Introduce metadata-driven AI model features and parameters

[MikeAlhayek]

Fix #120

Replaces hardcoded, provider-specific model options with an extensible registry of model features (binary capabilities) and model parameters (configurable options carrying kind, allowed values, ranges, and defaults).

AI deployments declare which registered definitions their model exposes and may narrow the allowed values, default, or numeric bounds. AI profiles, profile templates, and chat interactions store the selected values, and the runtime binds them into the outgoing request. Values for parameters a deployment does not expose are never rendered and never sent.

Framework:

• adds the capability abstractions, descriptors, and metadata models
• adds AddCoreAIModelCapabilities, AddAIModelFeature, and AddAIModelParameter
• registers eight built-in features and the reasoningEffort parameter
• adds DefaultAIModelCapabilityService to merge registrations with deployment metadata without mutating the registered descriptors
• adds ModelParametersAICompletionServiceHandler as the single enforcement point, with deployment-default fallback and binder dispatch
• adds IAIModelParameterBinder and a reasoning effort binder that sets ChatOptions.Reasoning.Effort
• maps the resolved effort onto ChatCompletionOptions.ReasoningEffortLevel in AzureOpenAICompletionClient so both request paths behave the same
• adds CompletionServiceConfigureContext.Deployment
• adds a ModelParameters front-matter key to the markdown template parser

Sample hosts:

• adds a deployment capability editor and a metadata-driven parameter editor to the AI deployment, profile, template, and chat interaction screens in CrestApps.Core.Mvc.Web
• adds the equivalent ModelCapabilitiesEditor and ModelParametersEditor components to CrestApps.Core.Blazor.Web

Docs:

• adds the Model Capabilities guide and records the change in the 1.1.0 changelog