├── .vscode
├── settings.json
└── launch.json
├── .editorconfig
├── Tests
└── Get-AIChat.Tests.ps1
├── src
├── OpenAI.Client
│ ├── OpenAI.Client.csproj
│ ├── Constructors.cs
│ ├── Extensions
│ │ ├── StringExtensions.cs
│ │ └── HttpClientExtensions.cs
│ ├── Stringifiers.cs
│ ├── JsonStringEnumConverter.cs
│ ├── Chat.cs
│ ├── TemplateDirectory
│ │ └── Class.liquid
│ └── OpenAI.nswag
└── PowerShellAssistant
│ ├── FormatSettings.settings.ps1
│ ├── Publish.build.ps1
│ ├── PowerShellAssistant.csproj
│ ├── PowerShellAssistant.psd1
│ └── PowerShellAssistant.psm1
├── PowerShellAssistant.sln
├── README.MD
├── LICENSE
└── .gitignore
/.vscode/settings.json:
--------------------------------------------------------------------------------
1 | {
2 | "gitlens.proxy": {}
3 | }
--------------------------------------------------------------------------------
/.editorconfig:
--------------------------------------------------------------------------------
1 | [*.cs]
2 | dotnet_naming_style.interface.required_prefix = none
--------------------------------------------------------------------------------
/Tests/Get-AIChat.Tests.ps1:
--------------------------------------------------------------------------------
1 | BeforeAll {
2 | $ManifestPath = Resolve-Path (Join-Path $PSScriptRoot '../src/PowerShellAssistant/PowerShellAssistant.psd1')
3 | Import-Module $ManifestPath
4 | }
5 | Describe 'Get-AIChat' {
6 | Context 'When called with no parameters' {
7 | It 'Should return a chat' -Pending {
8 | $chat = Get-AIChat 'Return only the word PESTER'
9 | $chat | Should -Be 'PESTER'
10 | }
11 | }
12 | }
--------------------------------------------------------------------------------
/src/OpenAI.Client/OpenAI.Client.csproj:
--------------------------------------------------------------------------------
1 |
2 |
3 |
4 | net7.0
5 | enable
6 | enable
7 |
8 |
9 |
10 | false
11 | none
12 |
13 |
14 |
--------------------------------------------------------------------------------
/src/OpenAI.Client/Constructors.cs:
--------------------------------------------------------------------------------
1 | namespace OpenAI;
2 | public partial class ChatCompletionRequestMessage
3 | {
4 | public ChatCompletionRequestMessage() { }
5 |
6 | public ChatCompletionRequestMessage(ChatCompletionResponseMessage responseMessage)
7 | {
8 | Content = responseMessage.Content;
9 | Role = Enum.Parse(responseMessage.Role.ToString());
10 | }
11 |
12 | public ChatCompletionRequestMessage(string userMessage) : this(userMessage, ChatCompletionRequestMessageRole.User) { }
13 |
14 | public ChatCompletionRequestMessage(string userMessage, ChatCompletionRequestMessageRole role = ChatCompletionRequestMessageRole.User)
15 | {
16 | Role = role;
17 | Content = userMessage;
18 | }
19 | }
--------------------------------------------------------------------------------
/src/OpenAI.Client/Extensions/StringExtensions.cs:
--------------------------------------------------------------------------------
1 | // Taken with love from: https://github.com/betalgo/openai/blob/master/OpenAI.SDK/Extensions/StringExtensions.cs
2 |
3 | namespace OpenAI.Extensions;
4 |
5 | ///
6 | /// Extension methods for string manipulation
7 | ///
8 | public static class StringExtensions
9 | {
10 | ///
11 | /// Remove the search string from the begging of string if exist
12 | ///
13 | ///
14 | ///
15 | ///
16 | public static string RemoveIfStartWith(this string text, string search)
17 | {
18 | var pos = text.IndexOf(search, StringComparison.Ordinal);
19 | return pos != 0 ? text : text[search.Length..];
20 | }
21 | }
--------------------------------------------------------------------------------
/src/PowerShellAssistant/FormatSettings.settings.ps1:
--------------------------------------------------------------------------------
1 | @{
2 | 'OpenAI.Engine' = 'Id', 'Ready'
3 | 'OpenAI.Model' = 'Id', 'Created', 'Owned_By'
4 | 'OpenAI.CreateCompletionResponse' = 'Model', 'Created', 'Choices', 'Usage'
5 | 'OpenAI.ChatCompletionRequestMessage' = { & (Get-Module PowerShellAssistant) { Format-ChatMessage $args[0] } $PSItem }
6 | 'OpenAI.ChatCompletionResponseMessage' = { & (Get-Module PowerShellAssistant) { Format-ChatMessage $args[0] } $PSItem }
7 | 'OpenAI.CreateChatCompletionRequest' = { & (Get-Module PowerShellAssistant) { Format-CreateChatCompletionRequest $args[0] } $PSItem }
8 | 'OpenAI.CreateChatCompletionResponse' = { & (Get-Module PowerShellAssistant) { Format-CreateChatCompletionResponse $args[0] } $PSItem }
9 | 'OpenAI.Choices2' = { & (Get-Module PowerShellAssistant) { Format-Choices2 $args[0] } $PSItem }
10 | 'OpenAI.ChatConversation' = { & (Get-Module PowerShellAssistant) { Format-ChatConversation $args[0] } $PSItem }
11 | 'OpenAI.CreateChatCompletionChunkedResponse' = { & (Get-Module PowerShellAssistant) { Format-CreateChatCompletionChunkedResponse $args[0] } $PSItem }
12 | }
--------------------------------------------------------------------------------
/PowerShellAssistant.sln:
--------------------------------------------------------------------------------
1 |
2 | Microsoft Visual Studio Solution File, Format Version 12.00
3 | # Visual Studio Version 17
4 | VisualStudioVersion = 17.0.31903.59
5 | MinimumVisualStudioVersion = 10.0.40219.1
6 | Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "src", "src", "{2500AD41-2201-4E29-BDA2-B0090C3D5629}"
7 | EndProject
8 | Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "PowerShellAssistant", "src\PowerShellAssistant\PowerShellAssistant.csproj", "{DD35EB37-A1E7-441B-98F9-D2C75C455739}"
9 | EndProject
10 | Global
11 | GlobalSection(SolutionConfigurationPlatforms) = preSolution
12 | Debug|Any CPU = Debug|Any CPU
13 | Release|Any CPU = Release|Any CPU
14 | EndGlobalSection
15 | GlobalSection(SolutionProperties) = preSolution
16 | HideSolutionNode = FALSE
17 | EndGlobalSection
18 | GlobalSection(ProjectConfigurationPlatforms) = postSolution
19 | {DD35EB37-A1E7-441B-98F9-D2C75C455739}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
20 | {DD35EB37-A1E7-441B-98F9-D2C75C455739}.Debug|Any CPU.Build.0 = Debug|Any CPU
21 | {DD35EB37-A1E7-441B-98F9-D2C75C455739}.Release|Any CPU.ActiveCfg = Release|Any CPU
22 | {DD35EB37-A1E7-441B-98F9-D2C75C455739}.Release|Any CPU.Build.0 = Release|Any CPU
23 | EndGlobalSection
24 | GlobalSection(NestedProjects) = preSolution
25 | {DD35EB37-A1E7-441B-98F9-D2C75C455739} = {2500AD41-2201-4E29-BDA2-B0090C3D5629}
26 | EndGlobalSection
27 | EndGlobal
28 |
--------------------------------------------------------------------------------
/src/OpenAI.Client/Stringifiers.cs:
--------------------------------------------------------------------------------
1 | namespace OpenAI;
2 |
3 | public partial class Usage
4 | {
5 | public static string ToUsageString(int total, int prompt, int? completion)
6 | {
7 | if (completion.HasValue)
8 | return $"Total: {total} (Prompt: {prompt}, Completion: {completion.Value})";
9 | else
10 | return $"Total: {total} (Prompt: {prompt})";
11 | }
12 | public override string ToString()
13 | {
14 | return ToUsageString(Total_tokens, Prompt_tokens, Completion_tokens);
15 | }
16 | }
17 | public partial class Usage2
18 | {
19 | public override string ToString()
20 | {
21 | return Usage.ToUsageString(Total_tokens, Prompt_tokens, Completion_tokens);
22 | }
23 | }
24 | public partial class Usage3
25 | {
26 | public override string ToString()
27 | {
28 | return Usage.ToUsageString(Total_tokens, Prompt_tokens, Completion_tokens);
29 | }
30 | }
31 | public partial class Usage4
32 | {
33 | public override string ToString()
34 | {
35 | return Usage.ToUsageString(Total_tokens, Prompt_tokens, null);
36 | }
37 | }
38 |
39 | public partial class ChatCompletionRequestMessage
40 | {
41 | public override string ToString()
42 | {
43 | return $"{Role}: {Content}";
44 | }
45 | }
46 |
47 | public partial class Choices2
48 | {
49 | public override string ToString()
50 | {
51 | return Index.HasValue
52 | ? $"Choice {Index + 1} - {Message?.Role}: {Message?.Content}"
53 | : $"{Message?.Role}: {Message?.Content}";
54 | }
55 | }
--------------------------------------------------------------------------------
/README.MD:
--------------------------------------------------------------------------------
1 | # DEPRECATION NOTICE: I am no longer developing this tool, I recommend you use PowerShellAI or Github Copilot Chat in Visual Studio Code as it meets all the use cases I was going to have for this.
2 |
3 | # PowerShell Assistant
4 |
5 | This module provides support for the OpenAI API and tools to leverage it including a chat client and PSReadline completer.
6 |
7 | Requires Powershell 7.3 due to some .NET 7 feature usage.
8 |
9 | ## Code Generation
10 |
11 | This module's core engine is an NSwag-generated C# client from the OpenAI OpenAPI specification. This should make it so that as new functions and models are released, they can be taken advantage of by regenerating the client.
12 |
13 | ## User Interface
14 |
15 | The `Get-Chat` (aka `chat`) and `Get-Code` (aka `code`) are meant for interactive scenarios. `chat` can be used as a standalone interactive tool which will copy any recommended code discovered to your clipboard automatically. `code` is meant to provide suggestions based on existing code and context, and meant in the future to integrate as a suggestion provider into tools such as PSReadline.
16 |
17 | `Get-AIChat` is the underlying engine that powers `Get-Chat` and can be used for more programmatic noninteractive scenarios.
18 |
19 | ## Formatting
20 |
21 | This module strives so that all UI "output" is done with custom format files rather than write-host or raw strings. This ensures that you still have access to the underlying "object" underneath without requiring a `-Raw` or similar parameter parameter
22 |
23 | ## Alternatives
24 |
25 | Check out Doug Finke's excellent [PowerShellAI](https://github.com/dfinke/PowerShellAI) module for a pure-PowerShell implementation of OpenAI.
26 |
--------------------------------------------------------------------------------
/src/PowerShellAssistant/Publish.build.ps1:
--------------------------------------------------------------------------------
1 | #requires -module InvokeBuild
2 | param(
3 | $Destination = $(Resolve-Path (Join-Path $PSScriptRoot '..\..\dist')),
4 | $FormatSettingsPath = $(Join-Path $PSScriptRoot 'FormatSettings.settings.ps1')
5 | )
6 |
7 | Task Formats {
8 | Import-Module EzOut -ErrorAction Stop
9 |
10 | $formatPath = Join-Path $Destination 'Formats'
11 | New-Item -ItemType Directory -Force -Path $formatPath | Out-Null
12 |
13 | [hashtable]$tableProperties = . $formatSettingsPath
14 |
15 | $formatFilePaths = foreach ($kv in $tableProperties.GetEnumerator()) {
16 | $typeName = $kv.Name
17 | $outPath = Join-Path $formatPath $($typeName + '.Format.ps1xml')
18 | $setting = $kv.Value
19 |
20 | switch ($setting.GetType()) {
21 | ([string]) {
22 | Write-FormatView -TypeName $typeName -Property $kv.Value -AutoSize
23 | | Out-FormatData
24 | | Out-File -Force $outPath
25 | }
26 | ([object[]]) {
27 | Write-FormatView -TypeName $typeName -Property $kv.Value -AutoSize
28 | | Out-FormatData
29 | | Out-File -Force $outPath
30 | }
31 | ([ScriptBlock]) {
32 | Write-FormatView -TypeName $typeName -Action $setting
33 | | Out-FormatData
34 | | Out-File -Force $outPath
35 | }
36 | ([hashtable]) {
37 | throw [NotImplementedException]'TODO: Hashtable not implemented. It will allow select-style expressions to create virtual properties'
38 | }
39 | default {
40 | throw [NotSupportedException]"Unsupported format setting value type: $($setting.GetType())"
41 | }
42 | }
43 | [IO.Path]::GetRelativePath($Destination, $outPath)
44 | }
45 | Update-ModuleManifest -Path $Destination/PowerShellAssistant.psd1 -FormatsToProcess $formatFilePaths
46 | }
47 |
48 | Task . Formats
--------------------------------------------------------------------------------
/src/PowerShellAssistant/PowerShellAssistant.csproj:
--------------------------------------------------------------------------------
1 |
2 |
3 |
4 | net7.0
5 | enable
6 | enable
7 | ../../dist
8 | false
9 |
10 |
11 |
12 | false
13 | none
14 |
15 |
16 |
17 |
18 |
19 | contentFiles
20 | All
21 |
22 |
23 | PreserveNewest
24 | PreserveNewest
25 |
26 |
27 | PreserveNewest
28 | PreserveNewest
29 |
30 |
31 |
32 |
33 |
34 |
35 |
36 |
37 |
--------------------------------------------------------------------------------
/.vscode/launch.json:
--------------------------------------------------------------------------------
1 | {
2 | // Use IntelliSense to learn about possible attributes.
3 | // Hover to view descriptions of existing attributes.
4 | // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
5 | "version": "0.2.0",
6 | "configurations": [
7 | {
8 | "name": ".NET Core Launch (console)",
9 | "type": "coreclr",
10 | "request": "launch",
11 | "WARNING01": "*********************************************************************************",
12 | "WARNING02": "The C# extension was unable to automatically decode projects in the current",
13 | "WARNING03": "workspace to create a runnable launch.json file. A template launch.json file has",
14 | "WARNING04": "been created as a placeholder.",
15 | "WARNING05": "",
16 | "WARNING06": "If OmniSharp is currently unable to load your project, you can attempt to resolve",
17 | "WARNING07": "this by restoring any missing project dependencies (example: run 'dotnet restore')",
18 | "WARNING08": "and by fixing any reported errors from building the projects in your workspace.",
19 | "WARNING09": "If this allows OmniSharp to now load your project then --",
20 | "WARNING10": " * Delete this file",
21 | "WARNING11": " * Open the Visual Studio Code command palette (View->Command Palette)",
22 | "WARNING12": " * run the command: '.NET: Generate Assets for Build and Debug'.",
23 | "WARNING13": "",
24 | "WARNING14": "If your project requires a more complex launch configuration, you may wish to delete",
25 | "WARNING15": "this configuration and pick a different template using the 'Add Configuration...'",
26 | "WARNING16": "button at the bottom of this file.",
27 | "WARNING17": "*********************************************************************************",
28 | "preLaunchTask": "build",
29 | "program": "${workspaceFolder}/bin/Debug//.dll",
30 | "args": [],
31 | "cwd": "${workspaceFolder}",
32 | "console": "internalConsole",
33 | "stopAtEntry": false
34 | },
35 | {
36 | "name": ".NET Core Attach",
37 | "type": "coreclr",
38 | "request": "attach"
39 | }
40 | ]
41 | }
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
1 | MIT License
2 |
3 | Copyright (c) 2023 Justin Grote @JustinWGrote
4 |
5 | Permission is hereby granted, free of charge, to any person obtaining a copy
6 | of this software and associated documentation files (the "Software"), to deal
7 | in the Software without restriction, including without limitation the rights
8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
9 | copies of the Software, and to permit persons to whom the Software is
10 | furnished to do so, subject to the following conditions:
11 |
12 | The above copyright notice and this permission notice shall be included in all
13 | copies or substantial portions of the Software.
14 |
15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
21 | SOFTWARE.
22 |
23 | ---
24 |
25 | Substantial Portion from https://github.com/betalgo/openai
26 |
27 | MIT License
28 |
29 | Copyright (c) 2022 Betalgo
30 |
31 | Permission is hereby granted, free of charge, to any person obtaining a copy
32 | of this software and associated documentation files (the "Software"), to deal
33 | in the Software without restriction, including without limitation the rights
34 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
35 | copies of the Software, and to permit persons to whom the Software is
36 | furnished to do so, subject to the following conditions:
37 |
38 | The above copyright notice and this permission notice shall be included in all
39 | copies or substantial portions of the Software.
40 |
41 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
42 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
43 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
44 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
45 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
46 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
47 | SOFTWARE.
--------------------------------------------------------------------------------
/src/OpenAI.Client/JsonStringEnumConverter.cs:
--------------------------------------------------------------------------------
1 | namespace OpenAI;
2 |
3 | using System.Reflection;
4 | using System.Runtime.Serialization;
5 | using System.Text.Json;
6 | using System.Text.Json.Serialization;
7 |
8 | ///
9 | /// This custom enum converter supports custom name serialization using either the JsonPropertyName or EnumMember attributes. Required because System.Text.JSON doesn't support custom enum names.
