chore: bump version to 0.5.3

Fixed CRITICAL bug where SchemaManager ignored VECTOR_DIMENSION environment variable.

Changes in 0.5.3:
- SchemaManager now correctly reads vector dimension from CloudConfiguration API
- Fixes FHIR-AI-Hackathon deployment issues with custom embedding dimensions
- Fixed iris.dbapi import issues in connection_pool.py (removed invalid Connection type hints)
- Added 9 comprehensive integration tests against real IRIS database (100% passing)
- Configuration priority chain (env > config > defaults) now works correctly
- Fixed pyproject.toml packaging to prevent namespace pollution (removed adapters* and evaluation_framework* from package)

Integration Test Coverage:
- ConnectionManager with CloudConfiguration environment variables (2 tests)
- SchemaManager dimension configuration with VECTOR_DIMENSION env var (3 tests)
- Configuration priority chain validation (3 tests)
- End-to-end configuration flow to database (1 test)

FHIR-AI-Hackathon Compatibility: SchemaManager now properly reads VECTOR_DIMENSION=1024 and other custom dimensions.

Author: tom-dyar

CHANGELOG.md

@@ -1,5 +1,33 @@
 # Changelog
 
+## [0.5.3] - 2025-11-12
+
+### Fixed
+- **CRITICAL**: Fixed SchemaManager bug where VECTOR_DIMENSION environment variable was ignored
+  - SchemaManager now correctly reads vector dimension from CloudConfiguration API
+  - Previous behavior: Always returned default 384 dimensions regardless of VECTOR_DIMENSION env var
+  - New behavior: Respects configuration priority (env > config > defaults) via Feature 058 CloudConfiguration
+  - Impact: Fixes FHIR-AI-Hackathon deployment issues where custom embedding dimensions were required
+- Fixed iris.dbapi import issues in connection_pool.py
+  - Replaced invalid `Connection` type hints with `Any` (iris.dbapi doesn't export Connection class)
+  - Removed incorrect `from iris.dbapi import Connection` import
+
+### Added
+- **Integration Test Coverage**: 9 comprehensive integration tests against real IRIS database
+  - `TestConnectionManagerIntegration`: 2 tests validating ConnectionManager with CloudConfiguration
+  - `TestSchemaManagerIntegration`: 3 tests validating SchemaManager dimension configuration
+  - `TestConfigurationPriorityChain`: 3 tests validating env > config > defaults priority
+  - `TestCompleteConfigurationFlow`: 1 test validating end-to-end configuration to database
+  - All tests verify real IRIS database operations (not mocked)
+  - Test Results: 9/9 passing (100%)
+
+### Technical Details
+- Files Modified:
+  - `iris_vector_rag/storage/schema_manager.py` - Lines 49-77: Changed from incorrect `config.get("embedding_model.dimension", 384)` to `cloud_config.vector.vector_dimension`
+  - `iris_vector_rag/common/connection_pool.py` - Replaced 7 Connection type hints with Any
+- Test Coverage: Added `tests/integration/test_cloud_config_integration.py` (400 lines)
+- FHIR-AI-Hackathon Compatibility: SchemaManager now properly reads VECTOR_DIMENSION=1024 and other custom dimensions
+
 ## [0.5.2] - 2025-11-12
 
 ### Added - Cloud Configuration Flexibility (Feature 058)

iris_vector_rag/__init__.py

@@ -18,7 +18,7 @@
 from .validation.validator import PreConditionValidator
 
 # Package version
-__version__ = "0.5.1"
+__version__ = "0.5.3"
 __author__ = "InterSystems IRIS RAG Templates Project"
 __description__ = "A comprehensive, production-ready framework for implementing Retrieval Augmented Generation (RAG) pipelines using InterSystems IRIS as the vector database backend."
 

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "iris-vector-rag"
-version = "0.5.2"
+version = "0.5.3"
 description = "Production-ready, extensible RAG framework with native IRIS vector search - unified API for basic, CRAG, GraphRAG, and ColBERT pipelines with RAGAS and DSPy integration"
 readme = "README.md"
 license = {text = "MIT"}
@@ -162,7 +162,7 @@ Changelog = "https://github.com/intersystems/rag-templates/blob/main/CHANGELOG.m
 rag-templates = "iris_vector_rag.cli:main"
 
 [tool.setuptools.packages.find]
-include = ["iris_vector_rag*", "adapters*", "evaluation_framework*"]
+include = ["iris_vector_rag*"]
 
 [tool.setuptools.package-data]
 iris_vector_rag = [