code365scripts.openai-help.xml
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<?xml version="1.0" encoding="utf-8"?>
<helpItems schema="maml" xmlns="http://msh"> <command:command xmlns:maml="http://schemas.microsoft.com/maml/2004/10" xmlns:command="http://schemas.microsoft.com/maml/dev/command/2004/10" xmlns:dev="http://schemas.microsoft.com/maml/dev/2004/10" xmlns:MSHelp="http://msdn.microsoft.com/mshelp"> <command:details> <command:name>New-ChatGPTConversation</command:name> <command:verb>New</command:verb> <command:noun>ChatGPTConversation</command:noun> <maml:description> <maml:para>Create a new ChatGPT conversation or get a Chat Completion result if you specify the prompt parameter directly</maml:para> </maml:description> </command:details> <maml:description> <maml:para>Create a new ChatGPT conversation, You can chat with the OpenAI service just like chat with a human. You can also get the chat completion result if you specify the prompt parameter.</maml:para> </maml:description> <command:syntax> <command:syntaxItem> <maml:name>New-ChatGPTConversation</maml:name> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="True (ByValue)" position="1" aliases="none"> <maml:name>prompt</maml:name> <maml:description> <maml:para>If you want to get result immediately, you can use this parameter to define the prompt. It will not start the chat conversation. If you provide a file path to this parameter, we will read the file as the prompt. You can also specify a url to this parameter, we will read the url as the prompt. You can read the prompt from a library (https://github.com/code365opensource/promptlibrary), by use "lib:xxxxx" as the prompt, for example, "lib:fitness".</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="token, access_token, accesstoken, key, apikey"> <maml:name>api_key</maml:name> <maml:description> <maml:para>The API key to access OpenAI service, if not specified, the API key will be read from environment variable OPENAI_API_KEY. You can also use "token" or "access_token" or "accesstoken" as the alias.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="engine, deployment"> <maml:name>model</maml:name> <maml:description> <maml:para>The model to use for this request, you can also set it in environment variable OPENAI_API_MODEL. If you are using Azure OpenAI Service, the model should be the deployment name you created in portal.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>endpoint</maml:name> <maml:description> <maml:para>The endpoint to use for this request, you can also set it in environment variable OPENAI_API_ENDPOINT. You can also use some special value to specify the endpoint, like "ollama", "local", "kimi", "zhipu".</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>system</maml:name> <maml:description> <maml:para>The system prompt, this is a string, you can use it to define the role you want it be, for example, "You are a chatbot, please answer the user's question according to the user's language." If you provide a file path to this parameter, we will read the file as the system prompt. You can also specify a url to this parameter, we will read the url as the system prompt. You can read the prompt from a library (https://github.com/code365opensource/promptlibrary), by use "lib:xxxxx" as the prompt, for example, "lib:fitness".</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>You are a chatbot, please answer the user's question according to the user's language.</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="settings"> <maml:name>config</maml:name> <maml:description> <maml:para>The dynamic settings for the API call, it can meet all the requirement for each model. please pass a custom object to this parameter, like @{temperature=1;max_tokens=1024}.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">PSObject</command:parameterValue> <dev:type> <maml:name>PSObject</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="out"> <maml:name>outFile</maml:name> <maml:description> <maml:para>If you want to save the result to a file, you can use this parameter to set the file path. You can also use "out" as the alias.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>json</maml:name> <maml:description> <maml:para>Send the response in json format.</maml:para> </maml:description> <dev:type> <maml:name>SwitchParameter</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>False</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="variables"> <maml:name>context</maml:name> <maml:description> <maml:para>If you want to pass some dymamic value to the prompt, you can use the context parameter here. It can be anything, you just specify a custom powershell object here. You define the variables in the system prompt or user prompt by using {{you_variable_name}} syntext, and then pass the data to the context parameter, like @{you_variable_name="your value"}. if there are multiple variables, you can use @{variable1="value1";variable2="value2"}.