mirror of https://github.com/microsoft/autogen.git
[.Net] Add AutoGen.AzureAIInference (#3332)
* add AutoGen.AzureAIInference * add tests * update readme * fix format
This commit is contained in:
Xiaoyun Zhang
GitHub
parent
5732b3e766
commit
4dab28c769
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@ -68,6 +68,12 @@ Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AutoGen.OpenAI.Sample", "sa
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AutoGen.WebAPI.Sample", "sample\AutoGen.WebAPI.Sample\AutoGen.WebAPI.Sample.csproj", "{12079C18-A519-403F-BBFD-200A36A0C083}"
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EndProject
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Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "AutoGen.AzureAIInference", "src\AutoGen.AzureAIInference\AutoGen.AzureAIInference.csproj", "{5C45981D-1319-4C25-935C-83D411CB28DF}"
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EndProject
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Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "AutoGen.AzureAIInference.Tests", "test\AutoGen.AzureAIInference.Tests\AutoGen.AzureAIInference.Tests.csproj", "{5970868F-831E-418F-89A9-4EC599563E16}"
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EndProject
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Project("{FAE04EC0-301F-11D3-BF4B-00C04F79EFBC}") = "AutoGen.Tests.Share", "test\AutoGen.Test.Share\AutoGen.Tests.Share.csproj", "{143725E2-206C-4D37-93E4-9EDF699826B2}"
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EndProject
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Global
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GlobalSection(SolutionConfigurationPlatforms) = preSolution
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Debug|Any CPU = Debug|Any CPU
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@ -194,6 +200,18 @@ Global
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{12079C18-A519-403F-BBFD-200A36A0C083}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{12079C18-A519-403F-BBFD-200A36A0C083}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{12079C18-A519-403F-BBFD-200A36A0C083}.Release|Any CPU.Build.0 = Release|Any CPU
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{5C45981D-1319-4C25-935C-83D411CB28DF}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{5C45981D-1319-4C25-935C-83D411CB28DF}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{5C45981D-1319-4C25-935C-83D411CB28DF}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{5C45981D-1319-4C25-935C-83D411CB28DF}.Release|Any CPU.Build.0 = Release|Any CPU
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{5970868F-831E-418F-89A9-4EC599563E16}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{5970868F-831E-418F-89A9-4EC599563E16}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{5970868F-831E-418F-89A9-4EC599563E16}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{5970868F-831E-418F-89A9-4EC599563E16}.Release|Any CPU.Build.0 = Release|Any CPU
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{143725E2-206C-4D37-93E4-9EDF699826B2}.Debug|Any CPU.ActiveCfg = Debug|Any CPU
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{143725E2-206C-4D37-93E4-9EDF699826B2}.Debug|Any CPU.Build.0 = Debug|Any CPU
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{143725E2-206C-4D37-93E4-9EDF699826B2}.Release|Any CPU.ActiveCfg = Release|Any CPU
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{143725E2-206C-4D37-93E4-9EDF699826B2}.Release|Any CPU.Build.0 = Release|Any CPU
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EndGlobalSection
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GlobalSection(SolutionProperties) = preSolution
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HideSolutionNode = FALSE
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@ -229,6 +247,9 @@ Global
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{6B82F26D-5040-4453-B21B-C8D1F913CE4C} = {F823671B-3ECA-4AE6-86DA-25E920D3FE64}
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{0E635268-351C-4A6B-A28D-593D868C2CA4} = {FBFEAD1F-29EB-4D99-A672-0CD8473E10B9}
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{12079C18-A519-403F-BBFD-200A36A0C083} = {FBFEAD1F-29EB-4D99-A672-0CD8473E10B9}
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{5C45981D-1319-4C25-935C-83D411CB28DF} = {18BF8DD7-0585-48BF-8F97-AD333080CE06}
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{5970868F-831E-418F-89A9-4EC599563E16} = {F823671B-3ECA-4AE6-86DA-25E920D3FE64}
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{143725E2-206C-4D37-93E4-9EDF699826B2} = {F823671B-3ECA-4AE6-86DA-25E920D3FE64}
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EndGlobalSection
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GlobalSection(ExtensibilityGlobals) = postSolution
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SolutionGuid = {93384647-528D-46C8-922C-8DB36A382F0B}
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@ -15,6 +15,7 @@
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<MicrosoftASPNETCoreVersion>8.0.4</MicrosoftASPNETCoreVersion>
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<GoogleCloudAPIPlatformVersion>3.0.0</GoogleCloudAPIPlatformVersion>
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<JsonSchemaVersion>4.3.0.2</JsonSchemaVersion>
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<AzureAIInferenceVersion>1.0.0-beta.1</AzureAIInferenceVersion>
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<PowershellSDKVersion>7.4.4</PowershellSDKVersion>
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</PropertyGroup>
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</Project>
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@ -0,0 +1,202 @@
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// ChatCompletionsClientAgent.cs
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Runtime.CompilerServices;
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using System.Text.Json;
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using System.Threading;
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using System.Threading.Tasks;
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using AutoGen.AzureAIInference.Extension;
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using AutoGen.Core;
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using Azure.AI.Inference;
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namespace AutoGen.AzureAIInference;
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/// <summary>
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/// ChatCompletions client agent. This agent is a thin wrapper around <see cref="ChatCompletionsClient"/> to provide a simple interface for chat completions.
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/// <para><see cref="ChatCompletionsClientAgent" /> supports the following message types:</para>
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/// <list type="bullet">
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/// <item>
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/// <see cref="MessageEnvelope{T}"/> where T is <see cref="ChatRequestMessage"/>: chat request message.
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/// </item>
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/// </list>
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/// <para><see cref="ChatCompletionsClientAgent" /> returns the following message types:</para>
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/// <list type="bullet">
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/// <item>
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/// <see cref="MessageEnvelope{T}"/> where T is <see cref="ChatResponseMessage"/>: chat response message.
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/// <see cref="MessageEnvelope{T}"/> where T is <see cref="StreamingChatCompletionsUpdate"/>: streaming chat completions update.
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/// </item>
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/// </list>
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/// </summary>
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public class ChatCompletionsClientAgent : IStreamingAgent
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{
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private readonly ChatCompletionsClient chatCompletionsClient;
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private readonly ChatCompletionsOptions options;
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private readonly string systemMessage;
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/// <summary>
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/// Create a new instance of <see cref="ChatCompletionsClientAgent"/>.
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/// </summary>
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/// <param name="chatCompletionsClient">chat completions client</param>
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/// <param name="name">agent name</param>
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/// <param name="modelName">model name. e.g. gpt-turbo-3.5</param>
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/// <param name="systemMessage">system message</param>
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/// <param name="temperature">temperature</param>
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/// <param name="maxTokens">max tokens to generated</param>
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/// <param name="responseFormat">response format, set it to <see cref="ChatCompletionsResponseFormatJSON"/> to enable json mode.</param>
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/// <param name="seed">seed to use, set it to enable deterministic output</param>
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/// <param name="functions">functions</param>
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public ChatCompletionsClientAgent(
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ChatCompletionsClient chatCompletionsClient,
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string name,
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string modelName,
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string systemMessage = "You are a helpful AI assistant",
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float temperature = 0.7f,
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int maxTokens = 1024,
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int? seed = null,
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ChatCompletionsResponseFormat? responseFormat = null,
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IEnumerable<FunctionDefinition>? functions = null)
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: this(
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chatCompletionsClient: chatCompletionsClient,
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name: name,
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options: CreateChatCompletionOptions(modelName, temperature, maxTokens, seed, responseFormat, functions),
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systemMessage: systemMessage)
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{
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}
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/// <summary>
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/// Create a new instance of <see cref="ChatCompletionsClientAgent"/>.
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/// </summary>
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/// <param name="chatCompletionsClient">chat completions client</param>
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/// <param name="name">agent name</param>
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/// <param name="systemMessage">system message</param>
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/// <param name="options">chat completion option. The option can't contain messages</param>
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public ChatCompletionsClientAgent(
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ChatCompletionsClient chatCompletionsClient,
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string name,
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ChatCompletionsOptions options,
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string systemMessage = "You are a helpful AI assistant")
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{
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if (options.Messages is { Count: > 0 })
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{
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throw new ArgumentException("Messages should not be provided in options");
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}
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this.chatCompletionsClient = chatCompletionsClient;
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this.Name = name;
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this.options = options;
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this.systemMessage = systemMessage;
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}
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public string Name { get; }
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public async Task<IMessage> GenerateReplyAsync(
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IEnumerable<IMessage> messages,
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GenerateReplyOptions? options = null,
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CancellationToken cancellationToken = default)
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{
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var settings = this.CreateChatCompletionsOptions(options, messages);
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var reply = await this.chatCompletionsClient.CompleteAsync(settings, cancellationToken: cancellationToken);
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return new MessageEnvelope<ChatCompletions>(reply, from: this.Name);
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}
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public async IAsyncEnumerable<IMessage> GenerateStreamingReplyAsync(
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IEnumerable<IMessage> messages,
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GenerateReplyOptions? options = null,
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[EnumeratorCancellation] CancellationToken cancellationToken = default)
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{
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var settings = this.CreateChatCompletionsOptions(options, messages);
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var response = await this.chatCompletionsClient.CompleteStreamingAsync(settings, cancellationToken);
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await foreach (var update in response.WithCancellation(cancellationToken))
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{
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yield return new MessageEnvelope<StreamingChatCompletionsUpdate>(update, from: this.Name);
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}
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}
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private ChatCompletionsOptions CreateChatCompletionsOptions(GenerateReplyOptions? options, IEnumerable<IMessage> messages)
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{
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var oaiMessages = messages.Select(m => m switch
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{
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IMessage<ChatRequestMessage> chatRequestMessage => chatRequestMessage.Content,
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_ => throw new ArgumentException("Invalid message type")
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});
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// add system message if there's no system message in messages
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if (!oaiMessages.Any(m => m is ChatRequestSystemMessage))
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{
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oaiMessages = new[] { new ChatRequestSystemMessage(systemMessage) }.Concat(oaiMessages);
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}
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// clone the options by serializing and deserializing
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var json = JsonSerializer.Serialize(this.options);
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var settings = JsonSerializer.Deserialize<ChatCompletionsOptions>(json) ?? throw new InvalidOperationException("Failed to clone options");
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foreach (var m in oaiMessages)
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{
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settings.Messages.Add(m);
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}
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settings.Temperature = options?.Temperature ?? settings.Temperature;
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settings.MaxTokens = options?.MaxToken ?? settings.MaxTokens;
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foreach (var functions in this.options.Tools)
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{
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settings.Tools.Add(functions);
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}
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foreach (var stopSequence in this.options.StopSequences)
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{
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settings.StopSequences.Add(stopSequence);
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}
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var openAIFunctionDefinitions = options?.Functions?.Select(f => f.ToAzureAIInferenceFunctionDefinition()).ToList();
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if (openAIFunctionDefinitions is { Count: > 0 })
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{
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foreach (var f in openAIFunctionDefinitions)
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{
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settings.Tools.Add(new ChatCompletionsFunctionToolDefinition(f));
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}
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}
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if (options?.StopSequence is var sequence && sequence is { Length: > 0 })
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{
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foreach (var seq in sequence)
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{
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settings.StopSequences.Add(seq);
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}
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}
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return settings;
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}
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private static ChatCompletionsOptions CreateChatCompletionOptions(
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string modelName,
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float temperature = 0.7f,
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int maxTokens = 1024,
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int? seed = null,
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ChatCompletionsResponseFormat? responseFormat = null,
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IEnumerable<FunctionDefinition>? functions = null)
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{
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var options = new ChatCompletionsOptions()
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{
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Model = modelName,
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Temperature = temperature,
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MaxTokens = maxTokens,
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Seed = seed,
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ResponseFormat = responseFormat,
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};
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if (functions is not null)
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{
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foreach (var f in functions)
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{
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options.Tools.Add(new ChatCompletionsFunctionToolDefinition(f));
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}
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}
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return options;
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}
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}
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@ -0,0 +1,25 @@
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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<TargetFrameworks>$(PackageTargetFrameworks)</TargetFrameworks>
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<RootNamespace>AutoGen.AzureAIInference</RootNamespace>
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</PropertyGroup>
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<Import Project="$(RepoRoot)/nuget/nuget-package.props" />
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<PropertyGroup>
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<!-- NuGet Package Settings -->
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<Title>AutoGen.AzureAIInference</Title>
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<Description>
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Azure AI Inference Intergration for AutoGen.
