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Release Notes: ClaimAuditAI v1.0.1
This release focuses on production-hardening the containerized deployment lifecycle, resolving startup database initialization errors, and fixing data seeding reliability issues reported during InterSystems Open Exchange verification.
Key Changes & Enhancements:
Build-Time FHIR Provisioning: Moved FHIR server installation (/fhir/r4) and recursive class compilation directly into the docker build phase (iris.script). This ensures all schema tables, vector indices, and custom classes are baked directly into the container image, resolving 404 endpoint errors and startup race conditions.
REST Output Stream Protection: Implemented a quiet mode (pQuiet parameter) in the database Setup() method. This suppresses terminal writes when database initialization is triggered from REST controllers, preventing HTTP response pollution and resolving client-side JSON parsing errors (Expecting value: line 1 column 1) during data seeding.
Programmatic Namespace Safety: Wrapped the sample data loader (LoadSampleData()) in a scoped in-memory namespace switch to INTEROP. This resolves the ServiceIdIdx registry lookup failure if the CLI seeding command is executed from a default namespace (e.g. USER).
Robust Container Start Fallbacks: Updated the runtime initialization script (init_iris.sh) to recursively compile all custom classes (including ClaimAudit.Data and ClaimAudit.FHIR) using LoadDir, ensuring correct compilation ordering when deploying with empty persistent volumes.
ZPM Package Alignment: Correctly registered ClaimAudit.Data.PKG in module.xml to track and compile the GraphStore class within ZPM.
Expanded Diagnostic Wiki: Added new troubleshooting guides to the project wiki detailing resolution steps for ServiceIdIdx failures, missing database tables, and REST output pollution.

Full Changelog: https://github.com/musketeers-br/TriageAide/compare/1.0.1...1.0.2

Full Changelog: https://github.com/musketeers-br/TriageAide/commits/1.0.1
A clinician dashboard with AI triage questions that automate pre-checkup intake, built on InterSystems IRIS for Health.
QuestionnaireResponse%Embedding.OpenAI + VECTOR_COSINE)Encounter, SNOMED-coded ServiceRequest, LOINC/SNOMED Observations, and a Communication alert on escalationdocker compose up — boots IRIS, the agent, and the UI, and self-seeds demo data







Lowercased all the property names to work well with %JSON.Adaptor
LastUser->lastuser
CreatedAt->createdat
updatedat property introduced

