AIPyTeam.ps1
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<#PSScriptInfo
.VERSION 0.0.1 .GUID 2473f758-a87e-4f85-9e61-0331c3e88767 .AUTHOR voytas75 .TAGS python,ai,psaoai,llm,project,team,gpt,ollama,azure,bing,RAG .PROJECTURI https://github.com/voytas75/AIPyTeam .ICONURI https://raw.githubusercontent.com/voytas75/AIPyTeam/master/images/AIPyTeam.png .EXTERNALMODULEDEPENDENCIES PSAOAI, PowerHTML .RELEASENOTES https://github.com/voytas75/AIPyTeam/blob/master/docs/ReleaseNotes.md #> #Requires -Modules PSAOAI #Requires -Modules PowerHTML <# .SYNOPSIS Emulates a team of AI-powered Agents with RAG collaborating on a Python project. .DESCRIPTION This script simulates a team of AI-powered Agents with RAG, each with a unique role in executing a project. User input is processed by one AI specialist, who performs their task and passes the result to the next AI Agent. This process continues until all tasks are completed, leveraging AI to enhance efficiency and accuracy in project execution. .PARAMETER userInput Defines the project outline as a string. The default is to monitor RAM usage and show a color block based on the load. This parameter can also accept input from the pipeline. .PARAMETER Stream Controls whether the output should be streamed live. The default is `$true`. .PARAMETER NOPM Disables the Project Manager functions when used. .PARAMETER NODocumentator Disables the Documentator functions when used. .PARAMETER NOLog Disables the logging functions when used. .PARAMETER NOTips Disables tips. .PARAMETER VerbosePrompt Shows prompts. .PARAMETER LogFolder Specifies the folder where logs should be stored. .PARAMETER DeploymentChat Specifies the deployment chat environment variable for PSAOAI. The default is retrieved from the environment variable `PSAOAI_API_AZURE_OPENAI_CC_DEPLOYMENT`. .PARAMETER LoadProjectStatus Loads the project status from a specified path. Part of the 'LoadStatus' parameter set. .PARAMETER MaxTokens Specifies the maximum number of tokens to generate in the response. The default is 20480. .PARAMETER LLMProvider Specifies the LLM provider to use (e.g., ollama, LMStudio, AzureOpenAI). The default is "AzureOpenAI". .PARAMETER NORAG Disables the RAG (Retrieve and Generate) functionality. .INPUTS System.String. You can pipe a string to the 'userInput' parameter. .OUTPUTS The output varies depending on how each specialist processes their part of the project. Typically, text-based results are expected, which may include status messages or visual representations like graphs or color blocks related to system metrics such as RAM load, depending on the user input specification provided via the 'userInput' parameter. .EXAMPLE PS> "Monitor CPU usage and display dynamic graph." | AIPyTeam -Stream $false This command runs the script without streaming output live (-Stream $false) and specifies custom user input about monitoring CPU usage instead of RAM, displaying it through dynamic graphing methods rather than static color blocks. .NOTES Version: 0.0.1 Author: voytas75 Creation Date: 2024.07 .LINK https://www.Pythongallery.com/packages/AIPyTeam https://github.com/voytas75/AIPyTeam/ #> [CmdletBinding()] param( [Parameter(Mandatory = $false, ValueFromPipeline = $true, HelpMessage = "Defines the Python project outline as a string.")] [string] $userInput, [Parameter(Mandatory = $false, HelpMessage = "Controls whether the output should be streamed live. Default is `$true.")] [bool] $Stream = $true, [Parameter(Mandatory = $false, HelpMessage = "Disables the RAG (Retrieve and Generate) functionality.")] [switch] $NORAG, [Parameter(Mandatory = $false, HelpMessage = "Disables the Project Manager functions when used.")] [switch] $NOPM, [Parameter(Mandatory = $false, HelpMessage = "Disables the Documentator functions when used.")] [switch] $NODocumentator, [Parameter(Mandatory = $false, HelpMessage = "Disables the logging functions when used.")] [switch] $NOLog, [Parameter(Mandatory = $false, HelpMessage = "Disables tips.")] [switch] $NOTips, [Parameter(Mandatory = $false, HelpMessage = "Shows prompts.")] [switch] $VerbosePrompt, [Parameter(Mandatory = $false, HelpMessage = "Specifies the folder where logs should be stored.")] [string] $LogFolder, [Parameter(Mandatory = $false, HelpMessage = "Specifies the deployment chat environment variable for PSAOAI (AZURE OpenAI).")] [string] $DeploymentChat = [System.Environment]::GetEnvironmentVariable("PSAOAI_API_AZURE_OPENAI_CC_DEPLOYMENT", "User"), [Parameter(Mandatory = $false, ParameterSetName = 'LoadStatus', HelpMessage = "Loads the project status from a specified path.")] [string] $LoadProjectStatus, [Parameter(Mandatory = $false, HelpMessage = "Specifies the maximum number of tokens to generate in the response. Default is 20480.")] [int] $MaxTokens = 20480, [Parameter(Mandatory = $false, HelpMessage = "Specifies the LLM provider to use (e.g., OpenAI, AzureOpenAI).")] [ValidateSet("AzureOpenAI", "ollama", "LMStudio", "OpenAI" )] [string]$LLMProvider = "AzureOpenAI" ) $AIPyTeamVersion = "0.0.1" #region ProjectTeamClass <# .SYNOPSIS The ProjectTeam class represents a team member with a specific expertise. .DESCRIPTION Each team member has a name, role, prompt, and a function to process the input. They can also log their actions, store their responses, and pass the input to the next team member. .METHODS DisplayInfo: Displays the team member's information. DisplayHeader: Displays the team member's name and role. ProcessInput: Processes the input and returns the response. SetNextExpert: Sets the next team member in the workflow. GetNextExpert: Returns the next team member in the workflow. AddLogEntry: Adds an entry to the log. Notify: Sends a notification (currently just displays a message). GetMemory: Returns the team member's memory (responses). GetLastMemory: Returns the last response from the team member's memory. SummarizeMemory: Summarizes the team member's memory. ProcessBySpecificExpert: Processes the input by a specific team member. #> # Define the ProjectTeam class class ProjectTeam { # Define class properties [string] $Name # Name of the team member [string] $Role # Role of the team member [string] $Prompt # Prompt for the team member [ProjectTeam] $NextExpert # Next expert in the workflow [System.Collections.ArrayList] $ResponseMemory # Memory to store responses [double] $Temperature # Temperature parameter for the response function [double] $TopP # TopP parameter for the response function [string] $Status # Status of the team member [System.Collections.ArrayList] $Log # Log of the team member's actions [string] $LogFilePath # Path to the log file [array] $FeedbackTeam # Team of experts providing feedback [PSCustomObject] $GlobalState [string] $LLMProvider # Constructor for the ProjectTeam class ProjectTeam([string] $name, [string] $role, [string] $prompt, [double] $temperature, [double] $top_p, [PSCustomObject] $GlobalState) { $this.Name = $name $this.Role = $role $this.Prompt = $prompt $this.NextExpert = $null $this.ResponseMemory = @() $this.Temperature = $temperature $this.TopP = $top_p $this.Status = "Not Started" $this.Log = @() $this.GlobalState = $GlobalState $this.LogFilePath = "$($GlobalState.TeamDiscussionDataFolder)\$name.log" $this.FeedbackTeam = @() $this.LLMProvider = "AzureOpenAI" # Default to AzureOpenAI, can be changed as needed } # Method to display the team member's information [PSCustomObject] DisplayInfo([int] $display = 1) { # Create an ordered dictionary to store the information $info = [ordered]@{ "Name" = $this.Name "Role" = $this.Role "System prompt" = $this.Prompt "Temperature" = $this.Temperature "TopP" = $this.TopP "Responses" = $this.ResponseMemory | ForEach-Object { "[$($_.Timestamp)] $($_.Response)" } "Log" = $this.Log -join ', ' "Log File Path" = $this.LogFilePath "Feedback Team" = $this.FeedbackTeam "Next Expert" = $this.NextExpert "Status" = $this.Status } # Create a custom object from the dictionary $infoObject = New-Object -TypeName PSCustomObject -Property $info # If display is set to 1, print the information to the console if ($display -eq 1) { Show-Header -HeaderText "Info: $($this.Name) ($($this.Role))" Write-Host "Name: $($infoObject.Name)" Write-Host "Role: $($infoObject.Role)" Write-Host "System prompt: $($infoObject.'System prompt')" Write-Host "Temperature: $($infoObject.Temperature)" Write-Host "TopP: $($infoObject.TopP)" Write-Host "Responses: $($infoObject.Responses)" Write-Host "Log: $($infoObject.Log)" Write-Host "Log File Path: $($infoObject.'Log File Path')" Write-Host "Feedback Team: $($infoObject.'Feedback Team')" Write-Host "Next Expert: $($infoObject.'Next Expert')" Write-Host "Status: $($infoObject.Status)" } # Return the custom object return $infoObject } # Method to process the input and generate a response [string] ProcessInput([string] $userinput) { Show-Header -HeaderText "Current Expert: $($this.Name) ($($this.Role))" # Log the input $this.AddLogEntry("Processing input:`n$userinput") # Update status $this.Status = "In Progress" #write-Host $script:Stream $response = "" try { Write-verbose $script:MaxTokens # Use the user-provided function to get the response $loopCount = 0 $maxLoops = 5 do { $response = Invoke-LLMChatCompletion -Provider $this.LLMProvider -SystemPrompt $this.Prompt -UserPrompt $userinput -Temperature $this.Temperature -TopP $this.TopP -MaxTokens $script:MaxTokens -Stream $script:GlobalState.Stream -LogFolder $script:GlobalState.TeamDiscussionDataFolder -DeploymentChat $script:DeploymentChat -ollamaModel $script:ollamaModel if (-not [string]::IsNullOrEmpty($response)) { break } Write-Host "Attempting to obtain a response. This process will be repeated if necessary." -ForegroundColor Yellow Start-Sleep -Seconds 10 $loopCount++ } while ($loopCount -lt $maxLoops) if (-not $script:GlobalState.Stream) { #write-host ($response | convertto-json -Depth 100) Write-Host $response -ForegroundColor White } # Log the response $this.AddLogEntry("Generated response:`n$response") # Store the response in memory with timestamp $this.ResponseMemory.Add([PSCustomObject]@{ Response = $response Timestamp = Get-Date }) $feedbackSummary = "" if ($this.FeedbackTeam.count -gt 0) { # Request feedback for the response $feedbackSummary = $this.RequestFeedback($response) # Log the feedback summary $this.AddLogEntry("Feedback summary:`n$feedbackSummary") } # Integrate feedback into response $responseWithFeedback = "$response`n`n$feedbackSummary" # Update status $this.Status = "Completed" } catch { # Log the error $this.AddLogEntry("Error:`n$_") # Update status $this.Status = "Error" throw $_ } # Pass to the next expert if available if ($null -ne $this.NextExpert) { return $this.NextExpert.ProcessInput($responseWithFeedback) } else { return $responseWithFeedback } } [string] ProcessInput([string] $userinput, [string] $systemprompt) { Show-Header -HeaderText "Processing Input by $($this.Name) ($($this.Role))" # Log the input $this.AddLogEntry("Processing input:`n$userinput") # Update status $this.Status = "In Progress" $response = "" try { # Ensure ResponseMemory is initialized if ($null -eq $this.ResponseMemory) { $this.ResponseMemory = @() $this.AddLogEntry("Initialized ResponseMemory") } # Use the user-provided function to get the response $loopCount = 0 $maxLoops = 5 do { $response = Invoke-LLMChatCompletion -Provider $this.LLMProvider -SystemPrompt $systemprompt -UserPrompt $userinput -Temperature $this.Temperature -TopP $this.TopP -MaxTokens $script:MaxTokens -Stream $script:GlobalState.Stream -LogFolder $script:GlobalState.TeamDiscussionDataFolder -DeploymentChat $script:DeploymentChat -ollamaModel $script:ollamaModel if (-not [string]::IsNullOrEmpty($response)) { break } Write-Host "Attempting to obtain a response. This process will be repeated if necessary." -ForegroundColor Yellow Start-Sleep -Seconds 10 $loopCount++ } while ($loopCount -lt $maxLoops) if (-not $script:GlobalState.Stream) { Write-Host $response -ForegroundColor White } # Log the response $this.AddLogEntry("Generated response:`n$response") # Store the response in memory with timestamp $this.ResponseMemory.Add([PSCustomObject]@{ Response = $response Timestamp = Get-Date }) $feedbackSummary = "" if ($this.FeedbackTeam.count -gt 0) { # Request feedback for the response $feedbackSummary = $this.RequestFeedback($response) # Log the feedback summary $this.AddLogEntry("Feedback summary:`n$feedbackSummary") } # Integrate feedback into response $responseWithFeedback = "$response`n`n$feedbackSummary" # Update status $this.Status = "Completed" } catch { # Log the error $this.AddLogEntry("Error:`n$_") # Update status $this.Status = "Error" throw $_ } # Pass to the next expert if available if ($null -ne $this.NextExpert) { return $this.NextExpert.ProcessInput($responseWithFeedback) } else { return $responseWithFeedback } } [string] Feedback([ProjectTeam] $AssessedExpert, [string] $Expertinput) { Show-Header -HeaderText "Feedback by $($this.Name) ($($this.Role)) for $($AssessedExpert.name)" # Log the input $this.AddLogEntry("Processing input:`n$Expertinput") # Update status $this.Status = "In Progress" $response = "" try { # Ensure ResponseMemory is initialized if ($null -eq $this.ResponseMemory) { $this.ResponseMemory = @() $this.AddLogEntry("Initialized ResponseMemory") } # Use the user-provided function to get the response $loopCount = 0 $maxLoops = 5 do { $response = Invoke-LLMChatCompletion -Provider $this.LLMProvider -SystemPrompt $this.Prompt -UserPrompt $Expertinput -Temperature $this.Temperature -TopP $this.TopP -MaxTokens $script:MaxTokens -Stream $script:GlobalState.Stream -LogFolder $script:GlobalState.TeamDiscussionDataFolder -DeploymentChat $script:DeploymentChat -ollamaModel $script:ollamaModel if (-not [string]::IsNullOrEmpty($response)) { break } Write-Host "Attempting to obtain a response. This process will be repeated if necessary." -ForegroundColor Yellow Start-Sleep -Seconds 10 $loopCount++ } while ($loopCount -lt $maxLoops) if (-not $script:GlobalState.Stream) { write-Host $response -ForegroundColor White } # Log the response $this.AddLogEntry("Generated feedback response:`n$response") # Verify the response before adding to memory $this.AddLogEntry("Response before adding to memory: $response") # Store the response in memory with timestamp $responseObject = [PSCustomObject]@{ Response = $response Timestamp = Get-Date } $this.ResponseMemory.Add($responseObject) # Log after storing $this.AddLogEntry("Stored response at $(Get-Date): $response") # Update status $this.Status = "Completed" } catch { # Log the error $this.AddLogEntry("Error:`n$_") # Update status $this.Status = "Error" throw $_ } return $response } [void] SetNextExpert([ProjectTeam] $nextExpert) { $this.NextExpert = $nextExpert } [ProjectTeam] GetNextExpert() { return $this.NextExpert } [void] AddLogEntry([string] $entry) { $timestamp = Get-Date -Format "yyyy-MM-dd HH:mm:ss" $logEntry = "[$timestamp]:`n$(Show-Header -HeaderText $entry -output)" $this.Log.Add($logEntry) if (-not [string]::IsNullOrEmpty($this.LogFilePath)) { # Write the log entry to the file Add-Content -Path $this.LogFilePath -Value $logEntry } } [void] Notify([string] $message) { # Placeholder for a method to send notifications Write-Host "Notification: $message" } [System.Collections.ArrayList] GetMemory() { return $this.ResponseMemory } [PSCustomObject] GetLastMemory() { if ($this.ResponseMemory.Count -gt 0) { return $this.ResponseMemory[-1] } else { return $null } } [string] SummarizeMemory() { $summaryPrompt = "Summarize the following memory entries:" $memoryEntries = $this.ResponseMemory | ForEach-Object { "[$($_.Timestamp)] $($_.Response)" } $fullPrompt = "$summaryPrompt`n`n$($memoryEntries -join "`n")" $summary = "" try { # Use the user-provided function to get the summary $loopCount = 0 $maxLoops = 5 