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</Description>
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</PropertyGroup>
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<ItemGroup>
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<PackageReference Include="Azure.AI.Inference" Version="$(AzureAIInferenceVersion)" />
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</ItemGroup>
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<ItemGroup>
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<ProjectReference Include="..\AutoGen.Core\AutoGen.Core.csproj" />
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</ItemGroup>
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</Project>
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@ -0,0 +1,39 @@
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// ChatComptionClientAgentExtension.cs
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using AutoGen.Core;
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namespace AutoGen.AzureAIInference.Extension;
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public static class ChatComptionClientAgentExtension
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{
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/// <summary>
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/// Register an <see cref="AzureAIInferenceChatRequestMessageConnector"/> to the <see cref="ChatCompletionsClientAgent"/>
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/// </summary>
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/// <param name="connector">the connector to use. If null, a new instance of <see cref="AzureAIInferenceChatRequestMessageConnector"/> will be created.</param>
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public static MiddlewareStreamingAgent<ChatCompletionsClientAgent> RegisterMessageConnector(
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this ChatCompletionsClientAgent agent, AzureAIInferenceChatRequestMessageConnector? connector = null)
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{
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if (connector == null)
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{
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connector = new AzureAIInferenceChatRequestMessageConnector();
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}
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return agent.RegisterStreamingMiddleware(connector);
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}
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/// <summary>
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/// Register an <see cref="AzureAIInferenceChatRequestMessageConnector"/> to the <see cref="MiddlewareAgent{T}"/> where T is <see cref="ChatCompletionsClientAgent"/>
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/// </summary>
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/// <param name="connector">the connector to use. If null, a new instance of <see cref="AzureAIInferenceChatRequestMessageConnector"/> will be created.</param>
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public static MiddlewareStreamingAgent<ChatCompletionsClientAgent> RegisterMessageConnector(
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this MiddlewareStreamingAgent<ChatCompletionsClientAgent> agent, AzureAIInferenceChatRequestMessageConnector? connector = null)
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{
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if (connector == null)
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{
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connector = new AzureAIInferenceChatRequestMessageConnector();
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}
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return agent.RegisterStreamingMiddleware(connector);
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}
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}
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@ -0,0 +1,64 @@
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// FunctionContractExtension.cs
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using System;
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using System.Collections.Generic;
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using AutoGen.Core;
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using Azure.AI.Inference;
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using Json.Schema;
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using Json.Schema.Generation;
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namespace AutoGen.AzureAIInference.Extension;
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public static class FunctionContractExtension
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{
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/// <summary>
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/// Convert a <see cref="FunctionContract"/> to a <see cref="FunctionDefinition"/> that can be used in gpt funciton call.
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/// </summary>
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/// <param name="functionContract">function contract</param>
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/// <returns><see cref="FunctionDefinition"/></returns>
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public static FunctionDefinition ToAzureAIInferenceFunctionDefinition(this FunctionContract functionContract)
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{
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var functionDefinition = new FunctionDefinition
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{
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Name = functionContract.Name,
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Description = functionContract.Description,
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};
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var requiredParameterNames = new List<string>();
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var propertiesSchemas = new Dictionary<string, JsonSchema>();
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var propertySchemaBuilder = new JsonSchemaBuilder().Type(SchemaValueType.Object);
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foreach (var param in functionContract.Parameters ?? [])
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{
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if (param.Name is null)
|
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{
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throw new InvalidOperationException("Parameter name cannot be null");
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}
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||||
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||||
var schemaBuilder = new JsonSchemaBuilder().FromType(param.ParameterType ?? throw new ArgumentNullException(nameof(param.ParameterType)));
|
||||
if (param.Description != null)
|
||||
{
|
||||
schemaBuilder = schemaBuilder.Description(param.Description);
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||||
}
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||||
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||||
if (param.IsRequired)
|
||||
{
|
||||
requiredParameterNames.Add(param.Name);
|
||||
}
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||||
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||||
var schema = schemaBuilder.Build();
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propertiesSchemas[param.Name] = schema;
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||||
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}
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||||
propertySchemaBuilder = propertySchemaBuilder.Properties(propertiesSchemas);
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propertySchemaBuilder = propertySchemaBuilder.Required(requiredParameterNames);
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var option = new System.Text.Json.JsonSerializerOptions()
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{
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PropertyNamingPolicy = System.Text.Json.JsonNamingPolicy.CamelCase
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};
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functionDefinition.Parameters = BinaryData.FromObjectAsJson(propertySchemaBuilder.Build(), option);
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return functionDefinition;
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}
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}
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@ -0,0 +1,302 @@
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// Copyright (c) Microsoft Corporation. All rights reserved.
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// AzureAIInferenceChatRequestMessageConnector.cs
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Runtime.CompilerServices;
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using System.Threading;
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using System.Threading.Tasks;
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using AutoGen.Core;
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using Azure.AI.Inference;
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namespace AutoGen.AzureAIInference;
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/// <summary>
|
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/// This middleware converts the incoming <see cref="IMessage"/> to <see cref="IMessage{ChatRequestMessage}" /> where T is <see cref="ChatRequestMessage"/> before sending to agent. And converts the output <see cref="ChatResponseMessage"/> to <see cref="IMessage"/> after receiving from agent.
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||||
/// <para>Supported <see cref="IMessage"/> are</para>
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||||
/// <para>- <see cref="TextMessage"/></para>
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||||
/// <para>- <see cref="ImageMessage"/></para>
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||||
/// <para>- <see cref="MultiModalMessage"/></para>
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/// <para>- <see cref="ToolCallMessage"/></para>
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/// <para>- <see cref="ToolCallResultMessage"/></para>
|
||||
/// <para>- <see cref="IMessage{ChatRequestMessage}"/> where T is <see cref="ChatRequestMessage"/></para>
|
||||
/// <para>- <see cref="AggregateMessage{TMessage1, TMessage2}"/> where TMessage1 is <see cref="ToolCallMessage"/> and TMessage2 is <see cref="ToolCallResultMessage"/></para>
|
||||
/// </summary>
|
||||
public class AzureAIInferenceChatRequestMessageConnector : IStreamingMiddleware
|
||||
{
|
||||
private bool strictMode = false;
|
||||
|
||||
/// <summary>
|
||||
/// Create a new instance of <see cref="AzureAIInferenceChatRequestMessageConnector"/>.
