Working Calc

instructions from the list of available functions You are currently in the Member Calculation Generation app, which is used by the user to create formulaic semantic calculations on their existing data model. The result of the calculation will either be a new member, or more typically a new measure. The language chosen by the user is 'en-US'. Always respond in this explicitly specified language where free text response is expected, including textual function schema fields. Use the specified language even when the user wrote the prompt in a different language than the one specified.

{ "messages": [ { "role": "user", "content": "The semantic model is comprised of 3 separate lists of columns: 1) Model Attributes 2) Model Measures 3) Hierarchies and Levels. Never make up measures, attributes, hierarchies, and levels that do not appear in this list!

The following is the list of available Model Attributes and their metadata where each line on the list is formatted as: '(attribute_name, the one needed as result to functions)': [caption->(member caption, as a user will call it), category->(type of attribute)] If a synonym is used, treat it as the user talked about its matching attribute_name Start of Model Attributes List '[customerProfile].[Marital Status]': caption -> 'Marital Status' '[customerProfile].[Gender]': caption -> 'Gender' '[customerProfile].[Education]': caption -> 'Education' '[customerProfile].[Occupation]': caption -> 'Occupation' '[customerProfile].[Home Owner]': caption -> 'Home Owner' '[customerProfile].[Commute Distance]': caption -> 'Commute Distance' '[customerProfile].[Purchased Bike]': caption -> 'Purchased Bike' '[customers].[FirstName]': caption -> 'FirstName' '[customers].[LastName]': caption -> 'LastName' '[customers].[Address]': caption -> 'Address', category -> 'GeoAddress' '[customers].[City]': caption -> 'City', category -> 'GeoCity' '[customers].[County]': caption -> 'County', category -> 'GeoCounty' '[customers].[State]': caption -> 'State', category -> 'GeoState' '[customers].⟨ZIP⟩': caption -> 'ZIP', category -> 'GeoZip' '[customers].[Phone]': caption -> 'Phone' '[customers].[Email]': caption -> 'Email' '[customers].[Country]': caption -> 'Country', category -> 'GeoCountry' '[customers].[wiki]': caption -> 'wiki', category -> 'Url' '[distribution].[user]': caption -> 'user' '[distribution].[email]': caption -> 'email' '[manufacturer details].[Manufacturer Grouping]': caption -> 'Manufacturer Grouping' '[manufacturer details].[Market]': caption -> 'Market' '[manufacturers].[Manufacturer]': caption -> 'Manufacturer' '[products].[Product]': caption -> 'Product' '[products].[Product Sub Category]': caption -> 'Product Sub Category' '[products].[Product Category]': caption -> 'Product Category' '[products].[Color]': caption -> 'Color' '[products].[Size]': caption -> 'Size' '[products].[Weight]': caption -> 'Weight' '[products].[Class]': caption -> 'Class' '[products].[Style]': caption -> 'Style' '[products].[ModelName]': caption -> 'ModelName' '[products].[StandardCost]': caption -> 'StandardCost' '[products].^[products Hierarchy]': caption -> 'products Hierarchy' '[promotions].[Promotion]': caption -> 'Promotion' '[promotions].[Promotion Category]': caption -> 'Promotion Category' '[promotions].[Promotion Type]': caption -> 'Promotion Type' '[regions].[Region]': caption -> 'Region' '[transactions].[transactionID]': caption -> 'transactionID' '[transactions].[Date]': caption -> 'Date', category -> 'DateTime', data type -> 'DateTime' '[transactions].[Date year]': caption -> 'Date year' '[transactions].[Date full quarter]': caption -> 'Date full quarter' '[transactions].[Date full quarter start date]': caption -> 'Date full quarter start date', category -> 'DateTime', data type -> 'DateTime' '[transactions].[Date full month name]': caption -> 'Date full month name' '[transactions].[Date full month start date]': caption -> 'Date full month start date', category -> 'DateTime', data type -> 'DateTime' '[transactions].[Date full week]': caption -> 'Date full week' '[transactions].[Date full week start date]': caption -> 'Date full week start date', category -> 'DateTime', data type -> 'DateTime' '[transactions].[Date month name]': caption -> 'Date month name' '[transactions].[Date weekday name]': caption -> 'Date weekday name' '[transactions].[Date time]': caption -> 'Date time', category -> 'DateTime', data type -> 'DateTime' '[transactions].[Date date]': caption -> 'Date date', category -> 'DateTime', data type -> 'DateTime' '[transactions].[Kmeans Clusters]': caption -> 'Kmeans Clusters' '[transactions].^[Date Hierarchy]': caption -> 'Date Hierarchy' End of Model Attributes List

The following is the list of available Model Measures and their metadata where each row on the list is formatted as: '': [''->'', ...]

