Version/2.0.0

[crvernon]

This pull request introduces significant new features and improvements across the codebase, focusing on advanced ML optimization, model emulation, expanded AI assistant capabilities, and enhanced CI coverage. It also updates documentation, environment configuration, and the test matrix to support new functionality and platforms.

Major feature additions and improvements:

Machine Learning Optimization and Emulation:

• Introduces a comprehensive ML optimization subsystem (scalable.ml) with learned resource prediction, adaptive scaling, feature extraction, model wrappers, distributed hyperparameter search, and model quality assessment. Adds a model emulation subsystem (scalable.emulation) for surrogate modeling, uncertainty-aware dispatch, and active learning strategies. Public APIs and CLI commands are provided for ML-backed recommendations and emulation. ([CHANGELOG.mdR8-R285])

AI Assistant and Cloud/Kubernetes Support:

• Expands the AI assistant subsystem with pluggable LLM backends, onboarding, diagnosis, plan explanation, workflow composition, and migration assistants. Adds support for Kubernetes, AWS, and GCP providers, cloud cost estimation, artifact storage, and manifest overlays. CLI and API are extended for these new capabilities. ([CHANGELOG.mdR8-R285])

Testing and CI Enhancements:

• Updates the test matrix to include macOS and Python 3.13, and adds a dedicated job for validating and planning example manifests in CI. [1]], [2]], [3]])

Documentation and Configuration:

• Updates the CHANGELOG.md with detailed release notes for all new features, breaking changes, and tests. Updates the README to reflect new capabilities, optional dependency groups, and system requirements. Adds an .env.example for OpenAI configuration. [1]], [2]], [3]], [4]], [5]])

Notable grouped changes:

1. ML Optimization & Emulation

• Adds scalable.ml and scalable.emulation subsystems: learned resource prediction, adaptive scaling, surrogate modeling, uncertainty calibration, and CLI integration. ([CHANGELOG.mdR8-R285])
• New optional dependency group [ml] for ML features. ([CHANGELOG.mdR8-R285])

2. AI Assistants & Cloud/Kubernetes

• Implements AI assistant commands (init-component, diagnose, explain, compose, migrate) with LLM backend support and heuristic fallback. ([CHANGELOG.mdR8-R285])
• Adds Kubernetes, AWS, and GCP provider support, cloud cost estimation, artifact storage, overlays, and related CLI/API changes. ([CHANGELOG.mdR8-R285])

3. CI and Testing

• Expands CI test matrix to include macOS and Python 3.13; adds validation and dry-run planning for example manifests in CI. [1]], [2]], [3]])
• Over 400 passing unit tests, including extensive new coverage for ML and AI features. ([CHANGELOG.mdR8-R285])

4. Documentation & Config

• Major updates to CHANGELOG.md and README.md for new features, usage, and requirements. [1]], [2]], [3]], [4]])
• Adds .env.example for OpenAI credentials and model configuration. ([.env.exampleR1-R13])

5. Maintenance & Versioning

• Updates versioning, export lists, and documentation links for new modules and features. [1]], [2]])

These changes collectively advance the project to a new phase with robust ML, emulation, AI, and cloud-native capabilities, while ensuring strong test coverage and clear documentation.