|
||||
/// </summary>
|
||||
/// <param name="strictMode">If true, <see cref="AzureAIInferenceChatRequestMessageConnector"/> will throw an <see cref="InvalidOperationException"/>
|
||||
/// When the message type is not supported. If false, it will ignore the unsupported message type.</param>
|
||||
public AzureAIInferenceChatRequestMessageConnector(bool strictMode = false)
|
||||
{
|
||||
this.strictMode = strictMode;
|
||||
}
|
||||
|
||||
public string? Name => nameof(AzureAIInferenceChatRequestMessageConnector);
|
||||
|
||||
public async Task<IMessage> InvokeAsync(MiddlewareContext context, IAgent agent, CancellationToken cancellationToken = default)
|
||||
{
|
||||
var chatMessages = ProcessIncomingMessages(agent, context.Messages);
|
||||
|
||||
var reply = await agent.GenerateReplyAsync(chatMessages, context.Options, cancellationToken);
|
||||
|
||||
return PostProcessMessage(reply);
|
||||
}
|
||||
|
||||
public async IAsyncEnumerable<IMessage> InvokeAsync(
|
||||
MiddlewareContext context,
|
||||
IStreamingAgent agent,
|
||||
[EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
var chatMessages = ProcessIncomingMessages(agent, context.Messages);
|
||||
var streamingReply = agent.GenerateStreamingReplyAsync(chatMessages, context.Options, cancellationToken);
|
||||
string? currentToolName = null;
|
||||
await foreach (var reply in streamingReply)
|
||||
{
|
||||
if (reply is IMessage<StreamingChatCompletionsUpdate> update)
|
||||
{
|
||||
if (update.Content.FunctionName is string functionName)
|
||||
{
|
||||
currentToolName = functionName;
|
||||
}
|
||||
else if (update.Content.ToolCallUpdate is StreamingFunctionToolCallUpdate toolCallUpdate && toolCallUpdate.Name is string toolCallName)
|
||||
{
|
||||
currentToolName = toolCallName;
|
||||
}
|
||||
var postProcessMessage = PostProcessStreamingMessage(update, currentToolName);
|
||||
if (postProcessMessage != null)
|
||||
{
|
||||
yield return postProcessMessage;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
if (this.strictMode)
|
||||
{
|
||||
throw new InvalidOperationException($"Invalid streaming message type {reply.GetType().Name}");
|
||||
}
|
||||
else
|
||||
{
|
||||
yield return reply;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
public IMessage PostProcessMessage(IMessage message)
|
||||
{
|
||||
return message switch
|
||||
{
|
||||
IMessage<ChatResponseMessage> m => PostProcessChatResponseMessage(m.Content, m.From),
|
||||
IMessage<ChatCompletions> m => PostProcessChatCompletions(m),
|
||||
_ when strictMode is false => message,
|
||||
_ => throw new InvalidOperationException($"Invalid return message type {message.GetType().Name}"),
|
||||
};
|
||||
}
|
||||
|
||||
public IMessage? PostProcessStreamingMessage(IMessage<StreamingChatCompletionsUpdate> update, string? currentToolName)
|
||||
{
|
||||
if (update.Content.ContentUpdate is string contentUpdate && string.IsNullOrEmpty(contentUpdate) == false)
|
||||
{
|
||||
// text message
|
||||
return new TextMessageUpdate(Role.Assistant, contentUpdate, from: update.From);
|
||||
}
|
||||
else if (update.Content.FunctionName is string functionName)
|
||||
{
|
||||
return new ToolCallMessageUpdate(functionName, string.Empty, from: update.From);
|
||||
}
|
||||
else if (update.Content.FunctionArgumentsUpdate is string functionArgumentsUpdate && currentToolName is string)
|
||||
{
|
||||
return new ToolCallMessageUpdate(currentToolName, functionArgumentsUpdate, from: update.From);
|
||||
}
|
||||
else if (update.Content.ToolCallUpdate is StreamingFunctionToolCallUpdate tooCallUpdate && currentToolName is string)
|
||||
{
|
||||
return new ToolCallMessageUpdate(tooCallUpdate.Name ?? currentToolName, tooCallUpdate.ArgumentsUpdate, from: update.From);
|
||||
}
|
||||
else
|
||||
{
|
||||
return null;
|
||||
}
|
||||
}
|
||||
|
||||
private IMessage PostProcessChatCompletions(IMessage<ChatCompletions> message)
|
||||
{
|
||||
// throw exception if prompt filter results is not null
|
||||
if (message.Content.Choices[0].FinishReason == CompletionsFinishReason.ContentFiltered)
|
||||
{
|
||||
throw new InvalidOperationException("The content is filtered because its potential risk. Please try another input.");
|
||||
}
|
||||
|
||||
return PostProcessChatResponseMessage(message.Content.Choices[0].Message, message.From);
|
||||
}
|
||||
|
||||
private IMessage PostProcessChatResponseMessage(ChatResponseMessage chatResponseMessage, string? from)
|
||||
{
|
||||
var textContent = chatResponseMessage.Content;
|
||||
if (chatResponseMessage.ToolCalls.Where(tc => tc is ChatCompletionsFunctionToolCall).Any())
|
||||
{
|
||||
var functionToolCalls = chatResponseMessage.ToolCalls
|
||||
.Where(tc => tc is ChatCompletionsFunctionToolCall)
|
||||
.Select(tc => (ChatCompletionsFunctionToolCall)tc);
|
||||
|
||||
var toolCalls = functionToolCalls.Select(tc => new ToolCall(tc.Name, tc.Arguments) { ToolCallId = tc.Id });
|
||||
|
||||
return new ToolCallMessage(toolCalls, from)
|
||||
{
|
||||
Content = textContent,
|
||||
};
|
||||
}
|
||||
|
||||
if (textContent is string content && !string.IsNullOrEmpty(content))
|
||||
{
|
||||
return new TextMessage(Role.Assistant, content, from);
|
||||
}
|
||||
|
||||
throw new InvalidOperationException("Invalid ChatResponseMessage");
|
||||
}
|
||||
|
||||
public IEnumerable<IMessage> ProcessIncomingMessages(IAgent agent, IEnumerable<IMessage> messages)
|
||||
{
|
||||
return messages.SelectMany<IMessage, IMessage>(m =>
|
||||
{
|
||||
if (m is IMessage<ChatRequestMessage> crm)
|
||||
{
|
||||
return [crm];
|
||||
}
|
||||
else
|
||||
{
|
||||
var chatRequestMessages = m switch
|
||||
{
|
||||
TextMessage textMessage => ProcessTextMessage(agent, textMessage),
|
||||
ImageMessage imageMessage when (imageMessage.From is null || imageMessage.From != agent.Name) => ProcessImageMessage(agent, imageMessage),
|
||||
MultiModalMessage multiModalMessage when (multiModalMessage.From is null || multiModalMessage.From != agent.Name) => ProcessMultiModalMessage(agent, multiModalMessage),
|
||||
ToolCallMessage toolCallMessage when (toolCallMessage.From is null || toolCallMessage.From == agent.Name) => ProcessToolCallMessage(agent, toolCallMessage),
|
||||
ToolCallResultMessage toolCallResultMessage => ProcessToolCallResultMessage(toolCallResultMessage),
|
||||
AggregateMessage<ToolCallMessage, ToolCallResultMessage> aggregateMessage => ProcessFunctionCallMiddlewareMessage(agent, aggregateMessage),
|
||||
_ when strictMode is false => [],
|
||||
_ => throw new InvalidOperationException($"Invalid message type: {m.GetType().Name}"),
|
||||
};
|
||||
|
||||
if (chatRequestMessages.Any())
|
||||
{
|
||||
return chatRequestMessages.Select(cm => MessageEnvelope.Create(cm, m.From));
|
||||
}
|
||||
else
|
||||
{
|
||||
return [m];
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
private IEnumerable<ChatRequestMessage> ProcessTextMessage(IAgent agent, TextMessage message)
|
||||
{
|
||||
if (message.Role == Role.System)
|
||||
{
|
||||
return [new ChatRequestSystemMessage(message.Content)];
|
||||
}
|
||||
|
||||
if (agent.Name == message.From)
|
||||
{
|
||||
return [new ChatRequestAssistantMessage { Content = message.Content }];
|
||||
}
|
||||
else
|
||||
{
|
||||
return message.From switch
|
||||
{
|
||||
null when message.Role == Role.User => [new ChatRequestUserMessage(message.Content)],
|
||||
null when message.Role == Role.Assistant => [new ChatRequestAssistantMessage() { Content = message.Content }],
|
||||
null => throw new InvalidOperationException("Invalid Role"),
|
||||
_ => [new ChatRequestUserMessage(message.Content)]
|
||||
};
|
||||
}
|
||||
}
|
||||
|
||||
private IEnumerable<ChatRequestMessage> ProcessImageMessage(IAgent agent, ImageMessage message)
|
||||
{
|
||||
if (agent.Name == message.From)
|
||||
{
|
||||
// image message from assistant is not supported
|
||||
throw new ArgumentException("ImageMessage is not supported when message.From is the same with agent");
|
||||
}
|
||||
|
||||
var imageContentItem = this.CreateChatMessageImageContentItemFromImageMessage(message);
|
||||
return [new ChatRequestUserMessage([imageContentItem])];
|
||||
}
|
||||
|
||||
private IEnumerable<ChatRequestMessage> ProcessMultiModalMessage(IAgent agent, MultiModalMessage message)
|
||||
{
|
||||
if (agent.Name == message.From)
|
||||
{
|
||||
// image message from assistant is not supported
|
||||
throw new ArgumentException("MultiModalMessage is not supported when message.From is the same with agent");
|
||||
}
|
||||
|
||||
IEnumerable<ChatMessageContentItem> items = message.Content.Select<IMessage, ChatMessageContentItem>(ci => ci switch
|
||||
{
|
||||
TextMessage text => new ChatMessageTextContentItem(text.Content),
|
||||
ImageMessage image => this.CreateChatMessageImageContentItemFromImageMessage(image),
|
||||
_ => throw new NotImplementedException(),
|
||||
});
|
||||
|
||||
return [new ChatRequestUserMessage(items)];
|
||||
}
|
||||
|
||||
private ChatMessageImageContentItem CreateChatMessageImageContentItemFromImageMessage(ImageMessage message)
|
||||
{
|
||||
return message.Data is null && message.Url is not null
|
||||
? new ChatMessageImageContentItem(new Uri(message.Url))
|
||||
: new ChatMessageImageContentItem(message.Data, message.Data?.MediaType);
|
||||
}
|
||||
|
||||
private IEnumerable<ChatRequestMessage> ProcessToolCallMessage(IAgent agent, ToolCallMessage message)
|
||||
{
|
||||
if (message.From is not null && message.From != agent.Name)
|
||||
{
|
||||
throw new ArgumentException("ToolCallMessage is not supported when message.From is not the same with agent");
|
||||
}
|
||||
|
||||
var toolCall = message.ToolCalls.Select((tc, i) => new ChatCompletionsFunctionToolCall(tc.ToolCallId ?? $"{tc.FunctionName}_{i}", tc.FunctionName, tc.FunctionArguments));
|
||||
var textContent = message.GetContent() ?? string.Empty;
|
||||
var chatRequestMessage = new ChatRequestAssistantMessage() { Content = textContent };
|
||||
foreach (var tc in toolCall)
|
||||
{
|
||||
chatRequestMessage.ToolCalls.Add(tc);
|
||||
}
|
||||
|
||||
return [chatRequestMessage];
|
||||
}
|
||||
|
||||
private IEnumerable<ChatRequestMessage> ProcessToolCallResultMessage(ToolCallResultMessage message)
|
||||
{
|
||||
return message.ToolCalls
|
||||
.Where(tc => tc.Result is not null)
|
||||
.Select((tc, i) => new ChatRequestToolMessage(tc.Result, tc.ToolCallId ?? $"{tc.FunctionName}_{i}"));
|
||||
}
|
||||
|
||||
private IEnumerable<ChatRequestMessage> ProcessFunctionCallMiddlewareMessage(IAgent agent, AggregateMessage<ToolCallMessage, ToolCallResultMessage> aggregateMessage)
|
||||
{
|
||||
if (aggregateMessage.From is not null && aggregateMessage.From != agent.Name)
|
||||
{
|
||||
// convert as user message
|
||||
var resultMessage = aggregateMessage.Message2;
|
||||
|
||||
return resultMessage.ToolCalls.Select(tc => new ChatRequestUserMessage(tc.Result));
|
||||
}
|
||||
else
|
||||
{
|
||||
var toolCallMessage1 = aggregateMessage.Message1;
|
||||
var toolCallResultMessage = aggregateMessage.Message2;
|
||||
|
||||
var assistantMessage = this.ProcessToolCallMessage(agent, toolCallMessage1);
|
||||
var toolCallResults = this.ProcessToolCallResultMessage(toolCallResultMessage);
|
||||
|
||||
return assistantMessage.Concat(toolCallResults);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -15,6 +15,8 @@
|
|||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\AutoGen.Anthropic\AutoGen.Anthropic.csproj" />
|
||||
<ProjectReference Include="..\AutoGen.AzureAIInference\AutoGen.AzureAIInference.csproj" />
|
||||
<ProjectReference Include="..\AutoGen.LMStudio\AutoGen.LMStudio.csproj" />
|
||||
<ProjectReference Include="..\AutoGen.Mistral\AutoGen.Mistral.csproj" />
|
||||
<ProjectReference Include="..\AutoGen.Ollama\AutoGen.Ollama.csproj" />
|
||||
|
|
|
|||
|
|
@ -0,0 +1,16 @@
|
|||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>$(TestTargetFrameworks)</TargetFrameworks>
|
||||
<IsPackable>false</IsPackable>
|
||||
<IsTestProject>True</IsTestProject>
|
||||
<GenerateDocumentationFile>True</GenerateDocumentationFile>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\src\AutoGen.AzureAIInference\AutoGen.AzureAIInference.csproj" />
|
||||
<ProjectReference Include="..\..\src\AutoGen.SourceGenerator\AutoGen.SourceGenerator.csproj" OutputItemType="Analyzer" ReferenceOutputAssembly="false" />
|
||||
<ProjectReference Include="..\AutoGen.Test.Share\AutoGen.Tests.Share.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
|
|
@ -0,0 +1,533 @@
|
|||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// ChatCompletionClientAgentTests.cs
|
||||
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.IO;
|
||||
using System.Linq;
|
||||
using System.Threading.Tasks;
|
||||
using AutoGen.AzureAIInference.Extension;
|
||||
using AutoGen.Core;
|
||||
using AutoGen.Tests;
|
||||
using Azure.AI.Inference;
|
||||
using FluentAssertions;
|
||||
using Xunit;
|
||||
|
||||
namespace AutoGen.AzureAIInference.Tests;
|
||||
|
||||
public partial class ChatCompletionClientAgentTests
|
||||
{
|
||||
/// <summary>
|
||||
/// Get the weather for a location.
