// Licensed to the .NET Foundation under one or more agreements.
// The .NET Foundation licenses this file to you under the MIT license.
 
using System;
using System.ClientModel;
using System.ClientModel.Primitives;
using System.Collections.Generic;
using System.ComponentModel;
using System.IO;
using System.Linq;
using System.Net.Http;
using System.Text;
using System.Text.Json;
using System.Text.Json.Nodes;
using System.Threading.Tasks;
using Microsoft.Extensions.Caching.Distributed;
using Microsoft.Extensions.Caching.Memory;
using OpenAI;
using OpenAI.Responses;
using Xunit;
 
#pragma warning disable S103 // Lines should not be too long
 
namespace Microsoft.Extensions.AI;
 
public class OpenAIResponseClientTests
{
    [Fact]
    public void AsIChatClient_InvalidArgs_Throws()
    {
        Assert.Throws<ArgumentNullException>("responseClient", () => ((OpenAIResponseClient)null!).AsIChatClient());
    }
 
    [Fact]
    public void AsIChatClient_ProducesExpectedMetadata()
    {
        Uri endpoint = new("http://localhost/some/endpoint");
        string model = "amazingModel";
 
        var client = new OpenAIClient(new ApiKeyCredential("key"), new OpenAIClientOptions { Endpoint = endpoint });
 
        IChatClient chatClient = client.GetOpenAIResponseClient(model).AsIChatClient();
        var metadata = chatClient.GetService<ChatClientMetadata>();
        Assert.Equal("openai", metadata?.ProviderName);
        Assert.Equal(endpoint, metadata?.ProviderUri);
        Assert.Equal(model, metadata?.DefaultModelId);
    }
 
    [Fact]
    public void GetService_SuccessfullyReturnsUnderlyingClient()
    {
        OpenAIResponseClient openAIClient = new OpenAIClient(new ApiKeyCredential("key")).GetOpenAIResponseClient("model");
        IChatClient chatClient = openAIClient.AsIChatClient();
 
        Assert.Same(chatClient, chatClient.GetService<IChatClient>());
        Assert.Same(openAIClient, chatClient.GetService<OpenAIResponseClient>());
 
        using IChatClient pipeline = chatClient
            .AsBuilder()
            .UseFunctionInvocation()
            .UseOpenTelemetry()
            .UseDistributedCache(new MemoryDistributedCache(Options.Options.Create(new MemoryDistributedCacheOptions())))
            .Build();
 
        Assert.NotNull(pipeline.GetService<FunctionInvokingChatClient>());
        Assert.NotNull(pipeline.GetService<DistributedCachingChatClient>());
        Assert.NotNull(pipeline.GetService<CachingChatClient>());
        Assert.NotNull(pipeline.GetService<OpenTelemetryChatClient>());
 
        Assert.Same(openAIClient, pipeline.GetService<OpenAIResponseClient>());
        Assert.IsType<FunctionInvokingChatClient>(pipeline.GetService<IChatClient>());
    }
 
    [Fact]
    public async Task BasicRequestResponse_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67d327649b288191aeb46a824e49dc40058a5e08c46a181d",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": 20,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "generate_summary": null
              },
              "store": true,
              "temperature": 0.5,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1.0,
              "usage": {
                "input_tokens": 26,
                "input_tokens_details": {
                  "cached_tokens": 0
                },
                "output_tokens": 10,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 36
              },
              "user": null,
              "metadata": {}
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
        });
        Assert.NotNull(response);
 
        Assert.Equal("resp_67d327649b288191aeb46a824e49dc40058a5e08c46a181d", response.ResponseId);
        Assert.Equal("resp_67d327649b288191aeb46a824e49dc40058a5e08c46a181d", response.ConversationId);
        Assert.Equal("Hello! How can I assist you today?", response.Text);
        Assert.Single(response.Messages.Single().Contents);
        Assert.Equal(ChatRole.Assistant, response.Messages.Single().Role);
        Assert.Equal("gpt-4o-mini-2024-07-18", response.ModelId);
        Assert.Equal(DateTimeOffset.FromUnixTimeSeconds(1_741_891_428), response.CreatedAt);
        Assert.Null(response.FinishReason);
 
        Assert.NotNull(response.Usage);
        Assert.Equal(26, response.Usage.InputTokenCount);
        Assert.Equal(10, response.Usage.OutputTokenCount);
        Assert.Equal(36, response.Usage.TotalTokenCount);
    }
 
    [Fact]
    public async Task BasicReasoningResponse_Streaming()
    {
        const string Input = """
            {
              "input":[{
                "type":"message",
                "role":"user",
                "content":[{
                  "type":"input_text",
                  "text":"Calculate the sum of the first 5 positive integers."
                }]
              }],
              "reasoning": {
                "summary": "detailed",
                "effort": "low"
              },
              "model": "o4-mini",
              "stream": true
            }
            """;
 
        // Compressed down for testing purposes; real-world output would be larger.
        const string Output = """
            event: response.created
            data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_68b5ebab461881969ed94149372c2a530698ecbf1b9f2704","object":"response","created_at":1756752811,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"o4-mini-2025-04-16","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":"low","summary":"detailed"},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_68b5ebab461881969ed94149372c2a530698ecbf1b9f2704","object":"response","created_at":1756752811,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"o4-mini-2025-04-16","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":"low","summary":"detailed"},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","type":"reasoning","summary":[]}}
 
            event: response.reasoning_summary_part.added
            data: {"type":"response.reasoning_summary_part.added","sequence_number":3,"item_id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","output_index":0,"summary_index":0,"part":{"type":"summary_text","text":""}}
 
            event: response.reasoning_summary_text.delta
            data: {"type":"response.reasoning_summary_text.delta","sequence_number":4,"item_id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","output_index":0,"summary_index":0,"delta":"**Calcul","obfuscation":"sLkbFySM"}
 
            event: response.reasoning_summary_text.delta
            data: {"type":"response.reasoning_summary_text.delta","sequence_number":5,"item_id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","output_index":0,"summary_index":0,"delta":"ating","obfuscation":"dkm1f6DKqUj"}
 
            event: response.reasoning_summary_text.delta
            data: {"type":"response.reasoning_summary_text.delta","sequence_number":6,"item_id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","output_index":0,"summary_index":0,"delta":" a","obfuscation":"X8ahc2lfCf9eA1"}
 
            event: response.reasoning_summary_text.delta
            data: {"type":"response.reasoning_summary_text.delta","sequence_number":7,"item_id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","output_index":0,"summary_index":0,"delta":" simple","obfuscation":"1rLVyIaNl"}
 
            event: response.reasoning_summary_text.delta
            data: {"type":"response.reasoning_summary_text.delta","sequence_number":8,"item_id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","output_index":0,"summary_index":0,"delta":" sum","obfuscation":"jCK7mgNR80Re"}
 
            event: response.reasoning_summary_text.done
            data: {"type":"response.reasoning_summary_text.done","sequence_number":9,"item_id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","output_index":0,"summary_index":0,"text":"**Calculating a simple sum**"}
 
            event: response.reasoning_summary_part.done
            data: {"type":"response.reasoning_summary_part.done","sequence_number":10,"item_id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","output_index":0,"summary_index":0,"part":{"type":"summary_text","text":"**Calculating a simple sum**"}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":11,"output_index":0,"item":{"id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","type":"reasoning","summary":[{"type":"summary_text","text":"**Calculating a simple sum**"}]}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":12,"output_index":1,"item":{"id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","type":"message","status":"in_progress","content":[],"role":"assistant"}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","sequence_number":13,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":14,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":"The","logprobs":[],"obfuscation":"japg2KaCkjNsp"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":15,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" sum","logprobs":[],"obfuscation":"1BEqjKQ0KU41"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":16,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" of","logprobs":[],"obfuscation":"GUqom1rsdZsnT"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":17,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" the","logprobs":[],"obfuscation":"UmCms91yrTlg"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":18,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" first","logprobs":[],"obfuscation":"AyNbZpfTXo"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":19,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" ","logprobs":[],"obfuscation":"tuyz4HkKODFQRtk"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":20,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":"5","logprobs":[],"obfuscation":"QAwyISolmjXfTlc"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":21,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" positive","logprobs":[],"obfuscation":"2Euge1H"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":22,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" integers","logprobs":[],"obfuscation":"ih0Znt8"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":23,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" is","logprobs":[],"obfuscation":"oQihR5Pw8jRz5"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":24,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":" 15","logprobs":[],"obfuscation":"7TdJ1FWlZF8lTd"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":25,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"delta":".","logprobs":[],"obfuscation":"x2VAJKlWI8qjgYq"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","sequence_number":26,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"text":"The sum of the first 5 positive integers is 15.","logprobs":[]}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","sequence_number":27,"item_id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","output_index":1,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":"The sum of the first 5 positive integers is 15."}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":28,"output_index":1,"item":{"id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"The sum of the first 5 positive integers is 15."}],"role":"assistant"}}
 