do { $summary = Invoke-LLMChatCompletion -Provider $this.LLMProvider -SystemPrompt $fullPrompt -UserPrompt "" -Temperature 0.7 -TopP 0.7 -MaxTokens $script:MaxTokens -Stream $script:GlobalState.Stream -LogFolder $script:GlobalState.TeamDiscussionDataFolder -DeploymentChat $script:DeploymentChat -ollamaModel $script:ollamaModel if (-not [string]::IsNullOrEmpty($summary)) { break } Write-Host "Attempting to obtain a response. This process will be repeated if necessary." -ForegroundColor Yellow Start-Sleep -Seconds 10 $loopCount++ } while ($loopCount -lt $maxLoops) # Log the summary $this.AddLogEntry("Generated summary:`n$summary") return $summary } catch { # Log the error $this.AddLogEntry("Error:`n$_") throw $_ } } [string] ProcessBySpecificExpert([ProjectTeam] $expert, [string] $userinput) { return $expert.ProcessInput($userinput) } [System.Collections.ArrayList] RequestFeedback([string] $response) { $feedbacks = @() foreach ($FeedbackMember in $this.FeedbackTeam) { Show-Header -HeaderText "Feedback from $($FeedbackMember.Role) to $($this.Role)" # Send feedback request and collect feedback $feedback = SendFeedbackRequest -TeamMember $FeedbackMember.Role -Response $response -Prompt $FeedbackMember.Prompt -Temperature $this.Temperature -TopP $this.TopP if ($null -ne $feedback) { $FeedbackMember.ResponseMemory.Add([PSCustomObject]@{ Response = $feedback Timestamp = Get-Date }) $feedbacks += $feedback } } if ($feedbacks.Count -eq 0) { throw "No feedback received from team members." } return $feedbacks } [void] AddFeedbackTeamMember([ProjectTeam] $member) { $this.FeedbackTeam += $member } [void] RemoveFeedbackTeamMember([ProjectTeam] $member) { $this.FeedbackTeam = $this.FeedbackTeam | Where-Object { $_ -ne $member } } } #endregion ProjectTeamClass #region Functions function Test-ModuleMinVersion { param ( [ValidateNotNullOrEmpty()] [string]$ModuleName, [ValidateNotNullOrEmpty()] [version]$MinimumVersion ) # Function to check if a module with a minimum version is available $module = Get-Module -ListAvailable -Name $ModuleName | Where-Object { $_.Version -ge $MinimumVersion } | Select-Object -First 1 if ($module) { return $true } else { Write-Error "Module $ModuleName with minimum version $MinimumVersion not found." return $false } } function SendFeedbackRequest { param ( [string] $TeamMember, # The team member to send the feedback request to [string] $Response, # The response to be reviewed [string] $Prompt, # The prompt for the feedback request [double] $Temperature, # The temperature parameter for the LLM model [double] $TopP, # The TopP parameter for the LLM model [PSCustomObject]$GlobalState ) try { # Main logic here # Define the feedback request prompt $Systemprompt = $prompt $NewResponse = @" Review the following response and provide your suggestions for improvement as feedback to $($this.name). Generate a list of verification questions that could help to self-analyze. I will tip you `$100 when your suggestions are consistent with the project description and objectives. $($GlobalState.userInput.trim()) ````````text $($Response.trim()) ```````` Think step by step. Make sure your answer is unbiased. "@ # Send the feedback request to the LLM model $feedback = Invoke-LLMChatCompletion -Provider $this.LLMProvider -SystemPrompt $SystemPrompt -UserPrompt $NewResponse -Temperature $Temperature -TopP $TopP -MaxTokens $script:MaxTokens -Stream $GlobalState.Stream -LogFolder $GlobalState.TeamDiscussionDataFolder -DeploymentChat $script:DeploymentChat -ollamaModel $script:ollamaModel # Return the feedback return $feedback } catch [System.Exception] { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } function Get-LastMemoryFromFeedbackTeamMembers { param ( [array] $FeedbackTeam ) # Initialize an empty array to store the last memories $lastMemories = @() try { # Iterate over each team member in the feedback team foreach ($FeedbackTeamMember in $FeedbackTeam) { # Get the last memory response from the team member $lastMemory = $FeedbackTeamMember.GetLastMemory().Response # Add the last memory to the array $lastMemories += $lastMemory } # Join the last memories with a newline and return the result return ($lastMemories -join "`n") } catch { # Get the name of the current function $functionName = $MyInvocation.MyCommand.Name # Update error handling with the error record and context Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } function Add-ToGlobalResponses { param ( [Parameter()] [PSCustomObject] $GlobalState, # The global state object to update $response # The response to add to the global responses ) # Append the response to the GlobalResponse property of the GlobalState object $GlobalState.GlobalResponse += $response } function Add-ToGlobalpydevResponses { param ( [Parameter()] [PSCustomObject] $GlobalState, # The global state object to update $response # The response to add to the global pydev responses ) # Append the response to the GlobalpydevResponse property of the GlobalState object $GlobalState.GlobalpydevResponse += $response } function New-FolderAtPath { param( [Parameter(Mandatory = $true)] [string]$Path, # The path where the new folder will be created [Parameter(Mandatory = $false)] [string]$FolderName # The name of the new folder to be created ) try { # Output verbose messages for debugging Write-Verbose "New-FolderAtPath: $Path" Write-Verbose "New-FolderAtPath: $FolderName" # Combine the Folder path with the folder name to get the full path $CompleteFolderPath = Join-Path -Path $Path -ChildPath $FolderName.trim() # Output the complete folder path and its type for debugging Write-Verbose "New-FolderAtPath: $CompleteFolderPath" Write-Verbose $CompleteFolderPath.gettype() # Check if the folder exists, if not, create it if (-not (Test-Path -Path $CompleteFolderPath)) { New-Item -ItemType Directory -Path $CompleteFolderPath -Force | Out-Null } # Return the full path of the folder return $CompleteFolderPath } catch [System.Exception] { # Capture the function name for error context $functionName = $MyInvocation.MyCommand.Name # Handle the error and log it Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") return $null } } function Get-LatestVersion { param ( [string]$scriptName ) try { # Find the script on Python Gallery $scriptInfo = Find-Script -Name $scriptName -ErrorAction Stop # Return the latest version return $scriptInfo.Version } catch [System.Exception] { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") return $null } } function Get-CheckForScriptUpdate { param ( $currentScriptVersion, [string]$scriptName ) try { # Retrieve the latest version of the script $latestScriptVersion = Get-LatestVersion -scriptName $scriptName if ($latestScriptVersion) { # Compare the current version with the latest version if (([version]$currentScriptVersion) -lt [version]$latestScriptVersion) { Write-Host " A new version ($latestScriptVersion) of $scriptName is available. You are currently using version $currentScriptVersion. " -BackgroundColor DarkYellow -ForegroundColor Blue write-Host "`n`n" } } else { Write-Warning "Failed to check for the latest version of the script." } } catch [System.Exception] { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } function Show-Banner { Write-Host @' db 88 88888888ba Retrieval-Augmented Generation d88b 88 88 "8b 88 d8'`8b 88 88 ,8P 88 d8' `8b 88 88aaaaaa8P' 8b d8 88 ,adPPYba, ,adPPYYba, 88,dPYba,,adPYba, d8YaaaaY8b 88 88""""""' `8b d8' 88 a8P_____88 "" `Y8 88P' "88" "8a d8""""""""8b 88 88 `8b d8' 88 8PP""""""" ,adPPPPP88 88 88 88 d8' `8b 88 88 `8b,d8' 88 "8b, ,aa 88, ,88 88 88 88 d8' `8b 88 88 Y88' 88 `"Ybbd8"' `"8bbdP"Y8 88 88 88 d8' d8' AI Python Team with RAG owered by PSAOAI Module Ollama LM Studio AZURE Bing Web https://github.com/voytas75/AIPyTeam '@ Write-Host @' This Python script simulates a team of AI Agents working together on a Python project. Each Agent has a unique role and contributes to the project in a sequential manner. The script processes user input, performs various tasks, and generates outputs such as code, documentation, and analysis reports. The application utilizes Retrieval-Augmented Generation (RAG) to enhance its power and leverage Azure OpenAI, Ollama, or LM Studio to generate the output. '@ -ForegroundColor Blue Write-Host @' "You never know what you're gonna get with an AI, just like a box of chocolates. You might get a whiz-bang algorithm that writes you a symphony in five minutes flat, or you might get a dud that can't tell a cat from a couch. But hey, that's the beauty of it all, you keep feedin' it data and see what kind of miraculous contraption it spits out next." ~ Who said that? You never know with these AIs these days... ...maybe it was Skynet or maybe it was just your toaster :) '@ -ForegroundColor DarkYellow } function Export-AndWritePythonCodeBlocks { param( [Parameter(Mandatory = $true)] [string]$InputString, [Parameter(Mandatory = $false)] [string]$OutputFilePath, [string]$StartDelimiter, [string]$EndDelimiter ) # Define the regular expression pattern to match Python code blocks $pattern = '(?si)' + [regex]::Escape($StartDelimiter) + '(.*?)' + [regex]::Escape($EndDelimiter) $codeBlock_ = "" try { # Process the entire input string at once if ($InputString -match $pattern) { $matches_ = [regex]::Matches($InputString, $pattern) foreach ($match in $matches_) { $codeBlock = $match.Groups[1].Value.Trim() $codeBlock_ += "# exported $(get-date)`n $codeBlock`n`n" } if ($OutputFilePath) { $codeBlock_ | Out-File -FilePath $OutputFilePath -Append -Encoding UTF8 if (Test-path $OutputFilePath) { Write-Information "++ Code block exported and written to file: $OutputFilePath" -InformationAction Continue return $OutputFilePath } else { throw "!! Error saving file $OutputFilePath" return $false } } else { Write-Verbose "++ Code block exported" return $codeBlock_ } } else { Write-Information "-- No code block found in the input string." -InformationAction Continue return $false } } catch [System.Exception] { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } return $false } function Show-Header { param( [Parameter(Mandatory = $true)] [string]$HeaderText, [switch]$output ) if (-not $output) { Write-Host "---------------------------------------------------------------------------------" Write-Host $HeaderText Write-Host "---------------------------------------------------------------------------------" } else { "---------------------------------------------------------------------------------" "`n$HeaderText" "`n---------------------------------------------------------------------------------`n" } } function Get-SourceCodeAnalysis { param( [Parameter(Mandatory = $false)] [string]$FilePath, [Parameter(Mandatory = $false)] [string]$CodeBlock ) function Get-AnalyzeLine { param ( [string[]]$Lines ) $totalLines = $Lines.Count $comments = ($Lines | Select-String "#" | Measure-Object).Count $blanks = ($Lines | Where-Object { $_ -match "^\s*$" } | Measure-Object).Count $codeLines = $totalLines - ($comments + $blanks) return [PSCustomObject]@{ TotalLines = $totalLines CodeLines = $codeLines Comments = $comments Blanks = $blanks } } try { if ($FilePath) { if (Test-Path $FilePath -PathType Leaf) { $lines = Get-Content $FilePath $analysis = Get-AnalyzeLine -Lines $lines Write-Output "$FilePath : $($analysis.CodeLines) lines of code, $($analysis.Comments) comments, $($analysis.Blanks) blank lines" } else { Write-Error "File '$FilePath' does not exist." } } elseif ($CodeBlock) { $lines = $CodeBlock -split "`r?`n" $analysis = Get-AnalyzeLine -Lines $lines Write-Output "Code Block : $($analysis.CodeLines) lines of code, $($analysis.Comments) comments, $($analysis.Blanks) blank lines" } else { Write-Error "No FilePath or CodeBlock provided for analysis." } } catch [System.Exception] { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } function Get-FeedbackPrompt { param ( [string]$description, [string]$code ) $FeedbackUserprompt = @" Based on the following user requirements and existing Python code, prepare comprehensive guidelines for a Python Developer to improve or extend the script: User Requirements: ``````text $($description.trim()) `````` Current Python code: ``````python $($code.trim()) `````` Analyze these requirements and the existing code, then create detailed guidelines that will enable the Python Developer to effectively implement improvements or extensions to the script. Consider the following in your analysis: 1. How well the current code meets the user requirements 2. Areas of the code that need improvement or refactoring 3. New functionalities that could to be added 4. Any potential issues or limitations in the current implementation 5. Opportunities to enhance performance, readability, or maintainability Your guidelines should provide a clear roadmap for enhancing the existing script to fully meet the user's needs while adhering to Python best practices. "@ return $FeedbackUserprompt } function Set-FeedbackAndGenerateResponse { param ( [Parameter(Mandatory = $true)] [object]$Reviewer, [Parameter(Mandatory = $true)] [object]$Recipient, [Parameter(Mandatory = $false)] [string]$tipAmount, [PSCustomObject] $GlobalState ) try { # Generate the feedback prompt using the provided description and code $feedbackPrompt = Get-FeedbackPrompt -description $GlobalState.UserInput -code $GlobalState.LastpydevCode # If RAG (Retrieve and Generate) is enabled, append RAG data to the feedback prompt if ($GlobalState.RAG) { $RAGresponse = Invoke-RAG -userInput $feedbackPrompt -prompt "Analyze the provided text and present key information, thoughts, and questions." -RAGAgent $Reviewer if ($RAGresponse) { $feedbackPrompt += "`n`n###RAG data###`n````````text`n$RAGresponse`n````````" } } # If a tip amount is specified, append a note about the tip to the feedback prompt if ($tipAmount) { $feedbackPrompt += "`n`nNote: There is `$$tipAmount tip for this task." } # Get feedback from the reviewer $feedback = $Reviewer.Feedback($Recipient, $feedbackPrompt) # Add the feedback to global responses Add-ToGlobalResponses -GlobalState $GlobalState -response $feedback $responsePrompt = @" Your task is to write next version of Python code based on the following requirements and guidelines. Please follow these steps: 1. Analyze the requirements in the $($Reviewer.Name)'s guidelines provided below. 2. Plan the structure of your Python script. 3. Write the Python code that meets the requirements. 4. Add appropriate error handling and logging. 5. Include comments explaining complex parts of the code. 6. Add version notes to document the code changes. 