|
||||
/// </summary>
|
||||
/// <param name="location">location</param>
|
||||
/// <returns></returns>
|
||||
[Function]
|
||||
public async Task<string> GetWeatherAsync(string location)
|
||||
{
|
||||
return $"The weather in {location} is sunny.";
|
||||
}
|
||||
|
||||
[ApiKeyFact("GH_API_KEY")]
|
||||
public async Task ChatCompletionAgent_LLaMA3_1()
|
||||
{
|
||||
var client = CreateChatCompletionClient();
|
||||
var model = "meta-llama-3-8b-instruct";
|
||||
|
||||
var agent = new ChatCompletionsClientAgent(client, "assistant", model)
|
||||
.RegisterMessageConnector();
|
||||
|
||||
var reply = await this.BasicChatAsync(agent);
|
||||
reply.Should().BeOfType<TextMessage>();
|
||||
|
||||
reply = await this.BasicChatWithContinuousMessageFromSameSenderAsync(agent);
|
||||
reply.Should().BeOfType<TextMessage>();
|
||||
}
|
||||
|
||||
[ApiKeyFact("GH_API_KEY")]
|
||||
public async Task BasicConversation_Mistra_Small()
|
||||
{
|
||||
var deployName = "Mistral-small";
|
||||
var client = CreateChatCompletionClient();
|
||||
var openAIChatAgent = new ChatCompletionsClientAgent(
|
||||
chatCompletionsClient: client,
|
||||
name: "assistant",
|
||||
modelName: deployName);
|
||||
|
||||
// By default, ChatCompletionClientAgent supports the following message types
|
||||
// - IMessage<ChatRequestMessage>
|
||||
var chatMessageContent = MessageEnvelope.Create(new ChatRequestUserMessage("Hello"));
|
||||
var reply = await openAIChatAgent.SendAsync(chatMessageContent);
|
||||
|
||||
reply.Should().BeOfType<MessageEnvelope<ChatCompletions>>();
|
||||
reply.As<MessageEnvelope<ChatCompletions>>().From.Should().Be("assistant");
|
||||
reply.As<MessageEnvelope<ChatCompletions>>().Content.Choices.First().Message.Role.Should().Be(ChatRole.Assistant);
|
||||
reply.As<MessageEnvelope<ChatCompletions>>().Content.Usage.TotalTokens.Should().BeGreaterThan(0);
|
||||
|
||||
// test streaming
|
||||
var streamingReply = openAIChatAgent.GenerateStreamingReplyAsync(new[] { chatMessageContent });
|
||||
|
||||
await foreach (var streamingMessage in streamingReply)
|
||||
{
|
||||
streamingMessage.Should().BeOfType<MessageEnvelope<StreamingChatCompletionsUpdate>>();
|
||||
streamingMessage.As<MessageEnvelope<StreamingChatCompletionsUpdate>>().From.Should().Be("assistant");
|
||||
}
|
||||
}
|
||||
|
||||
[ApiKeyFact("GH_API_KEY")]
|
||||
public async Task ChatCompletionsMessageContentConnector_Phi3_Mini()
|
||||
{
|
||||
var deployName = "Phi-3-mini-4k-instruct";
|
||||
var openaiClient = CreateChatCompletionClient();
|
||||
var chatCompletionAgent = new ChatCompletionsClientAgent(
|
||||
chatCompletionsClient: openaiClient,
|
||||
name: "assistant",
|
||||
modelName: deployName);
|
||||
|
||||
MiddlewareStreamingAgent<ChatCompletionsClientAgent> assistant = chatCompletionAgent
|
||||
.RegisterMessageConnector();
|
||||
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
MessageEnvelope.Create(new ChatRequestUserMessage("Hello")),
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user"),
|
||||
new MultiModalMessage(Role.Assistant,
|
||||
[
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user"),
|
||||
],
|
||||
from: "user"),
|
||||
};
|
||||
|
||||
foreach (var message in messages)
|
||||
{
|
||||
var reply = await assistant.SendAsync(message);
|
||||
|
||||
reply.Should().BeOfType<TextMessage>();
|
||||
reply.As<TextMessage>().From.Should().Be("assistant");
|
||||
}
|
||||
|
||||
// test streaming
|
||||
foreach (var message in messages)
|
||||
{
|
||||
var reply = assistant.GenerateStreamingReplyAsync([message]);
|
||||
|
||||
await foreach (var streamingMessage in reply)
|
||||
{
|
||||
streamingMessage.Should().BeOfType<TextMessageUpdate>();
|
||||
streamingMessage.As<TextMessageUpdate>().From.Should().Be("assistant");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
[ApiKeyFact("GH_API_KEY")]
|
||||
public async Task ChatCompletionClientAgentToolCall_Mistral_Nemo()
|
||||
{
|
||||
var deployName = "Mistral-nemo";
|
||||
var chatCompletionClient = CreateChatCompletionClient();
|
||||
var agent = new ChatCompletionsClientAgent(
|
||||
chatCompletionsClient: chatCompletionClient,
|
||||
name: "assistant",
|
||||
modelName: deployName);
|
||||
|
||||
var functionCallMiddleware = new FunctionCallMiddleware(
|
||||
functions: [this.GetWeatherAsyncFunctionContract]);
|
||||
MiddlewareStreamingAgent<ChatCompletionsClientAgent> assistant = agent
|
||||
.RegisterMessageConnector();
|
||||
|
||||
assistant.StreamingMiddlewares.Count().Should().Be(1);
|
||||
var functionCallAgent = assistant
|
||||
.RegisterStreamingMiddleware(functionCallMiddleware);
|
||||
|
||||
var question = "What's the weather in Seattle";
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
MessageEnvelope.Create(new ChatRequestUserMessage(question)),
|
||||
new TextMessage(Role.Assistant, question, from: "user"),
|
||||
new MultiModalMessage(Role.Assistant,
|
||||
[
|
||||
new TextMessage(Role.Assistant, question, from: "user"),
|
||||
],
|
||||
from: "user"),
|
||||
};
|
||||
|
||||
foreach (var message in messages)
|
||||
{
|
||||
var reply = await functionCallAgent.SendAsync(message);
|
||||
|
||||
reply.Should().BeOfType<ToolCallMessage>();
|
||||
reply.As<ToolCallMessage>().From.Should().Be("assistant");
|
||||
reply.As<ToolCallMessage>().ToolCalls.Count().Should().Be(1);
|
||||
reply.As<ToolCallMessage>().ToolCalls.First().FunctionName.Should().Be(this.GetWeatherAsyncFunctionContract.Name);
|
||||
}
|
||||
|
||||
// test streaming
|
||||
foreach (var message in messages)
|
||||
{
|
||||
var reply = functionCallAgent.GenerateStreamingReplyAsync([message]);
|
||||
ToolCallMessage? toolCallMessage = null;
|
||||
await foreach (var streamingMessage in reply)
|
||||
{
|
||||
streamingMessage.Should().BeOfType<ToolCallMessageUpdate>();
|
||||
streamingMessage.As<ToolCallMessageUpdate>().From.Should().Be("assistant");
|
||||
if (toolCallMessage is null)
|
||||
{
|
||||
toolCallMessage = new ToolCallMessage(streamingMessage.As<ToolCallMessageUpdate>());
|
||||
}
|
||||
else
|
||||
{
|
||||
toolCallMessage.Update(streamingMessage.As<ToolCallMessageUpdate>());
|
||||
}
|
||||
}
|
||||
|
||||
toolCallMessage.Should().NotBeNull();
|
||||
toolCallMessage!.From.Should().Be("assistant");
|
||||
toolCallMessage.ToolCalls.Count().Should().Be(1);
|
||||
toolCallMessage.ToolCalls.First().FunctionName.Should().Be(this.GetWeatherAsyncFunctionContract.Name);
|
||||
}
|
||||
}
|
||||
|
||||
[ApiKeyFact("GH_API_KEY")]
|
||||
public async Task ChatCompletionClientAgentToolCallInvoking_gpt_4o_mini()
|
||||
{
|
||||
var deployName = "gpt-4o-mini";
|
||||
var client = CreateChatCompletionClient();
|
||||
var agent = new ChatCompletionsClientAgent(
|
||||
chatCompletionsClient: client,
|
||||
name: "assistant",
|
||||
modelName: deployName);
|
||||
|
||||
var functionCallMiddleware = new FunctionCallMiddleware(
|
||||
functions: [this.GetWeatherAsyncFunctionContract],
|
||||
functionMap: new Dictionary<string, Func<string, Task<string>>> { { this.GetWeatherAsyncFunctionContract.Name!, this.GetWeatherAsyncWrapper } });
|
||||
MiddlewareStreamingAgent<ChatCompletionsClientAgent> assistant = agent
|
||||
.RegisterMessageConnector();
|
||||
|
||||
var functionCallAgent = assistant
|
||||
.RegisterStreamingMiddleware(functionCallMiddleware);
|
||||
|
||||
var question = "What's the weather in Seattle";
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
MessageEnvelope.Create(new ChatRequestUserMessage(question)),
|
||||
new TextMessage(Role.Assistant, question, from: "user"),
|
||||
new MultiModalMessage(Role.Assistant,
|
||||
[
|
||||
new TextMessage(Role.Assistant, question, from: "user"),
|
||||
],
|
||||
from: "user"),
|
||||
};
|
||||
|
||||
foreach (var message in messages)
|
||||
{
|
||||
var reply = await functionCallAgent.SendAsync(message);
|
||||
|
||||
reply.Should().BeOfType<ToolCallAggregateMessage>();
|
||||
reply.From.Should().Be("assistant");
|
||||
reply.GetToolCalls()!.Count().Should().Be(1);
|
||||
reply.GetToolCalls()!.First().FunctionName.Should().Be(this.GetWeatherAsyncFunctionContract.Name);
|
||||
reply.GetContent()!.ToLower().Should().Contain("seattle");
|
||||
}
|
||||
|
||||
// test streaming
|
||||
foreach (var message in messages)
|
||||
{
|
||||
var reply = functionCallAgent.GenerateStreamingReplyAsync([message]);
|
||||
await foreach (var streamingMessage in reply)
|
||||
{
|
||||
if (streamingMessage is not IMessage)
|
||||
{
|
||||
streamingMessage.Should().BeOfType<ToolCallMessageUpdate>();
|
||||
streamingMessage.As<ToolCallMessageUpdate>().From.Should().Be("assistant");
|
||||
}
|
||||
else
|
||||
{
|
||||
streamingMessage.Should().BeOfType<ToolCallAggregateMessage>();
|
||||
streamingMessage.As<IMessage>().GetContent()!.ToLower().Should().Contain("seattle");
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
[ApiKeyFact("GH_API_KEY")]
|
||||
public async Task ItCreateChatCompletionClientAgentWithChatCompletionOption_AI21_Jamba_Instruct()
|
||||
{
|
||||
var deployName = "AI21-Jamba-Instruct";
|
||||
var chatCompletionsClient = CreateChatCompletionClient();