            event: response.completed
            data: {"type":"response.completed","sequence_number":29,"response":{"id":"resp_68b5ebab461881969ed94149372c2a530698ecbf1b9f2704","object":"response","created_at":1756752811,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"o4-mini-2025-04-16","output":[{"id":"rs_68b5ebabc0088196afb9fa86b487732d0698ecbf1b9f2704","type":"reasoning","summary":[{"type":"summary_text","text":"**Calculating a simple sum**"}]},{"id":"msg_68b5ebae5a708196b74b94f22ca8995e0698ecbf1b9f2704","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"The sum of the first 5 positive integers is 15."}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":"low","summary":"detailed"},"safety_identifier":null,"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":17,"input_tokens_details":{"cached_tokens":0},"output_tokens":122,"output_tokens_details":{"reasoning_tokens":64},"total_tokens":139},"user":null,"metadata":{}}}
 
 
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "o4-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("Calculate the sum of the first 5 positive integers.", new()
        {
            RawRepresentationFactory = options => new ResponseCreationOptions
            {
                ReasoningOptions = new()
                {
                    ReasoningEffortLevel = ResponseReasoningEffortLevel.Low,
                    ReasoningSummaryVerbosity = ResponseReasoningSummaryVerbosity.Detailed
                }
            }
        }))
        {
            updates.Add(update);
        }
 
        Assert.Equal("The sum of the first 5 positive integers is 15.", string.Concat(updates.Select(u => u.Text)));
 
        var createdAt = DateTimeOffset.FromUnixTimeSeconds(1_756_752_811);
        Assert.Equal(30, updates.Count);
 
        for (int i = 0; i < updates.Count; i++)
        {
            Assert.Equal("resp_68b5ebab461881969ed94149372c2a530698ecbf1b9f2704", updates[i].ResponseId);
            Assert.Equal("resp_68b5ebab461881969ed94149372c2a530698ecbf1b9f2704", updates[i].ConversationId);
            Assert.Equal(createdAt, updates[i].CreatedAt);
            Assert.Equal("o4-mini-2025-04-16", updates[i].ModelId);
            Assert.Null(updates[i].AdditionalProperties);
 
            if (i is (>= 4 and <= 8))
            {
                // Reasoning updates
                Assert.Single(updates[i].Contents);
                Assert.Null(updates[i].Role);
 
                var reasoning = Assert.IsType<TextReasoningContent>(updates[i].Contents.Single());
                Assert.NotNull(reasoning);
                Assert.NotNull(reasoning.Text);
            }
            else if (i is (>= 14 and <= 25) or 29)
            {
                // Response Complete and Assistant message updates
                Assert.Single(updates[i].Contents);
            }
            else
            {
                // Other updates
                Assert.Empty(updates[i].Contents);
            }
 
            Assert.Equal(i < updates.Count - 1 ? null : ChatFinishReason.Stop, updates[i].FinishReason);
        }
 
        UsageContent usage = updates.SelectMany(u => u.Contents).OfType<UsageContent>().Single();
        Assert.Equal(17, usage.Details.InputTokenCount);
        Assert.Equal(122, usage.Details.OutputTokenCount);
        Assert.Equal(139, usage.Details.TotalTokenCount);
    }
 
    [Fact]
    public async Task BasicRequestResponse_Streaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"hello"}]
                    }
                ],
                "stream":true,
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"in_progress","role":"assistant","content":[]}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"Hello"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"!"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":" How"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":" can"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":" I"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":" assist"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":" you"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":" today"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"?"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"text":"Hello! How can I assist you today?"}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hello! How can I assist you today?","annotations":[]}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello! How can I assist you today?","annotations":[]}]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"completed","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello! How can I assist you today?","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":{"input_tokens":26,"input_tokens_details":{"cached_tokens":0},"output_tokens":10,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":36},"user":null,"metadata":{}}}
 
 
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
        }))
        {
            updates.Add(update);
        }
 
        Assert.Equal("Hello! How can I assist you today?", string.Concat(updates.Select(u => u.Text)));
 
        var createdAt = DateTimeOffset.FromUnixTimeSeconds(1_741_892_091);
        Assert.Equal(17, updates.Count);
 
        for (int i = 0; i < updates.Count; i++)
        {
            Assert.Equal("resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77", updates[i].ResponseId);
            Assert.Equal("resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77", updates[i].ConversationId);
            Assert.Equal(createdAt, updates[i].CreatedAt);
            Assert.Equal("gpt-4o-mini-2024-07-18", updates[i].ModelId);
            Assert.Null(updates[i].AdditionalProperties);
            Assert.Equal((i >= 4 && i <= 12) || i == 16 ? 1 : 0, updates[i].Contents.Count);
            Assert.Equal(i < updates.Count - 1 ? null : ChatFinishReason.Stop, updates[i].FinishReason);
        }
 
        for (int i = 4; i < updates.Count; i++)
        {
            Assert.Equal(ChatRole.Assistant, updates[i].Role);
        }
 
        UsageContent usage = updates.SelectMany(u => u.Contents).OfType<UsageContent>().Single();
        Assert.Equal(26, usage.Details.InputTokenCount);
        Assert.Equal(10, usage.Details.OutputTokenCount);
        Assert.Equal(36, usage.Details.TotalTokenCount);
    }
 
    [Fact]
    public async Task ChatOptions_StrictRespected()
    {
        const string Input = """
            {
                "model": "gpt-4o-mini",
                "input": [
                    {
                        "type": "message",
                        "role": "user",
                        "content": [
                            {
                                "type": "input_text",
                                "text": "hello"
                            }
                        ]
                    }
                ],
                "tool_choice": "auto",
                "tools": [
                    {
                        "type": "function",
                        "name": "GetPersonAge",
                        "description": "Gets the age of the specified person.",
                        "parameters": {
                            "type": "object",
                            "required": [],
                            "properties": {},
                            "additionalProperties": false
                        },
                        "strict": true
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67d327649b288191aeb46a824e49dc40058a5e08c46a181d",
              "object": "response",
              "status": "completed",
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            Tools = [AIFunctionFactory.Create(() => 42, "GetPersonAge", "Gets the age of the specified person.")],
            AdditionalProperties = new()
            {
                ["strictJsonSchema"] = true,
            },
        });
        Assert.NotNull(response);
    }
 
    [Fact]
    public async Task ChatOptions_DoNotOverwrite_NotNullPropertiesInRawRepresentation_NonStreaming()
    {
        const string Input = """
            {
                "temperature": 0.5,
                "top_p": 0.5,
                "previous_response_id": "resp_42",
                "model": "gpt-4o-mini",
                "max_output_tokens": 10,
                "text": {
                    "format": {
                        "type": "text"
                    }
                },
                "tools": [
                    {
                        "type": "function",
                        "name": "GetPersonAge",
                        "description": "Gets the age of the specified person.",
                        "parameters": {
                            "type": "object",
                            "required": [
                                "personName"
                            ],
                            "properties": {
                                "personName": {
                                    "description": "The person whose age is being requested",
                                    "type": "string"
                                }
                            },
                            "additionalProperties": false
                        },
                        "strict": null
                    },
                    {
                        "type": "function",
                        "name": "GetPersonAge",
                        "description": "Gets the age of the specified person.",
                        "parameters": {
                            "type": "object",
                            "required": [
                                "personName"
                            ],
                            "properties": {
                                "personName": {
                                    "description": "The person whose age is being requested",
                                    "type": "string"
                                }
                            },
                            "additionalProperties": false
                        },
                        "strict": null
                    }
                ],
                "tool_choice": "auto",
                "input": [
                    {
                        "type": "message",
                        "role": "user",
                        "content": [
                            {
                                "type": "input_text",
                                "text": "hello"
                            }
                        ]
                    }
                ],
                "parallel_tool_calls": true
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67d327649b288191aeb46a824e49dc40058a5e08c46a181d",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": 20,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "generate_summary": null
              },
              "store": true,
              "temperature": 0.5,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1.0,
              "usage": {
                "input_tokens": 26,
                "input_tokens_details": {
                  "cached_tokens": 0
                },
                "output_tokens": 10,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 36
              },
              "user": null,
              "metadata": {}
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, modelId: "gpt-4o-mini");
        AIFunction tool = AIFunctionFactory.Create(([Description("The person whose age is being requested")] string personName) => 42, "GetPersonAge", "Gets the age of the specified person.");
 