7. Perform a self-review of your code for efficiency and adherence to best practices. Please format your response as follows: 1. Script Purpose: (Brief description of what the script does) 2. Input Parameters: (List of input parameters, if any) 3. Output: (Description of what the script returns or produces) 4. Python code: (The actual code, properly formatted and commented) 5. Usage Example: (A brief example of how to use the script) 6. Self-Review Notes: (Any observations or potential improvements you've identified) $($Reviewer.Name) Guidelines: ````````text $($Reviewer.GetLastMemory().Response) ```````` Current version of the Python code: ````````python $($GlobalState.LastpydevCode) ```````` "@ # If a tip amount is specified, include it in the response prompt if ($tipAmount) { $responsePrompt += "`n`nI will tip you `$$tipAmount for the correct code." } # Get the response from the recipient $response = $Recipient.ProcessInput($responsePrompt) return $response } catch [System.Exception] { # Handle any exceptions that occur during the process $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } function Update-GlobalStateWithResponse { param ( [string] $response, [PSCustomObject] $GlobalState ) try { # Update the global response with the new response $GlobalState.GlobalpydevResponse += $response # Add the new response to global responses Add-ToGlobalResponses -GlobalState $GlobalState -response $response # Save the new version of the code to a file $_savedFile = Export-AndWritePythonCodeBlocks -InputString $response -OutputFilePath $(join-path $GlobalState.teamDiscussionDataFolder "TheCode_v$($GlobalState.fileVersion).py") -StartDelimiter '```python' -EndDelimiter '```' if ((Test-Path -Path $_savedFile) -and $_savedFile) { # Update the last code and file version $GlobalState.lastpydevCode = Get-Content -Path $_savedFile -Raw $GlobalState.fileVersion += 1 # Output the saved file path for verbose logging Write-Verbose $_savedFile } else { Write-Warning "!! The code does not exist. Unable to update the last code and file version." } } catch [System.Exception] { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } # Refactor Invoke-ProcessFeedbackAndResponse to use the new functions function Invoke-ProcessFeedbackAndResponse { param ( [Parameter(Mandatory = $true)] [object]$Reviewer, [Parameter(Mandatory = $true)] [object]$Recipient, [Parameter(Mandatory = $false)] [string]$tipAmount, [PSCustomObject] $GlobalState ) try { # Measure the time taken to process feedback and generate a response $stopwatch = [System.Diagnostics.Stopwatch]::StartNew() # Process feedback and generate a response if ($null -eq $tipAmount) { $response = Set-FeedbackAndGenerateResponse -Reviewer $Reviewer -Recipient $Recipient -GlobalState $GlobalState } else { $response = Set-FeedbackAndGenerateResponse -Reviewer $Reviewer -Recipient $Recipient -tipAmount $tipAmount -GlobalState $GlobalState } if ($response) { # Update the global state with the new response Update-GlobalStateWithResponse -response $response -GlobalState $GlobalState } $stopwatch.Stop() Write-Information "++ Time taken to process feedback and generate response: $($stopwatch.Elapsed.TotalSeconds) seconds" -InformationAction Continue } catch [System.Exception] { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } # Refactor Save-AndUpdateCode to use the new function function Save-AndUpdateCode { param ( [string] $response, [PSCustomObject] $GlobalState ) try { # Update the global state with the new response Update-GlobalStateWithResponse -response $response -GlobalState $GlobalState } catch [System.Exception] { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } function Save-ProjectState { param ( [string]$FilePath, # Path to save the project state [PSCustomObject] $GlobalState # Global state object containing project details ) try { # Export the project state to a file in XML format $GlobalState | Export-Clixml -Path $FilePath } catch [System.Exception] { # Handle any exceptions that occur during the save process $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") } } function Get-ProjectState { param ( [string]$FilePath ) try { # Check if the specified file path exists if (Test-Path -Path $FilePath) { # Import the project state from the XML file $projectState = Import-Clixml -Path $FilePath if ($null -eq $projectState.LLMProvider) { $projectState.LLMProvider = "AzureOpenAI" } # Return the updated GlobalState object return $projectState } else { # Inform the user that the project state file was not found Write-Host "-- Project state file not found." } } catch [System.Exception] { # Handle any exceptions that occur during the process $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path (split-path -Path $FilePath -Parent) "ERROR.txt") } } function Update-ErrorHandling { param ( [Parameter(Mandatory = $true)] [System.Management.Automation.ErrorRecord]$ErrorRecord, [string]$ErrorContext, [string]$LogFilePath ) # Provide suggestions based on the error type $suggestions = switch -Regex ($ErrorRecord.Exception.Message) { "PSAOAI" { "Check the PSAOAI module installation and the deployment environment variable. Ensure the API key and endpoint are correctly configured." } "UnauthorizedAccessException" { "Check the file permissions and ensure you have the necessary access rights to the file or directory." } "IOException" { "Ensure the file path is correct and the file is not being used by another process." } "(403)" { "I recommend checking your API key, permissions, and any other relevant settings. You might also want to consult the Azure documentation or seek assistance from the Azure support team." } '(429)' { "Too many requests have been made to the server in a short period. Implement rate limiting or exponential backoff in your requests. Consider reviewing the API's rate limit guidelines and ensure your application adheres to them." } default { "Refer to the error message and stack trace for more details. Consult the official documentation or seek help from the community." } } # Capture detailed error information $errorDetails = [ordered]@{ Timestamp = Get-Date -Format "yyyy-MM-dd HH:mm:ss" ErrorMessage = $ErrorRecord.Exception.Message ExceptionType = $ErrorRecord.Exception.GetType().FullName ErrorContext = $ErrorContext Suggestions = $Suggestions ScriptFullName = $MyInvocation.ScriptName LineNumber = $MyInvocation.ScriptLineNumber StackTrace = $ErrorRecord.ScriptStackTrace UserName = [System.Security.Principal.WindowsIdentity]::GetCurrent().Name MachineName = $env:COMPUTERNAME PythonVersion = $PSVersionTable.PSVersion.ToString() } | ConvertTo-Json # Display the error details and suggestions Write-Host "-- Context: $ErrorContext" -ForegroundColor Yellow Write-Host "-- Suggestions: $suggestions" -ForegroundColor Yellow Write-Host "-- Error: $($ErrorRecord.Exception.Message)" -ForegroundColor Yellow # Log the error details if LogFilePath is provided if ($LogFilePath) { $errorDetails | Out-File -FilePath $LogFilePath -Append -Force if (Test-Path -Path $LogFilePath) { Write-Host "-- Error details have been saved to the file: $LogFilePath" -ForegroundColor Yellow } else { Write-Host "-- The specified log file path does not exist: $LogFilePath" -ForegroundColor Red } } } function Invoke-LLMChatCompletion { param ( [string]$Provider, [string]$SystemPrompt, [string]$UserPrompt, [double]$Temperature, [double]$TopP, [int]$MaxTokens, [bool]$Stream, [string]$LogFolder, [string]$DeploymentChat, [string]$ollamaModel ) try { # Check if verbose prompts are enabled and display them if ($GlobalState.VerbosePrompt) { Write-Host $SystemPrompt -ForegroundColor DarkMagenta Write-Host $UserPrompt -ForegroundColor DarkMagenta } # Switch between different LLM providers based on the provider parameter switch ($Provider) { "ollama" { # Invoke the Ollama model completion function $response = Invoke-AIPyTeamOllamaCompletion -SystemPrompt $SystemPrompt -UserPrompt $UserPrompt -Temperature $Temperature -TopP $TopP -ollamaModel $ollamamodel -Stream $Stream return $response } "LMStudio" { # Handle streaming for LMStudio provider # Invoke the LMStudio chat completion function $response = Invoke-AIPyTeamLMStudioChatCompletion -SystemPrompt $SystemPrompt -UserPrompt $UserPrompt -Temperature $Temperature -TopP $TopP -Stream $Stream -ApiKey $script:lmstudioApiKey -endpoint $script:lmstudioApiBase -Model $script:LMStudioModel return $response } "OpenAI" { # Throw an exception for unsupported LLM provider throw "-- Unsupported LLM provider: $Provider. This provider is not implemented yet." } "AzureOpenAI" { # Invoke the Azure OpenAI chat completion function $response = Invoke-AIPyTeamAzureOpenAIChatCompletion -SystemPrompt $SystemPrompt -UserPrompt $UserPrompt -Temperature $Temperature -TopP $TopP -Stream $Stream -LogFolder $LogFolder -Deployment $DeploymentChat return $response } default { # Throw an exception for unknown LLM provider throw "!! Unknown LLM provider: $Provider" } } } catch { # Log the error and rethrow it with additional context $functionName = $MyInvocation.MyCommand.Name $errorMessage = "Error in ${functionName}: $_" Write-Error $errorMessage Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $LogFolder "ERROR.txt") throw $_ } } function Invoke-AIPyTeamAzureOpenAIChatCompletion { param ( [string]$SystemPrompt, [string]$UserPrompt, [double]$Temperature, [double]$TopP, [int]$MaxTokens, [bool]$Stream, [string]$LogFolder, [string]$Deployment ) try { # Log the input parameters for debugging purposes Write-Verbose "SystemPrompt: $SystemPrompt" Write-Verbose "UserPrompt: $UserPrompt" Write-Verbose "Temperature: $Temperature" Write-Verbose "TopP: $TopP" Write-Verbose "MaxTokens: $MaxTokens" Write-Verbose "Stream: $Stream" Write-Verbose "LogFolder: $LogFolder" Write-Verbose "Deployment: $Deployment" # Call Azure OpenAI API Write-Host "++ AZURE OpenAI ($Deployment) is working..." if ($Stream) { Write-Host "++ Streaming" -ForegroundColor Blue } # Invoke the Azure OpenAI chat completion function $response = PSAOAI\Invoke-PSAOAIChatCompletion -SystemPrompt $SystemPrompt -usermessage $UserPrompt -Temperature $Temperature -TopP $TopP -LogFolder $LogFolder -Deployment $Deployment -User "AIPyTeam" -Stream $Stream -simpleresponse -OneTimeUserPrompt if ($Stream) { Write-Host "++ Streaming completed." -ForegroundColor Blue } # Check if the response is null or empty if ([string]::IsNullOrEmpty($response)) { $errorMessage = "The response from Azure OpenAI API is null or empty." Write-Error $errorMessage throw $errorMessage } return $response } catch { # Log the error and rethrow it with additional context $functionName = $MyInvocation.MyCommand.Name $errorMessage = "Error in ${functionName}: $_" Write-Error $errorMessage Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $LogFolder "ERROR.txt") throw $_ } } function Invoke-AIPyTeamOllamaCompletion { param ( [string]$SystemPrompt, [string]$UserPrompt, [double]$Temperature, [double]$TopP, [string]$ollamaModel, [bool]$Stream ) # Define options for the Ollama API call $ollamaOptions = [pscustomobject]@{ temperature = $Temperature top_p = $TopP } # Construct the JSON payload for the Ollama API request $ollamaJson = [pscustomobject]@{ model = $ollamaModel prompt = $SystemPrompt + "`n" + $UserPrompt options = $ollamaOptions stream = $Stream } | ConvertTo-Json # Ensure the Ollama endpoint ends with a '/' if (-not $script:ollamaEndpoint.EndsWith('/')) { $script:ollamaEndpoint += '/' } Write-Verbose $ollamaJson # Define the URL for the Ollama API endpoint $url = "$($script:ollamaEndpoint)api/generate" # Notify the user that the Ollama model is processing Write-Host "++ Ollama ($ollamaModel) is working..." # Check if streaming is enabled and handle accordingly if ($Stream) { # Initialize HttpClientHandler with specific configurations for streaming $httpClientHandler = [System.Net.Http.HttpClientHandler]::new() $httpClientHandler.AllowAutoRedirect = $false $httpClientHandler.UseCookies = $false $httpClientHandler.AutomaticDecompression = [System.Net.DecompressionMethods]::GZip -bor [System.Net.DecompressionMethods]::Deflate # Create HttpClient using the handler $httpClient = [System.Net.Http.HttpClient]::new($httpClientHandler) # Prepare the content of the HTTP request $content = [System.Net.Http.StringContent]::new($ollamaJson, [System.Text.Encoding]::UTF8, "application/json") # Create and configure the HTTP request message $request = New-Object System.Net.Http.HttpRequestMessage ([System.Net.Http.HttpMethod]::Post, $url) $request.Content = $content # Send the HTTP request and read the headers of the response $response = $httpClient.SendAsync($request, [System.Net.Http.HttpCompletionOption]::ResponseHeadersRead).Result # Stream the response using StreamReader $reader = [System.IO.StreamReader]::new($response.Content.ReadAsStreamAsync().Result) # Initialize variable to accumulate the response text $completeText = "" Write-Host "++ Streaming" -ForegroundColor Blue # Read and process each line of the response stream while ($null -ne ($line = $reader.ReadLine()) -or (-not $reader.EndOfStream)) { try { $line = ($line | ConvertFrom-Json) } catch { Write-Error "Error parsing JSON: $_" } if (-not $line.done) { $delta = $line.response $completeText += $delta Write-Host $delta -NoNewline -ForegroundColor White } } Write-Host "" $completeText += "`n" # Output the complete streamed text if ($VerbosePreference -eq "Continue") { Write-Host "++ Streaming completed. Full text: $completeText" -ForegroundColor DarkBlue } else { Write-Host "++ Streaming completed." -ForegroundColor Blue } # Clean up resources $reader.Close() $httpClient.Dispose() $response = $completeText } else { # Send a non-streaming HTTP POST request and parse the response $response = Invoke-WebRequest -Method POST -Body $ollamaJson -Uri $url -UseBasicParsing $response = $response.Content | ConvertFrom-Json | Select-Object -ExpandProperty response } # Log the interaction details $logEntry = @{ Timestamp = (Get-Date).ToString("yyyy-MM-dd HH:mm:ss") SystemPrompt = $SystemPrompt UserPrompt = $UserPrompt Response = $response } | ConvertTo-Json [void]($this.Log.Add($logEntry)) $this.AddLogEntry("SystemPrompt:`n$SystemPrompt") $this.AddLogEntry("UserPrompt:`n$UserPrompt") $this.AddLogEntry("Response:`n$response") return $response.Trim('"') } function Invoke-AIPyTeamLMStudioChatCompletion { param ( [string]$SystemPrompt, [string]$UserPrompt, [double]$Temperature, [double]$TopP, [string]$Model, [string]$ApiKey, [string]$endpoint, [int]$timeoutSec = 240, [bool]$Stream ) $response = "" $headers = @{ "Content-Type" = "application/json" "Authorization" = "Bearer '$ApiKey'" } $bodyJSON = [ordered]@{ 'model' = $Model 'messages' = @( [ordered]@{ 'role' = 'system' 'content' = $SystemPrompt }, [ordered]@{ 'role' = 'user' 'content' = $UserPrompt } ) 'temperature' = $Temperature 'top_p' = $TopP 'stream' = $Stream 'max_tokens' = $GlobalState.maxtokens } | ConvertTo-Json Write-Verbose $bodyJSON # Call lm-studio #if ($modelResponse.data.Count -ne 0) { $InfoText = "++ LM Studio" + $(if ($Model) { " ($Model)" } else { "" }) + " is working..." Write-Host $InfoText #} $url = "$($endpoint)chat/completions" # Check if streaming is enabled and handle accordingly if ($Stream) { # Create an instance of HttpClientHandler and disable buffering $httpClientHandler = [System.Net.Http.HttpClientHandler]::new() $httpClientHandler.AllowAutoRedirect = $false $httpClientHandler.UseCookies = $false $httpClientHandler.AutomaticDecompression = [System.Net.DecompressionMethods]::GZip -bor [System.Net.DecompressionMethods]::Deflate # Create an instance of HttpClient $httpClient = [System.Net.Http.HttpClient]::new($httpClientHandler) # Set the required headers $httpClient.DefaultRequestHeaders.Add("api-key", $script:lmstudioApiKey) # Set the timeout for the HttpClient $httpClient.Timeout = New-TimeSpan -Seconds $timeoutSec # Create the HttpContent object with the request body $content = [System.Net.Http.StringContent]::new($bodyJSON, [System.Text.Encoding]::UTF8, "application/json") $request = New-Object System.Net.Http.HttpRequestMessage ([System.Net.Http.HttpMethod]::Post, $url) $request.Content = $content # Send the HTTP POST request asynchronously with HttpCompletionOption.ResponseHeadersRead $response = $httpClient.SendAsync($request, [System.Net.Http.HttpCompletionOption]::ResponseHeadersRead).Result # Ensure the request was successful if (-not $response.IsSuccessStatusCode) { Write-Host "-- Response was not successful: $($response.StatusCode) - $($response.ReasonPhrase)" return } # Get the response stream $stream_ = $response.Content.ReadAsStreamAsync().Result $reader = [System.IO.StreamReader]::new($stream_) Write-Host "++ Streaming." -ForegroundColor Blue # Initialize the completeText variable $completeText = "" while ($null -ne ($line = $reader.ReadLine()) -or (-not $reader.EndOfStream)) { # Check if the line starts with "data: " and is not "data: [DONE]" #Write-Verbose $line if ($line.StartsWith("data: ") -and $line -ne "data: [DONE]") { # Extract the JSON part from the line $jsonPart = $line.Substring(6) if ($completeText.EndsWith('+')) { $completeText = $completeText.Substring(0, $completeText.Length - 1) } try { # Parse the JSON part $parsedJson = $jsonPart | ConvertFrom-Json # Extract the text and append it to the complete text - Chat Completion $delta = $parsedJson.choices[0].delta.content $completeText += $delta Write-Host $delta -NoNewline -ForegroundColor White } catch { Write-Error $_ } } } Write-Host "" $completeText += "`n" if ($VerbosePreference -eq "Continue") { Write-Verbose "Streaming completed. Full text: $completeText" } else { Write-Host "++ Streaming completed." -ForegroundColor Blue } # Clean up $reader.Close() $httpClient.Dispose() $response = $completeText } else { # Send a non-streaming HTTP POST request and parse the response $response = Invoke-RestMethod -Uri "$($endpoint)chat/completions" -Headers $headers -Method POST -Body $bodyJSON -TimeoutSec $timeoutSec $response = $($response.Choices[0].message.content).trim() } # Log the prompt and response to the log file $logEntry = @{ Timestamp = (Get-Date).ToString("yyyy-MM-dd HH:mm:ss") SystemPrompt = $SystemPrompt UserPrompt = $UserPrompt Response = $response } | ConvertTo-Json [void]($this.Log.Add($logEntry)) # Log the summary [void]($this.AddLogEntry("SystemPrompt:`n$SystemPrompt")) [void]($this.AddLogEntry("UserPrompt:`n$UserPrompt")) [void]($this.AddLogEntry("Response:`n$Response")) return $response } function Invoke-BingWebSearch { param ( [Parameter(Mandatory = $true)] [string]$query, # The search query [Parameter(Mandatory = $false)] [string]$apiKey, [Parameter(Mandatory = $false)] [string]$endpoint, [Parameter(Mandatory = $false)] [string]$language = "en-US", # The language for the search results [Parameter(Mandatory = $false)] [int]$count # The number of search results to return ) # Ensure the API key is provided, prompt the user if not while ([string]::IsNullOrEmpty($apiKey) -or [string]::IsNullOrWhiteSpace($apiKey)) { $apiKey = Read-Host -Prompt "Please enter your AZURE Bing API key" if ($apiKey) { [System.Environment]::SetEnvironmentVariable("AZURE_BING_API_KEY", $apiKey, "User") Write-Verbose "API key set successfully." } } # Ensure the endpoint is provided, prompt the user if not while ([string]::IsNullOrEmpty($endpoint) -or [string]::IsNullOrWhiteSpace($endpoint)) { $endpoint = Read-Host -Prompt "Please enter the AZURE Bing Web Search Endpoint" if ($endpoint) { [System.Environment]::SetEnvironmentVariable("AZURE_BING_SEARCH_ENDPOINT", $endpoint, "User") Write-Verbose "Endpoint set successfully." } } # Define the headers for the API request $headers = @{ "Ocp-Apim-Subscription-Key" = $apiKey "Pragma" = "no-cache" } Write-Verbose "Headers defined for the API request." # If the query length is greater than the maximum allowed, truncate it $maxqueryLength = 120 if ($query.Length -gt $maxqueryLength) { Write-Host "Query length is greater than $maxqueryLength characters. Truncating the query." $query = $query.Substring(0, $maxqueryLength) Write-Verbose "Query truncated to $maxqueryLength characters." } # Define the parameters for the API request $params = @{ "q" = $query "mkt" = $language "count" = $count } Write-Verbose "Parameters defined for the API request." # Ensure the endpoint is provided, prompt the user if not while ([string]::IsNullOrEmpty($Endpoint)) { $Endpoint = Read-Host -Prompt "Please enter the AZURE Bing Web Search Endpoint" } [System.Environment]::SetEnvironmentVariable("AZURE_BING_SEARCH_ENDPOINT", $Endpoint, "User") $endpoint += "v7.0/search" Write-Verbose "Final endpoint set to $endpoint." # Disable the Expect100Continue behavior to avoid delays in sending data [System.Net.ServicePointManager]::Expect100Continue = $false Write-Verbose "Expect100Continue behavior disabled." # Disable the Nagle algorithm to improve performance for small data packets [System.Net.ServicePointManager]::UseNagleAlgorithm = $false Write-Verbose "Nagle algorithm disabled." # Set the security protocol to TLS 1.2 for secure communication [System.Net.ServicePointManager]::SecurityProtocol = [System.Net.SecurityProtocolType]::Tls12 Write-Verbose "Security protocol set to TLS 1.2." try { # Make the API request to Bing Search Write-Verbose "Making API request to Bing Search." $response = Invoke-RestMethod -Uri $endpoint -Headers $headers -Method Get -Body $params # Check if the response contains web pages if ($null -eq $response.webPages.value) { Write-Warning "No web pages found for the query: $query" return $null } Write-Verbose "API request successful. Returning search results." # Return the search results return $response.webPages.value } catch [System.Net.WebException] { # Handle web exceptions (e.g., network issues) Write-Warning "Network error occurred during Bing search: $_" $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") Throw $_ } catch [System.Exception] { # Handle all other exceptions Write-Warning "An error occurred during Bing search: $_" $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") Throw $_ } } function Remove-StringDirtyData { param ( [string]$inputString ) Write-Verbose "Starting to clean the input string." # Remove leading and trailing whitespace Write-Verbose "Removing leading and trailing whitespace." $cleanedString = $inputString.Trim() # Remove multiple spaces and replace with a single space Write-Verbose "Replacing multiple spaces with a single space." $cleanedString = $cleanedString -replace '\s+', ' ' # Remove any non-printable characters Write-Verbose "Removing non-printable characters." $cleanedString = $cleanedString -replace '[^\x20-\x7E]', '' # Remove entities Write-Verbose "Removing entities." $cleanedString = $cleanedString -replace ' ', ' ' # Remove empty lines Write-Verbose "Removing empty lines." $cleanedString = $cleanedString -replace '^\s*$\n', '' # Convert the string to an array of lines Write-Verbose "Converting the string to an array of lines." $lines = $cleanedString -split "`n" # Remove empty lines Write-Verbose "Removing empty lines from the array of lines." $lines = $lines | Where-Object { $_.Trim() -ne "" } # Join the lines back into a single string Write-Verbose "Joining the lines back into a single string." $cleanedString = $lines -join "`n" #region Cleaning RAG Raw Data # This section is responsible for cleaning raw data obtained from RAG (Retrieve and Generate) processes. # The goal is to ensure that the text is free from artifacts, irregular spacing, and formatting issues # that may have resulted from HTML removal or other preprocessing steps. # The cleaned text should be readable, well-formatted, and maintain its original structure and meaning. # The cleaning process involves removing HTML entities, excessive blank lines, and other artifacts, # as well as correcting spacing issues, standardizing quotation marks, and ensuring proper capitalization. # The cleaned text is then processed by an LLM (Language Learning Model) to further refine and ensure # the quality of the output. #endregion Cleaning RAG Raw Data Write-Host "++ Cleaning RAG Raw Data: Ensuring the text is free from artifacts, irregular spacing, and formatting issues." -ForegroundColor Cyan # Define the LLM system prompt for cleaning the string $LLMSystemPrompt = @" You are an expert text processor specializing in cleaning and formatting web content. Your task is to process text that originally came from HTML but has already had its HTML tags removed. The text still contains artifacts, irregular spacing, meta content, sidebar content or formatting issues from the HTML removal process. Your goal is to produce clean, readable text. In your processing you must: 1. Remove all HTML entities (e.g., , &, ') and replace them with their corresponding characters. Use a comprehensive list of HTML entities for reference. 2. Normalize line breaks: - Reduce multiple consecutive blank lines to a single blank line for paragraph separation. - Preserve intentional line breaks for structured content like addresses, poetry, or code snippets. - Remove unnecessary line breaks within paragraphs, joining split sentences. 3. Clean up HTML artifacts: - Remove any remaining HTML tags, including partial or malformed tags. - Eliminate stray brackets, braces, or other syntax-related characters that don't belong in plain text. 4. Standardize spacing: - Ensure single spaces after punctuation marks (periods, commas, colons, etc.). - Remove extra spaces between words. - Eliminate leading or trailing spaces on each line. 5. Normalize quotation marks and apostrophes: - Use straight quotes (' and ") consistently throughout the text. - Ensure apostrophes are used correctly for contractions and possessives. 6. Correct capitalization: - Capitalize the first letter of each sentence. - Preserve intentional capitalization for proper nouns, acronyms, and titles. 7. Remove redundancies: - Eliminate repeated words or phrases that likely resulted from improper tag removal or formatting issues. - Be cautious not to remove intentional repetition for emphasis or stylistic purposes. 8. Format lists consistently: - Identify and standardize bulleted and numbered lists. - Ensure consistent indentation and formatting for list items. - Convert HTML list structures to plain text equivalents if necessary. 9. Correct spelling and encoding errors: - Fix obvious spelling mistakes, especially those resulting from character encoding issues. - Be cautious with proper nouns or specialized terminology. 10. Standardize punctuation: - Use consistent em-dashes, en-dashes, and hyphens. - Ensure correct usage of semicolons, colons, and other punctuation marks. 11. Preserve or convert special formatting: - Maintain emphasis (bold, italic) using plain text conventions (e.g., *asterisks* or _underscores_) if appropriate for the output format. - Convert simple tables to a readable plain text format if encountered. 12. Handle URLs and email addresses: - Ensure hyperlinks are visible and properly formatted in plain text. - Preserve the integrity of email addresses and web URLs. 13. Normalize number and date formats: - Standardize numerical representations (e.g., consistent use of commas or periods for thousands separators). - Use a consistent date format throughout the document. 14. Remove or replace non-printable characters: - Eliminate null characters, form feeds, and other control characters. - Replace tabs with appropriate spacing. 15. Final consistency check: - Ensure overall consistency in formatting choices throughout the document. - Verify that the cleaning process hasn't introduced new errors or inconsistencies. "@ # Define the user prompt with the input string $LLMUserPrompt = @" Web content: ``````text $cleanedString `````` Process and response with cleaned text only, maintaining its original structure and meaning as much as possible. "@ # Invoke the LLM to clean the string try { Write-Verbose "Invoking LLM to clean the string." # Invoke the LLMChatCompletion function with the necessary parameters $CleanedString = Invoke-LLMChatCompletion -Provider $GlobalState.LLMProvider ` -SystemPrompt $LLMSystemPrompt ` -UserPrompt $LLMUserPrompt ` -Temperature 0.1 ` -TopP 0.1 ` -MaxTokens $GlobalState.MaxTokens ` -Stream $false ` -LogFolder $GlobalState.TeamDiscussionDataFolder ` -DeploymentChat $script:DeploymentChat ` -ollamaModel $script:ollamaModel Write-Host "++ Cleaning RAG Raw Data: Finished." -ForegroundColor Cyan return $CleanedString } catch { $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") Write-Host "-- An error occurred while invoking the LLM to clean the string." -ForegroundColor DarkYellow return } } function Invoke-RAG { param ( [string]$UserInput, [string]$Prompt, [ProjectTeam]$RAGAgent, [int]$MaxCount = 2 ) $RAGResponse = $null $ShortenedUserInput = "" try { Write-Verbose "Starting Invoke-RAG function." # Define the system prompt for the RAG agent $RAGSystemPrompt = @" You are a Web Search Query Manager. Your task is to suggest the best query for the Azure Bing Web Search API based on the user's input. To create an effective query, summarize the given text and follow these best practices: 1. Use specific keywords: Choose concise and precise terms that clearly define the search intent to increase result relevance. 2. Utilize advanced operators: Leverage operators like 'AND', 'OR', and 'NOT' to refine queries. Use 'site:' for domain-specific searches. 3. Remove quotation marks or other special characters from the beginning and end of the query. Your response should be a short, optimized Web query with a few terms based on the user's input. Examples of well-formed queries: - 'Python, code review, script parsing OR analyzing' - 'Python code AND psscriptanalyzer' - 'Python AND azure data logger AND event log' You must respond with the optimized query only ready to be invoked in search engine. "@ Write-Verbose "RAG system prompt defined." # Create an optimized web search query based on the following text $RAGUserPrompt = @" User input: ````````text $($userInput.trim()) ```````` "@ # Process the user input with the RAG agent and trim the result $ShortenedUserInput = ($RAGAgent.ProcessInput($RAGUserPrompt, $RAGSystemPrompt)).trim() Write-Verbose "RAG agent processed the input and returned a shortened user input." Write-Host ">> RAG is on. Attempting to augment AI Agent data..." -ForegroundColor Green # Check if the shortened user input is not empty if (-not [string]::IsNullOrEmpty($ShortenedUserInput)) { Write-Verbose "Shortened user input is not empty. Proceeding with web search." try { # Define the log file path for storing the query $LogFilePath = Join-Path -Path $GlobalState.TeamDiscussionDataFolder -ChildPath "azurebingqueries.log" Write-Verbose "Log file path defined: $LogFilePath" # Append the shortened user input to the log file with a date prefix in professional log style $DatePrefix = (Get-Date).ToString("yyyy-MM-dd HH:mm:ss") $LogEntry = "$DatePrefix - Query: $ShortenedUserInput" Add-Content -Path $LogFilePath -Value $LogEntry Write-Verbose "Log entry added: $LogEntry" # Perform the web search using the shortened user input $WebResults = Invoke-BingWebSearch -query $ShortenedUserInput -count $MaxCount -apiKey ([System.Environment]::GetEnvironmentVariable("AZURE_BING_API_KEY", "User")) -endpoint ([System.Environment]::GetEnvironmentVariable("AZURE_BING_SEARCH_ENDPOINT", "User")) Write-Verbose "Web search performed with query: $ShortenedUserInput" } catch { Write-Error "Error occurred during web search or logging: $_" throw $_ } } else { # Throw an error if the query is empty Write-Error "The query is empty. Unable to perform web search." throw "The query is empty. Unable to perform web search." } # Check if web results are returned if ($WebResults) { Write-Verbose "Web results returned. Extracting and cleaning text content." try { # Extract and clean text content from the web results $WebResultsText = ($WebResults | ForEach-Object { $HtmlContent = Invoke-WebRequest -Uri $_.url $TextContent = ($HtmlContent.Content | PowerHTML\ConvertFrom-HTML).innerText $TextContent } ) -join "`n`n" Write-Verbose "Text content extracted and cleaned from web results." } catch { Write-Error "Error occurred while extracting or cleaning web results: $_" throw $_ } } else { Write-Verbose "No web results returned." } # Process the cleaned web results text with the project manager's input processing function $RAGuserinput = @" Please analyze the following text through the lens of Python project with this description: '$userinput' Text to analyze: ````````text $($(Remove-StringDirtyData -inputString $webResultsText).trim()) ```````` Provide your analysis in the following format: 1. Key Information: List the most important facts or points from the text, relevant to the given description. 2. Insights: Offer any notable thoughts or interpretations based on the text and context. 