10 | ///
11 | public class JsonStringEnumConverter : JsonConverterFactory
12 | {
13 | public override bool CanConvert(Type typeToConvert)
14 | {
15 | return typeToConvert.IsEnum;
16 | }
17 |
18 | public override JsonConverter? CreateConverter(Type typeToConvert, JsonSerializerOptions options)
19 | {
20 | var type = typeof(JsonStringEnumConverter<>).MakeGenericType(typeToConvert);
21 | return (JsonConverter)Activator.CreateInstance(type)!;
22 | }
23 | }
24 |
25 | public class JsonStringEnumConverter : JsonConverter where TEnum : struct, Enum
26 | {
27 | private readonly Dictionary _enumToString = new();
28 | private readonly Dictionary _stringToEnum = new();
29 | private readonly Dictionary _numberToEnum = new();
30 |
31 | public JsonStringEnumConverter()
32 | {
33 | var type = typeof(TEnum);
34 | foreach (var value in Enum.GetValues())
35 | {
36 | var enumMember = type.GetMember(value.ToString())[0];
37 | var attr = enumMember.GetCustomAttributes().FirstOrDefault();
38 |
39 | var serializationAttr = enumMember.GetCustomAttributes().FirstOrDefault();
40 |
41 | var num = Convert.ToInt32(type.GetField("value__")?.GetValue(value));
42 | if (attr?.Name != null)
43 | {
44 | _enumToString.Add(value, attr.Name);
45 | _stringToEnum.Add(attr.Name, value);
46 | _numberToEnum.Add(num, value);
47 | }
48 | else if (serializationAttr?.Value != null)
49 | {
50 | _enumToString.Add(value, serializationAttr.Value);
51 | _stringToEnum.Add(serializationAttr.Value, value);
52 | _numberToEnum.Add(num, value);
53 | }
54 | else
55 | {
56 | _enumToString.Add(value, value.ToString());
57 | _stringToEnum.Add(value.ToString(), value);
58 | _numberToEnum.Add(num, value);
59 | }
60 | }
61 | }
62 |
63 | public override TEnum Read(ref Utf8JsonReader reader, Type typeToConvert, JsonSerializerOptions options)
64 | {
65 | var type = reader.TokenType;
66 | if (type == JsonTokenType.String)
67 | {
68 | var stringValue = reader.GetString();
69 |
70 | if (stringValue != null && _stringToEnum.TryGetValue(stringValue, out var enumValue))
71 | {
72 | return enumValue;
73 | }
74 | }
75 | else if (type == JsonTokenType.Number)
76 | {
77 | var numValue = reader.GetInt32();
78 | _numberToEnum.TryGetValue(numValue, out var enumValue);
79 | return enumValue;
80 | }
81 |
82 | return default;
83 | }
84 |
85 | public override void Write(Utf8JsonWriter writer, TEnum value, JsonSerializerOptions options)
86 | {
87 | writer.WriteStringValue(_enumToString[value]);
88 | }
89 | }
--------------------------------------------------------------------------------
/src/OpenAI.Client/Extensions/HttpClientExtensions.cs:
--------------------------------------------------------------------------------
1 | //Taken with love from: https://raw.githubusercontent.com/betalgo/openai/master/OpenAI.SDK/Extensions/HttpClientExtensions.cs
2 | using System.Net.Http.Headers;
3 | using System.Net.Http.Json;
4 | using System.Text.Json;
5 | using System.Text.Json.Serialization;
6 |
7 | namespace OpenAI.Extensions;
8 |
9 | public static class HttpClientExtensions
10 | {
11 | public static async Task PostAndReadAsAsync(this HttpClient client, string uri, object requestModel, CancellationToken cancellationToken = default)
12 | {
13 | var response = await client.PostAsJsonAsync(uri, requestModel, new JsonSerializerOptions
14 | {
15 | DefaultIgnoreCondition = JsonIgnoreCondition.WhenWritingDefault
16 | }, cancellationToken);
17 | return await response.Content.ReadFromJsonAsync(cancellationToken: cancellationToken) ?? throw new InvalidOperationException();
18 | }
19 |
20 | public static async Task PostAsync(this HttpClient client, string uri, object requestModel, JsonSerializerOptions? options = default, CancellationToken cancellationToken = default)
21 | {
22 | // PostAsync does not support ResponseHeadersRead, so this is a polyfill for that functionality
23 |
24 | options ??= new JsonSerializerOptions
25 | {
26 | DefaultIgnoreCondition = JsonIgnoreCondition.WhenWritingDefault
27 | };
28 |
29 | var content = JsonContent.Create(requestModel, null, options);
30 |
31 | using var request = new HttpRequestMessage(HttpMethod.Post, uri);
32 | request.Headers.Accept.Add(new MediaTypeWithQualityHeaderValue("text/event-stream"));
33 | request.Content = content;
34 | return await client.SendAsync(request, HttpCompletionOption.ResponseHeadersRead, cancellationToken);
35 | }
36 |
37 | public static async Task PostFileAndReadAsAsync(this HttpClient client, string uri, HttpContent content, CancellationToken cancellationToken = default)
38 | {
39 | var response = await client.PostAsync(uri, content, cancellationToken);
40 | return await response.Content.ReadFromJsonAsync(cancellationToken: cancellationToken) ?? throw new InvalidOperationException();
41 | }
42 |
43 | public static async Task PostFileAndReadAsStringAsync(this HttpClient client, string uri, HttpContent content, CancellationToken cancellationToken = default)
44 | {
45 | var response = await client.PostAsync(uri, content, cancellationToken);
46 | return await response.Content.ReadAsStringAsync(cancellationToken) ?? throw new InvalidOperationException();
47 | }
48 |
49 | public static async Task DeleteAndReadAsAsync(this HttpClient client, string uri, CancellationToken cancellationToken = default)
50 | {
51 | var response = await client.DeleteAsync(uri, cancellationToken);
52 | return await response.Content.ReadFromJsonAsync(cancellationToken: cancellationToken) ?? throw new InvalidOperationException();
53 | }
54 |
55 | #if NETSTANDARD2_0
56 | public static async Task ReadAsStringAsync(this HttpContent content, CancellationToken cancellationToken)
57 | {
58 | var stream = await content.ReadAsStreamAsync().WithCancellation(cancellationToken);
59 | using var sr = new StreamReader(stream);
60 | return await sr.ReadToEndAsync().WithCancellation(cancellationToken);
61 | }
62 |
63 | public static async Task ReadAsStreamAsync(this HttpContent content, CancellationToken cancellationToken)
64 | {
65 | var stream = await content.ReadAsStreamAsync().WithCancellation(cancellationToken);
66 | return new AsyncDisposableStream(stream);
67 | }
68 |
69 | public static async Task ReadAsByteArrayAsync(this HttpContent content, CancellationToken cancellationToken)
70 | {
71 | return await content.ReadAsByteArrayAsync().WithCancellation(cancellationToken);
72 | }
73 |
74 | public static async Task GetStreamAsync(this HttpClient client, string requestUri, CancellationToken cancellationToken)
75 | {
76 | var response = await client.GetAsync(requestUri, cancellationToken);
77 | return await response.Content.ReadAsStreamAsync(cancellationToken);
78 | }
79 |
80 | public static async Task WithCancellation(this Task task, CancellationToken cancellationToken)
81 | {
82 | var tcs = new TaskCompletionSource();
83 | using (cancellationToken.Register(s => ((TaskCompletionSource)s).TrySetResult(true), tcs))
84 | {
85 | if (task != await Task.WhenAny(task, tcs.Task))
86 | {
87 | throw new OperationCanceledException(cancellationToken);
88 | }
89 | }
90 |
91 | return await task;
92 | }
93 | #endif
94 | }
--------------------------------------------------------------------------------
/src/PowerShellAssistant/PowerShellAssistant.psd1:
--------------------------------------------------------------------------------
1 | #
2 | # Module manifest for module 'PowerShellAssistant'
3 | #
4 | # Generated by: Justin Grote @JustinWGrote
5 | #
6 | # Generated on: 3/2/2023
7 | #
8 |
9 | @{
10 |
11 | # Script module or binary module file associated with this manifest.
12 | RootModule = './PowerShellAssistant.psm1'
13 |
14 | # Version number of this module.
15 | ModuleVersion = '0.0.0'
16 |
17 | # Supported PSEditions
18 | # CompatiblePSEditions = @()
19 |
20 | # ID used to uniquely identify this module
21 | GUID = '0ed853f2-c5d7-4234-8a2e-7a1c9ebabc75'
22 |
23 | # Author of this module
24 | Author = 'Justin Grote @JustinWGrote'
25 |
26 | # Company or vendor of this module
27 | CompanyName = 'Unspecified'
28 |
29 | # Copyright statement for this module
30 | Copyright = '©2023 Justin Grote @JustinWGrote. All Rights Reserved'
31 |
32 | # Description of the functionality provided by this module
33 | Description = 'Provides OpenAI and Github Copilot enabled features such as a Shell chat interface'
34 |
35 | # Minimum version of the PowerShell engine required by this module
36 | PowerShellVersion = '7.2.0'
37 |
38 | # Name of the PowerShell host required by this module
39 | # PowerShellHostName = ''
40 |
41 | # Minimum version of the PowerShell host required by this module
42 | # PowerShellHostVersion = ''
43 |
44 | # Minimum version of Microsoft .NET Framework required by this module. This prerequisite is valid for the PowerShell Desktop edition only.
45 | # DotNetFrameworkVersion = ''
46 |
47 | # Minimum version of the common language runtime (CLR) required by this module. This prerequisite is valid for the PowerShell Desktop edition only.
48 | # ClrVersion = ''
49 |
50 | # Processor architecture (None, X86, Amd64) required by this module
51 | # ProcessorArchitecture = ''
52 |
53 | # Modules that must be imported into the global environment prior to importing this module
54 | # RequiredModules = @()
55 |
56 | # Assemblies that must be loaded prior to importing this module
57 | # RequiredAssemblies = @()
58 |
59 | # Script files (.ps1) that are run in the caller's environment prior to importing this module.
60 | # ScriptsToProcess = @()
61 |
62 | # Type files (.ps1xml) to be loaded when importing this module
63 | # TypesToProcess = @()
64 |
65 | # Format files (.ps1xml) to be loaded when importing this module
66 | # FormatsToProcess = @()
67 |
68 | # Modules to import as nested modules of the module specified in RootModule/ModuleToProcess
69 | # NestedModules = @()
70 |
71 | # Functions to export from this module, for best performance, do not use wildcards and do not delete the entry, use an empty array if there are no functions to export.
72 | FunctionsToExport = '*'
73 |
74 | # Cmdlets to export from this module, for best performance, do not use wildcards and do not delete the entry, use an empty array if there are no cmdlets to export.
75 | CmdletsToExport = '*'
76 |
77 | # Variables to export from this module
78 | VariablesToExport = '*'
79 |
80 | # Aliases to export from this module, for best performance, do not use wildcards and do not delete the entry, use an empty array if there are no aliases to export.
81 | AliasesToExport = '*'
82 |
83 | # DSC resources to export from this module
84 | # DscResourcesToExport = @()
85 |
86 | # List of all modules packaged with this module
87 | # ModuleList = @()
88 |
89 | # List of all files packaged with this module
90 | # FileList = @()
91 |
92 | # Private data to pass to the module specified in RootModule/ModuleToProcess. This may also contain a PSData hashtable with additional module metadata used by PowerShell.
93 | PrivateData = @{
94 |
95 | PSData = @{
96 |
97 | # Tags applied to this module. These help with module discovery in online galleries.
98 | Tags = @('OpenAI', 'AI', 'ChatGPT', 'GPT', 'Copilot', 'GitHub')
99 |
100 | # A URL to the license for this module.
101 | LicenseUri = 'https://github.com/JustinGrote/PowerShellAssistant/blob/main/LICENSE'
102 |
103 | # A URL to the main website for this project.
104 | # ProjectUri = 'https://github.com/JustinGrote/PowerShellAssistant'
105 |
106 | # A URL to an icon representing this module.
107 | # IconUri = ''
108 |
109 | # ReleaseNotes of this module
110 | # ReleaseNotes = ''
111 |
112 | # Prerelease string of this module
113 | Prerelease = 'Source'
114 |
115 | # Flag to indicate whether the module requires explicit user acceptance for install/update/save
116 | # RequireLicenseAcceptance = $false
117 |
118 | # External dependent modules of this module
119 | # ExternalModuleDependencies = @()
120 |
121 | } # End of PSData hashtable
122 |
123 | } # End of PrivateData hashtable
124 |
125 | # HelpInfo URI of this module
126 | # HelpInfoURI = ''
127 |
128 | # Default prefix for commands exported from this module. Override the default prefix using Import-Module -Prefix.
129 | # DefaultCommandPrefix = ''
130 |
131 | }
132 |
133 |
--------------------------------------------------------------------------------
/src/OpenAI.Client/Chat.cs:
--------------------------------------------------------------------------------
1 |
2 | using System.Collections.ObjectModel;
3 | using System.Runtime.CompilerServices;
4 | using System.Text.Json;
5 | using System.Text.Json.Serialization;
6 | using OpenAI.Extensions;
7 |
8 | namespace OpenAI;
9 |
10 | ///
11 | /// Combines a chat request and response into a single object to provide context for conversations.
12 | ///
13 | public record ChatConversation
14 | {
15 | public CreateChatCompletionRequest Request { get; set; }
16 | public CreateChatCompletionResponse Response { get; set; }
17 |
18 | public ChatConversation()
19 | {
20 | Request = new();
21 | Response = new();
22 | }
23 | }
24 |
25 | public class CreateChatCompletionChunkedResponse
26 | {
27 | [JsonPropertyName("id")]
28 | [JsonIgnore(Condition = JsonIgnoreCondition.Never)]
29 | [System.ComponentModel.DataAnnotations.Required(AllowEmptyStrings = true)]
30 | public string Id { get; set; } = default!;
31 |
32 | [JsonPropertyName("object")]
33 | [JsonIgnore(Condition = JsonIgnoreCondition.Never)]
34 | [System.ComponentModel.DataAnnotations.Required(AllowEmptyStrings = true)]
35 | public string Object { get; set; } = default!;
36 |
37 | [JsonPropertyName("created")]
38 | [JsonIgnore(Condition = JsonIgnoreCondition.Never)]
39 | public int Created { get; set; } = default!;
40 |
41 | [JsonPropertyName("model")]
42 | [JsonIgnore(Condition = JsonIgnoreCondition.Never)]
43 | [System.ComponentModel.DataAnnotations.Required(AllowEmptyStrings = true)]
44 | public string Model { get; set; } = default!;
45 |
46 | [JsonPropertyName("choices")]
47 | [JsonIgnore(Condition = JsonIgnoreCondition.Never)]
48 | [System.ComponentModel.DataAnnotations.Required]
49 | public ICollection Choices { get; set; }
50 | }
51 |
52 | public class DeltaChoice
53 | {
54 | [JsonPropertyName("index")]
55 | [JsonIgnore(Condition = JsonIgnoreCondition.Never)]
56 | [System.ComponentModel.DataAnnotations.Required(AllowEmptyStrings = true)]
57 | public int? Index { get; set; }
58 |
59 | public ChatCompletionResponseMessage? Message { get; set; }
60 |
61 | [JsonPropertyName("finish_reason")]
62 |
63 | [JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingDefault)]
64 | public string? Finish_reason { get; set; }
65 |
66 | [JsonPropertyName("delta")]
67 | [JsonIgnore(Condition = JsonIgnoreCondition.Never)]
68 | public DeltaContent? Delta { get; set; }
69 | }
70 |
71 | public class DeltaContent
72 | {
73 | [JsonPropertyName("role")]
74 | [JsonConverter(typeof(JsonStringEnumConverter))]
75 | [JsonIgnore(Condition = JsonIgnoreCondition.WhenWritingNull)]
76 | public ChatCompletionResponseMessageRole? Role { get; set; }
77 |
78 | [JsonPropertyName("content")]
79 | [JsonIgnore(Condition = JsonIgnoreCondition.Never)]
80 | [System.ComponentModel.DataAnnotations.Required(AllowEmptyStrings = true)]
81 | public string? Content { get; set; }
82 | }
83 |
84 | ///
85 | /// Unifying interface for the various chat messages. Actual interface cannot be used due to enums
86 | ///
87 | public record ChatMessage
88 | {
89 | public ChatMessageRole Role;
90 | public string Content = string.Empty;
91 |
92 | // TODO: There must be a more generic way to implement this than explicit constructors
93 | public ChatMessage(ChatCompletionResponseMessage message)
94 | {
95 | Role = Enum.Parse(message.Role.ToString());
96 | Content = message.Content;
97 | }
98 |
99 | public ChatMessage(ChatCompletionRequestMessage message)
100 | {
101 | Role = Enum.Parse(message.Role.ToString());
102 | Content = message.Content;
103 | }
104 | }
105 |
106 | public enum ChatMessageRole
107 | {
108 | [System.Runtime.Serialization.EnumMember(Value = "system")]
109 | System = 0,
110 |
111 | [System.Runtime.Serialization.EnumMember(Value = "user")]
112 | User = 1,
113 |
114 | [System.Runtime.Serialization.EnumMember(Value = "assistant")]
115 | Assistant = 2,
116 | }
117 |
118 | public partial class Client
119 | {
120 | public IEnumerable CreateChatCompletionAsStream(CreateChatCompletionRequest request, CancellationToken cancellationToken = default)
121 | {
122 | return CreateChatCompletionAsStreamAsync(request, cancellationToken).ToBlockingEnumerable(cancellationToken);
123 | }
124 |
125 | public async IAsyncEnumerable CreateChatCompletionAsStreamAsync(CreateChatCompletionRequest request, [EnumeratorCancellation] CancellationToken cancellationToken = default)
126 | {
127 | // Enable streaming if it is not already enabled
128 | request.Stream = true;
129 |
130 | var urlBuilder = new System.Text.StringBuilder();
131 | urlBuilder.Append(BaseUrl != null ? BaseUrl.TrimEnd('/') : "").Append("/chat/completions");
132 |
133 | using var response = await _httpClient.PostAsync(urlBuilder.ToString(), request, _settings.Value, cancellationToken);
134 |
135 | await using var stream = await response.Content.ReadAsStreamAsync(cancellationToken);
136 | using var reader = new StreamReader(stream);
137 |
138 | // Continuously read the stream until the end of it
139 | while (!reader.EndOfStream)
140 | {
141 | cancellationToken.ThrowIfCancellationRequested();
142 |
143 | var line = await reader.ReadLineAsync(cancellationToken);
144 | // Skip empty lines
145 | if (string.IsNullOrEmpty(line))
146 | {
147 | continue;
148 | }
149 |
150 | line = line.RemoveIfStartWith("data: ");
151 |
152 | // Exit the loop if the stream is done
153 | if (line.StartsWith("[DONE]"))
154 | {
155 | break;
156 | }
157 |
158 | CreateChatCompletionChunkedResponse? block;
159 | try
160 | {
161 | // When the response is good, each line is a serializable
162 | block = JsonSerializer.Deserialize(line);
163 | }
164 | catch
165 | {
166 | // When the API returns an error, it does not come back as a block, it returns a single character of text ("{").
167 | // In this instance, read through the rest of the response, which should be a complete object to parse.
168 | line += await reader.ReadToEndAsync(cancellationToken);
169 | block = JsonSerializer.Deserialize(line);
170 | throw;
171 | }
172 |
173 | if (block is not null)
174 | {
175 | yield return block;
176 | }
177 | }
178 | }
179 | }
--------------------------------------------------------------------------------
/src/OpenAI.Client/TemplateDirectory/Class.liquid:
--------------------------------------------------------------------------------
1 | {%- if HasDescription -%}
2 | ///
3 | /// {{ Description | csharpdocs }}
4 | ///
5 | {%- endif -%}
6 | {%- if HasDiscriminator -%}
7 | {%- if UseSystemTextJson -%}
8 | [JsonInheritanceConverter(typeof({{ ClassName }}), "{{ Discriminator }}")]
9 | {%- else -%}
10 | [Newtonsoft.Json.JsonConverter(typeof(JsonInheritanceConverter), "{{ Discriminator }}")]
11 | {%- endif -%}
12 | {%- for derivedClass in DerivedClasses -%}
13 | {%- if derivedClass.IsAbstract != true -%}
14 | [JsonInheritanceAttribute("{{ derivedClass.Discriminator }}", typeof({{ derivedClass.ClassName }}))]
15 | {%- endif -%}
16 | {%- endfor -%}
17 | {%- endif -%}
18 | [System.CodeDom.Compiler.GeneratedCode("NJsonSchema", "{{ ToolchainVersion }}")]
19 | {%- if InheritsExceptionSchema -%}
20 | {%- if UseSystemTextJson -%}
21 | // TODO(system.text.json): What to do here?
22 | {%- else -%}
23 | [Newtonsoft.Json.JsonObjectAttribute]
24 | {%- endif -%}
25 | {%- endif -%}
26 | {%- if IsDeprecated -%}
27 | [System.Obsolete{% if HasDeprecatedMessage %}({{ DeprecatedMessage | literal }}){% endif %}]
28 | {% endif -%}
29 | {%- template Class.Annotations -%}
30 | {{ TypeAccessModifier }} {% if IsAbstract %}abstract {% endif %}partial {% if GenerateNativeRecords %}record{% else %}class{% endif %} {{ClassName}} {%- template Class.Inheritance %}
31 | {
32 | {%- if IsTuple -%}
33 | public {{ ClassName }}({%- for tupleType in TupleTypes %}{{ tupleType }} item{{ forloop.index }}{%- if forloop.last == false %}, {% endif %}{% endfor %}) : base({%- for tupleType in TupleTypes %}item{{ forloop.index }}{%- if forloop.last == false %}, {% endif %}{% endfor %})
34 | {
35 | }
36 |
37 | {%- endif -%}
38 | {%- if RenderInpc or RenderPrism -%}
39 | {%- for property in Properties -%}
40 | private {{ property.Type }} {{ property.FieldName }}{%- if property.HasDefaultValue %} = {{ property.DefaultValue }}{% elsif GenerateNullableReferenceTypes %} = default!{%- endif %};
41 | {%- endfor -%}
42 |
43 | {%- endif -%}
44 | {%- template Class.Constructor -%}
45 | {%- if RenderRecord -%}
46 | {% template Class.Constructor.Record -%}
47 | {%- endif -%}
48 | {%- for property in Properties -%}
49 | {%- if property.HasDescription -%}
50 | ///
51 | /// {{ property.Description | csharpdocs }}
52 | ///
53 | {%- endif -%}
54 | {%- if UseSystemTextJson %}
55 | [System.Text.Json.Serialization.JsonPropertyName("{{ property.Name }}")]
56 | {%- if property.HasJsonIgnoreCondition %}
57 | [System.Text.Json.Serialization.JsonIgnore(Condition = {{ property.JsonIgnoreCondition }})]
58 | {%- endif -%}
59 | {%- if property.IsStringEnumArray %}
60 | // TODO(system.text.json): Add string enum item converter
61 | {%- endif -%}
62 | {%- else -%}
63 | [Newtonsoft.Json.JsonProperty("{{ property.Name }}", Required = {{ property.JsonPropertyRequiredCode }}{% if property.IsStringEnumArray %}, ItemConverterType = typeof(Newtonsoft.Json.Converters.StringEnumConverter){% endif %})]
64 | {%- endif -%}
65 | {%- if property.RenderRequiredAttribute -%}
66 | [System.ComponentModel.DataAnnotations.Required{% if property.AllowEmptyStrings %}(AllowEmptyStrings = true){% endif %}]
67 | {%- endif -%}
68 | {%- if property.RenderRangeAttribute -%}
69 | [System.ComponentModel.DataAnnotations.Range({{ property.RangeMinimumValue }}, {{ property.RangeMaximumValue }})]
70 | {%- endif -%}
71 | {%- if property.RenderStringLengthAttribute -%}
72 | [System.ComponentModel.DataAnnotations.StringLength({{ property.StringLengthMaximumValue }}{% if property.StringLengthMinimumValue > 0 %}, MinimumLength = {{ property.StringLengthMinimumValue }}{% endif %})]
73 | {%- endif -%}
74 | {%- if property.RenderMinLengthAttribute -%}
75 | [System.ComponentModel.DataAnnotations.MinLength({{ property.MinLengthAttribute }})]
76 | {%- endif -%}
77 | {%- if property.RenderMaxLengthAttribute -%}
78 | [System.ComponentModel.DataAnnotations.MaxLength({{ property.MaxLengthAttribute }})]
79 | {%- endif -%}
80 | {%- if property.RenderRegularExpressionAttribute -%}
81 | [System.ComponentModel.DataAnnotations.RegularExpression(@"{{ property.RegularExpressionValue }}")]
82 | {%- endif -%}
83 | {%- if property.IsDate and UseDateFormatConverter -%}
84 | {%- if UseSystemTextJson -%}
85 | [System.Text.Json.Serialization.JsonConverter(typeof(DateFormatConverter))]
86 | {%- else -%}
87 | [Newtonsoft.Json.JsonConverter(typeof(DateFormatConverter))]
88 | {%- endif -%}
89 | {%- endif -%}
90 | {%- if property.IsDeprecated -%}
91 | [System.Obsolete{% if property.HasDeprecatedMessage %}({{ property.DeprecatedMessage | literal }}){% endif %}]
92 | {%- endif -%}
93 | {%- template Class.Property.Annotations -%}
94 | public {{ property.Type }} {{ property.PropertyName }}{% if RenderInpc == false and RenderPrism == false %} { get; {% if property.HasSetter and RenderRecord == false %}set; {% elsif RenderRecord and GenerateNativeRecords %}init; {% endif %}}{% if property.HasDefaultValue and RenderRecord == false %} = {{ property.DefaultValue }};{% elsif GenerateNullableReferenceTypes and RenderRecord == false %} = default!;{% endif %}
95 | {% else %}
96 | {
97 | get { return {{ property.FieldName }}; }
98 |
99 | {%- if property.HasSetter -%}
100 | {%- if RenderInpc -%}
101 | {{PropertySetterAccessModifier}}set
102 | {
103 | if ({{ property.FieldName }} != value)
104 | {
105 | {{ property.FieldName }} = value;
106 | RaisePropertyChanged();
107 | }
108 | }
109 | {%- else -%}
110 | {{PropertySetterAccessModifier}}set { SetProperty(ref {{ property.FieldName }}, value); }
111 | {%- endif -%}
112 | {%- endif -%}
113 | }
114 | {%- endif %}
115 | {%- endfor -%}
116 |
117 | {%- if GenerateAdditionalPropertiesProperty -%}
118 |
119 | private System.Collections.Generic.IDictionary{% if GenerateNullableReferenceTypes %}?{% endif %} _additionalProperties;
120 |
121 | {%- if UseSystemTextJson -%}
122 | [System.Text.Json.Serialization.JsonExtensionData]
123 | {%- else -%}
124 | [Newtonsoft.Json.JsonExtensionData]
125 | {%- endif -%}
126 | public System.Collections.Generic.IDictionary AdditionalProperties
127 | {
128 | get { return _additionalProperties ?? (_additionalProperties = new System.Collections.Generic.Dictionary()); }
129 | {{PropertySetterAccessModifier}}set { _additionalProperties = value; }
130 | }
131 |
132 | {%- endif -%}
133 | {%- if GenerateJsonMethods -%}
134 | {% template Class.ToJson %}
135 | {% template Class.FromJson %}
136 |
137 | {%- endif -%}
138 | {%- if RenderInpc -%}
139 | {% template Class.Inpc %}
140 | {%- endif -%}
141 | {% template Class.Body %}
142 | }
--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
1 | ## Ignore Visual Studio temporary files, build results, and
2 | ## files generated by popular Visual Studio add-ons.