        ChatOptions chatOptions = new()
        {
            RawRepresentationFactory = (c) =>
            {
                ResponseCreationOptions openAIOptions = new()
                {
                    MaxOutputTokenCount = 10,
                    PreviousResponseId = "resp_42",
                    TopP = 0.5f,
                    Temperature = 0.5f,
                    ParallelToolCallsEnabled = true,
                    ToolChoice = ResponseToolChoice.CreateAutoChoice(),
                    TextOptions = new ResponseTextOptions
                    {
                        TextFormat = ResponseTextFormat.CreateTextFormat()
                    },
                };
                openAIOptions.Tools.Add(tool.AsOpenAIResponseTool());
                return openAIOptions;
            },
            ModelId = null,
            MaxOutputTokens = 1,
            ConversationId = "foo",
            TopP = 0.125f,
            Temperature = 0.125f,
            AllowMultipleToolCalls = false,
            Tools = [tool],
            ToolMode = ChatToolMode.None,
            ResponseFormat = ChatResponseFormat.Json
        };
 
        var response = await client.GetResponseAsync("hello", chatOptions);
        Assert.NotNull(response);
        Assert.Equal("Hello! How can I assist you today?", response.Text);
    }
 
    [Fact]
    public async Task MultipleOutputItems_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67d327649b288191aeb46a824e49dc40058a5e08c46a181d",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": 20,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello!",
                      "annotations": []
                    }
                  ]
                },
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a182e",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": " How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "generate_summary": null
              },
              "store": true,
              "temperature": 0.5,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1.0,
              "usage": {
                "input_tokens": 26,
                "input_tokens_details": {
                  "cached_tokens": 0
                },
                "output_tokens": 10,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 36
              },
              "user": null,
              "metadata": {}
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
        });
        Assert.NotNull(response);
 
        Assert.Equal("resp_67d327649b288191aeb46a824e49dc40058a5e08c46a181d", response.ResponseId);
        Assert.Equal("resp_67d327649b288191aeb46a824e49dc40058a5e08c46a181d", response.ConversationId);
        Assert.Equal("gpt-4o-mini-2024-07-18", response.ModelId);
        Assert.Equal(DateTimeOffset.FromUnixTimeSeconds(1_741_891_428), response.CreatedAt);
        Assert.Null(response.FinishReason);
 
        Assert.Equal(2, response.Messages.Count);
        Assert.Equal(ChatRole.Assistant, response.Messages[0].Role);
        Assert.Equal("Hello!", response.Messages[0].Text);
        Assert.Equal(ChatRole.Assistant, response.Messages[1].Role);
        Assert.Equal(" How can I assist you today?", response.Messages[1].Text);
 
        Assert.NotNull(response.Usage);
        Assert.Equal(26, response.Usage.InputTokenCount);
        Assert.Equal(10, response.Usage.OutputTokenCount);
        Assert.Equal(36, response.Usage.TotalTokenCount);
    }
 
    [Theory]
    [InlineData("user")]
    [InlineData("tool")]
    public async Task McpToolCall_ApprovalRequired_NonStreaming(string role)
    {
        string input = """
            {
              "model": "gpt-4o-mini",
              "tools": [
                {
                  "type": "mcp",
                  "server_label": "deepwiki",
                  "server_url": "https://mcp.deepwiki.com/mcp"
                }
              ],
              "tool_choice": "auto",
              "input": [
                {
                  "type": "message",
                  "role": "user",
                  "content": [
                    {
                      "type": "input_text",
                      "text": "Tell me the path to the README.md file for Microsoft.Extensions.AI.Abstractions in the dotnet/extensions repository"
                    }
                  ]
                }
              ]
            }
            """;
 
        string output = """
            {
              "id": "resp_04e29d5bdd80bd9f0068e6b01f786081a29148febb92892aee",
              "object": "response",
              "created_at": 1759948831,
              "status": "completed",
              "background": false,
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "max_tool_calls": null,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "id": "mcpr_04e29d5bdd80bd9f0068e6b022a9c081a2ae898104b7a75051",
                  "type": "mcp_approval_request",
                  "arguments": "{\"repoName\":\"dotnet/extensions\"}",
                  "name": "ask_question",
                  "server_label": "deepwiki"
                }
              ],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "prompt_cache_key": null,
              "reasoning": {
                "effort": null,
                "summary": null
              },
              "safety_identifier": null,
              "service_tier": "default",
              "store": true,
              "temperature": 1.0,
              "text": {
                "format": {
                  "type": "text"
                },
                "verbosity": "medium"
              },
              "tool_choice": "auto",
              "tools": [
                {
                  "type": "mcp",
                  "allowed_tools": null,
                  "headers": null,
                  "require_approval": "always",
                  "server_description": null,
                  "server_label": "deepwiki",
                  "server_url": "https://mcp.deepwiki.com/<redacted>"
                }
              ],
              "top_logprobs": 0,
              "top_p": 1.0,
              "truncation": "disabled",
              "usage": {
                "input_tokens": 193,
                "input_tokens_details": {
                  "cached_tokens": 0
                },
                "output_tokens": 23,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 216
              },
              "user": null,
              "metadata": {}
            }
            """;
 
        var chatOptions = new ChatOptions
        {
            Tools = [new HostedMcpServerTool("deepwiki", new Uri("https://mcp.deepwiki.com/mcp"))]
        };
        McpServerToolApprovalRequestContent approvalRequest;
 
        using (VerbatimHttpHandler handler = new(input, output))
        using (HttpClient httpClient = new(handler))
        using (IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini"))
        {
            var response = await client.GetResponseAsync(
                "Tell me the path to the README.md file for Microsoft.Extensions.AI.Abstractions in the dotnet/extensions repository",
                chatOptions);
 
            approvalRequest = Assert.Single(response.Messages.SelectMany(m => m.Contents).OfType<McpServerToolApprovalRequestContent>());
            chatOptions.ConversationId = response.ConversationId;
        }
 
        input = $$"""
            {
                "previous_response_id": "resp_04e29d5bdd80bd9f0068e6b01f786081a29148febb92892aee",
                "model": "gpt-4o-mini",
                "tools": [
                    {
                        "type": "mcp",
                        "server_label": "deepwiki",
                        "server_url": "https://mcp.deepwiki.com/mcp"
                    }
                ],
                "tool_choice": "auto",
                "input": [
                    {
                        "type": "mcp_approval_response",
                        "approval_request_id": "mcpr_04e29d5bdd80bd9f0068e6b022a9c081a2ae898104b7a75051",
                        "approve": true
                    }
                ]
            }
            """;
 