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">PSObject</command:parameterValue> <dev:type> <maml:name>PSObject</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>headers</maml:name> <maml:description> <maml:para>If you want to pass some custom headers to the API call, you can use this parameter. You can pass a custom hashtable to this parameter, like @{header1="value1";header2="value2"}.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">PSObject</command:parameterValue> <dev:type> <maml:name>PSObject</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> </command:syntaxItem> </command:syntax> <command:parameters> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="token, access_token, accesstoken, key, apikey"> <maml:name>api_key</maml:name> <maml:description> <maml:para>The API key to access OpenAI service, if not specified, the API key will be read from environment variable OPENAI_API_KEY. You can also use "token" or "access_token" or "accesstoken" as the alias.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="engine, deployment"> <maml:name>model</maml:name> <maml:description> <maml:para>The model to use for this request, you can also set it in environment variable OPENAI_API_MODEL. If you are using Azure OpenAI Service, the model should be the deployment name you created in portal.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>endpoint</maml:name> <maml:description> <maml:para>The endpoint to use for this request, you can also set it in environment variable OPENAI_API_ENDPOINT. You can also use some special value to specify the endpoint, like "ollama", "local", "kimi", "zhipu".</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>system</maml:name> <maml:description> <maml:para>The system prompt, this is a string, you can use it to define the role you want it be, for example, "You are a chatbot, please answer the user's question according to the user's language." If you provide a file path to this parameter, we will read the file as the system prompt. You can also specify a url to this parameter, we will read the url as the system prompt. You can read the prompt from a library (https://github.com/code365opensource/promptlibrary), by use "lib:xxxxx" as the prompt, for example, "lib:fitness".</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>You are a chatbot, please answer the user's question according to the user's language.</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="True (ByValue)" position="1" aliases="none"> <maml:name>prompt</maml:name> <maml:description> <maml:para>If you want to get result immediately, you can use this parameter to define the prompt. It will not start the chat conversation. If you provide a file path to this parameter, we will read the file as the prompt. You can also specify a url to this parameter, we will read the url as the prompt. You can read the prompt from a library (https://github.com/code365opensource/promptlibrary), by use "lib:xxxxx" as the prompt, for example, "lib:fitness".</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="settings"> <maml:name>config</maml:name> <maml:description> <maml:para>The dynamic settings for the API call, it can meet all the requirement for each model. please pass a custom object to this parameter, like @{temperature=1;max_tokens=1024}.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">PSObject</command:parameterValue> <dev:type> <maml:name>PSObject</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="out"> <maml:name>outFile</maml:name> <maml:description> <maml:para>If you want to save the result to a file, you can use this parameter to set the file path. You can also use "out" as the alias.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>json</maml:name> <maml:description> <maml:para>Send the response in json format.</maml:para> </maml:description> <command:parameterValue required="false" variableLength="false">SwitchParameter</command:parameterValue> <dev:type> <maml:name>SwitchParameter</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>False</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="variables"> <maml:name>context</maml:name> <maml:description> <maml:para>If you want to pass some dymamic value to the prompt, you can use the context parameter here. It can be anything, you just specify a custom powershell object here. You define the variables in the system prompt or user prompt by using {{you_variable_name}} syntext, and then pass the data to the context parameter, like @{you_variable_name="your value"}. if there are multiple variables, you can use @{variable1="value1";variable2="value2"}.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">PSObject</command:parameterValue> <dev:type> <maml:name>PSObject</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>headers</maml:name> <maml:description> <maml:para>If you want to pass some custom headers to the API call, you can use this parameter. You can pass a custom hashtable to this parameter, like @{header1="value1";header2="value2"}.