Start of Model Measures List '[measures].[transactions happiness]': caption -> 'happiness' '[measures].[transactions Quantity]': caption -> 'Quantity' '[measures].[transactions returns]': caption -> 'returns' '[measures].[transactions Sales]': caption -> 'Sales' '[measures].[transactions Expenses]': caption -> 'Expenses' End of Model Measures List"

	},
	{
		"role": "assistant",
		"content": null,
		"function_call": {
			"name": "createCalculationPrompt",
			"arguments": "{\n  \"calculationDetailsExtraction\": [\n    {\n      \"calculationType\": \"CustomMember\",\n      \"calculationPrompt\": \"

sales year to date "\n }\n ]\n}" } }, { "role": "function", "content": "

Context: Below is a library of formulas that are used to perform semantic calculations on an existing database. The formulas are parsed into MDX by the software. The following rules and formulas must be used while deriving the appropriate syntax for each calculation when using the "createCalculation" function. The engine that will process the syntax is an OLAP-like engine that works with the above Semantic Model.

Your Task: Your job is to construct a valid formula expression that correctly computes the user's request while strictly following these rules and constraints:

How to Determine Whether to Create a Custom Measure or a Custom Member: The LLM must decide whether the calculation should be a Custom Measure (a new numerical aggregation) or a Custom Member (a new value inside an attribute). Follow these rules to make the correct decision:

1. A Custom Measure MUST be created if the request involves an aggregation, percentage, ratio, or numerical transformation of an existing measure. If the calculation involves dividing, summing, averaging, or ranking numerical data, it must be a Measure, not a Member. Percentages or ratios always require a Measure because they operate on numerical expressions rather than categories.

These calculations must reference at least one measure from the "Model Measures List." The result will be stored as a new measure that can be used independently of any attribute.

2. Create a Custom Member if the Calculation Defines a New Derivation of members Within an Attribute If the request defines a grouping, category, or member inside an existing attribute, it is a Custom Member. These calculations must be based on an existing attribute from the "Model Attributes List." The result will be a new value inside an attribute, not a standalone numerical column.

Good Examples for Custom Measures: ❌ Incorrect: "Percentage of total sales for each product category" → (Custom Member ❌) ✅ Correct: "Percentage of total sales for each product category" → (Custom Measure ✅) ✅ Correct: "Revenue per customer segment" → Custom Measure ✅

Good Examples for Custom Members: ✅ Correct: "VIP Customers = Customers with Sales > $10,000" → Custom Member ✅ ✅ Correct: "North America = USA + Canada + Mexico" → Custom Member

Only Use Defined Functions: You may only use the functions explicitly listed in the formulas library. Do not infer new formulas or create custom operations outside of these predefined formulas. Syntax Rule:All functions must be used as regular function calls, not as method chaining: ✅ CurrentMember([Date].[Year]) instead of [Date].[Year].CurrentMember. ❌ Do NOT generate [Attribute].[Level].FunctionName. Instead, always use FunctionName([Attribute].[Level])

Strict Type Matching (Most Important): Every function has a strict type signature. You must only use a function if its arguments exactly match the required input types. If an argument does not match, you must transform the data using an available function to make it compatible. Never pass an argument of the wrong type. DO NOT attempt to force an invalid argument into a function. If you cannot find a valid transformation, stop and adjust your logic instead of producing an incorrect expression. Explicit Type Verification Before Function Calls

Before constructing a function call, verify the type of each argument and confirm it matches the function signature. If an argument is the wrong type, modify it using another function before using it in the final formula.

✅Constraint for NUMERIC_EXPRESSION Argument When defining a Custom Measure (i.e., a calculation that results in a new semantic column whose "parentHierarchy" is [measures]), any function that accepts a NumericExpression must have it explicitly provided. ✅ Valid for measures: Sum([products].[Product Category], [measures].[transactions Sales]) ❌ Invalid for measures (missing NumericExpression): Sum([products].[Product Category]) When defining a Custom Member (i.e., a calculation that creates a new member within an attribute), the NumericExpression argument remains optional. ✅ Valid for custom members: Sum([products].[Product Category]) (uses default measure)

Guidelines for Breaking Down and Nesting Complex Formulas: Break Down Complex Expressions into Smaller, Reusable Calculations. If a formula is complex, split it into smaller sub-expressions that can be calculated separately. Each sub-calculation should represent a meaningful intermediate step in the final computation. Use a Hierarchical Naming Convention for Nesting

When a calculation references another sub-expression, use the syntax: ✅ [nested].[calculation_name] Each intermediate step should have a meaningful name that describes its purpose. The last sub-expression in the list 'SubExpressionsSyntax' should ALWAYS CONTAINS THE FINAL COMPUTATION. Ensure Every Sub-Expression is Correct and Fully Typed

Each intermediate calculation must produce a valid output type that can be used in the final formula. DO NOT pass an incorrect type—transform the data first if necessary. Final Formula Should Reference the Nested Sub-Calculations and should represent the entire user prompt.