        output = """
            {
              "id": "resp_06ee3b1962eeb8470068e6b21c377081a3a20dbf60eee7a736",
              "object": "response",
              "created_at": 1759949340,
              "status": "completed",
              "background": false,
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "max_tool_calls": null,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "id": "mcp_06ee3b1962eeb8470068e6b21cbaa081a3b5aa2a6c989f4c6f",
                  "type": "mcp_call",
                  "status": "completed",
                  "approval_request_id": "mcpr_06ee3b1962eeb8470068e6b192985c81a383a16059ecd8230e",
                  "arguments": "{\"repoName\":\"dotnet/extensions\",\"question\":\"What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?\"}",
                  "error": null,
                  "name": "ask_question",
                  "output": "The `README.md` file for `Microsoft.Extensions.AI.Abstractions` is located at `src/Libraries/Microsoft.Extensions.AI.Abstractions/README.md` within the `dotnet/extensions` repository.  This file provides an overview of the package, including installation instructions and usage examples for its core interfaces like `IChatClient` and `IEmbeddingGenerator`. \n\n## Path to README.md\n\nThe specific path to the `README.md` file for the `Microsoft.Extensions.AI.Abstractions` project is `src/Libraries/Microsoft.Extensions.AI.Abstractions/README.md`.  This path is also referenced in the `AI Extensions Framework` wiki page as a relevant source file. \n\n## Notes\n\nThe `Packaging.targets` file in the `eng/MSBuild` directory indicates that `README.md` files are included in packages when `IsPackable` and `IsShipping` properties are true.  This suggests that the `README.md` file located at `src/Libraries/Microsoft.Extensions.AI.Abstractions/README.md` is intended to be part of the distributed NuGet package for `Microsoft.Extensions.AI.Abstractions`. \n\nWiki pages you might want to explore:\n- [AI Extensions Framework (dotnet/extensions)](/wiki/dotnet/extensions#3)\n- [Chat Completion (dotnet/extensions)](/wiki/dotnet/extensions#3.3)\n\nView this search on DeepWiki: https://deepwiki.com/search/what-is-the-path-to-the-readme_315595bd-9b39-4f04-9fa3-42dc778fa9f3\n",
                  "server_label": "deepwiki"
                },
                {
                  "id": "msg_06ee3b1962eeb8470068e6b226ab0081a39fccce9aa47aedbc",
                  "type": "message",
                  "status": "completed",
                  "content": [
                    {
                      "type": "output_text",
                      "annotations": [],
                      "logprobs": [],
                      "text": "The `README.md` file for `Microsoft.Extensions.AI.Abstractions` is located at:\n\n```\nsrc/Libraries/Microsoft.Extensions.AI.Abstractions/README.md\n```\n\nThis file provides an overview of the `Microsoft.Extensions.AI.Abstractions` package, including installation instructions and usage examples for its core interfaces like `IChatClient` and `IEmbeddingGenerator`."
                    }
                  ],
                  "role": "assistant"
                }
              ],
              "parallel_tool_calls": true,
              "previous_response_id": "resp_06ee3b1962eeb8470068e6b18e0db881a3bdfd255a60327cdc",
              "prompt_cache_key": null,
              "reasoning": {
                "effort": null,
                "summary": null
              },
              "safety_identifier": null,
              "service_tier": "default",
              "store": true,
              "temperature": 1.0,
              "text": {
                "format": {
                  "type": "text"
                },
                "verbosity": "medium"
              },
              "tool_choice": "auto",
              "tools": [
                {
                  "type": "mcp",
                  "allowed_tools": null,
                  "headers": null,
                  "require_approval": "always",
                  "server_description": null,
                  "server_label": "deepwiki",
                  "server_url": "https://mcp.deepwiki.com/<redacted>"
                }
              ],
              "top_logprobs": 0,
              "top_p": 1.0,
              "truncation": "disabled",
              "usage": {
                "input_tokens": 542,
                "input_tokens_details": {
                  "cached_tokens": 0
                },
                "output_tokens": 72,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 614
              },
              "user": null,
              "metadata": {}
            }
            """;
 
        using (VerbatimHttpHandler handler = new(input, output))
        using (HttpClient httpClient = new(handler))
        using (IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini"))
        {
            var response = await client.GetResponseAsync(
                new ChatMessage(new ChatRole(role), [approvalRequest.CreateResponse(true)]), chatOptions);
 
            Assert.NotNull(response);
 
            Assert.Equal("resp_06ee3b1962eeb8470068e6b21c377081a3a20dbf60eee7a736", response.ResponseId);
            Assert.Equal("resp_06ee3b1962eeb8470068e6b21c377081a3a20dbf60eee7a736", response.ConversationId);
            Assert.Equal("gpt-4o-mini-2024-07-18", response.ModelId);
            Assert.Equal(DateTimeOffset.FromUnixTimeSeconds(1_759_949_340), response.CreatedAt);
            Assert.Null(response.FinishReason);
 
            var message = Assert.Single(response.Messages);
            Assert.Equal(ChatRole.Assistant, response.Messages[0].Role);
            Assert.Equal("The `README.md` file for `Microsoft.Extensions.AI.Abstractions` is located at:\n\n```\nsrc/Libraries/Microsoft.Extensions.AI.Abstractions/README.md\n```\n\nThis file provides an overview of the `Microsoft.Extensions.AI.Abstractions` package, including installation instructions and usage examples for its core interfaces like `IChatClient` and `IEmbeddingGenerator`.", response.Messages[0].Text);
 
            Assert.Equal(3, message.Contents.Count);
 
            var call = Assert.IsType<McpServerToolCallContent>(message.Contents[0]);
            Assert.Equal("mcp_06ee3b1962eeb8470068e6b21cbaa081a3b5aa2a6c989f4c6f", call.CallId);
            Assert.Equal("deepwiki", call.ServerName);
            Assert.Equal("ask_question", call.ToolName);
            Assert.NotNull(call.Arguments);
            Assert.Equal(2, call.Arguments.Count);
            Assert.Equal("dotnet/extensions", ((JsonElement)call.Arguments["repoName"]!).GetString());
            Assert.Equal("What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?", ((JsonElement)call.Arguments["question"]!).GetString());
 
            var result = Assert.IsType<McpServerToolResultContent>(message.Contents[1]);
            Assert.Equal("mcp_06ee3b1962eeb8470068e6b21cbaa081a3b5aa2a6c989f4c6f", result.CallId);
            Assert.NotNull(result.Output);
            Assert.StartsWith("The `README.md` file for `Microsoft.Extensions.AI.Abstractions` is located at", Assert.IsType<TextContent>(Assert.Single(result.Output)).Text);
 
            Assert.NotNull(response.Usage);
            Assert.Equal(542, response.Usage.InputTokenCount);
            Assert.Equal(72, response.Usage.OutputTokenCount);
            Assert.Equal(614, response.Usage.TotalTokenCount);
        }
    }
 