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">PSObject</command:parameterValue> <dev:type> <maml:name>PSObject</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> </command:parameters> <command:inputTypes /> <command:returnValues> <command:returnValue> <dev:type> <maml:name>System.String, the completion result.</maml:name> </dev:type> <maml:description> <maml:para></maml:para> </maml:description> </command:returnValue> </command:returnValues> <maml:alertSet> <maml:alert> <maml:para></maml:para> </maml:alert> </maml:alertSet> <command:examples> <command:example> <maml:title>-------------------------- EXAMPLE 1 --------------------------</maml:title> <dev:code>New-ChatGPTConversation</dev:code> <dev:remarks> <maml:para>Use OpenAI Service with all the default settings, will read the API key from environment variable (OPENAI_API_KEY), enter the chat mode.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 2 --------------------------</maml:title> <dev:code>New-ChatGPTConversation -api_key "your api key" -model "gpt-3.5-turbo"</dev:code> <dev:remarks> <maml:para>Use OpenAI Service with the specified api key and model, enter the chat mode.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 3 --------------------------</maml:title> <dev:code>chat -system "You help me to translate the text to Chinese."</dev:code> <dev:remarks> <maml:para>Use OpenAI Service to translate text (system prompt specified), will read the API key from environment variable (OPENAI_API_KEY), enter the chat mode.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 4 --------------------------</maml:title> <dev:code>chat -endpoint "ollama" -model "llama3"</dev:code> <dev:remarks> <maml:para>Use OpenAI Service with the local model, enter the chat mode.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 5 --------------------------</maml:title> <dev:code>chat -endpoint $endpoint $env:OPENAI_API_ENDPOINT_AZURE -model $env:OPENAI_API_MODEL_AZURE -api_key $env:OPENAI_API_KEY_AZURE</dev:code> <dev:remarks> <maml:para>Use Azure OpenAI Service with the specified api key and model, enter the chat mode.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 6 --------------------------</maml:title> <dev:code>gpt -system "Translate the text to Chinese." -prompt "Hello, how are you?"</dev:code> <dev:remarks> <maml:para>Use OpenAI Service to translate text (system prompt specified), will read the API key from environment variable (OPENAI_API_KEY), model from OPENAI_API_MODEL (if present) or use "gpt-3.5-turbo" as default, get the chat completion result directly.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 7 --------------------------</maml:title> <dev:code>"Hello, how are you?" | gpt -system "Translate the text to Chinese."</dev:code> <dev:remarks> <maml:para>Use OpenAI Service to translate text (system prompt specified, user prompt will pass from pipeline), will read the API key from environment variable (OPENAI_API_KEY), model from OPENAI_API_MODEL (if present) or use "gpt-3.5-turbo" as default, get the chat completion result directly.</maml:para> </dev:remarks> </command:example> </command:examples> <command:relatedLinks> <maml:navigationLink> <maml:linkText>https://github.com/chenxizhang/openai-powershell</maml:linkText> <maml:uri>https://github.com/chenxizhang/openai-powershell</maml:uri> </maml:navigationLink> </command:relatedLinks> </command:command> <command:command xmlns:maml="http://schemas.microsoft.com/maml/2004/10" xmlns:command="http://schemas.microsoft.com/maml/dev/command/2004/10" xmlns:dev="http://schemas.microsoft.com/maml/dev/2004/10" xmlns:MSHelp="http://msdn.microsoft.com/mshelp"> <command:details> <command:name>New-ImageGeneration</command:name> <command:verb>New</command:verb> <command:noun>ImageGeneration</command:noun> <maml:description> <maml:para>Generate image from prompt, using DALL-e-3 model.</maml:para> </maml:description> </command:details> <maml:description> <maml:para>Generate image from prompt, using DALL-e-3 model. The image size can be 1024x1024, 1792x1024, 1024x1792.</maml:para> </maml:description> <command:syntax> <command:syntaxItem> <maml:name>New-ImageGeneration</maml:name> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="1" aliases="none"> <maml:name>prompt</maml:name> <maml:description> <maml:para>The prompt to generate image, this is required, and it can pass from pipeline. If you want to use a file as prompt, you can specify the file path here. You can also specify a url as prompt, we will read the url as prompt. You can read the prompt from a library (https://github.com/code365opensource/promptlibrary), by use "lib:xxxxx" as the prompt, for example, "lib:fitness".</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>api_key</maml:name> <maml:description> <maml:para>The API key to access OpenAI service, if not specified, the API key will be read from environment variable OPENAI_API_KEY. if you use Azure OpenAI service, you can specify the API key by environment variable OPENAI_API_KEY_AZURE or OPENAI_API_KEY_AZURE_<environment>, the <environment> can be any names you want, for example, OPENAI_API_KEY_AZURE_DEV, OPENAI_API_KEY_AZURE_PROD, OPENAI_API_KEY_AZURE_TEST, etc.