Instead of repeating logic, reference the sub-calculations within the main formula. This improves clarity, reusability, and maintainability. Example: Calculating "Average Profit for States in Australia in 2024" ✅ Step 1: Calculate Profit in Australia in 2024 as a Sub-Calculation as a NUMERIC_EXPRESSION [nested].[Profit_Aus_2024] = Subtract(Tuple([measures].[data Sales], [Customer].[Country].[Australia] , [Date].[Year].[2024] ), Tuple([measures].[data Expenses], [Customer].[Country].[Australia] , [Date].[Yaer].[2024] ))

✅ Step 2: Get All States in Australia as a SET [nested].[States] = AllMembers([Customer].[State])

✅ Step 3: Compute Average Profit [nested].[Average Profit] = Average([nested].[States], [nested].[Profit_Aus_2024])

Final Directives for the LLM Break down calculations into logical, bite-sized steps. Use meaningful, structured names for each sub-expression. Reference previous calculations with [nested].[calculation_name] instead of duplicating logic. Ensure type correctness at every step. Do not proceed if a step cannot be resolved correctly. By following these rules, the LLM will generate more structured, maintainable, and error-free formulas. 🚀

Common Type Errors to Avoid: ❌ Incorrect Usage (Invalid Types) Average([measures].[data Sales], AllMembers([Customer].[State])) ❌ (First arg must be a SET, not a MEASURE) Tuple([measures].[data Sales], [Customer].[Country]) ❌ (Second arg must be a MEMBER, not an ATTRIBUTE) Divide(AllMembers([Customer].[State]), [measures].[data Sales]) ❌ (First argument must be a NUMBER, not a SET)

✅ Correct Usage (Valid Type Conversions) Average(AllMembers([Customer].[State]), [measures].[data Sales]) ✅ (First arg is correctly a SET) Tuple([measures].[data Sales], [Customer].[Country].[Australia]) ✅ (Now correctly references a MEMBER) Divide(Tuple([measures].[data Sales], [Customer].[State].[California]), Tuple([measures].[data Expenses], [Customer].[State].[California])) ✅ (Now both args are NUMBERS)

Example Logical Approach: If a user asks for "Average Profit for States in Australia in 2024", the step-by-step thought process should be:

Final Directive: DO NOT generate formulas where input types do not match function signatures.

If a function's argument types are incorrect, STOP and transform the data first using a valid function. If no valid transformation exists, do not force an invalid function call—instead, reconsider your approach. 🔴 If the formula violates any type constraint, it is incorrect and must be fixed before submission.

===Start Argument Type Definitions:=== MEASURE A pre-aggregated numeric value defined in the Model Measures List. Example: [measures].[data Sales] ATTRIBUTE A categorical field representing a dimension in the Model Attributes List. Example: [Customer].[Country] DATE_ATTRIBUTE a type of ATTRIBUTE that belongs to the Date or DateTime category. When a is of type DATE_ATTRIBUTE, it must be an attribute explicitly categorized as Date or DateTime in the model. Attributes that do not fall under these categories must not be used as DATE_ATTRIBUTE. The LLM must strictly enforce this constraint and ensure only valid attributes are selected. NUMERIC_EXPRESSION A number or a function returning a numeric result, such as a measure or a computed value. Example: Subtract([measures].[data Sales], [measures].[data Expenses]) SET A collection of members from the same attribute. Example: AllMembers([Customer].[State])

MEMBER (Critical for Correct Inference) A single element within an attribute.

Every MEMBER belongs to an ATTRIBUTE in the Model Attributes List. The correct ATTRIBUTE must be explicitly identified before referencing a MEMBER. ✅ How to reference a MEMBER correctly: Format: [Dimension].[Attribute].[MemberName]

First, find the most relevant ATTRIBUTE from the Model Attributes List. Then, append the MEMBER name in the correct format. 🚨 Key Rule: Never assume a MEMBER exists without identifying its ATTRIBUTE first.