    [Theory]
    [InlineData(false)]
    [InlineData(true)]
    public async Task McpToolCall_ApprovalNotRequired_NonStreaming(bool rawTool)
    {
        const string Input = """
            {
                "model": "gpt-4o-mini",
                "tools": [
                    {
                        "type": "mcp",
                        "server_label": "deepwiki",
                        "server_url": "https://mcp.deepwiki.com/mcp",
                        "require_approval": "never"
                    }
                ],
                "tool_choice": "auto",
                "input": [
                    {
                        "type": "message",
                        "role": "user",
                        "content": [
                            {
                                "type": "input_text",
                                "text": "Tell me the path to the README.md file for Microsoft.Extensions.AI.Abstractions in the dotnet/extensions repository"
                            }
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
                "id": "resp_68be416397ec81918c48ef286530b8140384f747588fc3f5",
                "object": "response",
                "created_at": 1757299043,
                "status": "completed",
                "background": false,
                "error": null,
                "incomplete_details": null,
                "instructions": null,
                "max_output_tokens": null,
                "max_tool_calls": null,
                "model": "gpt-4o-mini-2024-07-18",
                "output": [
                    {
                        "id": "mcpl_68be4163aa80819185e792abdcde71670384f747588fc3f5",
                        "type": "mcp_list_tools",
                        "server_label": "deepwiki",
                        "tools": [
                            {
                                "annotations": {
                                    "read_only": false
                                },
                                "description": "Get a list of documentation topics for a GitHub repository",
                                "input_schema": {
                                    "type": "object",
                                    "properties": {
                                        "repoName": {
                                            "type": "string",
                                            "description": "GitHub repository: owner/repo (e.g. \"facebook/react\")"
                                        }
                                    },
                                    "required": [
                                        "repoName"
                                    ],
                                    "additionalProperties": false,
                                    "$schema": "http://json-schema.org/draft-07/schema#"
                                },
                                "name": "read_wiki_structure"
                            },
                            {
                                "annotations": {
                                    "read_only": false
                                },
                                "description": "View documentation about a GitHub repository",
                                "input_schema": {
                                    "type": "object",
                                    "properties": {
                                        "repoName": {
                                            "type": "string",
                                            "description": "GitHub repository: owner/repo (e.g. \"facebook/react\")"
                                        }
                                    },
                                    "required": [
                                        "repoName"
                                    ],
                                    "additionalProperties": false,
                                    "$schema": "http://json-schema.org/draft-07/schema#"
                                },
                                "name": "read_wiki_contents"
                            },
                            {
                                "annotations": {
                                    "read_only": false
                                },
                                "description": "Ask any question about a GitHub repository",
                                "input_schema": {
                                    "type": "object",
                                    "properties": {
                                        "repoName": {
                                            "type": "string",
                                            "description": "GitHub repository: owner/repo (e.g. \"facebook/react\")"
                                        },
                                        "question": {
                                            "type": "string",
                                            "description": "The question to ask about the repository"
                                        }
                                    },
                                    "required": [
                                        "repoName",
                                        "question"
                                    ],
                                    "additionalProperties": false,
                                    "$schema": "http://json-schema.org/draft-07/schema#"
                                },
                                "name": "ask_question"
                            }
                        ]
                    },
                    {
                        "id": "mcp_68be4166acfc8191bc5e0a751eed358b0384f747588fc3f5",
                        "type": "mcp_call",
                        "approval_request_id": null,
                        "arguments": "{\"repoName\":\"dotnet/extensions\"}",
                        "error": null,
                        "name": "read_wiki_structure",
                        "output": "Available pages for dotnet/extensions:\n\n- 1 Overview\n- 2 Build System and CI/CD\n- 3 AI Extensions Framework\n  - 3.1 Core Abstractions\n  - 3.2 AI Function System\n  - 3.3 Chat Completion\n  - 3.4 Caching System\n  - 3.5 Evaluation and Reporting\n- 4 HTTP Resilience and Diagnostics\n  - 4.1 Standard Resilience\n  - 4.2 Hedging Strategies\n- 5 Telemetry and Compliance\n- 6 Testing Infrastructure\n  - 6.1 AI Service Integration Testing\n  - 6.2 Time Provider Testing",
                        "server_label": "deepwiki"
                    },
                    {
                        "id": "mcp_68be416900f88191837ae0718339a4ce0384f747588fc3f5",
                        "type": "mcp_call",
                        "approval_request_id": null,
                        "arguments": "{\"repoName\":\"dotnet/extensions\",\"question\":\"What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?\"}",
                        "error": null,
                        "name": "ask_question",
                        "output": "The `README.md` file for `Microsoft.Extensions.AI.Abstractions` is located at `src/Libraries/Microsoft.Extensions.AI.Abstractions/README.md` within the `dotnet/extensions` repository.  This file provides an overview of the `Microsoft.Extensions.AI.Abstractions` package, including installation instructions and usage examples for its core interfaces like `IChatClient` and `IEmbeddingGenerator`. \n\n## Path to README.md\n\nThe specific path to the `README.md` file for the `Microsoft.Extensions.AI.Abstractions` project is `src/Libraries/Microsoft.Extensions.AI.Abstractions/README.md`.  This path is also referenced in the `AI Extensions Framework` wiki page as a relevant source file. \n\n## Notes\n\nThe `Packaging.targets` file in the `eng/MSBuild` directory indicates that `README.md` files are included in packages when `IsPackable` and `IsShipping` properties are true.  This suggests that the `README.md` file located at `src/Libraries/Microsoft.Extensions.AI.Abstractions/README.md` is intended to be part of the distributed NuGet package for `Microsoft.Extensions.AI.Abstractions`. \n\nWiki pages you might want to explore:\n- [AI Extensions Framework (dotnet/extensions)](/wiki/dotnet/extensions#3)\n- [Chat Completion (dotnet/extensions)](/wiki/dotnet/extensions#3.3)\n\nView this search on DeepWiki: https://deepwiki.com/search/what-is-the-path-to-the-readme_315595bd-9b39-4f04-9fa3-42dc778fa9f3\n",
                        "server_label": "deepwiki"
                    },
                    {
                        "id": "msg_68be416fb43c819194a1d4ace2643a7e0384f747588fc3f5",
                        "type": "message",
                        "status": "completed",
                        "content": [
                            {
                                "type": "output_text",
                                "annotations": [],
                                "logprobs": [],
                                "text": "The `README.md` file for `Microsoft.Extensions.AI.Abstractions` is located at:\n\n```\nsrc/Libraries/Microsoft.Extensions.AI.Abstractions/README.md\n```\n\nThis file includes an overview, installation instructions, and usage examples related to the package."
                            }
                        ],
                        "role": "assistant"
                    }
                ],
                "parallel_tool_calls": true,
                "previous_response_id": null,
                "prompt_cache_key": null,
                "reasoning": {
                    "effort": null,
                    "summary": null
                },
                "safety_identifier": null,
                "service_tier": "default",
                "store": true,
                "temperature": 1,
                "text": {
                    "format": {
                        "type": "text"
                    },
                    "verbosity": "medium"
                },
                "tool_choice": "auto",
                "tools": [
                    {
                        "type": "mcp",
                        "allowed_tools": null,
                        "headers": null,
                        "require_approval": "never",
                        "server_description": null,
                        "server_label": "deepwiki",
                        "server_url": "https://mcp.deepwiki.com/<redacted>"
                    }
                ],
                "top_logprobs": 0,
                "top_p": 1,
                "truncation": "disabled",
                "usage": {
                    "input_tokens": 1329,
                    "input_tokens_details": {
                        "cached_tokens": 0
                    },
                    "output_tokens": 123,
                    "output_tokens_details": {
                        "reasoning_tokens": 0
                    },
                    "total_tokens": 1452
                },
                "user": null,
                "metadata": {}
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        AITool mcpTool = rawTool ?
            ResponseTool.CreateMcpTool("deepwiki", serverUri: new("https://mcp.deepwiki.com/mcp"), toolCallApprovalPolicy: new McpToolCallApprovalPolicy(GlobalMcpToolCallApprovalPolicy.NeverRequireApproval)).AsAITool() :
            new HostedMcpServerTool("deepwiki", new Uri("https://mcp.deepwiki.com/mcp"))
            {
                ApprovalMode = HostedMcpServerToolApprovalMode.NeverRequire,
            };
 
        ChatOptions chatOptions = new()
        {
            Tools = [mcpTool],
        };
 
        var response = await client.GetResponseAsync("Tell me the path to the README.md file for Microsoft.Extensions.AI.Abstractions in the dotnet/extensions repository", chatOptions);
        Assert.NotNull(response);
 
        Assert.Equal("resp_68be416397ec81918c48ef286530b8140384f747588fc3f5", response.ResponseId);
        Assert.Equal("resp_68be416397ec81918c48ef286530b8140384f747588fc3f5", response.ConversationId);
        Assert.Equal("gpt-4o-mini-2024-07-18", response.ModelId);
        Assert.Equal(DateTimeOffset.FromUnixTimeSeconds(1_757_299_043), response.CreatedAt);
        Assert.Null(response.FinishReason);
 
        var message = Assert.Single(response.Messages);
        Assert.Equal(ChatRole.Assistant, response.Messages[0].Role);
        Assert.Equal("The `README.md` file for `Microsoft.Extensions.AI.Abstractions` is located at:\n\n```\nsrc/Libraries/Microsoft.Extensions.AI.Abstractions/README.md\n```\n\nThis file includes an overview, installation instructions, and usage examples related to the package.", response.Messages[0].Text);
 
        Assert.Equal(6, message.Contents.Count);
 
        var firstCall = Assert.IsType<McpServerToolCallContent>(message.Contents[1]);
        Assert.Equal("mcp_68be4166acfc8191bc5e0a751eed358b0384f747588fc3f5", firstCall.CallId);
        Assert.Equal("deepwiki", firstCall.ServerName);
        Assert.Equal("read_wiki_structure", firstCall.ToolName);
        Assert.NotNull(firstCall.Arguments);
        Assert.Single(firstCall.Arguments);
        Assert.Equal("dotnet/extensions", ((JsonElement)firstCall.Arguments["repoName"]!).GetString());
 
        var firstResult = Assert.IsType<McpServerToolResultContent>(message.Contents[2]);
        Assert.Equal("mcp_68be4166acfc8191bc5e0a751eed358b0384f747588fc3f5", firstResult.CallId);
        Assert.NotNull(firstResult.Output);
        Assert.StartsWith("Available pages for dotnet/extensions", Assert.IsType<TextContent>(Assert.Single(firstResult.Output)).Text);
 
        var secondCall = Assert.IsType<McpServerToolCallContent>(message.Contents[3]);
        Assert.Equal("mcp_68be416900f88191837ae0718339a4ce0384f747588fc3f5", secondCall.CallId);
        Assert.Equal("deepwiki", secondCall.ServerName);
        Assert.Equal("ask_question", secondCall.ToolName);
        Assert.NotNull(secondCall.Arguments);
        Assert.Equal("dotnet/extensions", ((JsonElement)secondCall.Arguments["repoName"]!).GetString());
        Assert.Equal("What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?", ((JsonElement)secondCall.Arguments["question"]!).GetString());
 
        var secondResult = Assert.IsType<McpServerToolResultContent>(message.Contents[4]);
        Assert.Equal("mcp_68be416900f88191837ae0718339a4ce0384f747588fc3f5", secondResult.CallId);
        Assert.NotNull(secondResult.Output);
        Assert.StartsWith("The `README.md` file for `Microsoft.Extensions.AI.Abstractions` is located at", Assert.IsType<TextContent>(Assert.Single(secondResult.Output)).Text);
 