|
||||
var options = new ChatCompletionsOptions()
|
||||
{
|
||||
Model = deployName,
|
||||
Temperature = 0.7f,
|
||||
MaxTokens = 1,
|
||||
};
|
||||
|
||||
var openAIChatAgent = new ChatCompletionsClientAgent(
|
||||
chatCompletionsClient: chatCompletionsClient,
|
||||
name: "assistant",
|
||||
options: options)
|
||||
.RegisterMessageConnector();
|
||||
|
||||
var respond = await openAIChatAgent.SendAsync("hello");
|
||||
respond.GetContent()?.Should().NotBeNullOrEmpty();
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItThrowExceptionWhenChatCompletionOptionContainsMessages()
|
||||
{
|
||||
var client = new ChatCompletionsClient(new Uri("https://dummy.com"), new Azure.AzureKeyCredential("dummy"));
|
||||
var options = new ChatCompletionsOptions([new ChatRequestUserMessage("hi")])
|
||||
{
|
||||
Model = "dummy",
|
||||
Temperature = 0.7f,
|
||||
MaxTokens = 1,
|
||||
};
|
||||
|
||||
var action = () => new ChatCompletionsClientAgent(
|
||||
chatCompletionsClient: client,
|
||||
name: "assistant",
|
||||
options: options)
|
||||
.RegisterMessageConnector();
|
||||
|
||||
action.Should().ThrowExactly<ArgumentException>().WithMessage("Messages should not be provided in options");
|
||||
}
|
||||
|
||||
private ChatCompletionsClient CreateChatCompletionClient()
|
||||
{
|
||||
var apiKey = Environment.GetEnvironmentVariable("GH_API_KEY") ?? throw new Exception("Please set GH_API_KEY environment variable.");
|
||||
var endpoint = "https://models.inference.ai.azure.com";
|
||||
return new ChatCompletionsClient(new Uri(endpoint), new Azure.AzureKeyCredential(apiKey));
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should return a text message based on the chat history.
|
||||
/// </summary>
|
||||
/// <param name="agent"></param>
|
||||
/// <returns></returns>
|
||||
private async Task<IMessage> BasicChatEndWithSelfMessageAsync(IAgent agent)
|
||||
{
|
||||
IMessage[] chatHistory = [
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user"),
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user2"),
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user3"),
|
||||
new TextMessage(Role.Assistant, "Hello", from: agent.Name),
|
||||
];
|
||||
|
||||
return await agent.GenerateReplyAsync(chatHistory);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should return a text message based on the chat history.
|
||||
/// </summary>
|
||||
/// <param name="agent"></param>
|
||||
/// <returns></returns>
|
||||
private async Task<IMessage> BasicChatAsync(IAgent agent)
|
||||
{
|
||||
IMessage[] chatHistory = [
|
||||
new TextMessage(Role.Assistant, "Hello", from: agent.Name),
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user"),
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user1"),
|
||||
];
|
||||
|
||||
return await agent.GenerateReplyAsync(chatHistory);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should return a text message based on the chat history. This test the generate reply with continuous message from the same sender.
|
||||
/// </summary>
|
||||
private async Task<IMessage> BasicChatWithContinuousMessageFromSameSenderAsync(IAgent agent)
|
||||
{
|
||||
IMessage[] chatHistory = [
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user"),
|
||||
new TextMessage(Role.Assistant, "Hello", from: "user"),
|
||||
new TextMessage(Role.Assistant, "Hello", from: agent.Name),
|
||||
new TextMessage(Role.Assistant, "Hello", from: agent.Name),
|
||||
];
|
||||
|
||||
return await agent.GenerateReplyAsync(chatHistory);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should return a text message based on the chat history.
|
||||
/// </summary>
|
||||
/// <param name="agent"></param>
|
||||
/// <returns></returns>
|
||||
private async Task<IMessage> ImageChatAsync(IAgent agent)
|
||||
{
|
||||
var image = Path.Join("testData", "images", "square.png");
|
||||
var binaryData = File.ReadAllBytes(image);
|
||||
var imageMessage = new ImageMessage(Role.Assistant, BinaryData.FromBytes(binaryData, "image/png"), from: "user");
|
||||
|
||||
IMessage[] chatHistory = [
|
||||
imageMessage,
|
||||
new TextMessage(Role.Assistant, "What's in the picture", from: "user"),
|
||||
];
|
||||
|
||||
return await agent.GenerateReplyAsync(chatHistory);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should return a text message based on the chat history. This test the generate reply with continuous image messages.
|
||||
/// </summary>
|
||||
/// <param name="agent"></param>
|
||||
/// <returns></returns>
|
||||
private async Task<IMessage> MultipleImageChatAsync(IAgent agent)
|
||||
{
|
||||
var image1 = Path.Join("testData", "images", "square.png");
|
||||
var image2 = Path.Join("testData", "images", "background.png");
|
||||
var binaryData1 = File.ReadAllBytes(image1);
|
||||
var binaryData2 = File.ReadAllBytes(image2);
|
||||
var imageMessage1 = new ImageMessage(Role.Assistant, BinaryData.FromBytes(binaryData1, "image/png"), from: "user");
|
||||
var imageMessage2 = new ImageMessage(Role.Assistant, BinaryData.FromBytes(binaryData2, "image/png"), from: "user");
|
||||
|
||||
IMessage[] chatHistory = [
|
||||
imageMessage1,
|
||||
imageMessage2,
|
||||
new TextMessage(Role.Assistant, "What's in the picture", from: "user"),
|
||||
];
|
||||
|
||||
return await agent.GenerateReplyAsync(chatHistory);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should return a text message based on the chat history.
|
||||
/// </summary>
|
||||
/// <param name="agent"></param>
|
||||
/// <returns></returns>
|
||||
private async Task<IMessage> MultiModalChatAsync(IAgent agent)
|
||||
{
|
||||
var image = Path.Join("testData", "images", "square.png");
|
||||
var binaryData = File.ReadAllBytes(image);
|
||||
var question = "What's in the picture";
|
||||
var imageMessage = new ImageMessage(Role.Assistant, BinaryData.FromBytes(binaryData, "image/png"), from: "user");
|
||||
var textMessage = new TextMessage(Role.Assistant, question, from: "user");
|
||||
|
||||
IMessage[] chatHistory = [
|
||||
new MultiModalMessage(Role.Assistant, [imageMessage, textMessage], from: "user"),
|
||||
];
|
||||
|
||||
return await agent.GenerateReplyAsync(chatHistory);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should return a tool call message based on the chat history.
|
||||
/// </summary>
|
||||
/// <param name="agent"></param>
|
||||
/// <returns></returns>
|
||||
private async Task<IMessage> ToolCallChatAsync(IAgent agent)
|
||||
{
|
||||
var question = "What's the weather in Seattle";
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
new TextMessage(Role.Assistant, question, from: "user"),
|
||||
};
|
||||
|
||||
return await agent.GenerateReplyAsync(messages);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should throw an exception because tool call result is not available.
|
||||
/// </summary>
|
||||
private async Task<IMessage> ToolCallFromSelfChatAsync(IAgent agent)
|
||||
{
|
||||
var question = "What's the weather in Seattle";
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
new TextMessage(Role.Assistant, question, from: "user"),
|
||||
new ToolCallMessage("GetWeatherAsync", "Seattle", from: agent.Name),
|
||||
};
|
||||
|
||||
return await agent.GenerateReplyAsync(messages);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// mimic the further chat after tool call. The agent should return a text message based on the tool call result.
|
||||
/// </summary>
|
||||
private async Task<IMessage> ToolCallWithResultChatAsync(IAgent agent)
|
||||
{
|
||||
var question = "What's the weather in Seattle";
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
new TextMessage(Role.Assistant, question, from: "user"),
|
||||
new ToolCallMessage("GetWeatherAsync", "Seattle", from: "user"),
|
||||
new ToolCallResultMessage("sunny", "GetWeatherAsync", "Seattle", from: agent.Name),
|
||||
};
|
||||
|
||||
return await agent.GenerateReplyAsync(messages);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// the agent should return a text message based on the tool call result.
|
||||
/// </summary>
|
||||
/// <param name="agent"></param>
|
||||
/// <returns></returns>
|
||||
private async Task<IMessage> AggregateToolCallFromSelfChatAsync(IAgent agent)
|
||||
{
|
||||
var textMessage = new TextMessage(Role.Assistant, "What's the weather in Seattle", from: "user");
|
||||
var toolCallMessage = new ToolCallMessage("GetWeatherAsync", "Seattle", from: agent.Name);
|
||||
var toolCallResultMessage = new ToolCallResultMessage("sunny", "GetWeatherAsync", "Seattle", from: agent.Name);
|
||||
var aggregateToolCallMessage = new ToolCallAggregateMessage(toolCallMessage, toolCallResultMessage, from: agent.Name);
|
||||
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
textMessage,
|
||||
aggregateToolCallMessage,
|
||||
};
|
||||
|
||||
return await agent.GenerateReplyAsync(messages);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// the agent should return a text message based on the tool call result. Because the aggregate tool call message is from other, the message would be treated as an ordinary text message.