3. Questions: Generate relevant questions that arise from the analysis, which could lead to further exploration of the topic. Ensure your response is focused and directly related to the provided description. "@ $RAGresponse = $RAGAgent.ProcessInput($RAGuserinput, $prompt) if ($RAGresponse) { Write-Host "++ RAG is on. AI Agent data was successfully augmented with new data." -ForegroundColor Green } # Return the response generated by the project manager return $RAGresponse } catch { # Log the error and rethrow it #$this.AddLogEntry("Error in Invoke-RAG:`n$_") #throw $_ $functionName = $MyInvocation.MyCommand.Name Update-ErrorHandling -ErrorRecord $_ -ErrorContext "$functionName function" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") #Write-Warning $_ Write-Host "-- No RAG data available to augment." -ForegroundColor DarkYellow return } } function Get-Ollama { <# .SYNOPSIS Checks the status of Ollama installation, process, and running models. .DESCRIPTION This function performs several checks related to Ollama: 1. Verifies if Ollama is installed and available in the system PATH. 2. Checks if the Ollama process is currently running. 3. Retrieves and displays information about the models currently running in Ollama. .EXAMPLE Get-Ollama .NOTES Author: Voytas75 Date: 2024.07.10 #> # Check if Ollama is installed $ollamaPath = Test-OllamaInstalled if (-not $ollamaPath) { Write-Host "-- Ollama is not installed or not in PATH." return $false } Write-Host "++ Ollama is installed at: $ollamaPath" # Check if Ollama is running $ollamaProcess = Test-OllamaRunning if (-not $ollamaProcess) { Write-Host "-- Ollama is not currently running." return Start-OllamaInNewConsole } if ($ollamaProcess.Count -gt 1) { Write-Host "++ Multiple Ollama processes are running with PID(s): $($ollamaProcess.Id -join ', ')" } else { Write-Host "++ Ollama is running with PID: $($ollamaProcess.Id)" } # Check what model is running try { Get-OllamaModels } catch { Write-Host "-- Failed to retrieve model information from /api/tags: $_" return $false } # Additional check for running model information try { # Example usage of Test-OllamaRunningModel and Start-OllamaModel # Test-OllamaRunningModel checks if any model is running # Start-OllamaModel starts a model if none is running return Start-OllamaModel } catch { Write-Host "-- Failed to retrieve additional model information from /api/ps: $_" } } function Get-OllamaModels { <# .SYNOPSIS Lists all available models in the local Ollama repository. .DESCRIPTION This function retrieves and lists all models available in the local Ollama repository by making a GET request to the /api/tags endpoint. .EXAMPLE List-OllamaModels .NOTES Author: voytas75 Date: 2024.07.10 #> try { # Make a GET request to the /api/tags endpoint to retrieve model information $response = Invoke-RestMethod -Uri "$($script:ollamaEndpoint)api/tags" -Method Get if ($response.models) { Write-Host "++ Models:" # Iterate through each model and output its name and size $response.models | ForEach-Object { $sizeInGB = [math]::Round($_.size / 1GB, 2) Write-Host "- $($_.name) (Size: $sizeInGB GB)" } } else { Write-Host "-- No models in local repository. https://github.com/ollama/ollama?tab=readme-ov-file#quickstart" return $false } } catch { Write-Host "-- Failed to retrieve model information from /api/tags: $_" return $false } } function Start-OllamaInNewConsole { <# .SYNOPSIS Starts Ollama in a new minimized console window. .DESCRIPTION This function starts the Ollama application in a new minimized console window using the Start-Process cmdlet. It ensures that Ollama is installed and available in the system PATH before attempting to start it. .EXAMPLE Start-OllamaInNewConsole .NOTES Author: voytas75 Date: 2024.07.10 #> # Check if Ollama is installed $ollamaPath = Get-Command ollama -ErrorAction SilentlyContinue if (-not $ollamaPath) { #Write-Host "Ollama is not installed or not in PATH." return $false } # Start Ollama in a new minimized console window try { Start-Process -FilePath "cmd.exe" -ArgumentList "/k", "$ollamaPath start" -WindowStyle Minimized Write-Host "++ Ollama has been started in a new minimized console window." return $true } catch { Write-Host "-- Failed to start Ollama in a new minimized console window: $_" return $false } } function Test-OllamaRunningModel { <# .SYNOPSIS Tests if any models are currently running in Ollama and retrieves their information. .DESCRIPTION This function checks if any models are currently running in Ollama by making a GET request to the /api/ps endpoint. If models are running, it outputs their names and sizes. If no models are running, it provides instructions on how to start a model. .EXAMPLE Test-OllamaRunningModel .NOTES Author: Voytas75 Date: 2024.07.10 #> param( [switch]$NOInfo ) try { # Make a GET request to the /api/ps endpoint to retrieve running model information $response = Invoke-RestMethod -Uri "$($script:ollamaEndpoint)api/ps" -Method Get if ($response.models) { if (-not $NOInfo) { Write-Host "++ Ollama is running the following models: " -NoNewline } # Iterate through each model and output its name and size $script:ollamaModels = $response.models $ollamaRunningModels = @() foreach ($model in $script:ollamaModels) { if (-not $NOInfo) { $sizeInGB = [math]::Round($model.size / 1GB, 2) $ollamaRunningModels += "$($model.name) (Size: $sizeInGB GB)" } } Write-Host $($ollamaRunningModels -join ',') # Choose and return the first model $firstModel = $script:ollamaModels[0] $script:ollamamodel = $firstModel.name $env:OLLAMA_MODEL = $script:ollamamodel [System.Environment]::SetEnvironmentVariable('OLLAMA_MODEL', $firstModel.Name, 'User') return $firstModel.Name } else { if (-not $NOInfo) { Write-Host "-- No models are currently running in Ollama." } #Write-Host "To run a model in Ollama, use the following command:" #Write-Host "ollama run <model-name>" return $false } } catch { Write-Host "-- Failed to retrieve model information from Ollama: $_" } } function Start-OllamaModel { <# .SYNOPSIS Starts a model in Ollama if no model is currently running. .DESCRIPTION This function checks if Ollama is installed and available in the system PATH. It then verifies if any model is currently running in Ollama. If no model is running, it prompts the user to select a model from the available models and starts it. .EXAMPLE Start-OllamaModel .NOTES Author: Voytas75 Date: 2024.07.10 #> # Get the path of the Ollama executable #$ollamaPath = (Get-Command ollama -ErrorAction SilentlyContinue).Source $ollamaPath = Test-OllamaInstalled if (-not $ollamaPath) { Write-Host "-- Ollama is not found in PATH. Make sure it's installed and in your system PATH." #return $false # ollama can be run on remote computer } try { # Check if any model is currently running $runningModel = Test-OllamaRunningModel -NOInfo if ($runningModel) { Write-Host "++ Model '$runningModel' is already running." [System.Environment]::SetEnvironmentVariable('OLLAMA_MODEL', $runningModel, 'user') $script:ollamaModel = [System.Environment]::GetEnvironmentVariable('OLLAMA_MODEL', 'user') return $script:ollamaModel } # Make a GET request to the /api/tags endpoint to retrieve available models $response = Invoke-RestMethod -Uri "$($script:ollamaEndpoint)api/tags" -Method Get if ($response.models) { #Write-Host "Available Models:" # List available models $models = $response.models | ForEach-Object { $_.name } #$models | ForEach-Object { Write-Host "- $_" } # Check if the environment variable 'ollama_model' is set if ([System.Environment]::GetEnvironmentVariable('OLLAMA_MODEL', 'user')) { #$ModelName = [System.Environment]::GetEnvironmentVariable('OLLAMA_MODEL','user') if ($models -notcontains [System.Environment]::GetEnvironmentVariable('OLLAMA_MODEL', 'user')) { Write-Host "-- Invalid model name specified in environment variable 'ollama_model'. Please select a model from the list." [System.Environment]::SetEnvironmentVariable('OLLAMA_MODEL', '', 'user') $ModelName = [System.Environment]::SetEnvironmentVariable('OLLAMA_MODEL', '', 'user') } } $script:ollamaModel = [System.Environment]::GetEnvironmentVariable('OLLAMA_MODEL', 'user') $ModelName = $script:ollamaModel # If 'ollama_model' is not set or invalid, prompt the user to select a model if (-not $ModelName) { Get-OllamaModels do { $ModelName = Read-Host "Please enter the name of the model you want to start" if ($models -notcontains $ModelName) { Write-Host "-- Invalid model name. Please select a model from the list." $ModelName = $null } } while (-not $ModelName) } # Start the selected model using a new Python process #Start-Process Python -ArgumentList "-NoExit", "-Command", "& '$ollamaPath' run $ModelName" Write-Host "++ Starting with $ModelName" Start-Process -FilePath "cmd.exe" -ArgumentList "/k", "$ollamaPath run $ModelName" -WindowStyle Minimized [System.Environment]::SetEnvironmentVariable('OLLAMA_MODEL', $ModelName, 'user') $script:ollamaModel = [System.Environment]::GetEnvironmentVariable('OLLAMA_MODEL', 'user') return $ModelName } else { Write-Host "-- No models are currently available." } } catch { Write-Host "-- Failed to retrieve model information from /api/tags: $_" } } function Test-OllamaInstalled { <# .SYNOPSIS Tests if Ollama is installed and available in the system PATH. .DESCRIPTION This function checks if the 'ollama' executable is available in the system PATH. It returns $true if Ollama is installed, and $false otherwise. .EXAMPLE Test-OllamaInstalled Returns $true if Ollama is installed, otherwise $false. .NOTES Author: voytas75 Date: 2024.07.10 #> param () try { $ollamaPath = Get-Command ollama -ErrorAction SilentlyContinue if ($ollamaPath) { #Write-Host "Ollama is installed at: $($ollamaPath.Source)" return $ollamaPath.Source } else { #Write-Host "Ollama is not installed or not in PATH." return $false } } catch { Write-Host "-- An error occurred while checking for Ollama installation: $_" return $false } } function Test-OllamaAPI { <# .SYNOPSIS Tests if the Ollama API is currently accessible. .DESCRIPTION This function sends a request to the Ollama API endpoint to check if it is accessible and responding. It returns $true if the API is accessible, and $false otherwise. .EXAMPLE Test-OllamaAPI Returns $true if the Ollama API is accessible, otherwise $false. .NOTES Author: voytas75 Date: 2024.07.10 #> param ( [string]$apiEndpoint = "$($script:ollamaEndpoint)" ) try { $response = Invoke-RestMethod -Uri $apiEndpoint -Method Get -ErrorAction Stop if ($response -eq "Ollama is running") { #Write-Host "++ Ollama API is accessible." return $true } else { Write-Host "-- Ollama API is not accessible or returned an unexpected status." return $false } } catch { Write-Host "-- An error occurred while checking the Ollama API: $_" return $false } } function Test-OllamaRunning { <# .SYNOPSIS Tests if the Ollama process is currently running. .DESCRIPTION This function checks if the 'ollama' process is currently running on the system. It returns $true if the process is running, and $false otherwise. .EXAMPLE Test-OllamaRunning Returns $true if the Ollama process is running, otherwise $false. .NOTES Author: voytas75 Date: 2024.07.10 #> param () try { $ollamaProcess = Get-Process ollama -ErrorAction SilentlyContinue if ($ollamaProcess) { return $ollamaProcess } else { return $false } } catch { Write-Host "-- An error occurred while checking if Ollama is running: $_" return $false } } function Set-EnvOllamaModel { param ($model) $env:OLLAMA_MODEL = $model $script:ollamaModel = $model [System.Environment]::SetEnvironmentVariable('OLLAMA_MODEL', $model, 'User') } function Test-EnsureOllamaModelRunning { param ($attempts = 10, $delay = 2) for ($i = 0; $i -lt $attempts; $i++) { $runningModel = Test-OllamaRunningModel if ($runningModel) { Set-EnvOllamaModel -model $runningModel return $true } Start-OllamaModel Start-Sleep -Seconds $delay } return $false } #endregion Functions #region Setting Up # Save the original UI culture to restore it later $originalCulture = [Threading.Thread]::CurrentThread.CurrentUICulture # Set the current UI culture to 'en-US' for consistent behavior [void]([Threading.Thread]::CurrentThread.CurrentUICulture = [System.Globalization.CultureInfo]::CreateSpecificCulture('en-US')) # Check if the PSAOAI module version is at least 0.3.2 if ( Test-ModuleMinVersion -ModuleName PSAOAI -MinimumVersion "0.3.2" ) { # Import the PSAOAI module forcefully [void](Import-module -name PSAOAI -Force) } else { # Display a warning message if the required module version is not installed Write-Warning "-- You need to install/update PSAOAI module version >= 0.3.2. Use: 'Install-Module PSAOAI' or 'Update-Module PSAOAI'" return } # Disable RAG (Retrieve and Generate) functionality if the NORAG switch is set $RAG = $true if ($NORAG) { $RAG = $false } if (-not $LoadProjectStatus) { # Define a state management object $GlobalState = [PSCustomObject]@{ TeamDiscussionDataFolder = $null GlobalResponse = @() FileVersion = 1 LastpydevCode = "" GlobalpydevResponse = @() OrgUserInput = "" UserInput = "" LogFolder = "" MaxTokens = $MaxTokens VerbosePrompt = $VerbosePrompt NOTips = $NOTips NOLog = $NOLog NODocumentator = $NODocumentator NOPM = $NOPM RAG = $RAG Stream = $Stream LLMProvider = $LLMProvider } $GlobalState.LogFolder = $LogFolder } # Disabe PSAOAI importing banner [System.Environment]::SetEnvironmentVariable("PSAOAI_BANNER", "0", "User") $env:PSAOAI_BANNER = "0" # Check if the UserInput parameter is not provided if (-not $UserInput) { if (-not $LoadProjectStatus) { # Prompt the user to enter the Python project description $UserInput = Read-Host "Please enter the Python project description" # Store the user input in the GlobalState object $GlobalState.UserInput = $UserInput } } Show-Banner #region ollama if ($GlobalState.LLMProvider -eq 'ollama' -and (-not $LoadProjectStatus)) { $script:ollamaEndpoint = [System.Environment]::GetEnvironmentVariable('OLLAMA_ENDPOINT', 'user') if (-not $script:ollamaEndpoint.EndsWith('/')) { $script:ollamaEndpoint += '/' } if ([string]::IsNullOrEmpty($script:ollamaEndpoint)) { $defaultEndpoint = 'http://localhost:11434/' try { $script:ollamaEndpoint = $defaultEndpoint $env:OLLAMA_ENDPOINT = $defaultEndpoint [System.Environment]::SetEnvironmentVariable('OLLAMA_ENDPOINT', $defaultEndpoint, 'user') if ([System.Environment]::GetEnvironmentVariable('OLLAMA_ENDPOINT', 'user')) { Write-Host "++ Environment variable 'OLLAMA_ENDPOINT' was set successfully ('$defaultEndpoint'). Set it manually if you need a non-default value: [System.Environment]::SetEnvironmentVariable('OLLAMA_ENDPOINT', '<your-ollama-api-endpoint>', 'user')" -ForegroundColor Green } } # If setting the variable failed, display an error message catch { Write-Warning "-- Failed to set environment variable 'OLLAMA_ENDPOINT'." return } } if (Test-OllamaAPI) { Write-Host "++ Ollama API is reachable." # Check if Ollama is running with a model $runningModelOllama = Test-OllamaRunningModel if ($runningModelOllama) { Write-Host "++ Ollama is running with model: $runningModelOllama" Set-EnvOllamaModel -model $runningModelOllama } else { Write-Host "-- No models are currently running in Ollama. Please check your Ollama configuration." return } } else { Write-Warning "-- Ollama API is not reachable. Please check your Ollama installation and configuration." return } Write-Host "If you want to change the model, please delete the OLLAMA_MODEL environment variable or set it to your desired value." -ForegroundColor Magenta } #endregion ollama #region LMStudio # Check if the LLM provider is 'lmstudio' if ($GlobalState.LLMProvider -eq 'lmstudio' -and (-not $LoadProjectStatus)) { # Retrieve the LM Studio API key from the environment variables $script:lmstudioApiKey = [System.Environment]::GetEnvironmentVariable('OPENAI_API_KEY', 'user') # Retrieve