        Assert.NotNull(response.Usage);
        Assert.Equal(1329, response.Usage.InputTokenCount);
        Assert.Equal(123, response.Usage.OutputTokenCount);
        Assert.Equal(1452, response.Usage.TotalTokenCount);
    }
 
    [Fact]
    public async Task McpToolCall_ApprovalNotRequired_Streaming()
    {
        const string Input = """
            {
                "model": "gpt-4o-mini",
                "tools": [
                    {
                        "type": "mcp",
                        "server_label": "deepwiki",
                        "server_url": "https://mcp.deepwiki.com/mcp",
                        "require_approval": "never"
                    }
                ],
                "tool_choice": "auto",
                "input": [
                    {
                        "type": "message",
                        "role": "user",
                        "content": [
                            {
                                "type": "input_text",
                                "text": "Tell me the path to the README.md file for Microsoft.Extensions.AI.Abstractions in the dotnet/extensions repository"
                            }
                        ]
                    }
                ],
                "stream": true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_68be44fd7298819e82fd82c8516e970d03a2537be0e84a54","object":"response","created_at":1757299965,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[{"type":"mcp","allowed_tools":null,"headers":null,"require_approval":"never","server_description":null,"server_label":"deepwiki","server_url":"https://mcp.deepwiki.com/<redacted>"}],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_68be44fd7298819e82fd82c8516e970d03a2537be0e84a54","object":"response","created_at":1757299965,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[{"type":"mcp","allowed_tools":null,"headers":null,"require_approval":"never","server_description":null,"server_label":"deepwiki","server_url":"https://mcp.deepwiki.com/<redacted>"}],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"mcpl_68be44fd8f68819eba7a74a2f6d27a5a03a2537be0e84a54","type":"mcp_list_tools","server_label":"deepwiki","tools":[]}}
 
            event: response.mcp_list_tools.in_progress
            data: {"type":"response.mcp_list_tools.in_progress","sequence_number":3,"output_index":0,"item_id":"mcpl_68be44fd8f68819eba7a74a2f6d27a5a03a2537be0e84a54"}
 
            event: response.mcp_list_tools.completed
            data: {"type":"response.mcp_list_tools.completed","sequence_number":4,"output_index":0,"item_id":"mcpl_68be44fd8f68819eba7a74a2f6d27a5a03a2537be0e84a54"}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":5,"output_index":0,"item":{"id":"mcpl_68be44fd8f68819eba7a74a2f6d27a5a03a2537be0e84a54","type":"mcp_list_tools","server_label":"deepwiki","tools":[{"annotations":{"read_only":false},"description":"Get a list of documentation topics for a GitHub repository","input_schema":{"type":"object","properties":{"repoName":{"type":"string","description":"GitHub repository: owner/repo (e.g. \"facebook/react\")"}},"required":["repoName"],"additionalProperties":false,"$schema":"http://json-schema.org/draft-07/schema#"},"name":"read_wiki_structure"},{"annotations":{"read_only":false},"description":"View documentation about a GitHub repository","input_schema":{"type":"object","properties":{"repoName":{"type":"string","description":"GitHub repository: owner/repo (e.g. \"facebook/react\")"}},"required":["repoName"],"additionalProperties":false,"$schema":"http://json-schema.org/draft-07/schema#"},"name":"read_wiki_contents"},{"annotations":{"read_only":false},"description":"Ask any question about a GitHub repository","input_schema":{"type":"object","properties":{"repoName":{"type":"string","description":"GitHub repository: owner/repo (e.g. \"facebook/react\")"},"question":{"type":"string","description":"The question to ask about the repository"}},"required":["repoName","question"],"additionalProperties":false,"$schema":"http://json-schema.org/draft-07/schema#"},"name":"ask_question"}]}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":6,"output_index":1,"item":{"id":"mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54","type":"mcp_call","approval_request_id":null,"arguments":"","error":null,"name":"read_wiki_structure","output":null,"server_label":"deepwiki"}}
 
            event: response.mcp_call.in_progress
            data: {"type":"response.mcp_call.in_progress","sequence_number":7,"output_index":1,"item_id":"mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54"}
 
            event: response.mcp_call_arguments.delta
            data: {"type":"response.mcp_call_arguments.delta","sequence_number":8,"output_index":1,"item_id":"mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54","delta":"{\"repoName\":\"dotnet/extensions\"}","obfuscation":""}
 
            event: response.mcp_call_arguments.done
            data: {"type":"response.mcp_call_arguments.done","sequence_number":9,"output_index":1,"item_id":"mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54","arguments":"{\"repoName\":\"dotnet/extensions\"}"}
 
            event: response.mcp_call.completed
            data: {"type":"response.mcp_call.completed","sequence_number":10,"output_index":1,"item_id":"mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54"}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":11,"output_index":1,"item":{"id":"mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54","type":"mcp_call","approval_request_id":null,"arguments":"{\"repoName\":\"dotnet/extensions\"}","error":null,"name":"read_wiki_structure","output":"Available pages for dotnet/extensions:\n\n- 1 Overview\n- 2 Build System and CI/CD\n- 3 AI Extensions Framework\n  - 3.1 Core Abstractions\n  - 3.2 AI Function System\n  - 3.3 Chat Completion\n  - 3.4 Caching System\n  - 3.5 Evaluation and Reporting\n- 4 HTTP Resilience and Diagnostics\n  - 4.1 Standard Resilience\n  - 4.2 Hedging Strategies\n- 5 Telemetry and Compliance\n- 6 Testing Infrastructure\n  - 6.1 AI Service Integration Testing\n  - 6.2 Time Provider Testing","server_label":"deepwiki"}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":12,"output_index":2,"item":{"id":"mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54","type":"mcp_call","approval_request_id":null,"arguments":"","error":null,"name":"ask_question","output":null,"server_label":"deepwiki"}}
 
            event: response.mcp_call.in_progress
            data: {"type":"response.mcp_call.in_progress","sequence_number":13,"output_index":2,"item_id":"mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54"}
 
            event: response.mcp_call_arguments.delta
            data: {"type":"response.mcp_call_arguments.delta","sequence_number":14,"output_index":2,"item_id":"mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54","delta":"{\"repoName\":\"dotnet/extensions\",\"question\":\"What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?\"}","obfuscation":"IT"}
 
            event: response.mcp_call_arguments.done
            data: {"type":"response.mcp_call_arguments.done","sequence_number":15,"output_index":2,"item_id":"mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54","arguments":"{\"repoName\":\"dotnet/extensions\",\"question\":\"What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?\"}"}
 
