feat: exponential retry decorator

[a-klos]

This pull request introduces a robust, configurable retry decorator with exponential backoff and rate-limit handling for both synchronous and asynchronous functions. It also integrates the retry decorator settings into the infrastructure configuration, making them easily adjustable via environment variables and Kubernetes ConfigMaps. Comprehensive tests have been added to ensure correct behavior. The main changes are grouped below:

Retry Decorator Implementation and Utilities

• Added retry_with_backoff decorator in libs/rag-core-lib/src/rag_core_lib/impl/utils/retry_decorator.py, supporting configurable retries, exponential backoff, jitter, and rate-limit awareness for sync/async functions.
• Introduced utility functions in libs/rag-core-lib/src/rag_core_lib/impl/utils/utils.py for parsing rate-limit headers, normalizing dictionaries, and extracting status codes/headers from exceptions.

Configuration and Infrastructure Integration

• Created RetryDecoratorSettings in libs/rag-core-lib/src/rag_core_lib/impl/settings/retry_decorator_settings.py using Pydantic, allowing environment-based configuration of retry logic parameters.
• Added retryDecorator configuration block to infrastructure/rag/values.yaml for setting retry parameters via Helm values.
• Generated a new ConfigMap in infrastructure/rag/templates/configmap.yaml to expose retry decorator settings to Kubernetes deployments.
• Updated deployment templates (admin-backend/deployment.yaml, backend/deployment.yaml) to mount the new retry decorator ConfigMap. [1] [2]
• Added a Helm template helper for naming the retry decorator ConfigMap in _helpers.tpl.

Testing

• Added comprehensive unit tests in libs/rag-core-lib/tests/retry_decorator_test.py to validate retry logic, rate-limit handling, and configuration.

This PR covers the following feature request
#87

[Copilot]

Pull Request Overview

This PR introduces a robust retry decorator with exponential backoff and rate-limit handling for both synchronous and asynchronous functions, enabling configurable retry behavior through environment variables and Kubernetes configuration.

• Implements a configurable retry decorator with exponential backoff, jitter, and rate-limit awareness
• Integrates retry settings into infrastructure configuration via Helm values and ConfigMaps
• Adds comprehensive test coverage for retry scenarios including rate-limit handling

Reviewed Changes

Copilot reviewed 11 out of 12 changed files in this pull request and generated 2 comments.

Show a summary per file

File	Description
retry_decorator_test.py	Comprehensive test suite covering sync/async retry scenarios and rate-limit handling
utils.py	Utility functions for parsing rate-limit headers and extracting exception metadata
retry_decorator.py	Core retry decorator implementation with exponential backoff and rate-limit awareness
retry_decorator_settings.py	Pydantic settings model for configuring retry behavior via environment variables
pyproject.toml	Adds pytest-asyncio dependency for async test support
README.md	Documentation for retry decorator usage and configuration
values.yaml	Default retry configuration values for Helm deployment
configmap.yaml	ConfigMap template for retry decorator environment variables
deployment.yaml files	Integration of retry decorator ConfigMap into backend deployments
_helpers.tpl	Helm template helper for retry decorator ConfigMap naming

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