from Fabrify import FabrifyClient, ElementInference, ModellingContext, SuggestionHandler, DecisionType

from Autodesk.Revit.DB import ElementId

aiClient = FabrifyClient(doc)

def suggest_clt_wall(doc, element_id: ElementId):

"""

Suggest the most suitable CLT wall type for a given
Revit element and context.

Internally, the system leverages element context (type,
category, parameters) along with recent modeling
transactions to tailor the suggestion to inferred design
intent.

"""

# Instantiate a CLT assistant with a recency-weighted
transaction context.

activeContext = ModellingContext.Scaffold(env=Revit)

activeContext.OperationChain = ModellingContext.BuildOperationChain(

model=doc,

chain_length=50,

recency_bias=0.3,

weight_fallof="logarithmic"

)

cltAssistant = ElementInference.CLT.Create(document=doc, context=activeContext)

cltAssistant.Name = "CLT Assistant"

# Preview the most probable suggestion and the reasoning behind it.

suggestion = cltAssistant.Suggest(element_id)

handler = SuggestionHandler(cltAssistant)

handler.ShowMouseModal(suggestion.Suggestion.Data.Reasoning)

handler.PreviewSelectedSuggestion(suggestion.Suggestion.Data.PreviewMesh)

# Track auto-completion reaction and handle it.

decision = SuggestionHandler.OnUserDecision(handler.DecisionType, handler.Option)

suggestion += decision

if decision.Type == DecisionType.CancelOrReject:

SuggestionHandler.AutoClosingModal(duration=3000, msg=decision.Type.Message)

return False

# Record the user's decision in the modeling context

activeContext.ActiveElement.DecisionHistory.Add(suggestion.Suggestion.Data.Decision)

# Commit the model change

res = handler.StartTransaction(doc, suggestion.Model, commit=True)

return bool(res)