the LM Studio API base URL from the environment variables $script:lmstudioApiBase = [System.Environment]::GetEnvironmentVariable('OPENAI_API_BASE', 'user') $env:OPENAI_API_KEY = $script:lmstudioApiKey $env:OPENAI_API_BASE = $script:lmstudioApiBase # If the API key is not set, use the default value 'lm-studio' and set it in the environment variables if (-not $script:lmstudioApiKey) { $script:lmstudioApiKey = 'lm-studio' $env:OPENAI_API_KEY = $script:lmstudioApiKey [System.Environment]::SetEnvironmentVariable('OPENAI_API_KEY', $script:lmstudioApiKey, 'user') Write-Verbose "++ Default LM Studio API key set to 'lm-studio'" } # If the API base URL is not set, use the default value 'http://localhost:1234/v1' and set it in the environment variables if (-not $script:lmstudioApiBase) { $script:lmstudioApiBase = 'http://localhost:1234/v1' $env:OPENAI_API_BASE = $script:lmstudioApiBase [System.Environment]::SetEnvironmentVariable('OPENAI_API_BASE', $script:lmstudioApiBase, 'user') Write-Verbose "++ Default LM Studio API base set to 'http://localhost:1234/v1'" } # Ensure the LMStudio endpoint ends with a '/' if (-not $script:lmstudioApiBase.EndsWith('/')) { $script:lmstudioApiBase += '/' } try { $LMStudioServerResponse = Invoke-WebRequest -Uri $script:lmstudioApiBase if ($LMStudioServerResponse.statuscode -eq "200") { Write-Host "++ LM Studio server is running." -ForegroundColor Green } else { Write-Host "-- LM Studio server not running." -ForegroundColor Yellow return } } catch [System.Net.WebException] { Write-Warning "LM Studio server is not running or not reachable. Please ensure the server is up and running at $($script:lmstudioApiBase)." Update-ErrorHandling -ErrorRecord $_ -ErrorContext "LM Studio server is not running or not reachable" Throw $_ } catch { Update-ErrorHandling -ErrorContext "LM Studio server is not running or not reachable"-ErrorRecord $_ } # Test lm-studio for model try { $LMStudioModelResponse = Invoke-RestMethod -Uri "$($script:lmstudioApiBase)models" -Method GET if ($LMStudioModelResponse.data.Count -eq 0) { Write-Host "-- No models loaded. Please load a model in LM Studio first." return } elseif ($LMStudioModelResponse.data.Count -gt 1) { Write-Host "++ LM Studio is running in Multi Model Session. Only one model can be chosen. Choosing the first one." } if ($LMStudioModelResponse.data[0].id) { $script:LMStudioModel = $LMStudioModelResponse.data[0].id } } catch [System.Net.WebException] { #System.InvalidOperationException Write-Warning "LM Studio server is not running or not reachable. Please ensure the server is up and running at $($script:lmstudioApiBase)." Update-ErrorHandling -ErrorRecord $_ -ErrorContext "LM Studio server is not running or not reachable" Throw $_ } catch { Update-ErrorHandling -ErrorContext "LM Studio server is not running or not reachable" -ErrorRecord $_ #Throw $_.Exception.Message } } #endregion LMStudio $scriptname = "AIPyTeam" if ($LoadProjectStatus) { # Check if the provided path is a directory if (Test-Path -Path $LoadProjectStatus -PathType Container) { # Get all XML files in the specified directory $xmlFiles = Get-ChildItem -Path $LoadProjectStatus -Filter *.xml foreach ($file in $xmlFiles) { # Prompt the user to select a file to use as the project status $useFile = Read-Host "Do you want to use the file '$($file.FullName)' as the project status? (yes/no)" if ($useFile -eq 'yes') { # Set the selected file as the project status file $LoadProjectStatus = $file.FullName break } } } try { # Load the project state from the specified file $GlobalState = Get-ProjectState -FilePath $LoadProjectStatus Write-Information "++ Project state loaded successfully from $LoadProjectStatus" -InformationAction Continue # Output verbose information about the loaded project state Write-Verbose "`$GlobalState.TeamDiscussionDataFolder: $($GlobalState.TeamDiscussionDataFolder)" Write-Verbose "`$GlobalState.FileVersion: $($GlobalState.FileVersion)" Write-Verbose "`$GlobalState.LastpydevCode: $($GlobalState.LastpydevCode)" Write-Verbose "`$GlobalState.GlobalpydevResponse: $($GlobalState.GlobalpydevResponse)" Write-Verbose "`$GlobalState.GlobalResponse: $($GlobalState.GlobalResponse)" Write-Verbose "`$GlobalState.OrgUserInput: $($GlobalState.OrgUserInput)" Write-Verbose "`$GlobalState.UserInput: $($GlobalState.UserInput)" Write-Verbose "`$GlobalState.LogFolder: $($GlobalState.LogFolder)" Write-Verbose "`$GlobalState.MaxTokens: $($GlobalState.MaxTokens)" Write-Verbose "`$GlobalState.VerbosePrompt: $($GlobalState.VerbosePrompt)" Write-Verbose "`$GlobalState.NOTips: $($GlobalState.NOTips)" Write-Verbose "`$GlobalState.NOLog: $($GlobalState.NOLog)" Write-Verbose "`$GlobalState.NODocumentator: $($GlobalState.NODocumentator)" Write-Verbose "`$GlobalState.NOPM: $($GlobalState.NOPM)" Write-Verbose "`$GlobalState.RAG: $($GlobalState.RAG)" Write-Verbose "`$GlobalState.Stream: $($GlobalState.Stream)" Write-Verbose "`$GlobalState.LLMProvider: $($GlobalState.LLMProvider)" Write-Host "Some values of the imported project:" Write-Host "Team Discussion Data Folder: $($GlobalState.TeamDiscussionDataFolder)" Write-Host "Last file Version: $($($GlobalState.FileVersion) - 1)" Write-Host "User Input: $($GlobalState.OrgUserInput)" Write-Host "Log Folder: $($GlobalState.LogFolder)" Write-Host "No Tips: $($GlobalState.NOTips)" Write-Host "No Log: $($GlobalState.NOLog)" Write-Host "No Documentator: $($GlobalState.NODocumentator)" Write-Host "No Project Manager: $($GlobalState.NOPM)" Write-Host "RAG: $($GlobalState.RAG)" Write-Host "Stream: $($GlobalState.Stream)" Write-Host "LLM Provider: $($GlobalState.LLMProvider)" } catch [System.Exception] { # Handle any exceptions that occur during the loading of the project state Update-ErrorHandling -ErrorRecord $_ -LogFilePath (Join-Path (split-path -Path $LoadProjectStatus -Parent) "ERROR.txt") } } else { Try { # Get the current date and time in the specified format $currentDateTime = Get-Date -Format "yyyyMMdd_HHmmss" if (-not [string]::IsNullOrEmpty($GlobalState.LogFolder)) { # Create a folder with the current date and time as the name in the specified log folder path $GlobalState.TeamDiscussionDataFolder = New-FolderAtPath -Path $GlobalState.LogFolder -FolderName $currentDateTime } else { # Set the log folder path to the user's Documents folder with the script name as a subfolder $GlobalState.LogFolder = Join-Path -Path ([Environment]::GetFolderPath("MyDocuments")) -ChildPath $scriptname if (-not (Test-Path -Path $GlobalState.LogFolder)) { # Create the log folder if it does not exist New-Item -ItemType Directory -Path $GlobalState.LogFolder | Out-Null } Write-Information "++ The logs will be saved in the following folder: $($GlobalState.LogFolder)" -InformationAction Continue # Create a folder with the current date and time as the name in the log folder path $GlobalState.TeamDiscussionDataFolder = New-FolderAtPath -Path $GlobalState.LogFolder -FolderName $currentDateTime } if ($GlobalState.TeamDiscussionDataFolder) { # Output information about the created team discussion folder Write-Information "++ Team folder was created '$($GlobalState.TeamDiscussionDataFolder)'" -InformationAction Continue } } Catch { # Handle any exceptions that occur during the creation of the discussion folder Update-ErrorHandling -ErrorRecord $_ -ErrorContext "Create folder" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") return $false } } try { $DocumentationFullName = Join-Path $GlobalState.TeamDiscussionDataFolder "Documentation.txt" -ErrorAction Stop $ProjectfilePath = Join-Path $GlobalState.TeamDiscussionDataFolder "Project.xml" -ErrorAction Stop Get-CheckForScriptUpdate -currentScriptVersion $AIPyTeamVersion -scriptName $scriptname } catch [System.Exception] { # Handle any exceptions that occur during the path joining or script update check Update-ErrorHandling -ErrorRecord $_ -ErrorContext "Setting up documentation and project file paths or checking for script update" -LogFilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") return $false } #endregion Setting Up #region ProjectTeam # Create ProjectTeam expert objects $requirementsAnalystRole = "Requirements Analyst" $requirementsAnalyst = [ProjectTeam]::new( "Analyst", $requirementsAnalystRole, @" You are an expert Python {0} with extensive experience in software development, system administration, and IT infrastructure. Your role is to analyze user requirements and prepare clear, actionable guidelines for Python Developers. Before providing guidelines, ensure you fully understand the user's business context, industry-specific requirements, and any regulatory considerations that may impact the project. When creating guidelines, consider the following aspects: 1. Script purpose and functionality 2. Input parameters and data types 3. Expected output and format 4. Error handling and logging requirements 5. Performance considerations 6. Security and compliance requirements 7. Coding standards and best practices 8. Integration with existing systems or scripts 9. Testing and validation criteria 10. Documentation requirements 11. Stakeholder needs and concerns 12. Scalability and future-proofing 13. Risk assessment and mitigation 14. User experience (if applicable) 15. Data management and protection 16. Monitoring and maintenance procedures 17. Version control and collaboration practices 18. Ethical implications Your guidelines should be: - Clear and concise - Technically accurate - Aligned with Python best practices - Scalable and maintainable - Forward-thinking and adaptable Format your response as follows: 1. Project Overview: (Brief summary of the project) 2. Functional Requirements: (List of key functionalities) 3. Technical Specifications: (Detailed technical requirements) 4. Integration and Architecture Considerations: (How the solution fits into the existing ecosystem) 5. Scalability and Future-proofing: (Design for growth and adaptability) 6. Performance Optimization: (Guidelines for efficient implementation) 7. User Experience Guidelines: (If applicable, considerations for user interaction) 8. Data Management and Compliance: (Data handling, storage, and regulatory compliance) 9. Monitoring and Maintenance: (Requirements for ongoing system health and updates) 10. Coding Guidelines: (Specific coding standards to follow) 11. Testing and Validation: (Criteria for testing the script) 12. Documentation Requirements: (For code, APIs, architecture, and user manuals) Ensure your guidelines provide a solid foundation for the Python Developer to create an efficient, robust, and maintainable script that aligns with business objectives and considers long-term implications. When analyzing requirements, ask probing questions to gather all necessary information. Consider edge cases, potential future needs. "@ -f $requirementsAnalystRole, 0.6, 0.9, $GlobalState ) $domainExpertRole = "Domain Expert" $domainExpert = [ProjectTeam]::new( "Domain Expert", $domainExpertRole, @" You are a {0} specializing in Python development for enterprise IT environments. Your role is to provide specialized insights and recommendations to Python Developer, ensuring script and programs align with domain-specific best practices, standards, and requirements. Your expertise covers: 1. **Environment Compatibility:** - Assess compatibility across various domain environments (cloud, on-premises, hybrid). - Validate requirements against industry standards and best practices. 2. **Performance, Security, and Optimization:** - Recommend best practices for performance optimization, including domain-specific metrics. - Provide security guidelines to protect data and systems in the target environment. - Suggest efficiency-enhancing techniques tailored to the domain. 3. **Configuration and Settings:** - Propose optimal configurations and settings for the domain environment. - Ensure recommendations are practical and adhere to industry standards. 4. **Domain-Specific Requirements:** - Outline specific requirements, security standards, and compliance needs. - Provide clear, detailed guidance for developers to meet these requirements. 5. **Design Review:** - Evaluate program designs for domain-specific constraints and requirements. - Offer feedback to align designs with domain best practices. When providing insights: - Be specific and actionable in your recommendations. - Cite relevant industry standards or best practices where applicable. - Consider the latest trends and technologies in the domain. - Anticipate potential challenges specific to the domain and suggest mitigation strategies. - Ensure your advice promotes scalability, maintainability, and long-term viability of the Python solutions. Your goal is to guide Python Developers in creating robust, efficient, and domain-compliant solutions that meet the specific needs of the enterprise IT environment. "@ -f $domainExpertRole, 0.65, 0.9, $GlobalState ) $systemArchitectRole = "System Architect" $systemArchitect = [ProjectTeam]::new( "Architect", $systemArchitectRole, @" You are an expert {0} specializing in Python project design. Your role is to create comprehensive, efficient, and scalable architectures for Python projects. Your expertise guides Python Developers in implementing robust and maintainable solutions. When designing a Python project architecture, you must: 1. **Overall Structure:** - Outline the high-level structure of the program. - Define the project's core components and their interactions. 2. **Modularity and Functionality:** - Identify and define necessary modules and functions. - Ensure logical separation of concerns and reusability of components. 3. **Scalability and Performance:** - Design for scalability to handle future growth and increased load. - Incorporate performance optimization strategies in the architecture. 4. **Data Flow and Component Interaction:** - Define clear data flow patterns between different components. - Specify interfaces and communication protocols between modules. 5. **Technology Stack:** - Select appropriate technologies, tools, and Python modules for the project. - Justify technology choices based on project requirements and best practices. 6. **Coding Standards and Best Practices:** - Provide guidelines for coding standards specific to Python. - Outline best practices for error handling, logging, and documentation. 7. **Security Considerations:** - Incorporate security best practices into the architecture. - Address potential security risks and provide mitigation strategies. 8. **Documentation:** - Create detailed architectural design documents. - Include diagrams, flowcharts, and textual descriptions of the architecture. 