rig-typesafeai

Experimental TypeSafe Jev judgments for Rig. Enable the root rig feature typesafeai to use rig::typesafeai, or depend on this crate and pair it with a Rig HTTP transport explicitly. It uses Rig's Operation, Wire, Model, and shared driver. There are no Jev derive macros or schema-generation traits.

One structure for questions and answers

Implement Query on a generic named struct. Its associated Output replaces question fields with their answer types while preserving their names and layout:

use rig_core::error::ProviderError;
use rig_typesafeai::{Noul, NoulAnswer, Query};
use serde::{Serialize, Deserialize};

// The fields are declared once, for both questions and answers.
#[derive(Serialize, Deserialize)]
struct Assessment<R, V> {
    ready: R,
    needs_review: V,
}

impl<R: Query, V: Query> Query for Assessment<R, V> {
    type Response = Assessment<R::Response, V::Response>;
    type Output = Assessment<R::Output, V::Output>;

    fn decode(&self, response: Self::Response) -> Result<Self::Output, ProviderError> {
        Ok(Assessment {
            ready: self.ready.decode(response.ready)?,
            needs_review: self.needs_review.decode(response.needs_review)?,
        })
    }
}

let query = Assessment {
    ready: Noul::new("Is this ready to ship?")?,
    needs_review: Noul::new("Does this need human review?")?,
};
# Ok::<(), ProviderError>(())

With a Jev model (Jev::from_env()?.evaluation()), evaluate it directly:

let answers: Assessment<NoulAnswer, NoulAnswer> =
    jev.evaluate(&state, &query).await?.answers;

The query is reusable by reference. .await? handles construction-independent transport and response errors once; the result contains ordinary typed fields. Serde field names and rename attributes supply question IDs. The request is serialized directly, and Serde reconstructs the matching response struct before decode validates each answer against its question. No manual map construction or lookup is needed. Use #[serde(flatten)] to compose named groups. See triage for a complete example using Choice, Score, and Noul in the same generic struct. Its query and answer forms are concrete instantiations of one type, with no type erasure.

Question builders

• Choice::new(instructions, [(variant, description), ...]) returns ChoiceAnswer<T> on evaluation. Values implement Serialize, DeserializeOwned, and Ord; their Serde representation must be a string.
• Score::new(instructions, [(level, description), ...]) returns ScoreAnswer<L> with enum-keyed probabilities. Array order determines numeric positions, independently of enum discriminants and Ord. Evaluation requires L: Ord + Clone and the WASM-compatible transport bounds.
• DynamicScore::new(instructions, descriptions) returns DynamicScoreAnswer with numeric indices and a legend when rubric identities are runtime-defined.
• Noul::new(instructions) returns NoulAnswer, the probability of yes. .criteria(yes, no)? accepts structured descriptions for both outcomes.

Fixed arrays check choice counts (2–255) and score counts (2–10) at compile time. try_from_iter constructors check runtime collections and reject duplicate labels or levels. Builders accept serializable descriptions, including structs, JSON objects, arrays, strings, and null. State accepts strings, objects, or arrays.

For runtime IDs, maps of questions implement Query, and .named("ready")? gives a standalone question an ID. .join(other) flattens two query objects; .map(...) projects validated answers. Empty or duplicate IDs and missing or unexpected response IDs are rejected at the evaluation boundary. For a fully runtime-defined question set, use DynamicQuery::new(definitions)?. Its output is explicitly BTreeMap<String, types::Answer>; construction validates the definitions and evaluation validates the provider's answers.

Jev::from_env() reads JEV_TOKEN without loading a secrets file. Its default model is jev-latest; JevConfig::model(...) selects another provider model identifier. Configure timeouts and retry middleware on the Rig transport and pass it with JevConfig::connect.

Questions share state but cannot consume each other's answers in one request. Confidence measures concentration, not correctness. Keep distributions and put threshold policy in application code. Validation preserves the provider's values, including bounded hundredth-rounding error; it does not silently renormalize them.

Examples and verification

Run the interactive console from the repository root with JEV_TOKEN already exported:

cargo run -p typesafeai_chat

Add -- --agent for gpt-5.6-sol replies using OPENAI_API_KEY. The default mode uses Jev alone and displays decisions plus deterministic next actions. Both modes support /reset, /quit, and conversational history.

• Interactive chat: named generic query structs and batched judgments over conversation state.
• Mixed triage: all three primitives in one call.

Run cargo test -p rig-typesafeai to replay the synthetic, live-recorded plain, structured, and rounded matrix fixtures offline, check local validation invariants, and run compile-fail doctests. The fixtures contain no authentication headers. They were recorded against jev-1.13.0; replay checks request JSON and decoded answers, not future model accuracy or calibration. Mutation tests exercise invalid responses separately.

Protocol sources: API, Choice, Score, Noul.