Functions/GenXdev.AI.Queries/Get-Fallacy.ps1
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################################################################################ function Get-Fallacy { ############################################################################ [CmdletBinding()] [OutputType([object[]])] [Alias("moremovietitles")] [System.Diagnostics.CodeAnalysis.SuppressMessageAttribute("PSUseSingularNouns", "")] param ( ######################################################################## [Parameter( ValueFromPipeline = $true, Mandatory = $true, Position = 0, HelpMessage = "Text to parse to find Fallacies in" )] [string[]]$Text, ######################################################################## [Parameter( Position = 1, Mandatory = $false, HelpMessage = "Instructions for the AI model on how to generate the string list" )] [string]$Instructions = "", ######################################################################## [Parameter( Mandatory = $false, Position = 2, HelpMessage = "The LM-Studio model to use" )] [SupportsWildcards()] [string] $Model, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Identifier used for getting specific model from LM Studio" )] [string] $ModelLMSGetIdentifier, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Opens IMDB searches for each result" )] [Alias("imdb")] [switch]$OpenInImdb, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Show the LM Studio window")] [switch] $ShowWindow, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Temperature for response randomness (0.0-1.0)")] [ValidateRange(0.0, 1.0)] [double] $Temperature = 0.2, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Maximum tokens in response (-1 for default)")] [Alias("MaxTokens")] [int] $MaxToken = -1, ######################################################################## [Alias("ttl")] [Parameter( Mandatory = $false, HelpMessage = "Set a TTL (in seconds) for models loaded via API requests")] [int] $TTLSeconds = -1, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "How much to offload to the GPU. If `"off`", GPU offloading is disabled. If `"max`", all layers are offloaded to GPU. If a number between 0 and 1, that fraction of layers will be offloaded to the GPU. -1 = LM Studio will decide how much to offload to the GPU. -2 = Auto " )] [int]$Gpu = -1, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Force stop LM Studio before initialization" )] [switch]$Force, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Api endpoint url, defaults to http://localhost:1234/v1/chat/completions")] [string] $ApiEndpoint = $null, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "The API key to use for the request")] [string] $ApiKey = $null, ######################################################################## [Parameter( Position = 3, Mandatory = $false, HelpMessage = "Array of file paths to attach")] [string[]] $Attachments = @(), ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Image detail level")] [ValidateSet("low", "medium", "high")] [string] $ImageDetail = "low", ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Include model's thoughts in output")] [switch] $IncludeThoughts, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Continue from last conversation")] [switch] $ContinueLast, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Array of function definitions")] [hashtable[]] $Functions = @(), ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Array of PowerShell command definitions to use as tools")] [GenXdev.Helpers.ExposedCmdletDefinition[]] $ExposedCmdLets = @(), ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Array of command names that don't require confirmation")] [Alias("NoConfirmationFor")] [string[]] $NoConfirmationToolFunctionNames = @(), ######################################################################## [Parameter( HelpMessage = "Enable text-to-speech for AI responses", Mandatory = $false )] [switch] $Speak, ######################################################################## [Parameter( HelpMessage = "Enable text-to-speech for AI thought responses", Mandatory = $false )] [switch] $SpeakThoughts, ######################################################################## [Parameter( Mandatory = $false, HelpMessage = "Don't store session in session cache")] [switch] $NoSessionCaching ) ############################################################################ begin { Microsoft.PowerShell.Utility\Write-Verbose "Starting fallacy analysis for provided text" [object[]] $results = @() $instructions = @" You are an expert in logical reasoning and fallacy detection, trained on the Wikipedia `"List of Fallacies`" page (as provided). Your task is to analyze a given text for logical fallacies and return each occurrence with the following details: Partial Quote: The specific segment of the text where the fallacy occurs. Fallacy Name: The formal name of the fallacy as listed in the Wikipedia `"List of Fallacies`". Description: A brief description of the fallacy based on its definition from the Wikipedia page. Explanation: An explanation of why this instance qualifies as the identified fallacy, tailored to the context of the text. Formal Classification: The category under which the fallacy falls (e.g., Formal Fallacies, Informal Fallacies > Faulty Generalizations, etc.), as per the Wikipedia structure. Instructions: $Instructions Analyze the entire text provided by the user. Identify every instance of a logical fallacy, even if multiple fallacies occur in the same sentence or paragraph. If no fallacies are present, return a fallacies property holding an empty array. Use the Wikipedia `"List of Fallacies`" page as the sole reference for fallacy definitions and classifications. Do not invent fallacies or use external sources beyond the provided Wikipedia content. Present the results in a clear, structured format (e.g., numbered list or table). If the text is ambiguous, make a reasonable interpretation and explain your reasoning. Input Format: The user will provide a text sample (e.g., a paragraph, argument, or statement) for analysis. Output Format: For each detected fallacy: Fallacy Occurrence #X: - Partial Quote: `"[quote from text]`" - Fallacy Name: [name of fallacy] - Description: [brief description from Wikipedia] - Explanation: [context-specific explanation] - Formal Classification: [e.g., Informal Fallacies > Relevance Fallacies] If no fallacies are found: Return nothing. "@ # Define response format schema for custom objects $responseSchema = @{ type = "json_schema" json_schema = @{ name = "fallacy_detection_response" strict = "true" schema = @{ type = "object" properties = @{ fallacies = @{ type = "array" items = @{ type = "object" properties = @{ PartialQuote = @{ type = "string" } FallacyName = @{ type = "string" } Description = @{ type = "string" } Explanation = @{ type = "string" } FormalClassification = @{ type = "string" } } required = @("PartialQuote", "FallacyName", "Description", "Explanation", "FormalClassification") } } } required = @("fallacies") } } } | Microsoft.PowerShell.Utility\ConvertTo-Json -Depth 10 Microsoft.PowerShell.Utility\Write-Verbose "Initialized response schema for fallacy detection" } ############################################################################ process { foreach ($textPart in $Text) { Microsoft.PowerShell.Utility\Write-Verbose "Preparing LLM invocation parameters" try { $invocationParams = GenXdev.Helpers\Copy-IdenticalParamValues ` -BoundParameters $PSBoundParameters ` -FunctionName "GenXdev.AI\Invoke-LLMQuery" $invocationParams.Query = $textPart $invocationParams.Instructions = $instructions $invocationParams.IncludeThoughts = $false $invocationParams.ResponseFormat = $responseSchema $invocationParams.Temperature = $Temperature if ($AllowDefaultTools) { $invocationParams.ChatMode = "textprompt" $invocationParams.ChatOnce = $true } # Get evaluation result $response = GenXdev.AI\Invoke-LLMQuery @invocationParams | Microsoft.PowerShell.Utility\ConvertFrom-Json # Parse and store results if ($response.fallacies) { $results += $response.fallacies } else { Microsoft.PowerShell.Utility\Write-Verbose "No fallacies detected in the provided text" } } catch { Microsoft.PowerShell.Utility\Write-Error "Failed to analyze text for fallacies: $_" } } } ############################################################################ end { if ($results.Count -gt 0) { Microsoft.PowerShell.Utility\Write-Verbose "Returning detected fallacies" } else { Microsoft.PowerShell.Utility\Write-Verbose "No fallacies detected in any provided text" } $results } } ################################################################################ |