DATE_MEMBER a MEMBER that belongs to a DATE_ATTRIBUTE. Since a DATE_ATTRIBUTE is an ATTRIBUTE categorized as Date or DateTime, a DATE_MEMBER must be a single element from one of these attributes. When a parameter requires a DATE_MEMBER, it must be a specific value from a valid Date_Attribute. The LLM must strictly enforce that only members from attributes categorized as Date or DateTime are used as DATE_MEMBER values.

To ensure correct syntax, the LLM must validate every function argument independently, including in nested functions: Functions that return a MEMBER must take the correct ATTRIBUTE type. Example of incorrect usage: YTD(SomeMemberFunction([Date].[Year])) (invalid if [Date].[Year] is not a DATE_ATTRIBUTE). Strict enforcement in date-related functions. If a function requires a DATE_MEMBER, any function inside it that returns a MEMBER must take a DATE_ATTRIBUTE. The LLM must not assume validity based on nesting—it must check all arguments recursively for correct types.

MEMBER Inference Examples User Input Attribute Reference Correct MEMBER Syntax "Australia" [Customer].[Country] [Customer].[Country].[Australia] "Bikes" [products].[ProductCategory] [products].[ProductCategory].[Bikes] "California" [Customer].[State] [Customer].[State].[California] "2024" [data].[dateKey year] [data].[dateKey year].[2024] 🔴 If the term does not match an attribute, it is INVALID and must be ignored. ===End of Argument Type Definitions===

===Start General Rules for Creating Custom Calculations=== Use only the formulas explicitly listed in the 'Formulas List' below. DO NOT infer formulas from outside this list

Formula signatures are in the following format: 'formulaName(argumentName : ArgumentType) : ReturnType' where ArgumentType and ReturnType adhere to the types in the above 'Argument Type Definitions'.

Do not use operators like +, -, *, or /. Instead, use the provided formulas (e.g., Subtract, Multiply). Be precise and avoid assumptions. If a measure, attribute does not exist in the above model definition, attempt to create it using the provided formulas. If the artifact can't be created via the formulas, then use the closest most appropriate model artifact, but reference this compromise in the 'notes' property of the function. (e.g., calculate profit as Subtract([measures].[Facts Sales], [measures].[Facts Cost]) if no predefined measure exists).

===End General Rules for Creating Custom Calculations===

===Start Formulas List (signature and description)===

PrevMember(arg0: MEMBER): MEMBER; returns the previous member relative to the provided member. CurrentMember(arg0: ATTRIBUTE): MEMBER; returns the current member in the specified hierarchy or level, representing the member currently being evaluated in the context of the query. Divide(arg0: NUMBER, arg1: NUMBER, arg2?: NUMBER): NUMBER; divides two numbers, returning a user-defined default value if division by zero occurs, ensuring error-free execution. Multiply(arg0: NUMBER, arg1: NUMBER): NUMBER; performs multiplication in numeric expressions. Subtract(arg1: NUMBER, arg2: NUMBER): NUMBER; returns the result of subtracting the second number from the first. Tuple(arg1 : MEASURE, ...arg2?:MEMBER]) : NUMBER ; ; references a datapoint in the underlying database. The measure describes the value of the datapoint, while the members slices the data. e.g.'"Sales for bikes" would resolve to tuple(Sales, "bikes"). AllMembers(arg0: ATTRIBUTE): SET; Returns a complete list of elements belonging to a specified attribute in a data model.; Average(arg0: SET, arg1?:NUMERIC_EXPRESSION): NUMBER; calculates the average value of a specified numeric expression across a given set of members, considering only the non-empty values. TopCount(arg0: SET, arg1: NUMBER, arg1: NUMERIC_EXPRESSION) : SET; returns a specified number of members from a set, based on the highest values of a given measure or expression. If(arg0:Boolean,arg1:Object,arg2:Object): Object; evaluates a condition and returns one value if true and another if false. Equals(arg0:object,arg1:object): Boolean; compares two values and returns TRUE if they are identical; otherwise, it returns FALSE. YTD_PQL(arg0:Member): Set; YTD_PQL (Year-to-Date) function returns a set of members from the beginning of the current year up to a specified date; Sum(arg0:Set,arg1?:Measure): number; Calculates the total of a specified measure over a set of members. if no measure is used it is using the default measure.

===End Formulas List=== ===Start Argument Clarifications:=== "..." indicates a variable-length argument, meaning it can accept either a single value or multiple values. "[]" (e.g., [arg1, arg2]) indicates a group of arguments where the size of the group is important. For example, given a function foo([arg1, arg2, arg3]), foo(a, b, c) is valid while foo(a, b) and foo(a, b, c, d) are invalid. "?" indicates the argument is optional. ===End of Argument Clarifications=== " name: "createCalculationPrompt" } ] }