            event: response.mcp_call.completed
            data: {"type":"response.mcp_call.completed","sequence_number":16,"output_index":2,"item_id":"mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54"}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":17,"output_index":2,"item":{"id":"mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54","type":"mcp_call","approval_request_id":null,"arguments":"{\"repoName\":\"dotnet/extensions\",\"question\":\"What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?\"}","error":null,"name":"ask_question","output":"The path to the `README.md` file for `Microsoft.Extensions.AI.Abstractions` is `src/Libraries/Microsoft.Extensions.AI.Abstractions/README.md` . This file provides an overview of the `Microsoft.Extensions.AI.Abstractions` library, including installation instructions and usage examples for its core components like `IChatClient` and `IEmbeddingGenerator`   .\n\n## README.md Content Overview\nThe `README.md` file for `Microsoft.Extensions.AI.Abstractions` details the purpose of the library, which is to provide abstractions for generative AI components . It includes instructions on how to install the NuGet package `Microsoft.Extensions.AI.Abstractions` .\n\nThe document also provides usage examples for the `IChatClient` interface, which defines methods for interacting with AI services that offer \"chat\" capabilities . This includes examples for requesting both complete and streaming chat responses  .\n\nFurthermore, the `README.md` explains the `IEmbeddingGenerator` interface, which is used for generating vector embeddings from input values . It demonstrates how to use `GenerateAsync` to create embeddings . The file also discusses how both `IChatClient` and `IEmbeddingGenerator` implementations can be layered to create pipelines of functionality, incorporating features like caching and telemetry  .\n\nNotes:\nThe user's query specifically asked for the path to the `README.md` file for `Microsoft.Extensions.AI.Abstractions`. The provided codebase context, particularly the wiki page for \"AI Extensions Framework\", directly lists this file as a relevant source file . The content of the `README.md` file itself further confirms its relevance to the `Microsoft.Extensions.AI.Abstractions` library.\n\nWiki pages you might want to explore:\n- [AI Extensions Framework (dotnet/extensions)](/wiki/dotnet/extensions#3)\n- [Chat Completion (dotnet/extensions)](/wiki/dotnet/extensions#3.3)\n\nView this search on DeepWiki: https://deepwiki.com/search/what-is-the-path-to-the-readme_bb6bee43-3136-4b21-bc5d-02ca1611d857\n","server_label":"deepwiki"}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":18,"output_index":3,"item":{"id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","type":"message","status":"in_progress","content":[],"role":"assistant"}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","sequence_number":19,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":20,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"delta":"The","logprobs":[],"obfuscation":"a5sNdjeWpJXIK"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":21,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"delta":" path","logprobs":[],"obfuscation":"2oWbALsHrtv"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":22,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"delta":" to","logprobs":[],"obfuscation":"K8lRBCaiusvjP"}
 
            event: response.output_text.delta
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            event: response.output_text.delta
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            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":99,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"delta":" to","logprobs":[],"obfuscation":"uMNfozGkKe6xW"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":100,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"delta":" ask","logprobs":[],"obfuscation":"6rMOxwXhR8RY"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":101,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"delta":"!","logprobs":[],"obfuscation":"QPZMdhS0e5vYuRl"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","sequence_number":102,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"text":"The path to the `README.md` file for `Microsoft.Extensions.AI.Abstractions` in the `dotnet/extensions` repository is:\n\n```\nsrc/Libraries/Microsoft.Extensions.AI.Abstractions/README.md\n```\n\nThis file provides an overview of the library, installation instructions, and usage examples for its core components. If you have any more questions about it, feel free to ask!","logprobs":[]}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","sequence_number":103,"item_id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","output_index":3,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":"The path to the `README.md` file for `Microsoft.Extensions.AI.Abstractions` in the `dotnet/extensions` repository is:\n\n```\nsrc/Libraries/Microsoft.Extensions.AI.Abstractions/README.md\n```\n\nThis file provides an overview of the library, installation instructions, and usage examples for its core components. If you have any more questions about it, feel free to ask!"}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":104,"output_index":3,"item":{"id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"The path to the `README.md` file for `Microsoft.Extensions.AI.Abstractions` in the `dotnet/extensions` repository is:\n\n```\nsrc/Libraries/Microsoft.Extensions.AI.Abstractions/README.md\n```\n\nThis file provides an overview of the library, installation instructions, and usage examples for its core components. If you have any more questions about it, feel free to ask!"}],"role":"assistant"}}
 
            event: response.completed
            data: {"type":"response.completed","sequence_number":105,"response":{"id":"resp_68be44fd7298819e82fd82c8516e970d03a2537be0e84a54","object":"response","created_at":1757299965,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-mini-2024-07-18","output":[{"id":"mcpl_68be44fd8f68819eba7a74a2f6d27a5a03a2537be0e84a54","type":"mcp_list_tools","server_label":"deepwiki","tools":[{"annotations":{"read_only":false},"description":"Get a list of documentation topics for a GitHub repository","input_schema":{"type":"object","properties":{"repoName":{"type":"string","description":"GitHub repository: owner/repo (e.g. \"facebook/react\")"}},"required":["repoName"],"additionalProperties":false,"$schema":"http://json-schema.org/draft-07/schema#"},"name":"read_wiki_structure"},{"annotations":{"read_only":false},"description":"View documentation about a GitHub repository","input_schema":{"type":"object","properties":{"repoName":{"type":"string","description":"GitHub repository: owner/repo (e.g. \"facebook/react\")"}},"required":["repoName"],"additionalProperties":false,"$schema":"http://json-schema.org/draft-07/schema#"},"name":"read_wiki_contents"},{"annotations":{"read_only":false},"description":"Ask any question about a GitHub repository","input_schema":{"type":"object","properties":{"repoName":{"type":"string","description":"GitHub repository: owner/repo (e.g. \"facebook/react\")"},"question":{"type":"string","description":"The question to ask about the repository"}},"required":["repoName","question"],"additionalProperties":false,"$schema":"http://json-schema.org/draft-07/schema#"},"name":"ask_question"}]},{"id":"mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54","type":"mcp_call","approval_request_id":null,"arguments":"{\"repoName\":\"dotnet/extensions\"}","error":null,"name":"read_wiki_structure","output":"Available pages for dotnet/extensions:\n\n- 1 Overview\n- 2 Build System and CI/CD\n- 3 AI Extensions Framework\n  - 3.1 Core Abstractions\n  - 3.2 AI Function System\n  - 3.3 Chat Completion\n  - 3.4 Caching System\n  - 3.5 Evaluation and Reporting\n- 4 HTTP Resilience and Diagnostics\n  - 4.1 Standard Resilience\n  - 4.2 Hedging Strategies\n- 5 Telemetry and Compliance\n- 6 Testing Infrastructure\n  - 6.1 AI Service Integration Testing\n  - 6.2 Time Provider Testing","server_label":"deepwiki"},{"id":"mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54","type":"mcp_call","approval_request_id":null,"arguments":"{\"repoName\":\"dotnet/extensions\",\"question\":\"What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?\"}","error":null,"name":"ask_question","output":"The path to the `README.md` file for `Microsoft.Extensions.AI.Abstractions` is `src/Libraries/Microsoft.Extensions.AI.Abstractions/README.md` . This file provides an overview of the `Microsoft.Extensions.AI.Abstractions` library, including installation instructions and usage examples for its core components like `IChatClient` and `IEmbeddingGenerator`   .\n\n## README.md Content Overview\nThe `README.md` file for `Microsoft.Extensions.AI.Abstractions` details the purpose of the library, which is to provide abstractions for generative AI components . It includes instructions on how to install the NuGet package `Microsoft.Extensions.AI.Abstractions` .\n\nThe document also provides usage examples for the `IChatClient` interface, which defines methods for interacting with AI services that offer \"chat\" capabilities . This includes examples for requesting both complete and streaming chat responses  .\n\nFurthermore, the `README.md` explains the `IEmbeddingGenerator` interface, which is used for generating vector embeddings from input values . It demonstrates how to use `GenerateAsync` to create embeddings . The file also discusses how both `IChatClient` and `IEmbeddingGenerator` implementations can be layered to create pipelines of functionality, incorporating features like caching and telemetry  .\n\nNotes:\nThe user's query specifically asked for the path to the `README.md` file for `Microsoft.Extensions.AI.Abstractions`. The provided codebase context, particularly the wiki page for \"AI Extensions Framework\", directly lists this file as a relevant source file . The content of the `README.md` file itself further confirms its relevance to the `Microsoft.Extensions.AI.Abstractions` library.\n\nWiki pages you might want to explore:\n- [AI Extensions Framework (dotnet/extensions)](/wiki/dotnet/extensions#3)\n- [Chat Completion (dotnet/extensions)](/wiki/dotnet/extensions#3.3)\n\nView this search on DeepWiki: https://deepwiki.com/search/what-is-the-path-to-the-readme_bb6bee43-3136-4b21-bc5d-02ca1611d857\n","server_label":"deepwiki"},{"id":"msg_68be450c39e8819eb9bf6fcb9fd16ecb03a2537be0e84a54","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"The path to the `README.md` file for `Microsoft.Extensions.AI.Abstractions` in the `dotnet/extensions` repository is:\n\n```\nsrc/Libraries/Microsoft.Extensions.AI.Abstractions/README.md\n```\n\nThis file provides an overview of the library, installation instructions, and usage examples for its core components. If you have any more questions about it, feel free to ask!"}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[{"type":"mcp","allowed_tools":null,"headers":null,"require_approval":"never","server_description":null,"server_label":"deepwiki","server_url":"https://mcp.deepwiki.com/<redacted>"}],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":1420,"input_tokens_details":{"cached_tokens":0},"output_tokens":149,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":1569},"user":null,"metadata":{}}}
            