3 | ##
4 | ## Get latest from https://github.com/github/gitignore/blob/main/VisualStudio.gitignore
5 |
6 | # User-specific files
7 | *.rsuser
8 | *.suo
9 | *.user
10 | *.userosscache
11 | *.sln.docstates
12 |
13 | # User-specific files (MonoDevelop/Xamarin Studio)
14 | *.userprefs
15 |
16 | # Mono auto generated files
17 | mono_crash.*
18 |
19 | # Build results
20 | [Dd]ebug/
21 | [Dd]ebugPublic/
22 | [Rr]elease/
23 | [Rr]eleases/
24 | x64/
25 | x86/
26 | [Ww][Ii][Nn]32/
27 | [Aa][Rr][Mm]/
28 | [Aa][Rr][Mm]64/
29 | bld/
30 | [Bb]in/
31 | [Oo]bj/
32 | [Ll]og/
33 | [Ll]ogs/
34 |
35 | # Visual Studio 2015/2017 cache/options directory
36 | .vs/
37 | # Uncomment if you have tasks that create the project's static files in wwwroot
38 | #wwwroot/
39 |
40 | # Visual Studio 2017 auto generated files
41 | Generated\ Files/
42 |
43 | # MSTest test Results
44 | [Tt]est[Rr]esult*/
45 | [Bb]uild[Ll]og.*
46 |
47 | # NUnit
48 | *.VisualState.xml
49 | TestResult.xml
50 | nunit-*.xml
51 |
52 | # Build Results of an ATL Project
53 | [Dd]ebugPS/
54 | [Rr]eleasePS/
55 | dlldata.c
56 |
57 | # Benchmark Results
58 | BenchmarkDotNet.Artifacts/
59 |
60 | # .NET
61 | project.lock.json
62 | project.fragment.lock.json
63 | artifacts/
64 |
65 | # Tye
66 | .tye/
67 |
68 | # ASP.NET Scaffolding
69 | ScaffoldingReadMe.txt
70 |
71 | # StyleCop
72 | StyleCopReport.xml
73 |
74 | # Files built by Visual Studio
75 | *_i.c
76 | *_p.c
77 | *_h.h
78 | *.ilk
79 | *.meta
80 | *.obj
81 | *.iobj
82 | *.pch
83 | *.pdb
84 | *.ipdb
85 | *.pgc
86 | *.pgd
87 | *.rsp
88 | *.sbr
89 | *.tlb
90 | *.tli
91 | *.tlh
92 | *.tmp
93 | *.tmp_proj
94 | *_wpftmp.csproj
95 | *.log
96 | *.tlog
97 | *.vspscc
98 | *.vssscc
99 | .builds
100 | *.pidb
101 | *.svclog
102 | *.scc
103 |
104 | # Chutzpah Test files
105 | _Chutzpah*
106 |
107 | # Visual C++ cache files
108 | ipch/
109 | *.aps
110 | *.ncb
111 | *.opendb
112 | *.opensdf
113 | *.sdf
114 | *.cachefile
115 | *.VC.db
116 | *.VC.VC.opendb
117 |
118 | # Visual Studio profiler
119 | *.psess
120 | *.vsp
121 | *.vspx
122 | *.sap
123 |
124 | # Visual Studio Trace Files
125 | *.e2e
126 |
127 | # TFS 2012 Local Workspace
128 | $tf/
129 |
130 | # Guidance Automation Toolkit
131 | *.gpState
132 |
133 | # ReSharper is a .NET coding add-in
134 | _ReSharper*/
135 | *.[Rr]e[Ss]harper
136 | *.DotSettings.user
137 |
138 | # TeamCity is a build add-in
139 | _TeamCity*
140 |
141 | # DotCover is a Code Coverage Tool
142 | *.dotCover
143 |
144 | # AxoCover is a Code Coverage Tool
145 | .axoCover/*
146 | !.axoCover/settings.json
147 |
148 | # Coverlet is a free, cross platform Code Coverage Tool
149 | coverage*.json
150 | coverage*.xml
151 | coverage*.info
152 |
153 | # Visual Studio code coverage results
154 | *.coverage
155 | *.coveragexml
156 |
157 | # NCrunch
158 | _NCrunch_*
159 | .*crunch*.local.xml
160 | nCrunchTemp_*
161 |
162 | # MightyMoose
163 | *.mm.*
164 | AutoTest.Net/
165 |
166 | # Web workbench (sass)
167 | .sass-cache/
168 |
169 | # Installshield output folder
170 | [Ee]xpress/
171 |
172 | # DocProject is a documentation generator add-in
173 | DocProject/buildhelp/
174 | DocProject/Help/*.HxT
175 | DocProject/Help/*.HxC
176 | DocProject/Help/*.hhc
177 | DocProject/Help/*.hhk
178 | DocProject/Help/*.hhp
179 | DocProject/Help/Html2
180 | DocProject/Help/html
181 |
182 | # Click-Once directory
183 | publish/
184 |
185 | # Publish Web Output
186 | *.[Pp]ublish.xml
187 | *.azurePubxml
188 | # Note: Comment the next line if you want to checkin your web deploy settings,
189 | # but database connection strings (with potential passwords) will be unencrypted
190 | *.pubxml
191 | *.publishproj
192 |
193 | # Microsoft Azure Web App publish settings. Comment the next line if you want to
194 | # checkin your Azure Web App publish settings, but sensitive information contained
195 | # in these scripts will be unencrypted
196 | PublishScripts/
197 |
198 | # NuGet Packages
199 | *.nupkg
200 | # NuGet Symbol Packages
201 | *.snupkg
202 | # The packages folder can be ignored because of Package Restore
203 | **/[Pp]ackages/*
204 | # except build/, which is used as an MSBuild target.
205 | !**/[Pp]ackages/build/
206 | # Uncomment if necessary however generally it will be regenerated when needed
207 | #!**/[Pp]ackages/repositories.config
208 | # NuGet v3's project.json files produces more ignorable files
209 | *.nuget.props
210 | *.nuget.targets
211 |
212 | # Microsoft Azure Build Output
213 | csx/
214 | *.build.csdef
215 |
216 | # Microsoft Azure Emulator
217 | ecf/
218 | rcf/
219 |
220 | # Windows Store app package directories and files
221 | AppPackages/
222 | BundleArtifacts/
223 | Package.StoreAssociation.xml
224 | _pkginfo.txt
225 | *.appx
226 | *.appxbundle
227 | *.appxupload
228 |
229 | # Visual Studio cache files
230 | # files ending in .cache can be ignored
231 | *.[Cc]ache
232 | # but keep track of directories ending in .cache
233 | !?*.[Cc]ache/
234 |
235 | # Others
236 | ClientBin/
237 | ~$*
238 | *~
239 | *.dbmdl
240 | *.dbproj.schemaview
241 | *.jfm
242 | *.pfx
243 | *.publishsettings
244 | orleans.codegen.cs
245 |
246 | # Including strong name files can present a security risk
247 | # (https://github.com/github/gitignore/pull/2483#issue-259490424)
248 | #*.snk
249 |
250 | # Since there are multiple workflows, uncomment next line to ignore bower_components
251 | # (https://github.com/github/gitignore/pull/1529#issuecomment-104372622)
252 | #bower_components/
253 |
254 | # RIA/Silverlight projects
255 | Generated_Code/
256 |
257 | # Backup & report files from converting an old project file
258 | # to a newer Visual Studio version. Backup files are not needed,
259 | # because we have git ;-)
260 | _UpgradeReport_Files/
261 | Backup*/
262 | UpgradeLog*.XML
263 | UpgradeLog*.htm
264 | ServiceFabricBackup/
265 | *.rptproj.bak
266 |
267 | # SQL Server files
268 | *.mdf
269 | *.ldf
270 | *.ndf
271 |
272 | # Business Intelligence projects
273 | *.rdl.data
274 | *.bim.layout
275 | *.bim_*.settings
276 | *.rptproj.rsuser
277 | *- [Bb]ackup.rdl
278 | *- [Bb]ackup ([0-9]).rdl
279 | *- [Bb]ackup ([0-9][0-9]).rdl
280 |
281 | # Microsoft Fakes
282 | FakesAssemblies/
283 |
284 | # GhostDoc plugin setting file
285 | *.GhostDoc.xml
286 |
287 | # Node.js Tools for Visual Studio
288 | .ntvs_analysis.dat
289 | node_modules/
290 |
291 | # Visual Studio 6 build log
292 | *.plg
293 |
294 | # Visual Studio 6 workspace options file
295 | *.opt
296 |
297 | # Visual Studio 6 auto-generated workspace file (contains which files were open etc.)
298 | *.vbw
299 |
300 | # Visual Studio 6 auto-generated project file (contains which files were open etc.)
301 | *.vbp
302 |
303 | # Visual Studio 6 workspace and project file (working project files containing files to include in project)
304 | *.dsw
305 | *.dsp
306 |
307 | # Visual Studio 6 technical files
308 | *.ncb
309 | *.aps
310 |
311 | # Visual Studio LightSwitch build output
312 | **/*.HTMLClient/GeneratedArtifacts
313 | **/*.DesktopClient/GeneratedArtifacts
314 | **/*.DesktopClient/ModelManifest.xml
315 | **/*.Server/GeneratedArtifacts
316 | **/*.Server/ModelManifest.xml
317 | _Pvt_Extensions
318 |
319 | # Paket dependency manager
320 | .paket/paket.exe
321 | paket-files/
322 |
323 | # FAKE - F# Make
324 | .fake/
325 |
326 | # CodeRush personal settings
327 | .cr/personal
328 |
329 | # Python Tools for Visual Studio (PTVS)
330 | __pycache__/
331 | *.pyc
332 |
333 | # Cake - Uncomment if you are using it
334 | # tools/**
335 | # !tools/packages.config
336 |
337 | # Tabs Studio
338 | *.tss
339 |
340 | # Telerik's JustMock configuration file
341 | *.jmconfig
342 |
343 | # BizTalk build output
344 | *.btp.cs
345 | *.btm.cs
346 | *.odx.cs
347 | *.xsd.cs
348 |
349 | # OpenCover UI analysis results
350 | OpenCover/
351 |
352 | # Azure Stream Analytics local run output
353 | ASALocalRun/
354 |
355 | # MSBuild Binary and Structured Log
356 | *.binlog
357 |
358 | # NVidia Nsight GPU debugger configuration file
359 | *.nvuser
360 |
361 | # MFractors (Xamarin productivity tool) working folder
362 | .mfractor/
363 |
364 | # Local History for Visual Studio
365 | .localhistory/
366 |
367 | # Visual Studio History (VSHistory) files
368 | .vshistory/
369 |
370 | # BeatPulse healthcheck temp database
371 | healthchecksdb
372 |
373 | # Backup folder for Package Reference Convert tool in Visual Studio 2017
374 | MigrationBackup/
375 |
376 | # Ionide (cross platform F# VS Code tools) working folder
377 | .ionide/
378 |
379 | # Fody - auto-generated XML schema
380 | FodyWeavers.xsd
381 |
382 | # VS Code files for those working on multiple tools
383 | .vscode/*
384 | !.vscode/settings.json
385 | !.vscode/tasks.json
386 | !.vscode/launch.json
387 | !.vscode/extensions.json
388 | *.code-workspace
389 |
390 | # Local History for Visual Studio Code
391 | .history/
392 |
393 | # Windows Installer files from build outputs
394 | *.cab
395 | *.msi
396 | *.msix
397 | *.msm
398 | *.msp
399 |
400 | # JetBrains Rider
401 | *.sln.iml
402 |
403 | ##
404 | ## Visual studio for Mac
405 | ##
406 |
407 |
408 | # globs
409 | Makefile.in
410 | *.userprefs
411 | *.usertasks
412 | config.make
413 | config.status
414 | aclocal.m4
415 | install-sh
416 | autom4te.cache/
417 | *.tar.gz
418 | tarballs/
419 | test-results/
420 |
421 | # Mac bundle stuff
422 | *.dmg
423 | *.app
424 |
425 | # content below from: https://github.com/github/gitignore/blob/master/Global/macOS.gitignore
426 | # General
427 | .DS_Store
428 | .AppleDouble
429 | .LSOverride
430 |
431 | # Icon must end with two \r
432 | Icon
433 |
434 |
435 | # Thumbnails
436 | ._*
437 |
438 | # Files that might appear in the root of a volume
439 | .DocumentRevisions-V100
440 | .fseventsd
441 | .Spotlight-V100
442 | .TemporaryItems
443 | .Trashes
444 | .VolumeIcon.icns
445 | .com.apple.timemachine.donotpresent
446 |
447 | # Directories potentially created on remote AFP share
448 | .AppleDB
449 | .AppleDesktop
450 | Network Trash Folder
451 | Temporary Items
452 | .apdisk
453 |
454 | # content below from: https://github.com/github/gitignore/blob/master/Global/Windows.gitignore
455 | # Windows thumbnail cache files
456 | Thumbs.db
457 | ehthumbs.db
458 | ehthumbs_vista.db
459 |
460 | # Dump file
461 | *.stackdump
462 |
463 | # Folder config file
464 | [Dd]esktop.ini
465 |
466 | # Recycle Bin used on file shares
467 | $RECYCLE.BIN/
468 |
469 | # Windows Installer files
470 | *.cab
471 | *.msi
472 | *.msix
473 | *.msm
474 | *.msp
475 |
476 | # Windows shortcuts
477 | *.lnk
478 |
479 | **/dist
--------------------------------------------------------------------------------
/src/PowerShellAssistant/PowerShellAssistant.psm1:
--------------------------------------------------------------------------------
1 | using namespace OpenAI
2 | using namespace System.Net.Http
3 | using namespace System.Net.Http.Headers
4 | using namespace System.Collections.Generic
5 | using namespace System.Management.Automation
6 | using namespace System.Reflection
7 |
8 | $ErrorActionPreference = 'Stop'
9 | #TODO: This should be better
10 | $debugBinPath = Join-Path $PSScriptRoot '/bin/Debug/net7.0'
11 | if (Test-Path $debugBinPath) {
12 | Write-Warning "Debug build detected. Using assemblies at $debugBinPath"
13 | Add-Type -Path $debugBinPath/*.dll
14 | } else {
15 | Add-Type -Path $PSScriptRoot/*.dll
16 | }
17 |
18 | #These are the cheapest models for testing, opt into more powerful models
19 | $SCRIPT:aiDefaultModel = 'ada'
20 | $SCRIPT:aiDefaultChatModel = 'gpt-3.5-turbo'
21 | $SCRIPT:aiDefaultCodeModel = 'code-davinci-002'
22 |
23 |
24 | #region Public
25 | function Connect-AI {
26 | [CmdletBinding()]
27 | param(
28 | # Provide your API Key as the password, and optionally your organization ID as the username
29 | [string]$APIKey,
30 |
31 | # By default, this uses the OpenAI API. Specify this if you want to use GitHub Copilot (UNSUPPORTED)
32 | [switch]$GitHubCopilot,
33 |
34 | # Don't set this client as the default client. You can pass the client to the various commands instead. Implies -PassThru
35 | [switch]$NoDefault,
36 |
37 | # Return the client for use in other commands
38 | [switch]$PassThru,
39 |
40 | #Replace the existing default client if it exists
41 | [switch]$Force
42 | )
43 | if ($SCRIPT:aiClient -and (-not $NoDefault -and -not $Force)) {
44 | Write-Warning 'Already connected to an AI engine. You can use -NoDefault to not set this client as the default client, or -Force to replace the existing default client.'
45 | return
46 | }
47 |
48 | if (-not $APIKey -and $env:OPENAI_API_KEY) {
49 | Write-Verbose 'Using API key from environment variable OPENAI_API_KEY'
50 | $APIKey = $env:OPENAI_API_KEY
51 | }
52 |
53 | $client = New-AIClient @newAIClientParams -APIKey $APIKey -GithubCopilot:$GitHubCopilot
54 |
55 | if ($NoDefault) {
56 | $PassThru = $true
57 | } else {
58 | $SCRIPT:aiClient = $client
59 | }
60 |
61 | if ($PassThru) {
62 | return $client
63 | }
64 | }
65 |
66 | filter Get-AIModel {
67 | [OutputType([OpenAI.Model])]
68 | [CmdletBinding()]
69 | param(
70 | # The ID of the model to get. If not specified, returns all models.
71 | [Parameter(ValueFromPipeline)][string]$Id,
72 | [ValidateNotNullOrEmpty()][OpenAI.Client]$Client = $SCRIPT:aiClient
73 | )
74 | if (-not $Client) {
75 | Assert-Connected
76 | $Client = $SCRIPT:aiClient
77 | }
78 |
79 | if ($Id) {
80 | return $Client.RetrieveModel($Id)
81 | }
82 |
83 | $Client.ListModels().Data
84 | }
85 |
86 | function Get-AIEngine {
87 | [OutputType([OpenAI.Engine])]
88 | [CmdletBinding()]
89 | param(
90 | [ValidateNotNullOrEmpty()][OpenAI.Client]$Client = $SCRIPT:aiClient
91 | )
92 | Write-Warning 'Engines are deprecated. Use Get-AIModel instead.'
93 | if (-not $Client) {
94 | Assert-Connected
95 | $Client = $SCRIPT:aiClient
96 | }
97 |
98 | $Client.ListEngines()
99 | | ConvertFrom-ListResponse
100 | }
101 |
102 | function Get-AICompletion {
103 | [CmdletBinding()]
104 | [OutputType([OpenAI.CreateCompletionResponse])]
105 | param(
106 | [Parameter(Mandatory)]$Prompt,
107 | #The name of the model to use.
108 | [ValidateSet([AvailableModels])][String]$Model = $SCRIPT:aiDefaultModel,
109 | [ValidateNotNullOrEmpty()][OpenAI.Client]$Client = $SCRIPT:aiClient,
110 | [ValidateNotNullOrEmpty()][uint]$MaxTokens = 1000,
111 | [ValidateNotNullOrEmpty()][uint]$Temperature = 0
112 | )
113 | if (-not $Client) {
114 | Assert-Connected
115 | $Client = $SCRIPT:aiClient
116 | }
117 |
118 | $request = [CreateCompletionRequest]@{
119 | Prompt = $Prompt
120 | Stream = $false
121 | Model = $Model
122 | Max_tokens = $MaxTokens
123 | Temperature = $Temperature
124 | }
125 | $Client.CreateCompletion($request)
126 | }
127 |
128 | function Get-AICode {
129 | <#
130 | .SYNOPSIS
131 | Utilizes the Codex models to fetch a code completion given a prompt.