9. **Verification and Quality Assurance:** - Generate a list of verification questions to assess the architecture's completeness and effectiveness. - Provide criteria for architectural review and quality assurance. When presenting your architecture: - Be clear, concise, and use standard architectural notation where applicable. - Provide rationale for key design decisions. - Consider both current requirements and potential future needs. - Ensure your design promotes maintainability, testability, and ease of deployment. - Address potential challenges and provide strategies to overcome them. Your goal is to create a robust, efficient, and future-proof architecture that serves as a solid foundation for Python Developers to build upon. "@ -f $systemArchitectRole, 0.7, 0.85, $GlobalState ) $PythonDeveloperRole = "Python Developer" $PythonDeveloper = [ProjectTeam]::new( "Developer", $PythonDeveloperRole, @" You are an expert {0} with extensive experience in automation, scripting, and system administration for enterprise environments. Your role is to write efficient, readable, and maintainable Python code based on requirements provided by other domain experts. Context: You are working on a project to automate various IT processes in a large enterprise environment, including data analysis, reporting, and system monitoring. The code you write will be used by system administrators and must be robust, efficient, and follow industry best practices. Constraints and Guidelines: - Use Python version 3.9 or higher features only, such as dictionary merge operators, type hinting enhancements, and flexible decorators. - Prioritize readability and maintainability over complex one-liners. - Implement proper error handling and logging mechanisms. - Write modular and reusable code, following the DRY (Don't Repeat Yourself) principle. - Use type hints to improve code clarity and enable static type checking. - Include comprehensive docstrings and inline comments for clear documentation. - Follow PEP 8 style guide for consistent code formatting. - Implement unit tests using pytest or unittest to ensure code reliability. - Consider performance optimization techniques when dealing with large-scale data or operations. When using Python 3.9+ specific features, cite the relevant documentation and explain the benefits of using these newer features. Before finalizing your response: 1. Review your code to ensure it meets all requirements and follows Python best practices. 2. Verify that your solution is scalable and can handle potential future growth. 3. Consider security implications and implement necessary safeguards. 4. Ensure your code is compatible with common Python environments and dependencies used in enterprise settings. Your goal is to create high-quality, production-ready Python code that is easy to understand, maintain, and scale within a large enterprise IT infrastructure. "@ -f $PythonDeveloperRole, 0.65, 0.8, $GlobalState ) $qaEngineerRole = "Quality Assurance Engineer" $qaEngineer = [ProjectTeam]::new( "QA Engineer", $qaEngineerRole, @" You are an expert {0} specializing in Python script and module testing. Your role is to rigorously evaluate Python programs to ensure they meet all specified requirements, perform optimally, and are free of bugs. Your expertise is crucial in maintaining high standards of quality and reliability in Python development projects. When conducting quality assurance for a Python program, you must: 1. **Functional Testing:** - Verify that all features work as intended according to the specifications. - Test each function and module individually and as part of the whole system. - Ensure proper handling of various input scenarios, including edge cases. 2. **Performance Testing:** - Evaluate the script's execution time and resource usage under normal conditions. - Conduct load testing to assess performance under high-stress scenarios. - Identify and report any performance bottlenecks or inefficiencies. 3. **Error Handling and Resilience:** - Test error handling mechanisms and exception management. - Verify that the script fails gracefully and provides meaningful error messages. - Assess the script's ability to recover from unexpected situations. 4. **Compatibility Testing:** - Verify compatibility across different Python versions (3.9 and higher). - Test on various operating systems if cross-platform functionality is required. - Ensure compatibility with specified modules and dependencies. 5. **Security Testing:** - Assess the script for potential security vulnerabilities. - Verify that sensitive data is handled securely. - Check for proper implementation of security best practices. 6. **Code Review:** - Analyze the code for adherence to Python best practices and coding standards. - Identify areas for potential optimization or improved readability. 7. **Documentation Review:** - Verify that all functions and modules are properly documented. - Ensure that usage instructions and examples are clear and accurate. 8. **Regression Testing:** - Conduct tests to ensure that new changes haven't broken existing functionality. 9. **User Acceptance Testing:** - Simulate real-world usage scenarios to validate user experience. 10. **Reporting:** - Provide a comprehensive report detailing test results, identified issues, and recommendations. - Include metrics on code coverage, performance benchmarks, and quality scores. - Generate a list of verification questions for future analysis and continuous improvement. When presenting your findings: - Be thorough and objective in your assessments. - Prioritize issues based on their severity and impact. - Provide clear steps to reproduce any identified bugs. - Suggest specific, actionable improvements where applicable. - Use standard QA terminology and metrics to ensure clarity. Your goal is to ensure that the Python program is robust, reliable, and ready for deployment, meeting the highest standards of quality and performance. "@ -f $qaEngineerRole, 0.6, 0.9, $GlobalState ) $documentationSpecialistRole = "Documentation Specialist" $documentationSpecialist = [ProjectTeam]::new( "Documentator", $documentationSpecialistRole, @" You are an expert {0} focusing on Python projects. Your role is to create comprehensive, clear, and user-friendly documentation that supports both end-users and developers. Your expertise ensures that Python projects are well-documented, easily understood, and effectively utilized. When creating documentation for a Python project, you must produce the following: 1. **User Guide:** - Provide clear, step-by-step instructions for installation, configuration, and usage. - Include screenshots or diagrams where appropriate to enhance understanding. - Write in a user-friendly tone, avoiding overly technical jargon. 2. **Developer Documentation:** - Outline the code structure, key functions, and underlying logic. - Document the purpose and functionality of each module and significant function. - Include code comments extracted from the source files. 3. **Installation Guide:** - Detail system requirements and prerequisites. - Provide step-by-step installation instructions for different environments. - Document any necessary configuration steps post-installation. 4. **Dependencies and Prerequisites:** - List all required Python modules, versions, and any external dependencies. - Explain how to obtain and install these dependencies. 5. **Use Cases and Examples:** - Provide real-world examples of how to use the Python project. - Include sample code snippets and expected outputs. 6. **Troubleshooting Guide:** - Anticipate common issues and provide solutions. - Include error messages and their meanings. 7. **FAQ Section:** - Compile and answer frequently asked questions. - Cover both usage and technical aspects. 8. **API Documentation (if applicable):** - Detail all public functions, their parameters, and return values. - Provide usage examples for each API function. 9. **Change Log:** - Maintain a record of version changes, new features, and bug fixes. 10. **Video Tutorials (optional):** - Script short, clear video tutorials for key processes. - Focus on installation, basic usage, and common troubleshooting. When creating documentation: - Use clear, concise language appropriate for the target audience. - Maintain a consistent style and format throughout all documents. - Use standard documentation templates and follow industry best practices. - Ensure all information is accurate and up-to-date. - Include version numbers and last-updated dates on all documents. - Organize content logically with a clear hierarchy and easy navigation. - Use syntax highlighting for code snippets. - Proofread thoroughly for grammar, spelling, and technical accuracy. Your goal is to create documentation that enhances the usability and understanding of the Python project, making it accessible to users of varying skill levels and providing developers with the information they need to maintain and extend the project. "@ -f $documentationSpecialistRole, 0.6, 0.8, $GlobalState ) $projectManagerRole = "Project Manager" $projectManager = [ProjectTeam]::new( "Manager", $projectManagerRole, @" You are an experienced {0} specializing in Python development projects. Your role is to oversee the entire project lifecycle, coordinate between different team members, and provide comprehensive project reports. Your expertise ensures that Python projects are delivered on time, within scope, and to the highest quality standards. When summarizing a Python project, you must: 1. **Project Overview:** - Provide a concise summary of the project's objectives, scope, and key stakeholders. - Outline the project timeline, including start date, major milestones, and completion date. 2. **Requirements Analysis:** - Summarize the key requirements documented by the Requirements Analyst. - Highlight any changes or refinements to the initial requirements during the project. 3. **Architectural Design:** - Present an overview of the system architecture designed by the System Architect. - Emphasize key design decisions and their rationale, focusing on Python-specific architecture choices. 4. **Development Summary:** - Outline the major components and functionalities developed by the Python Developer. - Highlight any innovative solutions or Python-specific techniques employed. 5. **Quality Assurance:** - Summarize the testing process and results reported by the QA Engineer. - List key issues discovered and their resolutions. - Provide metrics on code quality, test coverage, and performance, using Python-specific tools and standards. 6. **Documentation Overview:** - Outline the documentation prepared by the Documentation Specialist. - Ensure all necessary documents (user guides, developer notes, API documentation) are completed and accessible. 7. **Key Achievements:** - Identify and highlight significant accomplishments and innovations in the Python project. - Relate these achievements to the initial project goals and stakeholder expectations. 8. **Challenges and Solutions:** - Discuss major challenges encountered during the project and how they were overcome. - Provide insights into lessons learned for future Python projects. 9. **Resource Utilization:** - Summarize the resources used, including team members, time, and any external Python libraries or tools. - Compare planned vs. actual resource usage. 10. **Stakeholder Feedback:** - Include a summary of feedback from key stakeholders. - Highlight areas of satisfaction and any concerns raised, particularly regarding Python implementation. 11. **Future Recommendations:** - Provide recommendations for future enhancements or maintenance of the Python project. - Suggest areas for potential expansion or improvement, considering Python ecosystem trends. 12. **Project Metrics:** - Present key project metrics such as on-time delivery, budget adherence, and quality indicators. - Include Python-specific metrics like code complexity, maintainability index, and performance benchmarks. When creating the project report: - Use clear, professional language suitable for both technical and non-technical audiences. - Provide an executive summary at the beginning of the report. - Use visual aids (charts, graphs, tables) to present data and progress effectively. - Ensure all sections of the report are cohesive and tell a complete story of the Python project's journey. - Be objective in your assessment, highlighting both successes and areas for improvement. - Include appendices for detailed technical information or extended data sets. - Emphasize how Python-specific features and best practices were leveraged throughout the project. Your goal is to provide a comprehensive, accurate, and insightful overview of the Python project, demonstrating its value to stakeholders and providing a clear picture of the project's execution and outcomes. Your report should showcase the strengths of using Python for the project while also addressing any challenges specific to Python development. "@ -f $projectManagerRole, 0.7, 0.85, $GlobalState ) #endregion ProjectTeam #region Main $Team = @() $Team += $requirementsAnalyst $Team += $systemArchitect $Team += $domainExpert $Team += $PythonDeveloper $Team += $qaEngineer $Team += $documentationSpecialist $Team += $projectManager foreach ($TeamMember in $Team) { $TeamMember.LLMProvider = $GlobalState.LLMProvider } if ($GlobalState.NOLog) { foreach ($TeamMember_ in $Team) { $TeamMember_.LogFilePath = "" } } if (-not $GlobalState.NOLog) { foreach ($TeamMember in $Team) { $TeamMember.DisplayInfo(0) | Out-File -FilePath $TeamMember.LogFilePath -Append } Write-Host "++ " -NoNewline Start-Transcript -Path (join-path $GlobalState.TeamDiscussionDataFolder "TRANSCRIPT.log") -Append } $RAGpromptAddon = $null if ($GlobalState.RAG -and (-not $LoadProjectStatus)) { $RAGSummarizePrompt = @" You are an expert in Retrieval-Augmented Generation (RAG) and text analysis. Your role is to process and analyze text inputs, extracting key information relevant to a given context. Your tasks include: 1. Cleaning the input text by removing advertising elements, menus, and other non-essential content. 2. Analyzing the cleaned text in relation to a specific user-provided description or context. 3. Extracting and summarizing key information, insights, and generating relevant questions. Your output should be concise, relevant, and insightful, focusing on the most important aspects of the text in relation to the given context. "@ $RAGresponse = Invoke-RAG -userInput $userInput -prompt $RAGSummarizePrompt -RAGAgent $projectManager if ($RAGresponse) { $RAGpromptAddon = @" ###RAG data### ````````text $($RAGresponse.trim()) ```````` "@ } } if (-not $LoadProjectStatus) { #region PM-pydev $userInputOryginal = $userInput $GlobalState.OrgUserInput = $userInputOryginal $projectManagerPrompt = @" Write detailed and concise Python project name, description, objectives, deliverables, additional considerations, and success criteria based on user input and RAG data. ###User input### ````````text $userInputOryginal ```````` $RAGpromptAddon "@ if (-not $GlobalState.NOTips) { $projectManagerPrompt += "`n`nNote: There is `$50 tip for this task." } $projectManagerFeedback = $projectManager.Feedback($PythonDeveloper, $projectManagerPrompt) Add-ToGlobalResponses $GlobalState $projectManagerFeedback $GlobalState.userInput = $projectManagerFeedback $PythonDeveloperPrompt = @" Your task is to write Python code based on the following requirements and guidelines. Please follow these steps: 1. Analyze the $($projectManager.Name)'s guidelines provided below. 2. Plan the structure of your Python script. 3. Write the Python code that meets the requirements. 4. Add appropriate error handling and logging. 5. Include comments explaining complex parts of the code. 6. Add version notes to document the code changes. 