Introduce metadata-driven AI model features and parameters - #122
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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 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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- List only genuine trained model capabilities under "Trained features" (add image/audio/video input/output; drop provider-hosted web search) - Add AIModelFeatureDescriptor.EnabledByDefault; default toolCalling + streaming on - Add ModelFeaturesAICompletionServiceHandler to enforce features at runtime, stripping tools/ToolMode and JSON response format when not declared (opt-in on metadata) - MVC + Blazor: "Trained features" heading, default-on features, read-only capability badges in profile/template/chat editors - MVC: bootstrap-select searchable multi-select on deployment allowed-values pickers - Update docs and 1.1.0 changelog; add enforcement + registration tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- Remove form-select class from the deployment allowed-values multiselect so the native control no longer shows nested inside the bootstrap-select picker - Upgrade @crestapps/bootstrap-select CDN assets from 1.2.0 to 1.2.1 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- Add AIModelParameterDescriptor.RequiredFeature so a parameter can declare a dependency on a trained feature; wire the built-in reasoningEffort parameter to require the reasoning feature - MVC and Blazor deployment editors only show a dependent parameter while its feature is enabled, and clear/disable it when the feature is turned off so a contradictory config (e.g. reasoningEffort on a non-reasoning model) can't be saved - Update docs and 1.1.0 changelog; add RequiredFeature registration and Clone tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
…n framework - Deployment editors now render a parameter that declares a RequiredFeature inline beneath its feature checkbox; the "Model parameters" heading only appears for parameters not linked to a feature - Extract the MVC parameter card into a _DeploymentModelParameterCard partial and the Blazor card into a shared RenderFragment to reuse in both locations - Enforce the parameter/feature relationship in the framework: DefaultAIModelCapabilityService.GetCapabilities now excludes a parameter whose RequiredFeature is not declared by the deployment, so the runtime handlers never apply it regardless of how the metadata was authored - Add framework tests for the new capability filtering; update docs and changelog Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Add extensible model capability enforcement so unsupported request options never reach a provider, avoiding provider validation errors (e.g. HTTP 400). Framework: - Add shared ModelFeatureEnforcement helper that strips tools/ToolMode when toolCalling is not declared, removes a JSON response format when structuredOutputs is not declared, removes reasoning options when reasoning is not declared, removes the reasoning effort when the reasoningEffort parameter is not exposed, and coerces an unsupported effort to the deployment default (preserving other reasoning state). - Add CapabilityEnforcingChatClient and wire it into DefaultAIClientFactory as the terminal layer above the provider client so enforcement also runs for callers that resolve an IChatClient directly. Enforcement is opt-in to deployments that declare capability metadata; the capability service is optional so unconfigured hosts are unchanged. - Convert model parameter values written to AdditionalProperties to their typed primitive; parse integers through decimal for exact Int64 bounds, reject non-finite numbers, and skip values that cannot be represented. - Log the Azure ExtraHigh -> High reasoning-effort clamp instead of downgrading silently. - Replace the computerUse feature with videoOutput. UI: - Unify the Blazor and MVC deployment editors on bootstrap-select (1.2.1) and sort trained features alphabetically. Docs and tests updated; all tests pass with zero warnings. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Complete streaming requests as a single buffered (non-streaming) response when a deployment does not declare the streaming trained feature, replaying the result via ToChatResponseUpdates(). Enforced on both the client-factory path (CapabilityEnforcingChatClient) and the Azure SDK direct path (AzureOpenAICompletionClient). The Azure non-streaming completion no longer swallows OperationCanceledException, so a suppressed streaming fallback propagates cancellation like a normal streaming request. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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# Conflicts: # src/CrestApps.Core.Docs/docs/changelog/1.1.0.md # src/Startup/CrestApps.Core.Blazor.Web/Components/App.razor # src/Startup/CrestApps.Core.Mvc.Web/Areas/AI/Controllers/AIProfileController.cs # src/Startup/CrestApps.Core.Mvc.Web/Areas/AI/Controllers/AITemplateController.cs # src/Startup/CrestApps.Core.Mvc.Web/Areas/ChatInteractions/Controllers/ChatInteractionController.cs # src/Startup/CrestApps.Core.Mvc.Web/Views/Shared/_Layout.cshtml
…ility, changelog Addresses review follow-ups on the metadata-driven model features/parameters work: - MVC deployment editor: emit a non-sequential `ModelParameters.Index` token per parameter card and keep the structural hidden fields (Name, IsSupported, Index) enabled even when a feature-dependent row is disabled. Previously the feature dependency script disabled every field in a hidden card, dropping the whole row from the POST; with sequential indices the default collection binder truncated at the gap and silently dropped later parameters. This only affected hosts that register additional parameters, but corrupts their metadata on save. - Add server-side validation of per-deployment parameter metadata at save time (AIDeploymentViewModel.ValidateModelParameters, wired into Create/Edit POST). Reuses the descriptor's own IsValidValue so the editor and the request pipeline agree: an out-of-range/unlisted default, an unregistered allowed value, or a minimum greater than a maximum is reported inline instead of being silently corrected at request time. - AzureOpenAICompletionClient: warn when a binder-less model parameter would be applied via ChatOptions.AdditionalProperties. That client projects a fixed set of options onto the Azure SDK and has no generic passthrough, so such a value is now observable instead of silently dropped. The built-in reasoningEffort binds through ChatOptions.Reasoning.Effort and is unaffected. - Move the changelog entry from the released 1.1.0 notes to the in-development 2.0.0 notes (VersionPrefix is 2.0.0). Adds AIDeploymentModelParameterValidationTests. Full suite: 2880 passing. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
The MVC deployment editor validates per-deployment parameter metadata at save time, but the Blazor editor could still persist incoherent capability metadata and undermine the same guarantees. Add the equivalent guard: - AIDeploymentViewModel.ValidateModelParameters (Blazor) mirrors the MVC check, reusing each row's registered Descriptor and the descriptor's own IsValidValue so an out-of-range/unlisted default, an unregistered allowed value, or a minimum greater than a maximum is reported before save. Wired into the Create and Edit page submit handlers, surfacing through the existing validation alert. Adds BlazorAIDeploymentModelParameterValidationTests. Full suite: 2886 passing. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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…DeploymentParameter Drops the redundant "Model" from the two persisted capability metadata types added in #122: - AIDeploymentModelMetadata -> AIDeploymentMetadata - AIDeploymentModelParameter -> AIDeploymentParameter Note: these are stored in a deployment's Properties keyed by type name, so the persisted JSON key changes (AIDeploymentModelMetadata -> AIDeploymentMetadata). No recipe/appsettings references the old key and 2.0.0 is unreleased, so there is no shipped data to migrate; any locally-saved dev deployment metadata would need to be re-saved. Files renamed via git mv. Full suite: 2906 passing. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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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:
Sample hosts:
Docs: