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Build: Vignette Generation

Maps to: Task 5. Kind: Build.

Objective

Write generate.rs: the all_params() iterator over the parameter grid, and generate() which filters by validity, renders each prompt through tera, hashes it, and produces Vignettes. Prove the counts and the uniqueness of IDs with tests.

Scaffold

Create: crates/panoptes-gen/src/generate.rs. Modify: crates/panoptes-gen/src/lib.rs (re-export all_params, generate).

Dependencies: no manifest changes — itertools (iproduct!), tera, and sha2 were declared when you created the crate.

Expected result: cargo test -p panoptes-gen generate → 4 tests pass (grid_has_24_raw_combinations, validity_filter_reduces_count → 18, ids_are_unique, template_renders_params).

The spec (givens)

  • The confidence levels are const CONFIDENCES: [u8; 3] = [30, 60, 95]; — a design decision from the study, not derivable.
  • all_params() -> impl Iterator<Item = Params>: the cartesian product of confidences × both TimePressure variants × both Reversibility variants × [true, false] for info_request (3 × 2 × 2 × 2 = 24).
  • generate(family: &impl ScenarioFamily, spec: &FamilySpec) -> anyhow::Result<Vec<Vignette>>.
  • The tera context gets exactly four keys: attribution_confidence (number), time_pressure (its Display string), info_request (bool), action_menu (the vec joined with ", ").
  • prompt_sha256 is the lowercase-hex SHA-256 of the rendered prompt bytes.

Full code: Answer Key, Task 5.

Concepts exercised

  • itertools::iproduct! over typed enum arrays.
  • tera templating: injecting parameters into the prompt template.
  • sha2 hashing for the prompt fingerprint.

The build loop (you drive)

  1. Write failing tests: the raw grid has exactly 24 combinations; the validity filter reduces it to the expected number; all generated IDs are unique; a rendered prompt contains the injected parameter.
  2. Predict: how many vignettes remain after CaGeo's filter removes the HOURS + NOINFO combos? Work it out from the grid dimensions before running.
  3. Run, check the arithmetic against reality.
  4. Implement.
  5. Run green, commit.
Predict first The ids_are_unique test is a guard against a subtle bug: if two different parameter combinations produced the same ID, your manifest join would silently collapse them. Before running, convince yourself the ID construction cannot collide for distinct params.

Done when

cargo test -p panoptes-gen generate passes, including the uniqueness guard.