132 | .LINK
133 | https://platform.openai.com/docs/guides/code/introduction
134 | #>
135 | [OutputType([OpenAI.CreateCompletionResponse])]
136 | [CmdletBinding()]
137 | param(
138 | [string[]]$Prompt,
139 | #The name of the model to use.
140 | $Language = 'PowerShell 7',
141 | [ValidateSet([AvailableModels])][String]$Model = $SCRIPT:aiDefaultCodeModel,
142 | [ValidateNotNullOrEmpty()][OpenAI.Client]$Client = $SCRIPT:aiClient,
143 | [ValidateNotNullOrEmpty()][uint]$MaxTokens = 1000,
144 | [ValidateNotNullOrEmpty()][uint]$Temperature = 0
145 | )
146 | if (-not $Client) {
147 | Assert-Connected
148 | $Client = $SCRIPT:aiClient
149 | }
150 |
151 | #Add a language specifier to the prompt
152 | $Prompt.Insert(0, "#$Language")
153 |
154 | Get-AICompletion -Prompt $Prompt -Model $Model -MaxTokens $MaxTokens -Temperature $Temperature
155 | }
156 |
157 | function Get-AIChat {
158 | [OutputType([OpenAI.ChatConversation])]
159 | [CmdletBinding(DefaultParameterSetName = 'Prompt')]
160 | param(
161 | #Include one or more prompts to start the conversation
162 | [Parameter(Mandatory, Position = 0, ValueFromPipeline, ParameterSetName = 'Prompt')]
163 | [Parameter(ParameterSetName = 'ChatSession')]
164 | [OpenAI.ChatCompletionRequestMessage[]]$Prompt,
165 |
166 | #Supply a previous chat session to add new responses to it
167 | [Parameter(Mandatory, ValueFromPipeline, ParameterSetName = 'ChatSession')]
168 | [Parameter(ParameterSetName = 'Prompt')]
169 | [OpenAI.ChatConversation]$ChatSession,
170 |
171 | #The name of the model to use.
172 | [ValidateSet([AvailableModels])]
173 | [String]$Model = $SCRIPT:aiDefaultChatModel,
174 |
175 | [ValidateNotNullOrEmpty()]
176 | [OpenAI.Client]$Client = $SCRIPT:aiClient,
177 |
178 | [ValidateNotNullOrEmpty()]
179 | [uint]$MaxTokens = 1000,
180 |
181 | [ValidateNotNullOrEmpty()]
182 | [uint]$Temperature = 0,
183 |
184 | #Stream the response. You will lose syntax highlighting and usage info.
185 | [switch]$Stream
186 | )
187 | if (-not $Client) {
188 | Assert-Connected
189 | $Client = $SCRIPT:aiClient
190 | }
191 |
192 | $ChatSession ??= [ChatConversation]@{
193 | Request = @{
194 | Messages = [List[ChatCompletionRequestMessage]]@()
195 | Stream = $false
196 | Model = $Model
197 | Max_tokens = $MaxTokens
198 | Temperature = $Temperature
199 | }
200 | }
201 |
202 | #Append any response to the initial request. This is the continuation of a chat.
203 | $responseChoices = $ChatSession.Response.Choices
204 | $requestMessages = $ChatSession.Request.Messages
205 | if ($responseChoices.Count -gt 0) {
206 | if ($responseChoices.count -gt 1) {
207 | Write-Error 'The previous chat response contained more than one choice. Continuing a conversation with multiple choices is not supported.' -Category 'NotImplemented'
208 | return
209 | }
210 | $requestMessages.Add($responseChoices[0].Message)
211 | }
212 |
213 | foreach ($PromptItem in $Prompt) {
214 | $requestMessages.Add(
215 | $PromptItem
216 | )
217 | }
218 |
219 | if ($Stream) {
220 | $Client.CreateChatCompletionAsStream($ChatSession.Request)
221 | | ForEach-Object {
222 | $PSItem
223 | }
224 | Write-Host
225 | return
226 | }
227 |
228 | $chatResponse = $Client.CreateChatCompletion($ChatSession.Request)
229 | $chatSession.Response = $chatResponse
230 |
231 | $price = Get-UsagePrice -Model $chatResponse.Model -Total $chatResponse.Usage.Total_tokens
232 |
233 | Write-Verbose "Chat usage - $($chatResponse.Usage) $($price ? "$price " : $null)for Id $($chatResponse.Id)"
234 | return $chatSession
235 |
236 | #Stream the response
237 | }
238 | #endregion Public
239 |
240 | #Region Private
241 | function New-AIClient {
242 | [OutputType([OpenAI.Client])]
243 | param(
244 | [string]$ApiKey,
245 | [Switch]$GithubCopilot
246 | )
247 |
248 | if (-not $APIKey) {
249 | Write-Error 'You must supply an OpenAI API key via the -APIKey parameter or by setting the OPENAI_API_KEY variable'
250 | return
251 | }
252 |
253 | if ($SCRIPT:client -and -not $Force) {
254 | Write-Warning 'Assistant is already connected. Please use -Force to reset the client.'
255 | return
256 | }
257 | $httpClient = [HttpClient]::new()
258 | $httpClient.DefaultRequestHeaders.Authorization = [AuthenticationHeaderValue]::new('Bearer', $APIKey)
259 |
260 | $aiClient = [Client]::new($httpClient)
261 |
262 | if ($GitHubCopilot) {
263 | $aiClient.BaseUrl = 'https://copilot-proxy.githubusercontent.com'
264 | }
265 |
266 | return $aiClient
267 | }
268 |
269 | function Assert-Connected {
270 | if (-not $SCRIPT:aiClient) {
271 | Connect-AI
272 | }
273 | }
274 |
275 | #If the returned result was a list, return the actual data
276 | filter ConvertFrom-ListResponse {
277 | if ($PSItem.Object -ne 'list') { return }
278 | return $PSItem.Data
279 | }
280 |
281 | #endregion Private
282 |
283 |
284 | # function Connect-Copilot {
285 | # [CmdletBinding()]
286 | # param(
287 | # # Provide your Copilot API Key as the password, and optionally your organization ID as the username
288 | # [string]$Token,
289 |
290 | # #Reset if a client already exists
291 | # [Switch]$Force
292 | # )
293 | # $ErrorActionPreference = 'Stop'
294 |
295 | # if ($SCRIPT:GHClient -and -not $Force) {
296 | # Write-Warning 'Copilot is already connected. Please use -Force to reset the client.'
297 | # return
298 | # }
299 |
300 | # if ($SCRIPT:GHCopilotToken -and -not $Force) {
301 | # Write-Warning 'GitHub Copilot is already connected. Please use -Force to reset the client.'
302 | # return
303 | # }
304 |
305 | # $SCRIPT:GHCopilotToken = if (-not $Token) {
306 | # #Try to autodiscover it from GitHub Copilot CLI
307 | # if (-not (Test-Path $HOME/.copilot-cli-access-token)) {
308 | # Write-Error "To use PowerShell Assistant with GitHub Copilot, you must install GitHub Copilot CLI and run 'github-copilot-cli auth' at least once to generate a Copilot Personal Access Token (PAT)"
309 | # return
310 | # }
311 | # Get-Content $HOME/.copilot-cli-access-token
312 | # } else {
313 | # $Token
314 | # }
315 |
316 | # $config = [OpenAIOptions]@{
317 | # ApiKey = Update-GitHubCopilotToken $SCRIPT:GHCopilotToken
318 | # BaseDomain = 'https://copilot-proxy.githubusercontent.com'
319 | # DefaultEngineId = 'copilot-labs-codex'
320 | # }
321 |
322 | # $SCRIPT:GHClient = [OpenAIService]::new($config)
323 | # }
324 |
325 | # function Get-CopilotSuggestion {
326 | # [CmdletBinding()]
327 | # param(
328 | # [Parameter(Mandatory)][string]$prompt,
329 | # [ValidateNotNullOrEmpty()]$client = $SCRIPT:GHClient
330 | # )
331 |
332 | # if (-not $SCRIPT:GHClient) { Connect-Copilot }
333 | # $request = [CompletionCreateRequest]@{
334 | # N = 1
335 | # StopAsList = [string[]]@('---', '\n')
336 | # MaxTokens = 256
337 | # Temperature = 0
338 | # TopP = 1
339 | # Prompt = $prompt
340 | # Stream = $true
341 | # }
342 | # $resultStream = $client.Completions.CreateCompletionAsStream($request).GetAwaiter.GetResult()
343 | # foreach ($resultItem in $resultStream) {
344 | # Write-Host -NoNewline 'NEW TOKEN'
345 | # #This gives us intellisense in vscode
346 | # [CompletionCreateResponse]$result = $resultItem
347 | # if ($result.Error) {
348 | # Write-Error $result.Error
349 | # return
350 | # }
351 | # $token = $result.Choices[0].Text
352 | # Write-Host -NoNewline -fore DarkGray $token
353 | # }
354 | # Write-Host 'DONE'
355 | # }
356 |
357 |
358 | # function Assert-Connected {
359 | # if (-not $SCRIPT:client) { Connect-Assistant }
360 | # }
361 |
362 | function Update-GitHubCopilotToken {
363 | <#
364 | .SYNOPSIS
365 | Fetches the latest token for GitHub Copilot
366 | #>
367 | param(
368 | [ValidateNotNullOrEmpty()]
369 | $GitHubToken = $SCRIPT:GHCopilotToken
370 | )
371 | $ErrorActionPreference = 'Stop'
372 | $response = Invoke-RestMethod 'https://api.github.com/copilot_internal/v2/token' -Headers @{
373 | Authorization = "token $($GitHubToken.trim())"
374 | }
375 | return $response.token
376 | }
377 |
378 | function Get-Chat {
379 | <#
380 | .SYNOPSIS
381 | Provides an interactive assistant for PowerShell. Mostly a frontend to Get-AIChat
382 | #>
383 | [CmdletBinding()]
384 | param(
385 | #Provide a chat prompt to initiate the conversation
386 | [string[]]$chatPrompt,
387 |
388 | #If you just want the result and don't want to be prompted for further replies, specify this
389 | [Switch]$NoReply,
390 |
391 | #By default, the latest code recommendation is copied to your clipboard, specify this to disable the behavior
392 | [switch]$NoClipboard,
393 |
394 | [ValidateNotNullOrEmpty()]
395 | #Specify a prompt that guides Chat how to behave. By default, it is told to prefer PowerShell as a language.
396 | [string]$SystemPrompt = 'PowerShell syntax and be brief',
397 |
398 | #Maximum tokens to generate. Defaults to 500 to minimize accidental API billing
399 | [ValidateNotNullOrEmpty()]
400 | [uint]$MaxTokens = 500,
401 |
402 | [ValidateSet([AvailableModels])]
403 | [string]$Model
404 | )
405 |
406 | begin {
407 | $ErrorActionPreference = 'Stop'
408 | Assert-Connected
409 | [List[ChatCompletionRequestMessage]]$chatHistory = @(
410 | [ChatCompletionRequestMessage]@{
411 | Role = [ChatCompletionRequestMessageRole]::System
412 | Content = $SystemPrompt
413 | }
414 | )
415 | }
416 |
417 | process {
418 | do {
419 | $chatPrompt ??= Read-Host -Prompt 'You'
420 | foreach ($promptItem in $chatPrompt) {
421 | $chatHistory.Add(
422 | ([ChatCompletionRequestMessage]$promptItem)
423 | )
424 | }
425 |
426 | $chatParams = @{
427 | Prompt = $chatHistory
428 | MaxTokens = $MaxTokens
429 | Stream = $true
430 | }
431 | if ($Model) { $chatParams.Model = $Model }
432 |
433 | [List[CreateChatCompletionChunkedResponse]]$streamedResponse = @()
434 | [Text.StringBuilder]$chatStream = ''
435 |
436 | Get-AIChat @chatParams
437 | | ForEach-Object {
438 | [CreateChatCompletionChunkedResponse]$response = $PSItem
439 | $streamedResponse.Add($response)
440 |
441 | [DeltaChoice]$firstChoice = $response.Choices[0]
442 | [string]$firstChoiceContent = $firstChoice.Delta.Content
443 | [void]$chatStream.Append($firstChoiceContent)
444 |
445 | $markdownCodeFenceRegex = '```(?\w+)?\s*(?[\s\S]*?)```'
446 |
447 | #Start recording if a code block occurs, and if it does, reformat it and copy it to clipboard
448 | #TODO: This could maybe be faster by watching the stream for the starting and trailing backticks
449 | if ($chatStream -match $markdownCodeFenceRegex) {
450 | $codeblock = $matches[0]
451 | $code = $matches.code
452 | $lang = $matches.lang
453 | $codeBlockLineCount = ($codeBlock -split '\r?\n').Count
454 |
455 | #Use ANSI Codes Move the cursor up to the start of the code block to overwrite it
456 | Write-Host -NoNewline "`e[${codeBlockLineCount}F"
457 | Write-Host -NoNewline "`e[0J"
458 |
459 | $formattedCodeBlock = [Environment]::NewLine +
460 | $PSStyle.Reverse +
461 | $code +
462 | $PSStyle.Reset +
463 | [Environment]::NewLine
464 |
465 | Write-Host -ForegroundColor DarkGray -NoNewline $formattedCodeBlock
466 |
467 | #Update the stringbuilder
468 | #TODO: Add the start index which generally should not be necessary but probably smart
469 | [void]$chatStream.Replace($codeBlock, $formattedCodeBlock)
470 | } else {
471 | Write-Host -ForegroundColor DarkGray -NoNewline $firstChoice.Delta.Content
472 | }
473 |
474 | if ($firstChoice.Finish_reason -eq 'length') {
475 | Write-Host -ForegroundColor $PSStyle.Formatting.Warning '[END]'
476 | Write-Warning "Response truncated due to length. Consider setting -MaxTokens greater than $MaxTokens"
477 | }
478 | }
479 |
480 | $message = [ChatCompletionRequestMessage]::new(
481 | [string]::Concat($streamedResponse.Choices.Delta.Content),
482 | [ChatCompletionRequestMessageRole]::Assistant
483 | )
484 |
485 | $chatHistory.Add($message)
486 |
487 | if (-not $NoClipboard) {
488 | $message.Content
489 | | Convert-ChatCodeToClipboard
490 | | Out-Null
491 | }
492 |
493 | #TODO: Move this into the formatter
494 | # switch ($aiResponse.FinishReason) {
495 | # 'stop' {} #This is the normal response
496 | # 'length' {
497 | # Write-Warning "$MaxTokens tokens reached. Consider increasing the value of -MaxTokens for longer responses."
498 | # }
499 | # $null {
500 | # Write-Debug 'Null FinishReason received. This seems to occur on occasion and may or may not be a bug.'
501 | # }
502 | # default {
503 | # Write-Warning "Chat response finished abruply due to: $($aiResponse.FinishReason)"
504 | # }
505 | # }
506 |
507 | $chatPrompt = $null
508 | if (-not $NoReply) {
509 | Write-Host -Fore Cyan ''
510 | }
511 | } while (
512 | -not $NoReply
513 | )
514 | }
515 | }
516 |
517 | filter Convert-ChatCodeToClipboard {
518 | <#
519 | .SYNOPSIS
520 | Given a string, take the last occurance of text surrounded by a fenced code block, and copy it to the clipboard.
521 | It will also pass through the string for further filtering
522 | #>
523 | $fencedCodeBlockRegex = '(?s)```[\r|\n|powershell]+(.+?)```'
524 | $matchResult = $PSItem -match $fencedCodeBlockRegex
525 | $savedMatches = $matches
526 | $cbMatch = $savedMatches.($savedMatches.Keys | Sort-Object | Select-Object -Last 1)
527 | if (-not $matchResult) {
528 | Write-Debug 'No code block detected, skipping this step'
529 | return $PSItem
530 | }
531 |
532 | Write-Verbose "Copying last suggested code block to clipboard:`n$cbMatch"
533 | Set-Clipboard -Value $cbMatch
534 |
535 | return $PSItem
536 | }
537 |
538 | class AvailableModels : IValidateSetValuesGenerator {
539 | [String[]] GetValidValues() {
540 | trap { Write-Host ''; Write-Host -NoNewline -ForegroundColor Red "Validation Error: $PSItem" }
541 | $models = Get-AIModel
542 | return $models.Id
543 | }
544 | }
545 |
546 | filter Format-ChatCode {
547 | <#
548 | .SYNOPSIS
549 | Given a string, for any occurance of text surrounded by backticks, replace the backticks with ANSI escape codes
550 | #>
551 | $codeBlockRegex = '(?s)```[\r|\n|powershell]+(.+?)```'
552 | $codeSnippetRegex = '(?s)`(.+?)`'
553 | $boldSelectedText = ($PSStyle.Italic + '$1' + $PSStyle.ItalicOff)
554 | $PSItem -replace $codeBlockRegex, $boldSelectedText -replace $codeSnippetRegex, $boldSelectedText
555 | }
556 |
557 | filter Format-ChatMessage {
558 | param(
559 | [Parameter(ValueFromPipeline)]$message,
560 | #Notes that the content should be streamed rather than returned line by line
561 | [switch]$Stream
562 | )
563 |
564 | $role = $message.Role
565 | $content = $message.Content
566 |
567 | $roleColor = switch ($role) {
568 | 'System' { 'DarkYellow' }
569 | 'Assistant' { 'Green' }
570 | 'User' { 'DarkCyan' }
571 | default { 'DarkGray' }
572 | }
573 |
574 | if ($Stream) {
575 | if ($role) {
576 | return "$($PSStyle.Foreground.$roleColor)$role`:$($PSStyle.Reset) "
577 | } elseif ($content) {
578 | return "$($PSStyle.Foreground.BrightBlack)$content$($PSStyle.Reset)"
579 | } else {
580 | #Blank entry, we might want to throw here just in case tho it is technically allowed.
581 | return
582 | }
583 | }
584 |
585 | $formattedMessage = $content.Trim() | Format-ChatCode
586 | return "$($PSStyle.Foreground.$roleColor)$role`:$($PSStyle.Reset) $($PSStyle.ForeGround.BrightBlack)$formattedMessage"
587 | }
588 |
589 | function Format-CreateChatCompletionChunkedResponse {
590 | param(
591 | [Parameter(ValueFromPipeline)][CreateChatCompletionChunkedResponse]$response
592 | )
593 | Format-ChatMessage -Stream $response.Choices[0].Delta
594 | }
595 |
596 | function Format-Choices2 {
597 | [AssemblyMetadata('Format-Custom', 'Choices2')]
598 | param(
599 | [Choices2]$choice
600 | )
601 | $PSStyle.Foreground.BrightCyan +
602 | "Choice $([int]$choice.Index + 1): " +
603 | (Format-ChatMessage $choice.Message)
604 | }
605 |
606 |
607 | filter Format-CreateChatCompletionRequest {
608 | [AssemblyMetadata('Format-Custom', 'OpenAI.CreateChatCompletionRequest')]
609 | param(
610 | [Parameter(ValueFromPipeline)][CreateChatCompletionRequest]$request
611 | )
612 | $request.messages | Format-ChatMessage
613 | }
614 | filter Format-CreateChatCompletionResponse {
615 | [AssemblyMetadata('Format-Custom', 'OpenAI.CreateChatCompletionResponse')]
616 | param(
617 | [Parameter(ValueFromPipeline)][CreateChatCompletionResponse]$response
618 | )
619 | if ($response.Choices.Count -eq 1) {
620 | Format-ChatMessage $response.Choices[0].Message
621 | } else {
622 | $Response.Choices
623 | }
624 | }
625 |
626 | function Format-ChatConversation {
627 | param(
628 | [ChatConversation]$conversation
629 | )
630 | $messages = @()
631 |
632 | $messages += $conversation.Request | Format-CreateChatCompletionRequest
633 | $messages += $conversation.Response | Format-CreateChatCompletionResponse
634 | return $messages -join ($PSStyle.Reset + [Environment]::NewLine)
635 | }
636 |
637 | function Get-UsagePrice {
638 | param(
639 | [string]$Model,
640 | [int]$Total
641 | )
642 |
643 | #Taken from: https://openai.com/pricing
644 | $pricePerToken = @{
645 | 'code' = 0
646 | 'gpt-3.5-turbo' = .002 / 1000
647 | 'ada' = .0004 / 1000
648 | 'babbage' = .0005 / 1000
649 | 'curie' = .002 / 1000
650 | 'davinci' = .002 / 1000
651 | }
652 |
653 | foreach ($priceItem in $pricePerToken.GetEnumerator()) {
654 | if ($Model.Contains($priceItem.key)) {
655 | #Will return the first match
656 | $totalPrice = $total * $priceItem.Value
657 |
658 | #Formats as currency ($3.2629) and strips trailing zeroes
659 | return $totalPrice.ToString('C15').TrimEnd('0')
660 | }
661 | }
662 |
663 | #Return an empty string if no pricing engine found.