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>endpoint</maml:name> <maml:description> <maml:para>The endpoint to access OpenAI service, if not specified, the endpoint will be read from environment variable OPENAI_ENDPOINT. if you use Azure OpenAI service, you can specify the endpoint by environment variable OPENAI_ENDPOINT_AZURE or OPENAI_ENDPOINT_AZURE_<environment>, the <environment> can be any names you want, for example, OPENAI_ENDPOINT_AZURE_DEV, OPENAI_ENDPOINT_AZURE_PROD, OPENAI_ENDPOINT_AZURE_TEST, etc.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="true" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>azure</maml:name> <maml:description> <maml:para>Use Azure OpenAI service, if specified, the API key and endpoint will be read from environment variable OPENAI_API_KEY_AZURE or OPENAI_API_KEY_AZURE_<environment>, the <environment> can be any names you want, for example, OPENAI_API_KEY_AZURE_DEV, OPENAI_API_KEY_AZURE_PROD, OPENAI_API_KEY_AZURE_TEST, etc. and OPENAI_ENDPOINT_AZURE or OPENAI_ENDPOINT_AZURE_<environment>.</maml:para> </maml:description> <dev:type> <maml:name>SwitchParameter</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>False</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>size</maml:name> <maml:description> <maml:para>The size of the image to generate, the value can be small (1024x1024), medium(1792x1024), large(1024x1792), the default is small.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>Small</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="out"> <maml:name>outfolder</maml:name> <maml:description> <maml:para>The folder to save the generated image, default is current folder. You can use out as the alias of this parameter.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>.</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="env"> <maml:name>environment</maml:name> <maml:description> <maml:para>The environment name, if you use Azure OpenAI service, you can specify the environment by this parameter, the environment name can be any names you want, for example, dev, prod, test, etc, the environment name will be used to read the API key and endpoint from environment variable, for example, OPENAI_API_KEY_AZURE_DEV, OPENAI_ENDPOINT_AZURE_DEV, etc. You can use env as the alias of this parameter.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> </command:syntaxItem> </command:syntax> <command:parameters> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="1" aliases="none"> <maml:name>prompt</maml:name> <maml:description> <maml:para>The prompt to generate image, this is required, and it can pass from pipeline. If you want to use a file as prompt, you can specify the file path here. You can also specify a url as prompt, we will read the url as prompt. You can read the prompt from a library (https://github.com/code365opensource/promptlibrary), by use "lib:xxxxx" as the prompt, for example, "lib:fitness".</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>api_key</maml:name> <maml:description> <maml:para>The API key to access OpenAI service, if not specified, the API key will be read from environment variable OPENAI_API_KEY. if you use Azure OpenAI service, you can specify the API key by environment variable OPENAI_API_KEY_AZURE or OPENAI_API_KEY_AZURE_<environment>, the <environment> can be any names you want, for example, OPENAI_API_KEY_AZURE_DEV, OPENAI_API_KEY_AZURE_PROD, OPENAI_API_KEY_AZURE_TEST, etc.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>endpoint</maml:name> <maml:description> <maml:para>The endpoint to access OpenAI service, if not specified, the endpoint will be read from environment variable OPENAI_ENDPOINT. if you use Azure OpenAI service, you can specify the endpoint by environment variable OPENAI_ENDPOINT_AZURE or OPENAI_ENDPOINT_AZURE_<environment>, the <environment> can be any names you want, for example, OPENAI_ENDPOINT_AZURE_DEV, OPENAI_ENDPOINT_AZURE_PROD, OPENAI_ENDPOINT_AZURE_TEST, etc.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> <command:parameter required="true" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>azure</maml:name> <maml:description> <maml:para>Use Azure OpenAI service, if specified, the API key and endpoint will be read from environment variable OPENAI_API_KEY_AZURE or OPENAI_API_KEY_AZURE_<environment>, the <environment> can be any names you want, for example, OPENAI_API_KEY_AZURE_DEV, OPENAI_API_KEY_AZURE_PROD, OPENAI_API_KEY_AZURE_TEST, etc. and OPENAI_ENDPOINT_AZURE or OPENAI_ENDPOINT_AZURE_<environment>.</maml:para> </maml:description> <command:parameterValue required="false" variableLength="false">SwitchParameter</command:parameterValue> <dev:type> <maml:name>SwitchParameter</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>False</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="none"> <maml:name>size</maml:name> <maml:description> <maml:para>The size of the image to generate, the value can be small (1024x1024), medium(1792x1024), large(1024x1792), the default is small.