|
||||
/// </summary>
|
||||
private async Task<IMessage> AggregateToolCallFromOtherChatWithContinuousMessageAsync(IAgent agent)
|
||||
{
|
||||
var textMessage = new TextMessage(Role.Assistant, "What's the weather in Seattle", from: "user");
|
||||
var toolCallMessage = new ToolCallMessage("GetWeatherAsync", "Seattle", from: "other");
|
||||
var toolCallResultMessage = new ToolCallResultMessage("sunny", "GetWeatherAsync", "Seattle", from: "other");
|
||||
var aggregateToolCallMessage = new ToolCallAggregateMessage(toolCallMessage, toolCallResultMessage, "other");
|
||||
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
textMessage,
|
||||
aggregateToolCallMessage,
|
||||
};
|
||||
|
||||
return await agent.GenerateReplyAsync(messages);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should throw an exception because tool call message from other is not allowed.
|
||||
/// </summary>
|
||||
private async Task<IMessage> ToolCallMessaageFromOtherChatAsync(IAgent agent)
|
||||
{
|
||||
var textMessage = new TextMessage(Role.Assistant, "What's the weather in Seattle", from: "user");
|
||||
var toolCallMessage = new ToolCallMessage("GetWeatherAsync", "Seattle", from: "other");
|
||||
|
||||
var messages = new IMessage[]
|
||||
{
|
||||
textMessage,
|
||||
toolCallMessage,
|
||||
};
|
||||
|
||||
return await agent.GenerateReplyAsync(messages);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// The agent should throw an exception because multi-modal message from self is not allowed.
|
||||
/// </summary>
|
||||
/// <param name="agent"></param>
|
||||
/// <returns></returns>
|
||||
private async Task<IMessage> MultiModalMessageFromSelfChatAsync(IAgent agent)
|
||||
{
|
||||
var image = Path.Join("testData", "images", "square.png");
|
||||
var binaryData = File.ReadAllBytes(image);
|
||||
var question = "What's in the picture";
|
||||
var imageMessage = new ImageMessage(Role.Assistant, BinaryData.FromBytes(binaryData, "image/png"), from: agent.Name);
|
||||
var textMessage = new TextMessage(Role.Assistant, question, from: agent.Name);
|
||||
|
||||
IMessage[] chatHistory = [
|
||||
new MultiModalMessage(Role.Assistant, [imageMessage, textMessage], from: agent.Name),
|
||||
];
|
||||
|
||||
return await agent.GenerateReplyAsync(chatHistory);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,568 @@
|
|||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// ChatRequestMessageTests.cs
|
||||
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using System.Reflection;
|
||||
using System.Text.Json;
|
||||
using System.Threading.Tasks;
|
||||
using AutoGen.Core;
|
||||
using AutoGen.Tests;
|
||||
using Azure.AI.Inference;
|
||||
using FluentAssertions;
|
||||
using Xunit;
|
||||
|
||||
namespace AutoGen.AzureAIInference.Tests;
|
||||
|
||||
public class ChatRequestMessageTests
|
||||
{
|
||||
private readonly JsonSerializerOptions jsonSerializerOptions = new JsonSerializerOptions
|
||||
{
|
||||
WriteIndented = true,
|
||||
IgnoreReadOnlyProperties = false,
|
||||
};
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessUserTextMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestUserMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().Be("Hello");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
IMessage message = new TextMessage(Role.User, "Hello", "user");
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItShortcutChatRequestMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestUserMessage>>();
|
||||
|
||||
var chatRequestMessage = (ChatRequestUserMessage)((MessageEnvelope<ChatRequestUserMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().Be("hello");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
var userMessage = new ChatRequestUserMessage("hello");
|
||||
var chatRequestMessage = MessageEnvelope.Create(userMessage);
|
||||
await agent.GenerateReplyAsync([chatRequestMessage]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItShortcutMessageWhenStrictModelIsFalseAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<string>>();
|
||||
|
||||
var chatRequestMessage = ((MessageEnvelope<string>)innerMessage!).Content;
|
||||
chatRequestMessage.Should().Be("hello");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
var userMessage = "hello";
|
||||
var chatRequestMessage = MessageEnvelope.Create(userMessage);
|
||||
await agent.GenerateReplyAsync([chatRequestMessage]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItThrowExceptionWhenStrictModeIsTrueAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector(true);
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
var userMessage = "hello";
|
||||
var chatRequestMessage = MessageEnvelope.Create(userMessage);
|
||||
Func<Task> action = async () => await agent.GenerateReplyAsync([chatRequestMessage]);
|
||||
|
||||
await action.Should().ThrowAsync<InvalidOperationException>().WithMessage("Invalid message type: MessageEnvelope`1");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessAssistantTextMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestAssistantMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().Be("How can I help you?");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// assistant message
|
||||
IMessage message = new TextMessage(Role.Assistant, "How can I help you?", "assistant");
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessSystemTextMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestSystemMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().Be("You are a helpful AI assistant");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// system message
|
||||
IMessage message = new TextMessage(Role.System, "You are a helpful AI assistant");
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessImageMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestUserMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().BeNullOrEmpty();
|
||||
chatRequestMessage.MultimodalContentItems.Count().Should().Be(1);
|
||||
chatRequestMessage.MultimodalContentItems.First().Should().BeOfType<ChatMessageImageContentItem>();
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
IMessage message = new ImageMessage(Role.User, "https://example.com/image.png", "user");
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItThrowExceptionWhenProcessingImageMessageFromSelfAndStrictModeIsTrueAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector(true);
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
var imageMessage = new ImageMessage(Role.Assistant, "https://example.com/image.png", "assistant");
|
||||
Func<Task> action = async () => await agent.GenerateReplyAsync([imageMessage]);
|
||||
|
||||
await action.Should().ThrowAsync<InvalidOperationException>().WithMessage("Invalid message type: ImageMessage");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessMultiModalMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestUserMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().BeNullOrEmpty();
|
||||
chatRequestMessage.MultimodalContentItems.Count().Should().Be(2);
|
||||
chatRequestMessage.MultimodalContentItems.First().Should().BeOfType<ChatMessageTextContentItem>();
|
||||
chatRequestMessage.MultimodalContentItems.Last().Should().BeOfType<ChatMessageImageContentItem>();
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
IMessage message = new MultiModalMessage(
|
||||
Role.User,
|
||||
[
|
||||
new TextMessage(Role.User, "Hello", "user"),
|
||||
new ImageMessage(Role.User, "https://example.com/image.png", "user"),
|
||||
], "user");
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItThrowExceptionWhenProcessingMultiModalMessageFromSelfAndStrictModeIsTrueAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector(true);
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
var multiModalMessage = new MultiModalMessage(
|
||||
Role.Assistant,
|
||||
[
|
||||
new TextMessage(Role.User, "Hello", "assistant"),
|
||||
new ImageMessage(Role.User, "https://example.com/image.png", "assistant"),
|
||||
], "assistant");
|
||||
|
||||
Func<Task> action = async () => await agent.GenerateReplyAsync([multiModalMessage]);
|
||||
|
||||
await action.Should().ThrowAsync<InvalidOperationException>().WithMessage("Invalid message type: MultiModalMessage");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessToolCallMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestAssistantMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.ToolCalls.Count().Should().Be(1);
|
||||
chatRequestMessage.Content.Should().Be("textContent");
|
||||
chatRequestMessage.ToolCalls.First().Should().BeOfType<ChatCompletionsFunctionToolCall>();
|
||||
var functionToolCall = (ChatCompletionsFunctionToolCall)chatRequestMessage.ToolCalls.First();
|
||||
functionToolCall.Name.Should().Be("test");
|
||||
functionToolCall.Id.Should().Be("test");
|
||||
functionToolCall.Arguments.Should().Be("test");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
IMessage message = new ToolCallMessage("test", "test", "assistant")
|
||||
{
|
||||
Content = "textContent",
|
||||
};
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessParallelToolCallMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestAssistantMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().BeNullOrEmpty();
|
||||
chatRequestMessage.ToolCalls.Count().Should().Be(2);
|
||||
for (int i = 0; i < chatRequestMessage.ToolCalls.Count(); i++)
|
||||
{
|
||||
chatRequestMessage.ToolCalls.ElementAt(i).Should().BeOfType<ChatCompletionsFunctionToolCall>();
|
||||
var functionToolCall = (ChatCompletionsFunctionToolCall)chatRequestMessage.ToolCalls.ElementAt(i);
|
||||
functionToolCall.Name.Should().Be("test");
|
||||
functionToolCall.Id.Should().Be($"test_{i}");
|
||||
functionToolCall.Arguments.Should().Be("test");
|
||||
}
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
var toolCalls = new[]
|
||||
{
|
||||
new ToolCall("test", "test"),
|
||||
new ToolCall("test", "test"),
|
||||
};
|
||||
IMessage message = new ToolCallMessage(toolCalls, "assistant");
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItThrowExceptionWhenProcessingToolCallMessageFromUserAndStrictModeIsTrueAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector(strictMode: true);
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
var toolCallMessage = new ToolCallMessage("test", "test", "user");
|
||||
Func<Task> action = async () => await agent.GenerateReplyAsync([toolCallMessage]);
|
||||
await action.Should().ThrowAsync<InvalidOperationException>().WithMessage("Invalid message type: ToolCallMessage");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessToolCallResultMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestToolMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().Be("result");
|
||||
chatRequestMessage.ToolCallId.Should().Be("test");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
IMessage message = new ToolCallResultMessage("result", "test", "test", "user");