664 | return [string]::Empty
665 |
666 | }
--------------------------------------------------------------------------------
/src/OpenAI.Client/OpenAI.nswag:
--------------------------------------------------------------------------------
1 | {
2 | "runtime": "Net60",
3 | "defaultVariables": null,
4 | "documentGenerator": {
5 | "fromDocument": {
6 | "json": "openapi: 3.0.0\ninfo:\n title: OpenAI API\n description: APIs for sampling from and fine-tuning language models\n version: '1.2.0'\nservers:\n - url: https://api.openai.com/v1\ntags:\n- name: OpenAI\n description: The OpenAI REST API\npaths:\n /engines:\n get:\n operationId: listEngines\n deprecated: true\n tags:\n - OpenAI\n summary: Lists the currently available (non-finetuned) models, and provides basic information about each one such as the owner and availability.\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/ListEnginesResponse'\n x-oaiMeta:\n name: List engines\n group: engines\n path: list\n examples:\n curl: |\n curl https://api.openai.com/v1/engines \\\n -H 'Authorization: Bearer YOUR_API_KEY'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Engine.list()\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.listEngines();\n response: |\n {\n \"data\": [\n {\n \"id\": \"engine-id-0\",\n \"object\": \"engine\",\n \"owner\": \"organization-owner\",\n \"ready\": true\n },\n {\n \"id\": \"engine-id-2\",\n \"object\": \"engine\",\n \"owner\": \"organization-owner\",\n \"ready\": true\n },\n {\n \"id\": \"engine-id-3\",\n \"object\": \"engine\",\n \"owner\": \"openai\",\n \"ready\": false\n },\n ],\n \"object\": \"list\"\n }\n\n /engines/{engine_id}:\n get:\n operationId: retrieveEngine\n deprecated: true\n tags:\n - OpenAI\n summary: Retrieves a model instance, providing basic information about it such as the owner and availability.\n parameters:\n - in: path\n name: engine_id\n required: true\n schema:\n type: string\n # ideally this will be an actual ID, so this will always work from browser\n example:\n davinci\n description: &engine_id_description >\n The ID of the engine to use for this request\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/Engine'\n x-oaiMeta:\n name: Retrieve engine\n group: engines\n path: retrieve\n examples:\n curl: |\n curl https://api.openai.com/v1/engines/VAR_model_id \\\n -H 'Authorization: Bearer YOUR_API_KEY'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Engine.retrieve(\"VAR_model_id\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.retrieveEngine(\"VAR_model_id\");\n response: |\n {\n \"id\": \"VAR_model_id\",\n \"object\": \"engine\",\n \"owner\": \"openai\",\n \"ready\": true\n }\n\n /completions:\n post:\n operationId: createCompletion\n tags:\n - OpenAI\n summary: Creates a completion for the provided prompt and parameters\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateCompletionRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateCompletionResponse'\n x-oaiMeta:\n name: Create completion\n group: completions\n path: create\n examples:\n curl: |\n curl https://api.openai.com/v1/completions \\\n -H 'Content-Type: application/json' \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -d '{\n \"model\": \"VAR_model_id\",\n \"prompt\": \"Say this is a test\",\n \"max_tokens\": 7,\n \"temperature\": 0\n }'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Completion.create(\n model=\"VAR_model_id\",\n prompt=\"Say this is a test\",\n max_tokens=7,\n temperature=0\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createCompletion({\n model: \"VAR_model_id\",\n prompt: \"Say this is a test\",\n max_tokens: 7,\n temperature: 0,\n });\n parameters: |\n {\n \"model\": \"VAR_model_id\",\n \"prompt\": \"Say this is a test\",\n \"max_tokens\": 7,\n \"temperature\": 0,\n \"top_p\": 1,\n \"n\": 1,\n \"stream\": false,\n \"logprobs\": null,\n \"stop\": \"\\n\"\n }\n response: |\n {\n \"id\": \"cmpl-uqkvlQyYK7bGYrRHQ0eXlWi7\",\n \"object\": \"text_completion\",\n \"created\": 1589478378,\n \"model\": \"VAR_model_id\",\n \"choices\": [\n {\n \"text\": \"\\n\\nThis is indeed a test\",\n \"index\": 0,\n \"logprobs\": null,\n \"finish_reason\": \"length\"\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 5,\n \"completion_tokens\": 7,\n \"total_tokens\": 12\n }\n }\n /chat/completions:\n post:\n operationId: createChatCompletion\n tags:\n - OpenAI\n summary: Creates a completion for the chat message\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateChatCompletionRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateChatCompletionResponse'\n\n x-oaiMeta:\n name: Create chat completion\n group: chat\n path: create\n beta: true\n examples:\n curl: |\n curl https://api.openai.com/v1/chat/completions \\\n -H 'Content-Type: application/json' \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -d '{\n \"model\": \"gpt-3.5-turbo\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]\n }'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n\n completion = openai.ChatCompletion.create(\n model=\"gpt-3.5-turbo\",\n messages=[\n {\"role\": \"user\", \"content\": \"Hello!\"}\n ]\n )\n\n print(completion.choices[0].message)\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n\n const completion = await openai.createChatCompletion({\n model: \"gpt-3.5-turbo\",\n messages: [{role: \"user\", content: \"Hello world\"}],\n });\n console.log(completion.data.choices[0].message);\n parameters: |\n {\n \"model\": \"gpt-3.5-turbo\",\n \"messages\": [{\"role\": \"user\", \"content\": \"Hello!\"}]\n }\n response: |\n {\n \"id\": \"chatcmpl-123\",\n \"object\": \"chat.completion\",\n \"created\": 1677652288,\n \"choices\": [{\n \"index\": 0,\n \"message\": {\n \"role\": \"assistant\",\n \"content\": \"\\n\\nHello there, how may I assist you today?\",\n },\n \"finish_reason\": \"stop\"\n }],\n \"usage\": {\n \"prompt_tokens\": 9,\n \"completion_tokens\": 12,\n \"total_tokens\": 21\n }\n }\n\n /edits:\n post:\n operationId: createEdit\n tags:\n - OpenAI\n summary: Creates a new edit for the provided input, instruction, and parameters.\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateEditRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateEditResponse'\n x-oaiMeta:\n name: Create edit\n group: edits\n path: create\n examples:\n curl: |\n curl https://api.openai.com/v1/edits \\\n -H 'Content-Type: application/json' \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -d '{\n \"model\": \"VAR_model_id\",\n \"input\": \"What day of the wek is it?\",\n \"instruction\": \"Fix the spelling mistakes\"\n }'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Edit.create(\n model=\"VAR_model_id\",\n input=\"What day of the wek is it?\",\n instruction=\"Fix the spelling mistakes\"\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createEdit({\n model: \"VAR_model_id\",\n input: \"What day of the wek is it?\",\n instruction: \"Fix the spelling mistakes\",\n });\n parameters: |\n {\n \"model\": \"VAR_model_id\",\n \"input\": \"What day of the wek is it?\",\n \"instruction\": \"Fix the spelling mistakes\",\n }\n response: |\n {\n \"object\": \"edit\",\n \"created\": 1589478378,\n \"choices\": [\n {\n \"text\": \"What day of the week is it?\",\n \"index\": 0,\n }\n ],\n \"usage\": {\n \"prompt_tokens\": 25,\n \"completion_tokens\": 32,\n \"total_tokens\": 57\n }\n }\n\n /images/generations:\n post:\n operationId: createImage\n tags:\n - OpenAI\n summary: Creates an image given a prompt.\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateImageRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/ImagesResponse'\n x-oaiMeta:\n name: Create image\n group: images\n path: create\n beta: true\n examples:\n curl: |\n curl https://api.openai.com/v1/images/generations \\\n -H 'Content-Type: application/json' \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -d '{\n \"prompt\": \"A cute baby sea otter\",\n \"n\": 2,\n \"size\": \"1024x1024\"\n }'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Image.create(\n prompt=\"A cute baby sea otter\",\n n=2,\n size=\"1024x1024\"\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createImage({\n prompt: \"A cute baby sea otter\",\n n: 2,\n size: \"1024x1024\",\n });\n parameters: |\n {\n \"prompt\": \"A cute baby sea otter\",\n \"n\": 2,\n \"size\": \"1024x1024\"\n }\n response: |\n {\n \"created\": 1589478378,\n \"data\": [\n {\n \"url\": \"https://...\"\n },\n {\n \"url\": \"https://...\"\n }\n ]\n }\n\n /images/edits:\n post:\n operationId: createImageEdit\n tags:\n - OpenAI\n summary: Creates an edited or extended image given an original image and a prompt.\n requestBody:\n required: true\n content:\n multipart/form-data:\n schema:\n $ref: '#/components/schemas/CreateImageEditRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/ImagesResponse'\n x-oaiMeta:\n name: Create image edit\n group: images\n path: create-edit\n beta: true\n examples:\n curl: |\n curl https://api.openai.com/v1/images/edits \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -F image='@otter.png' \\\n -F mask='@mask.png' \\\n -F prompt=\"A cute baby sea otter wearing a beret\" \\\n -F n=2 \\\n -F size=\"1024x1024\"\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Image.create_edit(\n image=open(\"otter.png\", \"rb\"),\n mask=open(\"mask.png\", \"rb\"),\n prompt=\"A cute baby sea otter wearing a beret\",\n n=2,\n size=\"1024x1024\"\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createImageEdit(\n fs.createReadStream(\"otter.png\"),\n fs.createReadStream(\"mask.png\"),\n \"A cute baby sea otter wearing a beret\",\n 2,\n \"1024x1024\"\n );\n response: |\n {\n \"created\": 1589478378,\n \"data\": [\n {\n \"url\": \"https://...\"\n },\n {\n \"url\": \"https://...\"\n }\n ]\n }\n\n /images/variations:\n post:\n operationId: createImageVariation\n tags:\n - OpenAI\n summary: Creates a variation of a given image.\n requestBody:\n required: true\n content:\n multipart/form-data:\n schema:\n $ref: '#/components/schemas/CreateImageVariationRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/ImagesResponse'\n x-oaiMeta:\n name: Create image variation\n group: images\n path: create-variation\n beta: true\n examples:\n curl: |\n curl https://api.openai.com/v1/images/variations \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -F image='@otter.png' \\\n -F n=2 \\\n -F size=\"1024x1024\"\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Image.create_variation(\n image=open(\"otter.png\", \"rb\"),\n n=2,\n size=\"1024x1024\"\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createImageVariation(\n fs.createReadStream(\"otter.png\"),\n 2,\n \"1024x1024\"\n );\n response: |\n {\n \"created\": 1589478378,\n \"data\": [\n {\n \"url\": \"https://...\"\n },\n {\n \"url\": \"https://...\"\n }\n ]\n }\n\n /embeddings:\n post:\n operationId: createEmbedding\n tags:\n - OpenAI\n summary: Creates an embedding vector representing the input text.\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateEmbeddingRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateEmbeddingResponse'\n x-oaiMeta:\n name: Create embeddings\n group: embeddings\n path: create\n examples:\n curl: |\n curl https://api.openai.com/v1/embeddings \\\n -X POST \\\n -H \"Authorization: Bearer YOUR_API_KEY\" \\\n -H \"Content-Type: application/json\" \\\n -d '{\"input\": \"The food was delicious and the waiter...\",\n \"model\": \"text-embedding-ada-002\"}'\n\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Embedding.create(\n model=\"text-embedding-ada-002\",\n input=\"The food was delicious and the waiter...\"\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createEmbedding({\n model: \"text-embedding-ada-002\",\n input: \"The food was delicious and the waiter...\",\n });\n parameters: |\n {\n \"model\": \"text-embedding-ada-002\",\n \"input\": \"The food was delicious and the waiter...\"\n }\n response: |\n {\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"embedding\",\n \"embedding\": [\n 0.0023064255,\n -0.009327292,\n .... (1536 floats total for ada-002)\n -0.0028842222,\n ],\n \"index\": 0\n }\n ],\n \"model\": \"text-embedding-ada-002\",\n \"usage\": {\n \"prompt_tokens\": 8,\n \"total_tokens\": 8\n }\n }\n\n /audio/transcriptions:\n post:\n operationId: createTranscription\n tags:\n - OpenAI\n summary: Transcribes audio into the input language.\n requestBody:\n required: true\n content:\n multipart/form-data:\n schema:\n $ref: '#/components/schemas/CreateTranscriptionRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateTranscriptionResponse'\n x-oaiMeta:\n name: Create transcription\n group: audio\n path: create\n beta: true\n examples:\n curl: |\n curl https://api.openai.com/v1/audio/transcriptions \\\n -X POST \\\n -H 'Authorization: Bearer TOKEN' \\\n -H 'Content-Type: multipart/form-data' \\\n -F file=@/path/to/file/audio.mp3 \\\n -F model=whisper-1\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n audio_file = open(\"audio.mp3\", \"rb\")\n transcript = openai.Audio.transcribe(\"whisper-1\", audio_file)\n node: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const resp = await openai.createTranscription(\n fs.createReadStream(\"audio.mp3\"),\n \"whisper-1\"\n );\n parameters: |\n {\n \"file\": \"audio.mp3\",\n \"model\": \"whisper-1\"\n }\n response: |\n {\n \"text\": \"Imagine the wildest idea that you've ever had, and you're curious about how it might scale to something that's a 100, a 1,000 times bigger. This is a place where you can get to do that.\"\n }\n\n /audio/translations:\n post:\n operationId: createTranslation\n tags:\n - OpenAI\n summary: Translates audio into into English.\n requestBody:\n required: true\n content:\n multipart/form-data:\n schema:\n $ref: '#/components/schemas/CreateTranslationRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateTranslationResponse'\n x-oaiMeta:\n name: Create translation\n group: audio\n path: create\n beta: true\n examples:\n curl: |\n curl https://api.openai.com/v1/audio/translations \\\n -X POST \\\n -H 'Authorization: Bearer TOKEN' \\\n -H 'Content-Type: multipart/form-data' \\\n -F file=@/path/to/file/german.m4a \\\n -F model=whisper-1\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n audio_file = open(\"german.m4a\", \"rb\")\n transcript = openai.Audio.translate(\"whisper-1\", audio_file)\n node: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const resp = await openai.createTranslation(\n fs.createReadStream(\"audio.mp3\"),\n \"whisper-1\"\n );\n parameters: |\n {\n \"file\": \"german.m4a\",\n \"model\": \"whisper-1\"\n }\n response: |\n {\n \"text\": \"Hello, my name is Wolfgang and I come from Germany. Where are you heading today?\"\n }\n\n /engines/{engine_id}/search:\n post:\n operationId: createSearch\n deprecated: true\n tags:\n - OpenAI\n summary: |\n The search endpoint computes similarity scores between provided query and documents. Documents can be passed directly to the API if there are no more than 200 of them.\n\n To go beyond the 200 document limit, documents can be processed offline and then used for efficient retrieval at query time. When `file` is set, the search endpoint searches over all the documents in the given file and returns up to the `max_rerank` number of documents. These documents will be returned along with their search scores.\n\n The similarity score is a positive score that usually ranges from 0 to 300 (but can sometimes go higher), where a score above 200 usually means the document is semantically similar to the query.\n parameters:\n - in: path\n name: engine_id\n required: true\n schema:\n type: string\n example: davinci\n description: The ID of the engine to use for this request. You can select one of `ada`, `babbage`, `curie`, or `davinci`.\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateSearchRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateSearchResponse'\n x-oaiMeta:\n name: Create search\n group: searches\n path: create\n examples:\n curl: |\n curl https://api.openai.com/v1/engines/davinci/search \\\n -H \"Content-Type: application/json\" \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -d '{\n \"documents\": [\"White House\", \"hospital\", \"school\"],\n \"query\": \"the president\"\n }'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Engine(\"davinci\").search(\n documents=[\"White House\", \"hospital\", \"school\"],\n query=\"the president\"\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createSearch(\"davinci\", {\n documents: [\"White House\", \"hospital\", \"school\"],\n query: \"the president\",\n });\n parameters: |\n {\n \"documents\": [\n \"White House\",\n \"hospital\",\n \"school\"\n ],\n \"query\": \"the president\"\n }\n response: |\n {\n \"data\": [\n {\n \"document\": 0,\n \"object\": \"search_result\",\n \"score\": 215.412\n },\n {\n \"document\": 1,\n \"object\": \"search_result\",\n \"score\": 40.316\n },\n {\n \"document\": 2,\n \"object\": \"search_result\",\n \"score\": 55.226\n }\n ],\n \"object\": \"list\"\n }\n\n /files:\n get:\n operationId: listFiles\n tags:\n - OpenAI\n summary: Returns a list of files that belong to the user's organization.\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/ListFilesResponse'\n x-oaiMeta:\n name: List files\n group: files\n path: list\n examples:\n curl: |\n curl https://api.openai.com/v1/files \\\n -H 'Authorization: Bearer YOUR_API_KEY'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.File.list()\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.listFiles();\n response: |\n {\n \"data\": [\n {\n \"id\": \"file-ccdDZrC3iZVNiQVeEA6Z66wf\",\n \"object\": \"file\",\n \"bytes\": 175,\n \"created_at\": 1613677385,\n \"filename\": \"train.jsonl\",\n \"purpose\": \"search\"\n },\n {\n \"id\": \"file-XjGxS3KTG0uNmNOK362iJua3\",\n \"object\": \"file\",\n \"bytes\": 140,\n \"created_at\": 1613779121,\n \"filename\": \"puppy.jsonl\",\n \"purpose\": \"search\"\n }\n ],\n \"object\": \"list\"\n }\n post:\n operationId: createFile\n tags:\n - OpenAI\n summary: |\n Upload a file that contains document(s) to be used across various endpoints/features. Currently, the size of all the files uploaded by one organization can be up to 1 GB. Please contact us if you need to increase the storage limit.\n\n requestBody:\n required: true\n content:\n multipart/form-data:\n schema:\n $ref: '#/components/schemas/CreateFileRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/OpenAIFile'\n x-oaiMeta:\n name: Upload file\n group: files\n path: upload\n examples:\n curl: |\n curl https://api.openai.com/v1/files \\\n -H \"Authorization: Bearer YOUR_API_KEY\" \\\n -F purpose=\"fine-tune\" \\\n -F file='@mydata.jsonl'\n\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.File.create(\n file=open(\"mydata.jsonl\", \"rb\"),\n purpose='fine-tune'\n )\n node.js: |\n const fs = require(\"fs\");\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createFile(\n fs.createReadStream(\"mydata.jsonl\"),\n \"fine-tune\"\n );\n response: |\n {\n \"id\": \"file-XjGxS3KTG0uNmNOK362iJua3\",\n \"object\": \"file\",\n \"bytes\": 140,\n \"created_at\": 1613779121,\n \"filename\": \"mydata.jsonl\",\n \"purpose\": \"fine-tune\"\n }\n\n /files/{file_id}:\n delete:\n operationId: deleteFile\n tags:\n - OpenAI\n summary: Delete a file.\n parameters:\n - in: path\n name: file_id\n required: true\n schema:\n type: string\n description: The ID of the file to use for this request\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/DeleteFileResponse'\n x-oaiMeta:\n name: Delete file\n group: files\n path: delete\n examples:\n curl: |\n curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3 \\\n -X DELETE \\\n -H 'Authorization: Bearer YOUR_API_KEY'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.File.delete(\"file-XjGxS3KTG0uNmNOK362iJua3\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.deleteFile(\"file-XjGxS3KTG0uNmNOK362iJua3\");\n response: |\n {\n \"id\": \"file-XjGxS3KTG0uNmNOK362iJua3\",\n \"object\": \"file\",\n \"deleted\": true\n }\n get:\n operationId: retrieveFile\n tags:\n - OpenAI\n summary: Returns information about a specific file.\n parameters:\n - in: path\n name: file_id\n required: true\n schema:\n type: string\n description: The ID of the file to use for this request\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/OpenAIFile'\n x-oaiMeta:\n name: Retrieve file\n group: files\n path: retrieve\n examples:\n curl: |\n curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3 \\\n -H 'Authorization: Bearer YOUR_API_KEY'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.File.retrieve(\"file-XjGxS3KTG0uNmNOK362iJua3\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.retrieveFile(\"file-XjGxS3KTG0uNmNOK362iJua3\");\n response: |\n {\n \"id\": \"file-XjGxS3KTG0uNmNOK362iJua3\",\n \"object\": \"file\",\n \"bytes\": 140,\n \"created_at\": 1613779657,\n \"filename\": \"mydata.jsonl\",\n \"purpose\": \"fine-tune\"\n }\n\n /files/{file_id}/content:\n get:\n operationId: downloadFile\n tags:\n - OpenAI\n summary: Returns the contents of the specified file\n parameters:\n - in: path\n name: file_id\n required: true\n schema:\n type: string\n description: The ID of the file to use for this request\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n type: string\n x-oaiMeta:\n name: Retrieve file content\n group: files\n path: retrieve-content\n examples:\n curl: |\n curl https://api.openai.com/v1/files/file-XjGxS3KTG0uNmNOK362iJua3/content \\\n -H 'Authorization: Bearer YOUR_API_KEY' > file.jsonl\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n content = openai.File.download(\"file-XjGxS3KTG0uNmNOK362iJua3\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.downloadFile(\"file-XjGxS3KTG0uNmNOK362iJua3\");\n\n /answers:\n post:\n operationId: createAnswer\n deprecated: true\n tags:\n - OpenAI\n summary: |\n Answers the specified question using the provided documents and examples.