct 2026
About this project
An R client for TypeSafe's Jev, a System One model that answers typed questions about text or structured data. Instead of generating prose, Jev returns probabilities: whether a condition holds (noul), which of several options applies (choice), or where the input sits on an ordered scale (score). That makes the answers easy to use directly in code and to aggregate across many records. Set your API key in the TYPESAFEAPIKEY environment variable, for example in /.Renviron:
Quoted from the project's README. Read the full README.
Works forJev for Classification
Used inJev for Software & DevTools
Highlights
- jev_noul, jev_choice, and jev_score express yes-no, pick-one, and ordered-scale judgments over a shared state.
- One jev call evaluates independent questions against the same string or named-list state in parallel.
- jev_map runs the same questions over vectors, lists, or data-frame rows into one tidy row per record.
- jev_tidy, jev_probabilities, jev_answer, and jev_usage expose tidy frames, distributions, raw answers, and tokens.
Watch out
Set TYPESAFE_API_KEY in the environment and calibrate decision thresholds on your own data before acting on probabilities. Copy reviewed against the repository README on 2026-10-04, not from running it.
Questions about this entry
Short answers drawn from the linked project or page.
A chat model returns prose you must parse, with unstable wording across retries. Here each question declares noul, choice, or score semantics, and answers come back as probabilities with confidence that code can aggregate directly.
Ask one narrow judgment per question, spell out what yes and no mean for nouls, give choice questions a no-match option, and make each score level a concrete standalone situation.
Failed requests are kept as NA rows with the message in .error, so a batch still returns one tidy row per record. Rate-limit and overload responses retry with exponential backoff.
Yes. jev_request builds the httr2 request without sending it for dry runs or parallel perform, jev_models lists available model names, and TYPESAFE_BASE_URL points at another endpoint.
State can be a string, a named list, or a one-row data frame, and questions can refer to its fields by name inside backticks. For example, with a state holding a title and a letter, a Noul can ask whether the letter is mainly about housing by naming it in backticks inside the instructions.
Printing it shows the model and input and output tokens plus one line per answer, such as a Noul probability, a Choice with confidence, or a Score position with confidence. From there jev_tidy returns one row, jev_probabilities returns the full distribution over levels, jev_answer returns one raw answer, and jev_usage returns the token counts.
jev_map runs the same questions over a character vector, a list of states, or the rows of a data frame and returns one tidy row per record, binding cleanly with dplyr. jev_request builds the httr2 request without sending it, so you can dry-run it or hand it to req_perform_parallel, and jev_models lists the names and aliases available to your account.
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