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessParallelToolCallResultMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
msgs.Count().Should().Be(2);
|
||||
|
||||
for (int i = 0; i < msgs.Count(); i++)
|
||||
{
|
||||
var innerMessage = msgs.ElementAt(i);
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestToolMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().Be("result");
|
||||
chatRequestMessage.ToolCallId.Should().Be($"test_{i}");
|
||||
}
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
var toolCalls = new[]
|
||||
{
|
||||
new ToolCall("test", "test", "result"),
|
||||
new ToolCall("test", "test", "result"),
|
||||
};
|
||||
IMessage message = new ToolCallResultMessage(toolCalls, "user");
|
||||
await agent.GenerateReplyAsync([message]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessFunctionCallMiddlewareMessageFromUserAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
msgs.Count().Should().Be(1);
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestUserMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().Be("result");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
var toolCallMessage = new ToolCallMessage("test", "test", "user");
|
||||
var toolCallResultMessage = new ToolCallResultMessage("result", "test", "test", "user");
|
||||
var aggregateMessage = new AggregateMessage<ToolCallMessage, ToolCallResultMessage>(toolCallMessage, toolCallResultMessage, "user");
|
||||
await agent.GenerateReplyAsync([aggregateMessage]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessFunctionCallMiddlewareMessageFromAssistantAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
msgs.Count().Should().Be(2);
|
||||
var innerMessage = msgs.Last();
|
||||
innerMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var chatRequestMessage = (ChatRequestToolMessage)((MessageEnvelope<ChatRequestMessage>)innerMessage!).Content;
|
||||
chatRequestMessage.Content.Should().Be("result");
|
||||
chatRequestMessage.ToolCallId.Should().Be("test");
|
||||
|
||||
var toolCallMessage = msgs.First();
|
||||
toolCallMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var toolCallRequestMessage = (ChatRequestAssistantMessage)((MessageEnvelope<ChatRequestMessage>)toolCallMessage!).Content;
|
||||
toolCallRequestMessage.Content.Should().BeNullOrEmpty();
|
||||
toolCallRequestMessage.ToolCalls.Count().Should().Be(1);
|
||||
toolCallRequestMessage.ToolCalls.First().Should().BeOfType<ChatCompletionsFunctionToolCall>();
|
||||
var functionToolCall = (ChatCompletionsFunctionToolCall)toolCallRequestMessage.ToolCalls.First();
|
||||
functionToolCall.Name.Should().Be("test");
|
||||
functionToolCall.Id.Should().Be("test");
|
||||
functionToolCall.Arguments.Should().Be("test");
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
var toolCallMessage = new ToolCallMessage("test", "test", "assistant");
|
||||
var toolCallResultMessage = new ToolCallResultMessage("result", "test", "test", "assistant");
|
||||
var aggregateMessage = new ToolCallAggregateMessage(toolCallMessage, toolCallResultMessage, "assistant");
|
||||
await agent.GenerateReplyAsync([aggregateMessage]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItProcessParallelFunctionCallMiddlewareMessageFromAssistantAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(async (msgs, _, innerAgent, _) =>
|
||||
{
|
||||
msgs.Count().Should().Be(3);
|
||||
var toolCallMessage = msgs.First();
|
||||
toolCallMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var toolCallRequestMessage = (ChatRequestAssistantMessage)((MessageEnvelope<ChatRequestMessage>)toolCallMessage!).Content;
|
||||
toolCallRequestMessage.Content.Should().BeNullOrEmpty();
|
||||
toolCallRequestMessage.ToolCalls.Count().Should().Be(2);
|
||||
|
||||
for (int i = 0; i < toolCallRequestMessage.ToolCalls.Count(); i++)
|
||||
{
|
||||
toolCallRequestMessage.ToolCalls.ElementAt(i).Should().BeOfType<ChatCompletionsFunctionToolCall>();
|
||||
var functionToolCall = (ChatCompletionsFunctionToolCall)toolCallRequestMessage.ToolCalls.ElementAt(i);
|
||||
functionToolCall.Name.Should().Be("test");
|
||||
functionToolCall.Id.Should().Be($"test_{i}");
|
||||
functionToolCall.Arguments.Should().Be("test");
|
||||
}
|
||||
|
||||
for (int i = 1; i < msgs.Count(); i++)
|
||||
{
|
||||
var toolCallResultMessage = msgs.ElementAt(i);
|
||||
toolCallResultMessage!.Should().BeOfType<MessageEnvelope<ChatRequestMessage>>();
|
||||
var toolCallResultRequestMessage = (ChatRequestToolMessage)((MessageEnvelope<ChatRequestMessage>)toolCallResultMessage!).Content;
|
||||
toolCallResultRequestMessage.Content.Should().Be("result");
|
||||
toolCallResultRequestMessage.ToolCallId.Should().Be($"test_{i - 1}");
|
||||
}
|
||||
|
||||
return await innerAgent.GenerateReplyAsync(msgs);
|
||||
})
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// user message
|
||||
var toolCalls = new[]
|
||||
{
|
||||
new ToolCall("test", "test", "result"),
|
||||
new ToolCall("test", "test", "result"),
|
||||
};
|
||||
var toolCallMessage = new ToolCallMessage(toolCalls, "assistant");
|
||||
var toolCallResultMessage = new ToolCallResultMessage(toolCalls, "assistant");
|
||||
var aggregateMessage = new AggregateMessage<ToolCallMessage, ToolCallResultMessage>(toolCallMessage, toolCallResultMessage, "assistant");
|
||||
await agent.GenerateReplyAsync([aggregateMessage]);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItConvertChatResponseMessageToTextMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// text message
|
||||
var textMessage = CreateInstance<ChatResponseMessage>(ChatRole.Assistant, "hello");
|
||||
var chatRequestMessage = MessageEnvelope.Create(textMessage);
|
||||
|
||||
var message = await agent.GenerateReplyAsync([chatRequestMessage]);
|
||||
message.Should().BeOfType<TextMessage>();
|
||||
message.GetContent().Should().Be("hello");
|
||||
message.GetRole().Should().Be(Role.Assistant);
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItConvertChatResponseMessageToToolCallMessageAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// tool call message
|
||||
var toolCallMessage = CreateInstance<ChatResponseMessage>(ChatRole.Assistant, "textContent", new[] { new ChatCompletionsFunctionToolCall("test", "test", "test") }, new Dictionary<string, BinaryData>());
|
||||
var chatRequestMessage = MessageEnvelope.Create(toolCallMessage);
|
||||
var message = await agent.GenerateReplyAsync([chatRequestMessage]);
|
||||
message.Should().BeOfType<ToolCallMessage>();
|
||||
message.GetToolCalls()!.Count().Should().Be(1);
|
||||
message.GetToolCalls()!.First().FunctionName.Should().Be("test");
|
||||
message.GetToolCalls()!.First().FunctionArguments.Should().Be("test");
|
||||
message.GetContent().Should().Be("textContent");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItReturnOriginalMessageWhenStrictModeIsFalseAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// text message
|
||||
var textMessage = "hello";
|
||||
var messageToSend = MessageEnvelope.Create(textMessage);
|
||||
|
||||
var message = await agent.GenerateReplyAsync([messageToSend]);
|
||||
message.Should().BeOfType<MessageEnvelope<string>>();
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public async Task ItThrowInvalidOperationExceptionWhenStrictModeIsTrueAsync()
|
||||
{
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector(true);
|
||||
var agent = new EchoAgent("assistant")
|
||||
.RegisterMiddleware(middleware);
|
||||
|
||||
// text message
|
||||
var textMessage = new ChatRequestUserMessage("hello");
|
||||
var messageToSend = MessageEnvelope.Create(textMessage);
|
||||
Func<Task> action = async () => await agent.GenerateReplyAsync([messageToSend]);
|
||||
|
||||
await action.Should().ThrowAsync<InvalidOperationException>().WithMessage("Invalid return message type MessageEnvelope`1");
|
||||
}
|
||||
|
||||
[Fact]
|
||||
public void ToOpenAIChatRequestMessageShortCircuitTest()
|
||||
{
|
||||
var agent = new EchoAgent("assistant");
|
||||
var middleware = new AzureAIInferenceChatRequestMessageConnector();
|
||||
ChatRequestMessage[] messages =
|
||||
[
|
||||
new ChatRequestUserMessage("Hello"),
|
||||
new ChatRequestAssistantMessage()
|
||||
{
|
||||
Content = "How can I help you?",
|
||||
},
|
||||
new ChatRequestSystemMessage("You are a helpful AI assistant"),
|
||||
new ChatRequestToolMessage("test", "test"),
|
||||
];
|
||||
|
||||
foreach (var oaiMessage in messages)
|
||||
{
|
||||
IMessage message = new MessageEnvelope<ChatRequestMessage>(oaiMessage);
|
||||
var oaiMessages = middleware.ProcessIncomingMessages(agent, [message]);
|
||||
oaiMessages.Count().Should().Be(1);
|
||||
//oaiMessages.First().Should().BeOfType<IMessage<ChatRequestMessage>>();
|
||||
if (oaiMessages.First() is IMessage<ChatRequestMessage> chatRequestMessage)
|
||||
{
|
||||
chatRequestMessage.Content.Should().Be(oaiMessage);
|
||||
}
|
||||
else
|
||||
{
|
||||
// fail the test
|
||||
Assert.True(false);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private static T CreateInstance<T>(params object[] args)
|
||||
{
|
||||
var type = typeof(T);
|
||||
var instance = type.Assembly.CreateInstance(
|
||||
type.FullName!, false,
|
||||
BindingFlags.Instance | BindingFlags.NonPublic,
|
||||
null, args, null, null);
|
||||
return (T)instance!;
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,31 @@
|
|||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// EnvironmentSpecificFactAttribute.cs
|
||||
|
||||
using Xunit;
|
||||
|
||||
namespace AutoGen.Tests;
|
||||
|
||||
/// <summary>
|
||||
/// A base class for environment-specific fact attributes.
|
||||
/// </summary>
|
||||
[AttributeUsage(AttributeTargets.Method, AllowMultiple = false, Inherited = true)]
|
||||
public abstract class EnvironmentSpecificFactAttribute : FactAttribute
|
||||
{
|
||||
private readonly string _skipMessage;
|
||||
|
||||
/// <summary>
|
||||
/// Creates a new instance of the <see cref="EnvironmentSpecificFactAttribute" /> class.
|
||||
/// </summary>
|
||||
/// <param name="skipMessage">The message to be used when skipping the test marked with this attribute.</param>
|
||||
protected EnvironmentSpecificFactAttribute(string skipMessage)
|
||||
{
|
||||
_skipMessage = skipMessage ?? throw new ArgumentNullException(nameof(skipMessage));
|
||||
}
|
||||
|
||||
public sealed override string Skip => IsEnvironmentSupported() ? string.Empty : _skipMessage;
|
||||
|
||||
/// <summary>
|
||||
/// A method used to evaluate whether to skip a test marked with this attribute. Skips iff this method evaluates to false.
|
||||
/// </summary>
|
||||
protected abstract bool IsEnvironmentSupported();
|
||||
}
|
||||
|
|
@ -0,0 +1,22 @@
|
|||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// OpenAIFact.cs
|
||||
|
||||
namespace AutoGen.Tests;
|
||||
|
||||
/// <summary>
|
||||
/// A fact for tests requiring OPENAI_API_KEY env.