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>Small</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="out"> <maml:name>outfolder</maml:name> <maml:description> <maml:para>The folder to save the generated image, default is current folder. You can use out as the alias of this parameter.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>.</dev:defaultValue> </command:parameter> <command:parameter required="false" variableLength="true" globbing="false" pipelineInput="False" position="named" aliases="env"> <maml:name>environment</maml:name> <maml:description> <maml:para>The environment name, if you use Azure OpenAI service, you can specify the environment by this parameter, the environment name can be any names you want, for example, dev, prod, test, etc, the environment name will be used to read the API key and endpoint from environment variable, for example, OPENAI_API_KEY_AZURE_DEV, OPENAI_ENDPOINT_AZURE_DEV, etc. You can use env as the alias of this parameter.</maml:para> </maml:description> <command:parameterValue required="true" variableLength="false">String</command:parameterValue> <dev:type> <maml:name>String</maml:name> <maml:uri /> </dev:type> <dev:defaultValue>None</dev:defaultValue> </command:parameter> </command:parameters> <command:inputTypes /> <command:returnValues> <command:returnValue> <dev:type> <maml:name>System.String, the file path of the generated image.</maml:name> </dev:type> <maml:description> <maml:para></maml:para> </maml:description> </command:returnValue> </command:returnValues> <maml:alertSet> <maml:alert> <maml:para></maml:para> </maml:alert> </maml:alertSet> <command:examples> <command:example> <maml:title>-------------------------- EXAMPLE 1 --------------------------</maml:title> <dev:code>New-ImageGeneration -prompt "A painting of a cat sitting on a chair"</dev:code> <dev:remarks> <maml:para>Use dall-e-3 model to generate image, the image size is 1024x1024, the generated image will be saved to current folder.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 2 --------------------------</maml:title> <dev:code>image -prompt "A painting of a cat sitting on a chair"</dev:code> <dev:remarks> <maml:para>Use the alias (image) to generate image, the image size is 1024x1024, the generated image will be saved to current folder.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 3 --------------------------</maml:title> <dev:code>"A painting of a cat sitting on a chair" | New-ImageGeneration</dev:code> <dev:remarks> <maml:para>Pass the prompt from pipeline, the image size is 1024x1024, the generated image will be saved to current folder.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 4 --------------------------</maml:title> <dev:code>New-ImageGeneration -prompt "A painting of a cat sitting on a chair" -size medium -outfolder "c:\temp" -api_key "your API key" -endpoint "your endpoint"</dev:code> <dev:remarks> <maml:para>Use dall-e-3 model to generate image, the image size is 1792x1024, the generated image will be saved to c:\temp folder, use your own API key and endpoint.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 5 --------------------------</maml:title> <dev:code>New-ImageGeneration -prompt "A painting of a cat sitting on a chair" -size small -outfolder "c:\temp" -azure</dev:code> <dev:remarks> <maml:para>Use dall-e-3 model to generate image, the image size is 1024x1024, the generated image will be saved to c:\temp folder, use Azure OpenAI service.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 6 --------------------------</maml:title> <dev:code>New-ImageGeneration -prompt "A painting of a cat sitting on a chair" -size small -outfolder "c:\temp" -azure -environment "dev"</dev:code> <dev:remarks> <maml:para>Use dall-e-3 model to generate image, the image size is 1024x1024, the generated image will be saved to c:\temp folder, use Azure OpenAI service, read API key and endpoint from environment variable OPENAI_API_KEY_AZURE_DEV and OPENAI_ENDPOINT_AZURE_DEV.</maml:para> </dev:remarks> </command:example> <command:example> <maml:title>-------------------------- EXAMPLE 7 --------------------------</maml:title> <dev:code>New-ImageGeneration -outfolder "c:\temp" -azure -prompt "c:\temp\prompt.txt"</dev:code> <dev:remarks> <maml:para>Use dall-e-3 model to generate image, the image size is 1024x1024, the generated image will be saved to c:\temp folder, use Azure OpenAI service, and use prompt from file c:\temp\prompt.txt</maml:para> </dev:remarks> </command:example> </command:examples> <command:relatedLinks> <maml:navigationLink> <maml:linkText>https://github.com/chenxizhang/openai-powershell</maml:linkText> <maml:uri>https://github.com/chenxizhang/openai-powershell</maml:uri> </maml:navigationLink> </command:relatedLinks> </command:command> </helpItems> |