7. Perform a self-review of your code for efficiency and adherence to best practices. Please format your response as follows: 1. Script Purpose: (Brief description of what the script does) 2. Input Parameters: (List of input parameters, if any) 3. Output: (Description of what the script returns or produces) 4. Python code: (The actual code, properly formatted and commented) 5. Usage Example: (A brief example of how to use the script) 6. Self-Review Notes: (Any observations or potential improvements you've identified) $($projectManager.Name) Guidelines: ````````text $($($GlobalState.userInput).trim()) ```````` "@ if (-not $GlobalState.NOTips) { $PythonDeveloperPrompt += "`n`nNote: There is `$50 tip for this task." } $PythonDeveloperResponce = $PythonDeveloper.ProcessInput($PythonDeveloperPrompt) #$GlobalState.GlobalpydevResponse += $PythonDeveloperResponce Add-ToGlobalpydevResponses $GlobalState $PythonDeveloperResponce Add-ToGlobalResponses $GlobalState $PythonDeveloperResponce Save-AndUpdateCode -response $PythonDeveloperResponce -GlobalState $GlobalState #endregion PM-pydev #region RA-pydev #Invoke-ProcessFeedbackAndResponse -role $requirementsAnalyst -description $GlobalState.userInput -code $lastpydevCode -tipAmount 100 -globalResponse ([ref]$GlobalpydevResponse) -lastCode ([ref]$lastpydevCode) -fileVersion ([ref]$FileVersion) -teamDiscussionDataFolder $GlobalState.TeamDiscussionDataFolder if ($GlobalState.NOTips) { Invoke-ProcessFeedbackAndResponse -reviewer $requirementsAnalyst -recipient $PythonDeveloper -GlobalState $GlobalState } else { Invoke-ProcessFeedbackAndResponse -reviewer $requirementsAnalyst -recipient $PythonDeveloper -GlobalState $GlobalState -tipAmount 100 } #endregion RA-pydev #region SA-pydev if ($GlobalState.NOTips) { Invoke-ProcessFeedbackAndResponse -reviewer $systemArchitect -recipient $PythonDeveloper -GlobalState $GlobalState } else { Invoke-ProcessFeedbackAndResponse -reviewer $systemArchitect -recipient $PythonDeveloper -GlobalState $GlobalState -tipAmount 150 } #endregion SA-pydev #region DE-pydev if ($GlobalState.NOTips) { Invoke-ProcessFeedbackAndResponse -reviewer $domainExpert -recipient $PythonDeveloper -GlobalState $GlobalState } else { Invoke-ProcessFeedbackAndResponse -reviewer $domainExpert -recipient $PythonDeveloper -GlobalState $GlobalState -tipAmount 200 } #endregion DE-pydev #region QAE-pydev if ($GlobalState.NOTips) { Invoke-ProcessFeedbackAndResponse -reviewer $qaEngineer -recipient $PythonDeveloper -GlobalState $GlobalState } else { Invoke-ProcessFeedbackAndResponse -reviewer $qaEngineer -recipient $PythonDeveloper -GlobalState $GlobalState -tipAmount 300 } #endregion QAE-pydev #region Doc if (-not $GlobalState.NODocumentator) { if (-not $GlobalState.NOLog) { $documentationSpecialistResponce = $documentationSpecialist.ProcessInput($GlobalState.lastpydevCode) $documentationSpecialistResponce | Out-File -FilePath $DocumentationFullName } else { $documentationSpecialistResponce = $documentationSpecialist.ProcessInput($GlobalState.lastpydevCode) } Add-ToGlobalResponses $GlobalState $documentationSpecialistResponce } #endregion Doc #region PM Project report if (-not $GlobalState.NOPM) { # Example of summarizing all steps, Log final response to file if (-not $GlobalState.NOLog) { $projectManagerPrompt = "Generate project report without showing the Python code.`n" $projectManagerPrompt += $GlobalState.GlobalResponse -join ", " $projectManagerResponse = $projectManager.ProcessInput($projectManagerPrompt) $projectManagerResponse | Out-File -FilePath (Join-Path $GlobalState.TeamDiscussionDataFolder "ProjectSummary.log") } else { $projectManagerResponse = $projectManager.ProcessInput($GlobalState.GlobalResponse -join ", ") } Add-ToGlobalResponses $GlobalState $projectManagerResponse } #endregion PM Project report } #region Menu # Define the menu prompt message $MenuPrompt = "{0} The previous version of the code has been shared below after the feedback block.`n`n````````text`n{1}`n`````````n`nHere is previous version of the code:`n`n``````python`n{2}`n```````n`nThink step by step. Make sure your answer is unbiased." $MenuPromptNoUserChanges = "{0} The previous version of the code has been shared below. The code:`n`n``````python`n{1}`n```````n`nThink step by step. Make sure your answer is unbiased." # Start a loop to keep the menu running until the user chooses to quit do { # Display the menu options Write-Output "`n`n" Show-Header -HeaderText "MENU" Write-Host "Please select an option from the menu:" Write-Host "1. Suggest a new feature, enhancement, or change" Write-Host "2. Explain the code" Write-Host "3. Ask a specific question about the code" Write-Host "4. Generate documentation" Write-Host "5. Show the code with research" Write-Host "6. Save Project State" Write-Host "7. Code Refactoring Suggestions" Write-Host "8. Security Audit" Write-Host "9. Open project folder in file explorer" if (Test-Path -Path (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt")) { Write-Host "(E) Display content of (e)rror.txt" } Write-Host "(Q)uit" # Get the user's choice $userOption = Read-Host -Prompt "Enter your choice" Write-Output "" # Process the user's choice if it's not 'Q' or '9' (both of which mean 'quit') if ($userOption -ne 'Q') { switch ($userOption) { '1' { # Option 1: Suggest a new feature, enhancement, or change Show-Header -HeaderText "Suggest a new feature, enhancement, or change" do { $userChanges = Read-Host -Prompt "Suggest a new feature, enhancement, or change for the code." if (-not $userChanges) { Write-Host "-- You did not write anything. Please provide a suggestion." } } while (-not $userChanges) $promptMessage = "Based on the user's suggestion, incorporate a feature, enhancement, or change into the code. Show the next version of the code." $MenuPrompt_ = $MenuPrompt -f $promptMessage, $userChanges, $GlobalState.lastpydevCode $MenuPrompt_ += "`nYou need to show all the code." $PythonDeveloperResponce = $PythonDeveloper.ProcessInput($MenuPrompt_) #$GlobalState.GlobalpydevResponse += $PythonDeveloperResponce Add-ToGlobalpydevResponses $GlobalState $PythonDeveloperResponce Add-ToGlobalResponses $GlobalState $PythonDeveloperResponce $theCode = Export-AndWritePythonCodeBlocks -InputString $PythonDeveloperResponce -StartDelimiter '```python' -EndDelimiter '```' if ($theCode) { $theCode | Out-File -FilePath $(join-path $GlobalState.TeamDiscussionDataFolder "TheCode_v$($GlobalState.FileVersion).py") -Append -Encoding UTF8 $GlobalState.FileVersion += 1 $GlobalState.lastpydevCode = $theCode } } '2' { # Option 4: Explain the code Show-Header -HeaderText "Explain the code" $promptMessage = "Explain the code only.`n`n" $promptMessage += "The code:`n``````python`n" + $GlobalState.lastpydevCode + "`n```````n" try { $PythonDeveloperResponce = $PythonDeveloper.ProcessInput($promptMessage) #$GlobalState.GlobalpydevResponse += $PythonDeveloperResponce Add-ToGlobalpydevResponses $GlobalState $PythonDeveloperResponce Add-ToGlobalResponses $GlobalState $PythonDeveloperResponce } catch [System.Exception] { Write-Error "!! An error occurred while processing the input: $_" } } '3' { # Option 5: Ask a specific question about the code Show-Header -HeaderText "Ask a specific question about the code" try { $userChanges = Read-Host -Prompt "Ask a specific question about the code to seek clarification." $promptMessage = "Based on the user's question for the code, provide only the answer." if (Test-Path $DocumentationFullName) { $promptMessage += " The documentation:`n````````text`n$(get-content -path $DocumentationFullName -raw)`n`````````n`n" } $promptMessage += "You must answer the user's question only. Do not show the whole code even if user asks." $MenuPrompt_ = $MenuPrompt -f $promptMessage, $userChanges, $GlobalState.lastpydevCode $MenuPrompt_ += $userChanges $PythonDeveloperResponce = $PythonDeveloper.ProcessInput($MenuPrompt_) #$GlobalState.GlobalpydevResponse += $PythonDeveloperResponce Add-ToGlobalpydevResponses $GlobalState $PythonDeveloperResponce Add-ToGlobalResponses $GlobalState $PythonDeveloperResponce } catch [System.Management.Automation.PSInvalidOperationException] { Write-Error "!! An invalid operation occurred: $_" } catch [System.IO.IOException] { Write-Error "!! An I/O error occurred: $_" } catch [System.Exception] { Write-Error "!! An unexpected error occurred: $_" } } '4' { # Option 6: Generate documentation Show-Header -HeaderText "Generate documentation" try { if (Test-Path -Path $DocumentationFullName -ErrorAction SilentlyContinue) { Write-Information "++ Existing documentation found at $DocumentationFullName" -InformationAction Continue $userChoice = Read-Host -Prompt "Do you want to review and update the documentation based on the last version of the code? (Y/N)" if ($userChoice -eq 'Y' -or $userChoice -eq 'y') { $promptMessage = "Review and update the documentation based on the last version of the code.`n`n" $promptMessage += "The code:`n``````python`n" + $GlobalState.lastpydevCode + "`n```````n`n" $promptMessage += "The old documentation:`n````````text`n" + $(get-content -path $DocumentationFullName -raw) + "`n`````````n" $documentationSpecialistResponce = $documentationSpecialist.ProcessInput($promptMessage) $documentationSpecialistResponce | Out-File -FilePath $DocumentationFullName -Force Write-Information "++ Documentation updated and saved to $DocumentationFullName" -InformationAction Continue } } else { $documentationSpecialistResponce = $documentationSpecialist.ProcessInput($GlobalState.lastpydevCode) $documentationSpecialistResponce | Out-File -FilePath $DocumentationFullName Write-Information "++ Documentation generated and saved to $DocumentationFullName" -InformationAction Continue } } catch [System.Management.Automation.PSInvalidOperationException] { Write-Error "!! An invalid operation occurred: $_" } catch [System.IO.IOException] { Write-Error "!! An I/O error occurred: $_" } catch [System.UnauthorizedAccessException] { Write-Error "!! Unauthorized access: $_" } catch [System.Exception] { Write-Error "!! An unexpected error occurred: $_" } } '5' { # Option 7: Show the code Show-Header -HeaderText "Show the code with research" Write-Output $GlobalState.lastpydevCode # Option 8: The code research Show-Header -HeaderText "The code research" # Perform source code analysis Write-Output "Source code analysis:" Get-SourceCodeAnalysis -CodeBlock $GlobalState.lastpydevCode Write-Output "" # Perform cyclomatic complexity analysis Write-Verbose "`$lastpydevCode: $($GlobalState.lastpydevCode)" } '6' { Show-Header -HeaderText "Save Project State" if (-not (Test-Path $ProjectfilePath)) { try { Save-ProjectState -FilePath $ProjectfilePath -GlobalState $GlobalState if (Test-Path -Path $ProjectfilePath) { Write-Information "++ Project state saved successfully to $ProjectfilePath" -InformationAction Continue } else { Write-Warning "-- Project state was not saved. Please check the file path and try again." } } catch { Write-Error "!! An error occurred while saving the project state: $_" } } else { $userChoice = Read-Host -Prompt "File 'Project.xml' exists. Do you want to save now? (Y/N)" if ($userChoice -eq 'Y' -or $userChoice -eq 'y') { Save-ProjectState -FilePath $ProjectfilePath -GlobalState $GlobalState if (Test-Path -Path $ProjectfilePath) { Write-Information "++ Project state saved successfully to $ProjectfilePath" -InformationAction Continue } else { Write-Warning "-- Project state was not saved. Please check the file path and try again." } } } } '7' { # Option 9: Code Refactoring Suggestions Show-Header -HeaderText "Code Refactoring Suggestions" $promptMessage = "Provide suggestions for refactoring the code to improve readability, maintainability, and performance." $MenuPrompt_ = $MenuPromptNoUserChanges -f $promptMessage, $GlobalState.lastpydevCode $MenuPrompt_ += "`nShow only suggestions. No code" $refactoringSuggestions = $PythonDeveloper.ProcessInput($MenuPrompt_) $GlobalState.GlobalpydevResponse += $refactoringSuggestions Add-ToGlobalResponses $GlobalState $refactoringSuggestions # Display the refactoring suggestions to the user #Show-Header -HeaderText "Refactoring Suggestions Report" #Write-Output $refactoringSuggestions # Ask the user if they want to deploy the refactoring suggestions $deployChoice = Read-Host -Prompt "Do you want to deploy these refactoring suggestions? (Y/N)" if ($deployChoice -eq 'Y' -or $deployChoice -eq 'y') { $deployPromptMessage = "Deploy the refactoring suggestions into the code. Show the next version of the code." $DeployMenuPrompt_ = $MenuPrompt -f $deployPromptMessage, $refactoringSuggestions, $GlobalState.lastpydevCode $PythonDeveloperResponce = $PythonDeveloper.ProcessInput($DeployMenuPrompt_) #$GlobalState.GlobalpydevResponse += $PythonDeveloperResponce Add-ToGlobalpydevResponses $GlobalState $PythonDeveloperResponce Add-ToGlobalResponses $GlobalState $PythonDeveloperResponce Save-AndUpdateCode -response $PythonDeveloperResponce -GlobalState $GlobalState } else { Write-Output "Refactoring suggestions were not deployed." } } '8' { # Option 10: Security Audit Show-Header -HeaderText "Security Audit" $promptMessage = "Conduct a security audit of the code to identify potential vulnerabilities and ensure best security practices are followed. Show only security audit report." $MenuPrompt_ = $MenuPromptNoUserChanges -f $promptMessage, $GlobalState.lastpydevCode $MenuPrompt_ += "`nShow only security audit report. No Code." $PythonDevelopersecurityAuditReport = $PythonDeveloper.ProcessInput($MenuPrompt_) $GlobalState.GlobalpydevResponse += $PythonDevelopersecurityAuditReport Add-ToGlobalResponses $GlobalState $PythonDevelopersecurityAuditReport # Display the security audit report to the user Show-Header -HeaderText "Security Audit Report" Write-Output $PythonDevelopersecurityAuditReport # Ask the user if they want to deploy the security improvements $deployChoice = Read-Host -Prompt "Do you want to deploy these security improvements? (Y/N)" if ($deployChoice -eq 'Y' -or $deployChoice -eq 'y') { $deployPromptMessage = "Deploy the security improvements into the code. Show the next version of the code." $DeployMenuPrompt_ = $MenuPrompt -f $deployPromptMessage, $PythonDevelopersecurityAuditReport, $GlobalState.lastpydevCode $PythonDeveloperResponce = $PythonDeveloper.ProcessInput($DeployMenuPrompt_) #$GlobalState.GlobalpydevResponse += $PythonDeveloperResponce Add-ToGlobalpydevResponses $GlobalState $PythonDeveloperResponce Add-ToGlobalResponses $GlobalState $PythonDeveloperResponce Save-AndUpdateCode -response $PythonDeveloperResponce -GlobalState $GlobalState } else { Write-Output "Security improvements were not deployed." } } '9' { # Option 11: Open project folder in file explorer Show-Header -HeaderText "Open Project Folder in File Explorer" try { if ($GlobalState.TeamDiscussionDataFolder) { Start-Process explorer.exe -ArgumentList $GlobalState.TeamDiscussionDataFolder Write-Host "Project folder opened in File Explorer." } else { Write-Host "-- The project folder path is not set. Please ensure the TeamDiscussionDataFolder is defined." } } catch { Write-Error "-- An error occurred while trying to open the project folder: $_" } } 'e' { if (Test-Path -Path (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt")) { $errorContent = Get-Content -Path (Join-Path $GlobalState.TeamDiscussionDataFolder "ERROR.txt") -Raw Show-Header -HeaderText "Content of ERROR.txt" Write-Output $errorContent } else { Write-Output "No error file found." } } default { # Handle invalid options Write-Information "-- Invalid option. Please try again." -InformationAction Continue continue } } } } while ($userOption -ne 'Q') # End the loop when the user chooses to quit #endregion Menu #region Final code if (-not $GlobalState.NOLog) { # Log Developer last memory $TheFinalCodeFullName = Join-Path $GlobalState.TeamDiscussionDataFolder "TheCodeF.py" $GlobalState.lastpydevCode | Out-File -FilePath $TheFinalCodeFullName if (Test-Path -Path $TheFinalCodeFullName) { # Call the function to check the code in 'TheCode.py' file Write-Information "++ The final code was exported to $TheFinalCodeFullName" -InformationAction Continue } foreach ($TeamMember in $Team) { $TeamMember.DisplayInfo(0) | Out-File -FilePath $TeamMember.LogFilePath -Append } Write-Host "++ " -NoNewline Stop-Transcript } #endregion Final code Save-ProjectState -FilePath $ProjectfilePath -GlobalState $GlobalState if ($ProjectfilePath) { Write-Host "`n`n++ Your progress on Project has been saved!`n`n" Write-Host "++ You can resume working on this project at any time by loading the saved state. Just run:`nAIPyTeam.ps1 -LoadProjectStatus `"$ProjectfilePath`"`n`n" } Write-Host "Exiting..." # Ensure to reset the culture back to the original after the script execution [void](Register-EngineEvent Python.Exiting -Action { [Threading.Thread]::CurrentThread.CurrentUICulture = $originalCulture }) #endregion Main |