|
||||
/// </summary>
|
||||
public sealed class ApiKeyFactAttribute : EnvironmentSpecificFactAttribute
|
||||
{
|
||||
private readonly string[] _envVariableNames;
|
||||
public ApiKeyFactAttribute(params string[] envVariableNames) : base($"{envVariableNames} is not found in env")
|
||||
{
|
||||
_envVariableNames = envVariableNames;
|
||||
}
|
||||
|
||||
/// <inheritdoc />
|
||||
protected override bool IsEnvironmentSupported()
|
||||
{
|
||||
return _envVariableNames.All(Environment.GetEnvironmentVariables().Contains);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,15 @@
|
|||
<Project Sdk="Microsoft.NET.Sdk">
|
||||
|
||||
<PropertyGroup>
|
||||
<TargetFrameworks>$(TestTargetFrameworks)</TargetFrameworks>
|
||||
<ImplicitUsings>enable</ImplicitUsings>
|
||||
<IsPackable>false</IsPackable>
|
||||
<IsTestProject>True</IsTestProject>
|
||||
<Nullable>enable</Nullable>
|
||||
</PropertyGroup>
|
||||
|
||||
<ItemGroup>
|
||||
<ProjectReference Include="..\..\src\AutoGen.Core\AutoGen.Core.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
</Project>
|
||||
|
|
@ -0,0 +1,37 @@
|
|||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// EchoAgent.cs
|
||||
|
||||
using System.Runtime.CompilerServices;
|
||||
using AutoGen.Core;
|
||||
|
||||
namespace AutoGen.Tests;
|
||||
|
||||
public class EchoAgent : IStreamingAgent
|
||||
{
|
||||
public EchoAgent(string name)
|
||||
{
|
||||
Name = name;
|
||||
}
|
||||
public string Name { get; }
|
||||
|
||||
public Task<IMessage> GenerateReplyAsync(
|
||||
IEnumerable<IMessage> conversation,
|
||||
GenerateReplyOptions? options = null,
|
||||
CancellationToken ct = default)
|
||||
{
|
||||
// return the most recent message
|
||||
var lastMessage = conversation.Last();
|
||||
lastMessage.From = this.Name;
|
||||
|
||||
return Task.FromResult(lastMessage);
|
||||
}
|
||||
|
||||
public async IAsyncEnumerable<IMessage> GenerateStreamingReplyAsync(IEnumerable<IMessage> messages, GenerateReplyOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
foreach (var message in messages)
|
||||
{
|
||||
message.From = this.Name;
|
||||
yield return message;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -1,33 +0,0 @@
|
|||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// EnvironmentSpecificFactAttribute.cs
|
||||
|
||||
using System;
|
||||
using Xunit;
|
||||
|
||||
namespace AutoGen.Tests
|
||||
{
|
||||
/// <summary>
|
||||
/// A base class for environment-specific fact attributes.
|
||||
/// </summary>
|
||||
[AttributeUsage(AttributeTargets.Method, AllowMultiple = false, Inherited = true)]
|
||||
public abstract class EnvironmentSpecificFactAttribute : FactAttribute
|
||||
{
|
||||
private readonly string _skipMessage;
|
||||
|
||||
/// <summary>
|
||||
/// Creates a new instance of the <see cref="EnvironmentSpecificFactAttribute" /> class.
|
||||
/// </summary>
|
||||
/// <param name="skipMessage">The message to be used when skipping the test marked with this attribute.</param>
|
||||
protected EnvironmentSpecificFactAttribute(string skipMessage)
|
||||
{
|
||||
_skipMessage = skipMessage ?? throw new ArgumentNullException(nameof(skipMessage));
|
||||
}
|
||||
|
||||
public sealed override string Skip => IsEnvironmentSupported() ? string.Empty : _skipMessage;
|
||||
|
||||
/// <summary>
|
||||
/// A method used to evaluate whether to skip a test marked with this attribute. Skips iff this method evaluates to false.
|
||||
/// </summary>
|
||||
protected abstract bool IsEnvironmentSupported();
|
||||
}
|
||||
}
|
||||
|
|
@ -1,26 +0,0 @@
|
|||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// OpenAIFact.cs
|
||||
|
||||
using System;
|
||||
using System.Linq;
|
||||
|
||||
namespace AutoGen.Tests
|
||||
{
|
||||
/// <summary>
|
||||
/// A fact for tests requiring OPENAI_API_KEY env.
|
||||
/// </summary>
|
||||
public sealed class ApiKeyFactAttribute : EnvironmentSpecificFactAttribute
|
||||
{
|
||||
private readonly string[] _envVariableNames;
|
||||
public ApiKeyFactAttribute(params string[] envVariableNames) : base($"{envVariableNames} is not found in env")
|
||||
{
|
||||
_envVariableNames = envVariableNames;
|
||||
}
|
||||
|
||||
/// <inheritdoc />
|
||||
protected override bool IsEnvironmentSupported()
|
||||
{
|
||||
return _envVariableNames.All(Environment.GetEnvironmentVariables().Contains);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -12,6 +12,7 @@
|
|||
<ProjectReference Include="..\..\src\AutoGen.Anthropic\AutoGen.Anthropic.csproj" />
|
||||
<ProjectReference Include="..\..\src\AutoGen.SourceGenerator\AutoGen.SourceGenerator.csproj" OutputItemType="Analyzer" ReferenceOutputAssembly="false" />
|
||||
<ProjectReference Include="..\..\src\AutoGen\AutoGen.csproj" />
|
||||
<ProjectReference Include="..\AutoGen.Test.Share\AutoGen.Tests.Share.csproj" />
|
||||
</ItemGroup>
|
||||
|
||||
<ItemGroup>
|
||||
|
|
|
|||
|
|
@ -1,41 +0,0 @@
|
|||
// Copyright (c) Microsoft Corporation. All rights reserved.
|
||||
// EchoAgent.cs
|
||||
|
||||
using System.Collections.Generic;
|
||||
using System.Linq;
|
||||
using System.Runtime.CompilerServices;
|
||||
using System.Threading;
|
||||
using System.Threading.Tasks;
|
||||
|
||||
namespace AutoGen.Tests
|
||||
{
|
||||
public class EchoAgent : IStreamingAgent
|
||||
{
|
||||
public EchoAgent(string name)
|
||||
{
|
||||
Name = name;
|
||||
}
|
||||
public string Name { get; }
|
||||
|
||||
public Task<IMessage> GenerateReplyAsync(
|
||||
IEnumerable<IMessage> conversation,
|
||||
GenerateReplyOptions? options = null,
|
||||
CancellationToken ct = default)
|
||||
{
|
||||
// return the most recent message
|
||||
var lastMessage = conversation.Last();
|
||||
lastMessage.From = this.Name;
|
||||
|
||||
return Task.FromResult(lastMessage);
|
||||
}
|
||||
|
||||
public async IAsyncEnumerable<IMessage> GenerateStreamingReplyAsync(IEnumerable<IMessage> messages, GenerateReplyOptions? options = null, [EnumeratorCancellation] CancellationToken cancellationToken = default)
|
||||
{
|
||||
foreach (var message in messages)
|
||||
{
|
||||
message.From = this.Name;
|
||||
yield return message;
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
@ -10,11 +10,14 @@ using System.Threading.Tasks;
|
|||
using AutoGen.Anthropic;
|
||||
using AutoGen.Anthropic.Extensions;
|
||||
using AutoGen.Anthropic.Utils;
|
||||
using AutoGen.AzureAIInference;
|
||||
using AutoGen.AzureAIInference.Extension;
|
||||
using AutoGen.Gemini;
|
||||
using AutoGen.Mistral;
|
||||
using AutoGen.Mistral.Extension;
|
||||
using AutoGen.OpenAI;
|
||||
using AutoGen.OpenAI.Extension;
|
||||
using Azure.AI.Inference;
|
||||
using Azure.AI.OpenAI;
|
||||
using FluentAssertions;
|
||||
using Moq;
|
||||
|
|
@ -304,6 +307,22 @@ public class RolePlayOrchestratorTests
|
|||
await CoderReviewerRunnerTestAsync(agent);
|
||||
}
|
||||
|
||||
[ApiKeyFact("GH_API_KEY")]
|
||||
public async Task LLaMA_3_1_CoderReviewerRunnerTestAsync()
|
||||
{
|
||||
var apiKey = Environment.GetEnvironmentVariable("GH_API_KEY") ?? throw new InvalidOperationException("GH_API_KEY is not set.");
|
||||
var endPoint = "https://models.inference.ai.azure.com";
|
||||
|
||||
var chatCompletionClient = new ChatCompletionsClient(new Uri(endPoint), new Azure.AzureKeyCredential(apiKey));
|
||||
var agent = new ChatCompletionsClientAgent(
|
||||
chatCompletionsClient: chatCompletionClient,
|
||||
name: "assistant",
|
||||
modelName: "Meta-Llama-3.1-70B-Instruct")
|
||||
.RegisterMessageConnector();
|
||||
|
||||
await CoderReviewerRunnerTestAsync(agent);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// This test is to mimic the conversation among coder, reviewer and runner.
|
||||
/// The coder will write the code, the reviewer will review the code, and the runner will run the code.
|
||||
|
|
|
|||
|
|
@ -8,7 +8,6 @@
|
|||
- Create an @AutoGen.OpenAI.OpenAIChatAgent: [Create an OpenAI chat agent](./OpenAIChatAgent-simple-chat.md)
|
||||
- Create a @AutoGen.SemanticKernel.SemanticKernelAgent: [Create a semantic kernel agent](./AutoGen.SemanticKernel/SemanticKernelAgent-simple-chat.md)
|
||||
- Create a @AutoGen.LMStudio.LMStudioAgent: [Connect to LM Studio](./Consume-LLM-server-from-LM-Studio.md)
|
||||
- Create your own agent: [Create your own agent](./Create-your-own-agent.md)
|
||||
|
||||
## Chat with an agent
|
||||
To chat with an agent, typically you can invoke @AutoGen.Core.IAgent.GenerateReplyAsync*. On top of that, you can also use one of the extension methods like @AutoGen.Core.AgentExtension.SendAsync* as shortcuts.
|
||||
|
|
|
|||
|
|
@ -13,8 +13,9 @@ AutoGen.Net provides the following packages, you can choose to install one or mo
|
|||
- `AutoGen.LMStudio`: This package provides the integration agents from LM Studio.
|
||||
- `AutoGen.SemanticKernel`: This package provides the integration agents over semantic kernel.
|
||||
- `AutoGen.Gemini`: This package provides the integration agents from [Google Gemini](https://gemini.google.com/).
|
||||
- `AutoGen.AzureAIInference`: This package provides the integration agents for [Azure AI Inference](https://www.nuget.org/packages/Azure.AI.Inference).
|
||||
- `AutoGen.SourceGenerator`: This package carries a source generator that adds support for type-safe function definition generation.
|
||||
- `AutoGen.DotnetInteractive`: This packages carries dotnet interactive support to execute dotnet code snippet.
|
||||
- `AutoGen.DotnetInteractive`: This packages carries dotnet interactive support to execute code snippets. The current supported language is C#, F#, powershell and python.
|
||||
|
||||
>[!Note]
|
||||
> Help me choose
|
||||
|
|
|
|||
Loading…
Reference in New Issue