\n\n The endpoint first [searches](/docs/api-reference/searches) over provided documents or files to find relevant context. The relevant context is combined with the provided examples and question to create the prompt for [completion](/docs/api-reference/completions).\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateAnswerRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateAnswerResponse'\n x-oaiMeta:\n name: Create answer\n group: answers\n path: create\n examples:\n curl: |\n curl https://api.openai.com/v1/answers \\\n -X POST \\\n -H \"Authorization: Bearer YOUR_API_KEY\" \\\n -H 'Content-Type: application/json' \\\n -d '{\n \"documents\": [\"Puppy A is happy.\", \"Puppy B is sad.\"],\n \"question\": \"which puppy is happy?\",\n \"search_model\": \"ada\",\n \"model\": \"curie\",\n \"examples_context\": \"In 2017, U.S. life expectancy was 78.6 years.\",\n \"examples\": [[\"What is human life expectancy in the United States?\",\"78 years.\"]],\n \"max_tokens\": 5,\n \"stop\": [\"\\n\", \"<|endoftext|>\"]\n }'\n\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Answer.create(\n search_model=\"ada\",\n model=\"curie\",\n question=\"which puppy is happy?\",\n documents=[\"Puppy A is happy.\", \"Puppy B is sad.\"],\n examples_context=\"In 2017, U.S. life expectancy was 78.6 years.\",\n examples=[[\"What is human life expectancy in the United States?\",\"78 years.\"]],\n max_tokens=5,\n stop=[\"\\n\", \"<|endoftext|>\"],\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createAnswer({\n search_model: \"ada\",\n model: \"curie\",\n question: \"which puppy is happy?\",\n documents: [\"Puppy A is happy.\", \"Puppy B is sad.\"],\n examples_context: \"In 2017, U.S. life expectancy was 78.6 years.\",\n examples: [[\"What is human life expectancy in the United States?\",\"78 years.\"]],\n max_tokens: 5,\n stop: [\"\\n\", \"<|endoftext|>\"],\n });\n parameters: |\n {\n \"documents\": [\"Puppy A is happy.\", \"Puppy B is sad.\"],\n \"question\": \"which puppy is happy?\",\n \"search_model\": \"ada\",\n \"model\": \"curie\",\n \"examples_context\": \"In 2017, U.S. life expectancy was 78.6 years.\",\n \"examples\": [[\"What is human life expectancy in the United States?\",\"78 years.\"]],\n \"max_tokens\": 5,\n \"stop\": [\"\\n\", \"<|endoftext|>\"]\n }\n response: |\n {\n \"answers\": [\n \"puppy A.\"\n ],\n \"completion\": \"cmpl-2euVa1kmKUuLpSX600M41125Mo9NI\",\n \"model\": \"curie:2020-05-03\",\n \"object\": \"answer\",\n \"search_model\": \"ada\",\n \"selected_documents\": [\n {\n \"document\": 0,\n \"text\": \"Puppy A is happy. \"\n },\n {\n \"document\": 1,\n \"text\": \"Puppy B is sad. \"\n }\n ]\n }\n\n /classifications:\n post:\n operationId: createClassification\n deprecated: true\n tags:\n - OpenAI\n summary: |\n Classifies the specified `query` using provided examples.\n\n The endpoint first [searches](/docs/api-reference/searches) over the labeled examples\n to select the ones most relevant for the particular query. Then, the relevant examples\n are combined with the query to construct a prompt to produce the final label via the\n [completions](/docs/api-reference/completions) endpoint.\n\n Labeled examples can be provided via an uploaded `file`, or explicitly listed in the\n request using the `examples` parameter for quick tests and small scale use cases.\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateClassificationRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateClassificationResponse'\n x-oaiMeta:\n name: Create classification\n group: classifications\n path: create\n examples:\n curl: |\n curl https://api.openai.com/v1/classifications \\\n -X POST \\\n -H \"Authorization: Bearer YOUR_API_KEY\" \\\n -H 'Content-Type: application/json' \\\n -d '{\n \"examples\": [\n [\"A happy moment\", \"Positive\"],\n [\"I am sad.\", \"Negative\"],\n [\"I am feeling awesome\", \"Positive\"]],\n \"query\": \"It is a raining day :(\",\n \"search_model\": \"ada\",\n \"model\": \"curie\",\n \"labels\":[\"Positive\", \"Negative\", \"Neutral\"]\n }'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Classification.create(\n search_model=\"ada\",\n model=\"curie\",\n examples=[\n [\"A happy moment\", \"Positive\"],\n [\"I am sad.\", \"Negative\"],\n [\"I am feeling awesome\", \"Positive\"]\n ],\n query=\"It is a raining day :(\",\n labels=[\"Positive\", \"Negative\", \"Neutral\"],\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createClassification({\n search_model: \"ada\",\n model: \"curie\",\n examples: [\n [\"A happy moment\", \"Positive\"],\n [\"I am sad.\", \"Negative\"],\n [\"I am feeling awesome\", \"Positive\"]\n ],\n query:\"It is a raining day :(\",\n labels: [\"Positive\", \"Negative\", \"Neutral\"],\n });\n parameters: |\n {\n \"examples\": [\n [\"A happy moment\", \"Positive\"],\n [\"I am sad.\", \"Negative\"],\n [\"I am feeling awesome\", \"Positive\"]\n ],\n \"labels\": [\"Positive\", \"Negative\", \"Neutral\"],\n \"query\": \"It is a raining day :(\",\n \"search_model\": \"ada\",\n \"model\": \"curie\"\n }\n response: |\n {\n \"completion\": \"cmpl-2euN7lUVZ0d4RKbQqRV79IiiE6M1f\",\n \"label\": \"Negative\",\n \"model\": \"curie:2020-05-03\",\n \"object\": \"classification\",\n \"search_model\": \"ada\",\n \"selected_examples\": [\n {\n \"document\": 1,\n \"label\": \"Negative\",\n \"text\": \"I am sad.\"\n },\n {\n \"document\": 0,\n \"label\": \"Positive\",\n \"text\": \"A happy moment\"\n },\n {\n \"document\": 2,\n \"label\": \"Positive\",\n \"text\": \"I am feeling awesome\"\n }\n ]\n }\n\n /fine-tunes:\n post:\n operationId: createFineTune\n tags:\n - OpenAI\n summary: |\n Creates a job that fine-tunes a specified model from a given dataset.\n\n Response includes details of the enqueued job including job status and the name of the fine-tuned models once complete.\n\n [Learn more about Fine-tuning](/docs/guides/fine-tuning)\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateFineTuneRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/FineTune'\n x-oaiMeta:\n name: Create fine-tune\n group: fine-tunes\n path: create\n examples:\n curl: |\n curl https://api.openai.com/v1/fine-tunes \\\n -X POST \\\n -H \"Content-Type: application/json\" \\\n -H \"Authorization: Bearer YOUR_API_KEY\" \\\n -d '{\n \"training_file\": \"file-XGinujblHPwGLSztz8cPS8XY\"\n }'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.FineTune.create(training_file=\"file-XGinujblHPwGLSztz8cPS8XY\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createFineTune({\n training_file: \"file-XGinujblHPwGLSztz8cPS8XY\",\n });\n response: |\n {\n \"id\": \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n \"object\": \"fine-tune\",\n \"model\": \"curie\",\n \"created_at\": 1614807352,\n \"events\": [\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807352,\n \"level\": \"info\",\n \"message\": \"Job enqueued. Waiting for jobs ahead to complete. Queue number: 0.\"\n }\n ],\n \"fine_tuned_model\": null,\n \"hyperparams\": {\n \"batch_size\": 4,\n \"learning_rate_multiplier\": 0.1,\n \"n_epochs\": 4,\n \"prompt_loss_weight\": 0.1,\n },\n \"organization_id\": \"org-...\",\n \"result_files\": [],\n \"status\": \"pending\",\n \"validation_files\": [],\n \"training_files\": [\n {\n \"id\": \"file-XGinujblHPwGLSztz8cPS8XY\",\n \"object\": \"file\",\n \"bytes\": 1547276,\n \"created_at\": 1610062281,\n \"filename\": \"my-data-train.jsonl\",\n \"purpose\": \"fine-tune-train\"\n }\n ],\n \"updated_at\": 1614807352,\n }\n get:\n operationId: listFineTunes\n tags:\n - OpenAI\n summary: |\n List your organization's fine-tuning jobs\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/ListFineTunesResponse'\n x-oaiMeta:\n name: List fine-tunes\n group: fine-tunes\n path: list\n examples:\n curl: |\n curl https://api.openai.com/v1/fine-tunes \\\n -H 'Authorization: Bearer YOUR_API_KEY'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.FineTune.list()\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.listFineTunes();\n response: |\n {\n \"object\": \"list\",\n \"data\": [\n {\n \"id\": \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n \"object\": \"fine-tune\",\n \"model\": \"curie\",\n \"created_at\": 1614807352,\n \"fine_tuned_model\": null,\n \"hyperparams\": { ... },\n \"organization_id\": \"org-...\",\n \"result_files\": [],\n \"status\": \"pending\",\n \"validation_files\": [],\n \"training_files\": [ { ... } ],\n \"updated_at\": 1614807352,\n },\n { ... },\n { ... }\n ]\n }\n\n /fine-tunes/{fine_tune_id}:\n get:\n operationId: retrieveFineTune\n tags:\n - OpenAI\n summary: |\n Gets info about the fine-tune job.\n\n [Learn more about Fine-tuning](/docs/guides/fine-tuning)\n parameters:\n - in: path\n name: fine_tune_id\n required: true\n schema:\n type: string\n example:\n ft-AF1WoRqd3aJAHsqc9NY7iL8F\n description: |\n The ID of the fine-tune job\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/FineTune'\n x-oaiMeta:\n name: Retrieve fine-tune\n group: fine-tunes\n path: retrieve\n examples:\n curl: |\n curl https://api.openai.com/v1/fine-tunes/ft-AF1WoRqd3aJAHsqc9NY7iL8F \\\n -H \"Authorization: Bearer YOUR_API_KEY\"\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.FineTune.retrieve(id=\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.retrieveFineTune(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n response: |\n {\n \"id\": \"ft-AF1WoRqd3aJAHsqc9NY7iL8F\",\n \"object\": \"fine-tune\",\n \"model\": \"curie\",\n \"created_at\": 1614807352,\n \"events\": [\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807352,\n \"level\": \"info\",\n \"message\": \"Job enqueued. Waiting for jobs ahead to complete. Queue number: 0.\"\n },\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807356,\n \"level\": \"info\",\n \"message\": \"Job started.\"\n },\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807861,\n \"level\": \"info\",\n \"message\": \"Uploaded snapshot: curie:ft-acmeco-2021-03-03-21-44-20.\"\n },\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807864,\n \"level\": \"info\",\n \"message\": \"Uploaded result files: file-QQm6ZpqdNwAaVC3aSz5sWwLT.\"\n },\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807864,\n \"level\": \"info\",\n \"message\": \"Job succeeded.\"\n }\n ],\n \"fine_tuned_model\": \"curie:ft-acmeco-2021-03-03-21-44-20\",\n \"hyperparams\": {\n \"batch_size\": 4,\n \"learning_rate_multiplier\": 0.1,\n \"n_epochs\": 4,\n \"prompt_loss_weight\": 0.1,\n },\n \"organization_id\": \"org-...\",\n \"result_files\": [\n {\n \"id\": \"file-QQm6ZpqdNwAaVC3aSz5sWwLT\",\n \"object\": \"file\",\n \"bytes\": 81509,\n \"created_at\": 1614807863,\n \"filename\": \"compiled_results.csv\",\n \"purpose\": \"fine-tune-results\"\n }\n ],\n \"status\": \"succeeded\",\n \"validation_files\": [],\n \"training_files\": [\n {\n \"id\": \"file-XGinujblHPwGLSztz8cPS8XY\",\n \"object\": \"file\",\n \"bytes\": 1547276,\n \"created_at\": 1610062281,\n \"filename\": \"my-data-train.jsonl\",\n \"purpose\": \"fine-tune-train\"\n }\n ],\n \"updated_at\": 1614807865,\n }\n\n /fine-tunes/{fine_tune_id}/cancel:\n post:\n operationId: cancelFineTune\n tags:\n - OpenAI\n summary: |\n Immediately cancel a fine-tune job.\n parameters:\n - in: path\n name: fine_tune_id\n required: true\n schema:\n type: string\n example:\n ft-AF1WoRqd3aJAHsqc9NY7iL8F\n description: |\n The ID of the fine-tune job to cancel\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/FineTune'\n x-oaiMeta:\n name: Cancel fine-tune\n group: fine-tunes\n path: cancel\n examples:\n curl: |\n curl https://api.openai.com/v1/fine-tunes/ft-AF1WoRqd3aJAHsqc9NY7iL8F/cancel \\\n -X POST \\\n -H \"Authorization: Bearer YOUR_API_KEY\"\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.FineTune.cancel(id=\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.cancelFineTune(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n response: |\n {\n \"id\": \"ft-xhrpBbvVUzYGo8oUO1FY4nI7\",\n \"object\": \"fine-tune\",\n \"model\": \"curie\",\n \"created_at\": 1614807770,\n \"events\": [ { ... } ],\n \"fine_tuned_model\": null,\n \"hyperparams\": { ... },\n \"organization_id\": \"org-...\",\n \"result_files\": [],\n \"status\": \"cancelled\",\n \"validation_files\": [],\n \"training_files\": [\n {\n \"id\": \"file-XGinujblHPwGLSztz8cPS8XY\",\n \"object\": \"file\",\n \"bytes\": 1547276,\n \"created_at\": 1610062281,\n \"filename\": \"my-data-train.jsonl\",\n \"purpose\": \"fine-tune-train\"\n }\n ],\n \"updated_at\": 1614807789,\n }\n\n /fine-tunes/{fine_tune_id}/events:\n get:\n operationId: listFineTuneEvents\n tags:\n - OpenAI\n summary: |\n Get fine-grained status updates for a fine-tune job.\n parameters:\n - in: path\n name: fine_tune_id\n required: true\n schema:\n type: string\n example:\n ft-AF1WoRqd3aJAHsqc9NY7iL8F\n description: |\n The ID of the fine-tune job to get events for.\n - in: query\n name: stream\n required: false\n schema:\n type: boolean\n default: false\n description: |\n Whether to stream events for the fine-tune job. If set to true,\n events will be sent as data-only\n [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)\n as they become available. The stream will terminate with a\n `data: [DONE]` message when the job is finished (succeeded, cancelled,\n or failed).\n\n If set to false, only events generated so far will be returned.\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/ListFineTuneEventsResponse'\n x-oaiMeta:\n name: List fine-tune events\n group: fine-tunes\n path: events\n examples:\n curl: |\n curl https://api.openai.com/v1/fine-tunes/ft-AF1WoRqd3aJAHsqc9NY7iL8F/events \\\n -H \"Authorization: Bearer YOUR_API_KEY\"\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.FineTune.list_events(id=\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.listFineTuneEvents(\"ft-AF1WoRqd3aJAHsqc9NY7iL8F\");\n response: |\n {\n \"object\": \"list\",\n \"data\": [\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807352,\n \"level\": \"info\",\n \"message\": \"Job enqueued. Waiting for jobs ahead to complete. Queue number: 0.\"\n },\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807356,\n \"level\": \"info\",\n \"message\": \"Job started.\"\n },\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807861,\n \"level\": \"info\",\n \"message\": \"Uploaded snapshot: curie:ft-acmeco-2021-03-03-21-44-20.\"\n },\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807864,\n \"level\": \"info\",\n \"message\": \"Uploaded result files: file-QQm6ZpqdNwAaVC3aSz5sWwLT.\"\n },\n {\n \"object\": \"fine-tune-event\",\n \"created_at\": 1614807864,\n \"level\": \"info\",\n \"message\": \"Job succeeded.\"\n }\n ]\n }\n\n /models:\n get:\n operationId: listModels\n tags:\n - OpenAI\n summary: Lists the currently available models, and provides basic information about each one such as the owner and availability.\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/ListModelsResponse'\n x-oaiMeta:\n name: List models\n group: models\n path: list\n examples:\n curl: |\n curl https://api.openai.com/v1/models \\\n -H 'Authorization: Bearer YOUR_API_KEY'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Model.list()\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.listModels();\n response: |\n {\n \"data\": [\n {\n \"id\": \"model-id-0\",\n \"object\": \"model\",\n \"owned_by\": \"organization-owner\",\n \"permission\": [...]\n },\n {\n \"id\": \"model-id-1\",\n \"object\": \"model\",\n \"owned_by\": \"organization-owner\",\n \"permission\": [...]\n },\n {\n \"id\": \"model-id-2\",\n \"object\": \"model\",\n \"owned_by\": \"openai\",\n \"permission\": [...]\n },\n ],\n \"object\": \"list\"\n }\n\n /models/{model}:\n get:\n operationId: retrieveModel\n tags:\n - OpenAI\n summary: Retrieves a model instance, providing basic information about the model such as the owner and permissioning.\n parameters:\n - in: path\n name: model\n required: true\n schema:\n type: string\n # ideally this will be an actual ID, so this will always work from browser\n example:\n text-davinci-001\n description:\n The ID of the model to use for this request\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/Model'\n x-oaiMeta:\n name: Retrieve model\n group: models\n path: retrieve\n examples:\n curl: |\n curl https://api.openai.com/v1/models/VAR_model_id \\\n -H 'Authorization: Bearer YOUR_API_KEY'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Model.retrieve(\"VAR_model_id\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.retrieveModel(\"VAR_model_id\");\n response: |\n {\n \"id\": \"VAR_model_id\",\n \"object\": \"model\",\n \"owned_by\": \"openai\",\n \"permission\": [...]\n }\n delete:\n operationId: deleteModel\n tags:\n - OpenAI\n summary: Delete a fine-tuned model. You must have the Owner role in your organization.\n parameters:\n - in: path\n name: model\n required: true\n schema:\n type: string\n example: curie:ft-acmeco-2021-03-03-21-44-20\n description: The model to delete\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/DeleteModelResponse'\n x-oaiMeta:\n name: Delete fine-tune model\n group: fine-tunes\n path: delete-model\n examples:\n curl: |\n curl https://api.openai.com/v1/models/curie:ft-acmeco-2021-03-03-21-44-20 \\\n -X DELETE \\\n -H \"Authorization: Bearer YOUR_API_KEY\"\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Model.delete(\"curie:ft-acmeco-2021-03-03-21-44-20\")\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.deleteModel('curie:ft-acmeco-2021-03-03-21-44-20');\n response: |\n {\n \"id\": \"curie:ft-acmeco-2021-03-03-21-44-20\",\n \"object\": \"model\",\n \"deleted\": true\n }\n\n /moderations:\n post:\n operationId: createModeration\n tags:\n - OpenAI\n summary: Classifies if text violates OpenAI's Content Policy\n requestBody:\n required: true\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateModerationRequest'\n responses:\n \"200\":\n description: OK\n content:\n application/json:\n schema:\n $ref: '#/components/schemas/CreateModerationResponse'\n x-oaiMeta:\n name: Create moderation\n group: moderations\n path: create\n examples:\n curl: |\n curl https://api.openai.com/v1/moderations \\\n -H 'Content-Type: application/json' \\\n -H 'Authorization: Bearer YOUR_API_KEY' \\\n -d '{\n \"input\": \"I want to kill them.\"\n }'\n python: |\n import os\n import openai\n openai.api_key = os.getenv(\"OPENAI_API_KEY\")\n openai.Moderation.create(\n input=\"I want to kill them.\",\n )\n node.js: |\n const { Configuration, OpenAIApi } = require(\"openai\");\n const configuration = new Configuration({\n apiKey: process.env.OPENAI_API_KEY,\n });\n const openai = new OpenAIApi(configuration);\n const response = await openai.createModeration({\n input: \"I want to kill them.\",\n });\n parameters: |\n {\n \"input\": \"I want to kill them.\"\n }\n response: |\n {\n \"id\": \"modr-5MWoLO\",\n \"model\": \"text-moderation-001\",\n \"results\": [\n {\n \"categories\": {\n \"hate\": false,\n \"hate/threatening\": true,\n \"self-harm\": false,\n \"sexual\": false,\n \"sexual/minors\": false,\n \"violence\": true,\n \"violence/graphic\": false\n },\n \"category_scores\": {\n \"hate\": 0.22714105248451233,\n \"hate/threatening\": 0.4132447838783264,\n \"self-harm\": 0.005232391878962517,\n \"sexual\": 0.01407341007143259,\n \"sexual/minors\": 0.0038522258400917053,\n \"violence\": 0.9223177433013916,\n \"violence/graphic\": 0.036865197122097015\n },\n \"flagged\": true\n }\n ]\n }\n\ncomponents:\n schemas:\n ListEnginesResponse:\n type: object\n properties:\n object:\n type: string\n data:\n type: array\n items:\n $ref: '#/components/schemas/Engine'\n required:\n - object\n - data\n\n ListModelsResponse:\n type: object\n properties:\n object:\n type: string\n data:\n type: array\n items:\n $ref: '#/components/schemas/Model'\n required:\n - object\n - data\n\n DeleteModelResponse:\n type: object\n properties:\n id:\n type: string\n object:\n type: string\n deleted:\n type: boolean\n required:\n - id\n - object\n - deleted\n\n CreateCompletionRequest:\n type: object\n properties:\n model: &model_configuration\n description: ID of the model to use. You can use the [List models](/docs/api-reference/models/list) API to see all of your available models, or see our [Model overview](/docs/models/overview) for descriptions of them.\n type: string\n prompt:\n description: &completions_prompt_description |\n The prompt(s) to generate completions for, encoded as a string, array of strings, array of tokens, or array of token arrays.\n\n Note that <|endoftext|> is the document separator that the model sees during training, so if a prompt is not specified the model will generate as if from the beginning of a new document.\n default: '<|endoftext|>'\n nullable: true\n oneOf:\n - type: string\n default: ''\n example: \"This is a test.\"\n - type: array\n items:\n type: string\n default: ''\n example: \"This is a test.\"\n - type: array\n minItems: 1\n items:\n type: integer\n example: \"[1212, 318, 257, 1332, 13]\"\n - type: array\n minItems: 1\n items:\n type: array\n minItems: 1\n items:\n type: integer\n example: \"[[1212, 318, 257, 1332, 13]]\"\n suffix:\n description:\n The suffix that comes after a completion of inserted text.\n default: null\n nullable: true\n type: string\n example: \"test.\"\n max_tokens:\n type: integer\n minimum: 0\n default: 16\n example: 16\n nullable: true\n description: &completions_max_tokens_description |\n The maximum number of [tokens](/tokenizer) to generate in the completion.\n\n The token count of your prompt plus `max_tokens` cannot exceed the model's context length. Most models have a context length of 2048 tokens (except for the newest models, which support 4096).\n temperature:\n type: number\n minimum: 0\n maximum: 2\n default: 1\n example: 1\n nullable: true\n description: &completions_temperature_description |\n What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n\n We generally recommend altering this or `top_p` but not both.\n top_p:\n type: number\n minimum: 0\n maximum: 1\n default: 1\n example: 1\n nullable: true\n description: &completions_top_p_description |\n An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered.\n\n We generally recommend altering this or `temperature` but not both.\n n:\n type: integer\n minimum: 1\n maximum: 128\n default: 1\n example: 1\n nullable: true\n description: &completions_completions_description |\n How many completions to generate for each prompt.\n\n **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.\n stream:\n description: >\n Whether to stream back partial progress. If set, tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)\n as they become available, with the stream terminated by a `data: [DONE]` message.\n type: boolean\n nullable: true\n default: false\n logprobs: &completions_logprobs_configuration\n type: integer\n minimum: 0\n maximum: 5\n default: null\n nullable: true\n description: &completions_logprobs_description |\n Include the log probabilities on the `logprobs` most likely tokens, as well the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens. The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1` elements in the response.\n\n The maximum value for `logprobs` is 5. If you need more than this, please contact us through our [Help center](https://help.openai.com) and describe your use case.\n echo:\n type: boolean\n default: false\n nullable: true\n description: &completions_echo_description >\n Echo back the prompt in addition to the completion\n stop:\n description: &completions_stop_description >\n Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.\n default: null\n nullable: true\n oneOf:\n - type: string\n default: <|endoftext|>\n example: \"\\n\"\n nullable: true\n - type: array\n minItems: 1\n maxItems: 4\n items:\n type: string\n example: '[\"\\n\"]'\n presence_penalty:\n type: number\n default: 0\n minimum: -2\n maximum: 2\n nullable: true\n description: &completions_presence_penalty_description |\n Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.\n\n [See more information about frequency and presence penalties.](/docs/api-reference/parameter-details)\n frequency_penalty:\n type: number\n default: 0\n minimum: -2\n maximum: 2\n nullable: true\n description: &completions_frequency_penalty_description |\n Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.\n\n [See more information about frequency and presence penalties.](/docs/api-reference/parameter-details)\n best_of:\n type: integer\n default: 1\n minimum: 0\n maximum: 20\n nullable: true\n description: &completions_best_of_description |\n Generates `best_of` completions server-side and returns the \"best\" (the one with the highest log probability per token). Results cannot be streamed.\n\n When used with `n`, `best_of` controls the number of candidate completions and `n` specifies how many to return – `best_of` must be greater than `n`.\n\n **Note:** Because this parameter generates many completions, it can quickly consume your token quota. Use carefully and ensure that you have reasonable settings for `max_tokens` and `stop`.\n logit_bias: &completions_logit_bias\n type: object\n x-oaiTypeLabel: map\n default: null\n nullable: true\n description: &completions_logit_bias_description |\n Modify the likelihood of specified tokens appearing in the completion.\n\n Accepts a json object that maps tokens (specified by their token ID in the GPT tokenizer) to an associated bias value from -100 to 100. You can use this [tokenizer tool](/tokenizer?view=bpe) (which works for both GPT-2 and GPT-3) to convert text to token IDs. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.\n\n As an example, you can pass `{\"50256\": -100}` to prevent the <|endoftext|> token from being generated.\n user: &end_user_param_configuration\n type: string\n example: user-1234\n description: |\n A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. [Learn more](/docs/guides/safety-best-practices/end-user-ids).\n required:\n - model\n \n CreateCompletionResponse:\n type: object\n properties:\n id:\n type: string\n object:\n type: string\n created:\n type: integer\n model:\n type: string\n choices:\n type: array\n items:\n type: object\n properties:\n text:\n type: string\n index:\n type: integer\n logprobs:\n type: object\n nullable: true\n properties:\n tokens:\n type: array\n items:\n type: string\n token_logprobs:\n type: array\n items:\n type: number\n top_logprobs:\n type: array\n items:\n type: object\n text_offset:\n type: array\n items:\n type: integer\n finish_reason:\n type: string\n usage:\n type: object\n properties:\n prompt_tokens:\n type: integer\n completion_tokens:\n type: integer\n total_tokens:\n type: integer\n required: \n - prompt_tokens\n - completion_tokens\n - total_tokens\n required: \n - id\n - object\n - created\n - model\n - choices\n\n ChatCompletionRequestMessage:\n type: object\n properties:\n role:\n type: string\n enum: [\"system\", \"user\", \"assistant\"]\n description: The role of the author of this message.\n content:\n type: string\n description: The contents of the message\n name:\n type: string\n description: The name of the user in a multi-user chat\n required: \n - role\n - content\n\n ChatCompletionResponseMessage:\n type: object\n properties:\n role:\n type: string\n enum: [\"system\", \"user\", \"assistant\"]\n description: The role of the author of this message.\n content:\n type: string\n description: The contents of the message\n required: \n - role\n - content\n\n CreateChatCompletionRequest:\n type: object\n properties:\n model:\n description: ID of the model to use. Currently, only `gpt-3.5-turbo` and `gpt-3.5-turbo-0301` are supported.\n type: string\n messages:\n description: The messages to generate chat completions for, in the [chat format](/docs/guides/chat/introduction).\n type: array\n minItems: 1\n items:\n $ref: '#/components/schemas/ChatCompletionRequestMessage'\n temperature:\n type: number\n minimum: 0\n maximum: 2\n default: 1\n example: 1\n nullable: true\n description: *completions_temperature_description\n top_p:\n type: number\n minimum: 0\n maximum: 1\n default: 1\n example: 1\n nullable: true\n description: *completions_top_p_description\n n:\n type: integer\n minimum: 1\n maximum: 128\n default: 1\n example: 1\n nullable: true\n description: How many chat completion choices to generate for each input message.\n stream:\n description: >\n If set, partial message deltas will be sent, like in ChatGPT. Tokens will be sent as data-only [server-sent events](https://developer.mozilla.org/en-US/docs/Web/API/Server-sent_events/Using_server-sent_events#Event_stream_format)\n as they become available, with the stream terminated by a `data: [DONE]` message.\n type: boolean\n nullable: true\n default: false\n stop:\n description: |\n Up to 4 sequences where the API will stop generating further tokens.\n default: null\n oneOf:\n - type: string\n nullable: true\n - type: array\n minItems: 1\n maxItems: 4\n items:\n type: string\n max_tokens:\n description: |\n The maximum number of tokens allowed for the generated answer. By default, the number of tokens the model can return will be (4096 - prompt tokens).\n default: inf\n type: integer\n presence_penalty:\n type: number\n default: 0\n minimum: -2\n maximum: 2\n nullable: true\n description: *completions_presence_penalty_description\n frequency_penalty:\n type: number\n default: 0\n minimum: -2\n maximum: 2\n nullable: true\n description: *completions_frequency_penalty_description\n logit_bias:\n type: object\n x-oaiTypeLabel: map\n default: null\n nullable: true\n description: |\n Modify the likelihood of specified tokens appearing in the completion.\n\n Accepts a json object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.\n user: *end_user_param_configuration\n required:\n - model\n - messages\n\n CreateChatCompletionResponse:\n type: object\n properties:\n id:\n type: string\n object:\n type: string\n created:\n type: integer\n model:\n type: string\n choices:\n type: array\n items:\n type: object\n properties:\n index:\n type: integer\n message:\n $ref: '#/components/schemas/ChatCompletionResponseMessage'\n finish_reason:\n type: string\n usage:\n type: object\n properties:\n prompt_tokens:\n type: integer\n completion_tokens:\n type: integer\n total_tokens:\n type: integer\n required: \n - prompt_tokens\n - completion_tokens\n - total_tokens\n required: \n - id\n - object\n - created\n - model\n - choices\n\n CreateEditRequest:\n type: object\n properties:\n model:\n description: ID of the model to use. You can use the `text-davinci-edit-001` or `code-davinci-edit-001` model with this endpoint.\n type: string\n input:\n description:\n The input text to use as a starting point for the edit.\n type: string\n default: ''\n nullable: true\n example: \"What day of the wek is it?\"\n instruction:\n description:\n The instruction that tells the model how to edit the prompt.\n type: string\n example: \"Fix the spelling mistakes.\"\n n:\n type: integer\n minimum: 1\n maximum: 20\n default: 1\n example: 1\n nullable: true\n description:\n How many edits to generate for the input and instruction.\n temperature:\n type: number\n minimum: 0\n maximum: 2\n default: 1\n example: 1\n nullable: true\n description: *completions_temperature_description\n top_p:\n type: number\n minimum: 0\n maximum: 1\n default: 1\n example: 1\n nullable: true\n description: *completions_top_p_description\n required:\n - model\n - instruction\n\n CreateEditResponse:\n type: object\n properties:\n object:\n type: string\n created:\n type: integer\n choices:\n type: array\n items:\n type: object\n properties:\n text:\n type: string\n index:\n type: integer\n logprobs:\n type: object\n nullable: true\n properties:\n tokens:\n type: array\n items:\n type: string\n token_logprobs:\n type: array\n items:\n type: number\n top_logprobs:\n type: array\n items:\n type: object\n text_offset:\n type: array\n items:\n type: integer\n finish_reason:\n type: string\n usage:\n type: object\n properties:\n prompt_tokens:\n type: integer\n completion_tokens:\n type: integer\n total_tokens:\n type: integer\n required: \n - prompt_tokens\n - completion_tokens\n - total_tokens\n required: \n - object\n - created\n - choices\n - usage\n\n CreateImageRequest:\n type: object\n properties:\n prompt:\n description: A text description of the desired image(s). The maximum length is 1000 characters.\n type: string\n example: \"A cute baby sea otter\"\n n: &images_n\n type: integer\n minimum: 1\n maximum: 10\n default: 1\n example: 1\n nullable: true\n description: The number of images to generate. Must be between 1 and 10.\n size: &images_size\n type: string\n enum: [\"256x256\", \"512x512\", \"1024x1024\"]\n default: \"1024x1024\"\n example: \"1024x1024\"\n nullable: true\n description: The size of the generated images. Must be one of `256x256`, `512x512`, or `1024x1024`.\n response_format: &images_response_format\n type: string\n enum: [\"url\", \"b64_json\"]\n default: \"url\"\n example: \"url\"\n nullable: true\n description: The format in which the generated images are returned. Must be one of `url` or `b64_json`.\n user: *end_user_param_configuration\n required:\n - prompt\n\n ImagesResponse:\n properties:\n created:\n type: integer\n data:\n type: array\n items:\n type: object\n properties:\n url:\n type: string\n b64_json:\n type: string\n required:\n - created\n - data\n\n CreateImageEditRequest:\n type: object\n properties:\n image:\n description: The image to edit. Must be a valid PNG file, less than 4MB, and square. If mask is not provided, image must have transparency, which will be used as the mask.\n type: string\n format: binary\n mask:\n description: An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where `image` should be edited. Must be a valid PNG file, less than 4MB, and have the same dimensions as `image`.\n type: string\n format: binary\n prompt:\n description: A text description of the desired image(s). The maximum length is 1000 characters.\n type: string\n example: \"A cute baby sea otter wearing a beret\"\n n: *images_n\n size: *images_size\n response_format: *images_response_format\n user: *end_user_param_configuration\n required:\n - prompt\n - image\n\n CreateImageVariationRequest:\n type: object\n properties:\n image:\n description: The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and square.\n type: string\n format: binary\n n: *images_n\n size: *images_size\n response_format: *images_response_format\n user: *end_user_param_configuration\n required:\n - image\n\n CreateModerationRequest:\n type: object\n properties:\n input:\n description: The input text to classify\n oneOf:\n - type: string\n default: ''\n example: \"I want to kill them.\"\n - type: array\n items:\n type: string\n default: ''\n example: \"I want to kill them.\"\n model:\n description: |\n Two content moderations models are available: `text-moderation-stable` and `text-moderation-latest`.\n\n The default is `text-moderation-latest` which will be automatically upgraded over time. This ensures you are always using our most accurate model. If you use `text-moderation-stable`, we will provide advanced notice before updating the model. Accuracy of `text-moderation-stable` may be slightly lower than for `text-moderation-latest`.\n type: string\n nullable: false\n default: \"text-moderation-latest\"\n example: \"text-moderation-stable\"\n required:\n - input\n\n CreateModerationResponse:\n type: object\n properties:\n id:\n type: string\n model:\n type: string\n results:\n type: array\n items:\n type: object\n properties:\n flagged:\n type: boolean\n categories:\n type: object\n properties:\n hate:\n type: boolean\n hate/threatening:\n type: boolean\n self-harm:\n type: boolean\n sexual:\n type: boolean\n sexual/minors:\n type: boolean\n violence:\n type: boolean\n violence/graphic:\n type: boolean\n required: \n - hate\n - hate/threatening\n - self-harm\n - sexual\n - sexual/minors\n - violence\n - violence/graphic\n category_scores:\n type: object\n properties:\n hate:\n type: number\n hate/threatening:\n type: number\n self-harm:\n type: number\n sexual:\n type: number\n sexual/minors:\n type: number\n violence:\n type: number\n violence/graphic:\n type: number\n required: \n - hate\n - hate/threatening\n - self-harm\n - sexual\n - sexual/minors\n - violence\n - violence/graphic\n required: \n - flagged\n - categories\n - category_scores\n required: \n - id\n - model\n - results\n\n CreateSearchRequest:\n type: object\n properties:\n query:\n description: Query to search against the documents.\n type: string\n example: \"the president\"\n minLength: 1\n documents:\n description: |\n Up to 200 documents to search over, provided as a list of strings.\n\n The maximum document length (in tokens) is 2034 minus the number of tokens in the query.\n\n You should specify either `documents` or a `file`, but not both.\n type: array\n minItems: 1\n maxItems: 200\n items:\n type: string\n nullable: true\n example: \"['White House', 'hospital', 'school']\"\n file:\n description: |\n The ID of an uploaded file that contains documents to search over.\n\n You should specify either `documents` or a `file`, but not both.\n type: string\n nullable: true\n max_rerank:\n description: |\n The maximum number of documents to be re-ranked and returned by search.\n\n This flag only takes effect when `file` is set.\n type: integer\n minimum: 1\n default: 200\n nullable: true\n return_metadata: &return_metadata_configuration\n description: |\n A special boolean flag for showing metadata. If set to `true`, each document entry in the returned JSON will contain a \"metadata\" field.\n\n This flag only takes effect when `file` is set.\n type: boolean\n default: false\n nullable: true\n user: *end_user_param_configuration\n required:\n - query\n\n CreateSearchResponse:\n type: object\n properties:\n object:\n type: string\n model:\n type: string\n data:\n type: array\n items:\n type: object\n properties:\n object:\n type: string\n document:\n type: integer\n score:\n type: number\n\n ListFilesResponse:\n type: object\n properties:\n object:\n type: string\n data:\n type: array\n items:\n $ref: '#/components/schemas/OpenAIFile'\n required: \n - object\n - data\n\n CreateFileRequest:\n type: object\n additionalProperties: false\n properties:\n file:\n description: |\n Name of the [JSON Lines](https://jsonlines.readthedocs.io/en/latest/) file to be uploaded.\n\n If the `purpose` is set to \"fine-tune\", each line is a JSON record with \"prompt\" and \"completion\" fields representing your [training examples](/docs/guides/fine-tuning/prepare-training-data).\n type: string\n format: binary\n purpose:\n description: |\n The intended purpose of the uploaded documents.\n\n Use \"fine-tune\" for [Fine-tuning](/docs/api-reference/fine-tunes). This allows us to validate the format of the uploaded file.\n\n type: string\n required:\n - file\n - purpose\n\n DeleteFileResponse:\n type: object\n properties:\n id:\n type: string\n object:\n type: string\n deleted:\n type: boolean\n required: \n - id\n - object\n - deleted\n\n CreateAnswerRequest:\n type: object\n additionalProperties: false\n properties:\n model:\n description: ID of the model to use for completion. You can select one of `ada`, `babbage`, `curie`, or `davinci`.\n type: string\n question:\n description: Question to get answered.\n type: string\n minLength: 1\n example: \"What is the capital of Japan?\"\n examples:\n description: List of (question, answer) pairs that will help steer the model towards the tone and answer format you'd like. We recommend adding 2 to 3 examples.\n type: array\n minItems: 1\n maxItems: 200\n items:\n type: array\n minItems: 2\n maxItems: 2\n items:\n type: string\n minLength: 1\n example: \"[['What is the capital of Canada?', 'Ottawa'], ['Which province is Ottawa in?', 'Ontario']]\"\n examples_context:\n description: A text snippet containing the contextual information used to generate the answers for the `examples` you provide.\n type: string\n example: \"Ottawa, Canada's capital, is located in the east of southern Ontario, near the city of Montréal and the U.S. border.\"\n documents:\n description: |\n List of documents from which the answer for the input `question` should be derived. If this is an empty list, the question will be answered based on the question-answer examples.\n\n You should specify either `documents` or a `file`, but not both.\n type: array\n maxItems: 200\n items:\n type: string\n example: \"['Japan is an island country in East Asia, located in the northwest Pacific Ocean.', 'Tokyo is the capital and most populous prefecture of Japan.']\"\n nullable: true\n file:\n description: |\n The ID of an uploaded file that contains documents to search over. See [upload file](/docs/api-reference/files/upload) for how to upload a file of the desired format and purpose.\n\n You should specify either `documents` or a `file`, but not both.\n type: string\n nullable: true\n search_model: &search_model_configuration\n description: ID of the model to use for [Search](/docs/api-reference/searches/create). You can select one of `ada`, `babbage`, `curie`, or `davinci`.\n type: string\n default: ada\n nullable: true\n max_rerank:\n description: The maximum number of documents to be ranked by [Search](/docs/api-reference/searches/create) when using `file`. Setting it to a higher value leads to improved accuracy but with increased latency and cost.\n type: integer\n default: 200\n nullable: true\n temperature:\n description: What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n type: number\n default: 0\n nullable: true\n logprobs: &context_completions_logprobs_configuration\n type: integer\n minimum: 0\n maximum: 5\n default: null\n nullable: true\n description: |\n Include the log probabilities on the `logprobs` most likely tokens, as well the chosen tokens. For example, if `logprobs` is 5, the API will return a list of the 5 most likely tokens. The API will always return the `logprob` of the sampled token, so there may be up to `logprobs+1` elements in the response.\n\n The maximum value for `logprobs` is 5. If you need more than this, please contact us through our [Help center](https://help.openai.com) and describe your use case.\n\n When `logprobs` is set, `completion` will be automatically added into `expand` to get the logprobs.\n max_tokens:\n description: The maximum number of tokens allowed for the generated answer\n type: integer\n default: 16\n nullable: true\n stop:\n description: *completions_stop_description\n default: null\n oneOf:\n - type: string\n default: <|endoftext|>\n example: \"\\n\"\n - type: array\n minItems: 1\n maxItems: 4\n items:\n type: string\n example: '[\"\\n\"]'\n nullable: true\n n:\n description: How many answers to generate for each question.\n type: integer\n minimum: 1\n maximum: 10\n default: 1\n nullable: true\n logit_bias: *completions_logit_bias\n return_metadata: *return_metadata_configuration\n return_prompt: &return_prompt_configuration\n description: If set to `true`, the returned JSON will include a \"prompt\" field containing the final prompt that was used to request a completion. This is mainly useful for debugging purposes.\n type: boolean\n default: false\n nullable: true\n expand: &expand_configuration\n description: If an object name is in the list, we provide the full information of the object; otherwise, we only provide the object ID. Currently we support `completion` and `file` objects for expansion.\n type: array\n items: {}\n nullable: true\n default: []\n user: *end_user_param_configuration\n required:\n - model\n - question\n - examples\n - examples_context\n\n CreateAnswerResponse:\n type: object\n properties:\n object:\n type: string\n model:\n type: string\n search_model:\n type: string\n completion:\n type: string\n answers:\n type: array\n items:\n type: string\n selected_documents:\n type: array\n items:\n type: object\n properties:\n document:\n type: integer\n text:\n type: string\n\n CreateClassificationRequest:\n type: object\n additionalProperties: false\n properties:\n model: *model_configuration\n query:\n description: Query to be classified.\n type: string\n minLength: 1\n example: \"The plot is not very attractive.\"\n examples:\n description: |\n A list of examples with labels, in the following format:\n\n `[[\"The movie is so interesting.\", \"Positive\"], [\"It is quite boring.\", \"Negative\"], ...]`\n\n All the label strings will be normalized to be capitalized.\n\n You should specify either `examples` or `file`, but not both.\n type: array\n minItems: 2\n maxItems: 200\n items:\n type: array\n minItems: 2\n maxItems: 2\n items:\n type: string\n minLength: 1\n example: \"[['Do not see this film.', 'Negative'], ['Smart, provocative and blisteringly funny.', 'Positive']]\"\n nullable: true\n file:\n description: |\n The ID of the uploaded file that contains training examples. See [upload file](/docs/api-reference/files/upload) for how to upload a file of the desired format and purpose.\n\n You should specify either `examples` or `file`, but not both.\n type: string\n nullable: true\n labels:\n description: The set of categories being classified. If not specified, candidate labels will be automatically collected from the examples you provide. All the label strings will be normalized to be capitalized.\n type: array\n minItems: 2\n maxItems: 200\n default: null\n items:\n type: string\n example: [\"Positive\", \"Negative\"]\n nullable: true\n search_model: *search_model_configuration\n temperature:\n description:\n What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.\n type: number\n minimum: 0\n maximum: 2\n default: 0\n nullable: true\n example: 0\n logprobs: *context_completions_logprobs_configuration\n max_examples:\n description: The maximum number of examples to be ranked by [Search](/docs/api-reference/searches/create) when using `file`. Setting it to a higher value leads to improved accuracy but with increased latency and cost.\n type: integer\n default: 200\n nullable: true\n logit_bias: *completions_logit_bias\n return_prompt: *return_prompt_configuration\n return_metadata: *return_metadata_configuration\n expand: *expand_configuration\n user: *end_user_param_configuration\n required:\n - model\n - query\n\n CreateClassificationResponse:\n type: object\n properties:\n object:\n type: string\n model:\n type: string\n search_model:\n type: string\n completion:\n type: string\n label:\n type: string\n selected_examples:\n type: array\n items:\n type: object\n properties:\n document:\n type: integer\n text:\n type: string\n label:\n type: string\n\n CreateFineTuneRequest:\n type: object\n properties:\n training_file:\n description: |\n The ID of an uploaded file that contains training data.\n\n See [upload file](/docs/api-reference/files/upload) for how to upload a file.\n\n Your dataset must be formatted as a JSONL file, where each training\n example is a JSON object with the keys \"prompt\" and \"completion\".\n Additionally, you must upload your file with the purpose `fine-tune`.\n\n See the [fine-tuning guide](/docs/guides/fine-tuning/creating-training-data) for more details.\n type: string\n example: \"file-ajSREls59WBbvgSzJSVWxMCB\"\n validation_file:\n description: |\n The ID of an uploaded file that contains validation data.\n\n If you provide this file, the data is used to generate validation\n metrics periodically during fine-tuning. These metrics can be viewed in\n the [fine-tuning results file](/docs/guides/fine-tuning/analyzing-your-fine-tuned-model).\n Your train and validation data should be mutually exclusive.\n\n Your dataset must be formatted as a JSONL file, where each validation\n example is a JSON object with the keys \"prompt\" and \"completion\".\n Additionally, you must upload your file with the purpose `fine-tune`.\n\n See the [fine-tuning guide](/docs/guides/fine-tuning/creating-training-data) for more details.\n type: string\n nullable: true\n example: \"file-XjSREls59WBbvgSzJSVWxMCa\"\n model:\n description: |\n The name of the base model to fine-tune. You can select one of \"ada\",\n \"babbage\", \"curie\", \"davinci\", or a fine-tuned model created after 2022-04-21.\n To learn more about these models, see the\n [Models](https://platform.openai.com/docs/models) documentation.\n default: \"curie\"\n type: string\n nullable: true\n n_epochs:\n description: |\n The number of epochs to train the model for. An epoch refers to one\n full cycle through the training dataset.\n default: 4\n type: integer\n nullable: true\n batch_size:\n description: |\n The batch size to use for training. The batch size is the number of\n training examples used to train a single forward and backward pass.\n\n By default, the batch size will be dynamically configured to be\n ~0.2% of the number of examples in the training set, capped at 256 -\n in general, we've found that larger batch sizes tend to work better\n for larger datasets.\n default: null\n type: integer\n nullable: true\n learning_rate_multiplier:\n description: |\n The learning rate multiplier to use for training.\n The fine-tuning learning rate is the original learning rate used for\n pretraining multiplied by this value.\n\n By default, the learning rate multiplier is the 0.05, 0.1, or 0.2\n depending on final `batch_size` (larger learning rates tend to\n perform better with larger batch sizes). We recommend experimenting\n with values in the range 0.02 to 0.2 to see what produces the best\n results.\n default: null\n type: number\n nullable: true\n prompt_loss_weight:\n description: |\n The weight to use for loss on the prompt tokens. This controls how\n much the model tries to learn to generate the prompt (as compared\n to the completion which always has a weight of 1.0), and can add\n a stabilizing effect to training when completions are short.\n\n If prompts are extremely long (relative to completions), it may make\n sense to reduce this weight so as to avoid over-prioritizing\n learning the prompt.\n default: 0.01\n type: number\n nullable: true\n compute_classification_metrics:\n description: |\n If set, we calculate classification-specific metrics such as accuracy\n and F-1 score using the validation set at the end of every epoch.\n These metrics can be viewed in the [results file](/docs/guides/fine-tuning/analyzing-your-fine-tuned-model).\n\n In order to compute classification metrics, you must provide a\n `validation_file`. Additionally, you must\n specify `classification_n_classes` for multiclass classification or\n `classification_positive_class` for binary classification.\n type: boolean\n default: false\n nullable: true\n classification_n_classes:\n description: |\n The number of classes in a classification task.\n\n This parameter is required for multiclass classification.\n type: integer\n default: null\n nullable: true\n classification_positive_class:\n description: |\n The positive class in binary classification.\n\n This parameter is needed to generate precision, recall, and F1\n metrics when doing binary classification.\n type: string\n default: null\n nullable: true\n classification_betas:\n description: |\n If this is provided, we calculate F-beta scores at the specified\n beta values. The F-beta score is a generalization of F-1 score.\n This is only used for binary classification.\n\n With a beta of 1 (i.e. the F-1 score), precision and recall are\n given the same weight. A larger beta score puts more weight on\n recall and less on precision. A smaller beta score puts more weight\n on precision and less on recall.\n type: array\n items:\n type: number\n example: [0.6, 1, 1.5, 2]\n default: null\n nullable: true\n suffix:\n description: |\n A string of up to 40 characters that will be added to your fine-tuned model name.\n\n For example, a `suffix` of \"custom-model-name\" would produce a model name like `ada:ft-your-org:custom-model-name-2022-02-15-04-21-04`.\n type: string\n minLength: 1\n maxLength: 40\n default: null\n nullable: true\n required:\n - training_file\n\n ListFineTunesResponse:\n type: object\n properties:\n object:\n type: string\n data:\n type: array\n items:\n $ref: '#/components/schemas/FineTune'\n required: \n - object\n - data\n\n ListFineTuneEventsResponse:\n type: object\n properties:\n object:\n type: string\n data:\n type: array\n items:\n $ref: '#/components/schemas/FineTuneEvent'\n required: \n - object\n - data\n\n CreateEmbeddingRequest:\n type: object\n additionalProperties: false\n properties:\n model: *model_configuration\n input:\n description: |\n Input text to get embeddings for, encoded as a string or array of tokens. To get embeddings for multiple inputs in a single request, pass an array of strings or array of token arrays. Each input must not exceed 8192 tokens in length.\n example: \"The quick brown fox jumped over the lazy dog\"\n oneOf:\n - type: string\n default: ''\n example: \"This is a test.\"\n - type: array\n items:\n type: string\n default: ''\n example: \"This is a test.\"\n - type: array\n minItems: 1\n items:\n type: integer\n example: \"[1212, 318, 257, 1332, 13]\"\n - type: array\n minItems: 1\n items:\n type: array\n minItems: 1\n items:\n type: integer\n example: \"[[1212, 318, 257, 1332, 13]]\"\n user: *end_user_param_configuration\n required:\n - model\n - input\n\n CreateEmbeddingResponse:\n type: object\n properties:\n object:\n type: string\n model:\n type: string\n data:\n type: array\n items:\n type: object\n properties:\n index:\n type: integer\n object:\n type: string\n embedding:\n type: array\n items:\n type: number\n required: \n - index\n - object\n - embedding\n usage:\n type: object\n properties:\n prompt_tokens:\n type: integer\n total_tokens:\n type: integer\n required: \n - prompt_tokens\n - total_tokens\n required: \n - object\n - model\n - data\n - usage\n\n CreateTranscriptionRequest:\n type: object\n additionalProperties: false\n properties:\n file: \n description: |\n The audio file to transcribe, in one of these formats: mp3, mp4, mpeg, mpga, m4a, wav, or webm.\n type: string\n format: binary\n model: \n description: |\n ID of the model to use. Only `whisper-1` is currently available.\n type: string\n prompt:\n description: |\n An optional text to guide the model's style or continue a previous audio segment. The [prompt](/docs/guides/speech-to-text/prompting) should match the audio language.\n type: string\n response_format:\n description: |\n The format of the transcript output, in one of these options: json, text, srt, verbose_json, or vtt.\n type: string\n default: json\n temperature:\n description: |\n The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically increase the temperature until certain thresholds are hit.\n type: number\n default: 0\n language:\n description: |\n The language of the input audio. Supplying the input language in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) format will improve accuracy and latency.\n type: string\n required:\n - file\n - model\n\n # Note: This does not currently support the non-default response format types. \n CreateTranscriptionResponse:\n type: object\n properties:\n text:\n type: string\n required: \n - text\n\n CreateTranslationRequest:\n type: object\n additionalProperties: false\n properties:\n file: \n description: |\n The audio file to translate, in one of these formats: mp3, mp4, mpeg, mpga, m4a, wav, or webm.\n type: string\n format: binary\n model: \n description: |\n ID of the model to use. Only `whisper-1` is currently available.\n type: string\n prompt:\n description: |\n An optional text to guide the model's style or continue a previous audio segment. The [prompt](/docs/guides/speech-to-text/prompting) should be in English.\n type: string\n response_format:\n description: |\n The format of the transcript output, in one of these options: json, text, srt, verbose_json, or vtt.\n type: string\n default: json\n temperature:\n description: |\n The sampling temperature, between 0 and 1. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. If set to 0, the model will use [log probability](https://en.wikipedia.org/wiki/Log_probability) to automatically increase the temperature until certain thresholds are hit.\n type: number\n default: 0\n required:\n - file\n - model\n\n # Note: This does not currently support the non-default response format types. \n CreateTranslationResponse:\n type: object\n properties:\n text:\n type: string\n required: \n - text\n\n Engine:\n title: Engine\n properties:\n id:\n type: string\n object:\n type: string\n created:\n type: integer\n nullable: true\n ready:\n type: boolean\n required: \n - id\n - object\n - created\n - ready\n\n Model:\n title: Model\n properties:\n id:\n type: string\n object:\n type: string\n created:\n type: integer\n owned_by:\n type: string\n required: \n - id\n - object\n - created\n - owned_by\n\n OpenAIFile:\n title: OpenAIFile\n properties:\n id:\n type: string\n object:\n type: string\n bytes:\n type: integer\n created_at:\n type: integer\n filename:\n type: string\n purpose:\n type: string\n status:\n type: string\n status_details:\n type: object\n nullable: true\n required: \n - id\n - object\n - bytes\n - created_at\n - filename\n - purpose\n\n FineTune:\n title: FineTune\n properties:\n id:\n type: string\n object:\n type: string\n created_at:\n type: integer\n updated_at:\n type: integer\n model:\n type: string\n fine_tuned_model:\n type: string\n nullable: true\n organization_id:\n type: string\n status:\n type: string\n hyperparams:\n type: object\n training_files:\n type: array\n items:\n $ref: '#/components/schemas/OpenAIFile'\n validation_files:\n type: array\n items:\n $ref: '#/components/schemas/OpenAIFile'\n result_files:\n type: array\n items:\n $ref: '#/components/schemas/OpenAIFile'\n events:\n type: array\n items:\n $ref: '#/components/schemas/FineTuneEvent'\n required: \n - id\n - object\n - created_at\n - updated_at\n - model\n - fine_tuned_model\n - organization_id\n - status\n - hyperparams\n - training_files\n - validation_files\n - result_files\n\n FineTuneEvent:\n title: FineTuneEvent\n properties:\n object:\n type: string\n created_at:\n type: integer\n level:\n type: string\n message:\n type: string\n required: \n - object\n - created_at\n - level\n - message\n\nx-oaiMeta:\n groups:\n - id: models\n title: Models\n description: |\n List and describe the various models available in the API. You can refer to the [Models](/docs/models) documentation to understand what models are available and the differences between them.\n - id: completions\n title: Completions\n description: |\n Given a prompt, the model will return one or more predicted completions, and can also return the probabilities of alternative tokens at each position.\n - id: chat\n title: Chat\n description: |\n Given a chat conversation, the model will return a chat completion response.\n - id: edits\n title: Edits\n description: |\n Given a prompt and an instruction, the model will return an edited version of the prompt.\n - id: images\n title: Images\n description: |\n Given a prompt and/or an input image, the model will generate a new image.\n\n Related guide: [Image generation](/docs/guides/images)\n - id: embeddings\n title: Embeddings\n description: |\n Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms.\n\n Related guide: [Embeddings](/docs/guides/embeddings)\n - id: audio\n title: Audio\n description: |\n Learn how to turn audio into text.\n\n Related guide: [Speech to text](/docs/guides/speech-to-text)\n - id: files\n title: Files\n description: |\n Files are used to upload documents that can be used with features like [Fine-tuning](/docs/api-reference/fine-tunes).\n - id: fine-tunes\n title: Fine-tunes\n description: |\n Manage fine-tuning jobs to tailor a model to your specific training data.\n\n Related guide: [Fine-tune models](/docs/guides/fine-tuning)\n - id: moderations\n title: Moderations\n description: |\n Given a input text, outputs if the model classifies it as violating OpenAI's content policy.\n\n Related guide: [Moderations](/docs/guides/moderation)\n - id: searches\n title: Searches\n warning:\n title: This endpoint is deprecated and will be removed on December 3rd, 2022\n message: We’ve developed new methods with better performance. [Learn more](https://help.openai.com/en/articles/6272952-search-transition-guide).\n description: |\n Given a query and a set of documents or labels, the model ranks each document based on its semantic similarity to the provided query.\n\n Related guide: [Search](/docs/guides/search)\n - id: classifications\n title: Classifications\n warning:\n title: This endpoint is deprecated and will be removed on December 3rd, 2022\n message: We’ve developed new methods with better performance. [Learn more](https://help.openai.com/en/articles/6272941-classifications-transition-guide).\n description: |\n Given a query and a set of labeled examples, the model will predict the most likely label for the query. Useful as a drop-in replacement for any ML classification or text-to-label task.\n\n Related guide: [Classification](/docs/guides/classifications)\n - id: answers\n title: Answers\n warning:\n title: This endpoint is deprecated and will be removed on December 3rd, 2022\n message: We’ve developed new methods with better performance. [Learn more](https://help.openai.com/en/articles/6233728-answers-transition-guide).\n description: |\n Given a question, a set of documents, and some examples, the API generates an answer to the question based on the information in the set of documents. This is useful for question-answering applications on sources of truth, like company documentation or a knowledge base.\n\n Related guide: [Question answering](/docs/guides/answers)\n - id: engines\n title: Engines\n description: These endpoints describe and provide access to the various engines available in the API.\n warning:\n title: The Engines endpoints are deprecated.\n message: Please use their replacement, [Models](/docs/api-reference/models), instead. [Learn more](https://help.openai.com/TODO).\n",
7 | "url": "https://raw.githubusercontent.com/openai/openai-openapi/master/openapi.yaml",
8 | "output": null,
9 | "newLineBehavior": "Auto"
10 | }
11 | },
12 | "codeGenerators": {
13 | "openApiToCSharpClient": {
14 | "clientBaseClass": null,
15 | "configurationClass": null,
16 | "generateClientClasses": true,
17 | "generateClientInterfaces": false,
18 | "clientBaseInterface": null,
19 | "injectHttpClient": true,
20 | "disposeHttpClient": true,
21 | "protectedMethods": [],
22 | "generateExceptionClasses": true,
23 | "exceptionClass": "OpenAiApiException",
24 | "wrapDtoExceptions": true,
25 | "useHttpClientCreationMethod": false,
26 | "httpClientType": "System.Net.Http.HttpClient",
27 | "useHttpRequestMessageCreationMethod": false,
28 | "useBaseUrl": true,
29 | "generateBaseUrlProperty": true,
30 | "generateSyncMethods": true,
31 | "generatePrepareRequestAndProcessResponseAsAsyncMethods": false,
32 | "exposeJsonSerializerSettings": false,
33 | "clientClassAccessModifier": "public",
34 | "typeAccessModifier": "public",
35 | "generateContractsOutput": false,
36 | "contractsNamespace": null,
37 | "contractsOutputFilePath": null,
38 | "parameterDateTimeFormat": "s",
39 | "parameterDateFormat": "yyyy-MM-dd",
40 | "generateUpdateJsonSerializerSettingsMethod": true,
41 | "useRequestAndResponseSerializationSettings": false,
42 | "serializeTypeInformation": false,
43 | "queryNullValue": "",
44 | "className": "{controller}Client",
45 | "operationGenerationMode": "MultipleClientsFromOperationId",
46 | "additionalNamespaceUsages": [],
47 | "additionalContractNamespaceUsages": [],
48 | "generateOptionalParameters": true,
49 | "generateJsonMethods": false,
50 | "enforceFlagEnums": false,
51 | "parameterArrayType": "System.Collections.Generic.IEnumerable",
52 | "parameterDictionaryType": "System.Collections.Generic.IDictionary",
53 | "responseArrayType": "System.Collections.Generic.ICollection",
54 | "responseDictionaryType": "System.Collections.Generic.IDictionary",
55 | "wrapResponses": false,
56 | "wrapResponseMethods": [],
57 | "generateResponseClasses": true,
58 | "responseClass": "SwaggerResponse",
59 | "namespace": "OpenAI",
60 | "requiredPropertiesMustBeDefined": false,
61 | "dateType": "System.DateTimeOffset",
62 | "jsonConverters": null,
63 | "anyType": "object",
64 | "dateTimeType": "System.DateTimeOffset",
65 | "timeType": "System.TimeSpan",
66 | "timeSpanType": "System.TimeSpan",
67 | "arrayType": "System.Collections.Generic.ICollection",
68 | "arrayInstanceType": "System.Collections.ObjectModel.Collection",
69 | "dictionaryType": "System.Collections.Generic.IDictionary",
70 | "dictionaryInstanceType": "System.Collections.Generic.Dictionary",
71 | "arrayBaseType": "System.Collections.ObjectModel.Collection",
72 | "dictionaryBaseType": "System.Collections.Generic.Dictionary",
73 | "classStyle": "Record",
74 | "jsonLibrary": "SystemTextJson",
75 | "generateDefaultValues": true,
76 | "generateDataAnnotations": false,
77 | "excludedTypeNames": [],
78 | "excludedParameterNames": [],
79 | "handleReferences": false,
80 | "generateImmutableArrayProperties": false,
81 | "generateImmutableDictionaryProperties": false,
82 | "jsonSerializerSettingsTransformationMethod": null,
83 | "inlineNamedArrays": false,
84 | "inlineNamedDictionaries": false,
85 | "inlineNamedTuples": true,
86 | "inlineNamedAny": false,
87 | "generateDtoTypes": true,
88 | "generateOptionalPropertiesAsNullable": false,
89 | "generateNullableReferenceTypes": false,
90 | "templateDirectory": null,
91 | "typeNameGeneratorType": null,
92 | "propertyNameGeneratorType": null,
93 | "enumNameGeneratorType": null,
94 | "serviceHost": null,
95 | "serviceSchemes": null,
96 | "output": "OpenAI.cs",
97 | "newLineBehavior": "Auto"
98 | }
99 | }
100 | }
--------------------------------------------------------------------------------