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        ChatOptions chatOptions = new()
        {
            Tools = [new HostedMcpServerTool("deepwiki", new Uri("https://mcp.deepwiki.com/mcp"))
                {
                    ApprovalMode = HostedMcpServerToolApprovalMode.NeverRequire,
                }
            ],
        };
 
        var response = await client.GetStreamingResponseAsync("Tell me the path to the README.md file for Microsoft.Extensions.AI.Abstractions in the dotnet/extensions repository", chatOptions)
            .ToChatResponseAsync();
        Assert.NotNull(response);
 
        Assert.Equal("resp_68be44fd7298819e82fd82c8516e970d03a2537be0e84a54", response.ResponseId);
        Assert.Equal("resp_68be44fd7298819e82fd82c8516e970d03a2537be0e84a54", response.ConversationId);
        Assert.Equal("gpt-4o-mini-2024-07-18", response.ModelId);
        Assert.Equal(DateTimeOffset.FromUnixTimeSeconds(1_757_299_965), response.CreatedAt);
        Assert.Equal(ChatFinishReason.Stop, response.FinishReason);
 
        var message = Assert.Single(response.Messages);
        Assert.Equal(ChatRole.Assistant, response.Messages[0].Role);
        Assert.StartsWith("The path to the `README.md` file", response.Messages[0].Text);
 
        Assert.Equal(6, message.Contents.Count);
 
        var firstCall = Assert.IsType<McpServerToolCallContent>(message.Contents[1]);
        Assert.Equal("mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54", firstCall.CallId);
        Assert.Equal("deepwiki", firstCall.ServerName);
        Assert.Equal("read_wiki_structure", firstCall.ToolName);
        Assert.NotNull(firstCall.Arguments);
        Assert.Single(firstCall.Arguments);
        Assert.Equal("dotnet/extensions", ((JsonElement)firstCall.Arguments["repoName"]!).GetString());
 
        var firstResult = Assert.IsType<McpServerToolResultContent>(message.Contents[2]);
        Assert.Equal("mcp_68be4503d45c819e89cb574361c8eba003a2537be0e84a54", firstResult.CallId);
        Assert.NotNull(firstResult.Output);
        Assert.StartsWith("Available pages for dotnet/extensions", Assert.IsType<TextContent>(Assert.Single(firstResult.Output)).Text);
 
        var secondCall = Assert.IsType<McpServerToolCallContent>(message.Contents[3]);
        Assert.Equal("mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54", secondCall.CallId);
        Assert.Equal("deepwiki", secondCall.ServerName);
        Assert.Equal("ask_question", secondCall.ToolName);
        Assert.NotNull(secondCall.Arguments);
        Assert.Equal("dotnet/extensions", ((JsonElement)secondCall.Arguments["repoName"]!).GetString());
        Assert.Equal("What is the path to the README.md file for Microsoft.Extensions.AI.Abstractions?", ((JsonElement)secondCall.Arguments["question"]!).GetString());
 
        var secondResult = Assert.IsType<McpServerToolResultContent>(message.Contents[4]);
        Assert.Equal("mcp_68be4505f134819e806c002f27cce0c303a2537be0e84a54", secondResult.CallId);
        Assert.NotNull(secondResult.Output);
        Assert.StartsWith("The path to the `README.md` file", Assert.IsType<TextContent>(Assert.Single(secondResult.Output)).Text);
 
        Assert.NotNull(response.Usage);
        Assert.Equal(1420, response.Usage.InputTokenCount);
        Assert.Equal(149, response.Usage.OutputTokenCount);
        Assert.Equal(1569, response.Usage.TotalTokenCount);
    }
 
    [Fact]
    public async Task GetResponseAsync_BackgroundResponses_FirstCall()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "background":true,
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed7",
              "object": "response",
              "created_at": 1758712522,
              "status": "queued",
              "background": true,
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-mini-2024-07-18",
              "output": [],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "generate_summary": null
              },
              "store": true,
              "temperature": 0.5,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1.0,
              "usage": null,
              "user": null,
              "metadata": {}
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            AllowBackgroundResponses = true,
        });
        Assert.NotNull(response);
 
        Assert.Equal("resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed7", response.ResponseId);
        Assert.Equal("resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed7", response.ConversationId);
        Assert.Empty(response.Messages);
 
        Assert.NotNull(response.ContinuationToken);
        var responsesContinuationToken = TestOpenAIResponsesContinuationToken.FromToken(response.ContinuationToken);
        Assert.Equal("resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed7", responsesContinuationToken.ResponseId);
        Assert.Null(responsesContinuationToken.SequenceNumber);
    }
 
    [Theory]
    [InlineData(ResponseStatus.Queued)]
    [InlineData(ResponseStatus.InProgress)]
    [InlineData(ResponseStatus.Completed)]
    [InlineData(ResponseStatus.Cancelled)]
    [InlineData(ResponseStatus.Failed)]
    [InlineData(ResponseStatus.Incomplete)]
    public async Task GetResponseAsync_BackgroundResponses_PollingCall(ResponseStatus expectedStatus)
    {
        var expectedInput = new HttpHandlerExpectedInput
        {
            Uri = new Uri("https://api.openai.com/v1/responses/resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed8"),
            Method = HttpMethod.Get,
        };
 
        string output = $$""""
            {
              "id": "resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed8",
              "object": "response",
              "created_at": 1758712522,
              "status": "{{ResponseStatusToRequestValue(expectedStatus)}}",
              "background": true,
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "model": "gpt-4o-mini-2024-07-18",
              "output": {{(expectedStatus is (ResponseStatus.Queued or ResponseStatus.InProgress)
                ? "[]"
                : """
                    [{
                      "type": "message",
                      "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                      "status": "completed",
                      "role": "assistant",
                      "content": [
                        {
                          "type": "output_text",
                          "text": "The background response result.",
                          "annotations": []
                        }
                      ]
                    }]
                    """
              )}},
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "reasoning": {
                "effort": null,
                "generate_summary": null
              },
              "store": true,
              "temperature": 0.5,
              "text": {
                "format": {
                  "type": "text"
                }
              },
              "tool_choice": "auto",
              "tools": [],
              "top_p": 1.0,
              "usage": null,
              "user": null,
              "metadata": {}
            }
            """";
 
        using VerbatimHttpHandler handler = new(expectedInput, output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var continuationToken = new TestOpenAIResponsesContinuationToken("resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed8");
 
        var response = await client.GetResponseAsync([], new()
        {
            ContinuationToken = continuationToken,
            AllowBackgroundResponses = true,
        });
        Assert.NotNull(response);
 
        Assert.Equal("resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed8", response.ResponseId);
        Assert.Equal("resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed8", response.ConversationId);
 
        switch (expectedStatus)
        {
            case ResponseStatus.Queued:
            case ResponseStatus.InProgress:
            {
                Assert.NotNull(response.ContinuationToken);
 
                var responsesContinuationToken = TestOpenAIResponsesContinuationToken.FromToken(response.ContinuationToken);
                Assert.Equal("resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed8", responsesContinuationToken.ResponseId);
                Assert.Null(responsesContinuationToken.SequenceNumber);
 
                Assert.Empty(response.Messages);
                break;
            }
 
            case ResponseStatus.Completed:
            case ResponseStatus.Cancelled:
            case ResponseStatus.Failed:
            case ResponseStatus.Incomplete:
            {
                Assert.Null(response.ContinuationToken);
 
                Assert.Equal("The background response result.", response.Text);
                Assert.Single(response.Messages.Single().Contents);
                Assert.Equal(ChatRole.Assistant, response.Messages.Single().Role);
                break;
            }
 
            default:
                throw new ArgumentOutOfRangeException(nameof(expectedStatus), expectedStatus, null);
        }
    }
 
    [Fact]
    public async Task GetResponseAsync_BackgroundResponses_PollingCall_WithMessages()
    {
        using VerbatimHttpHandler handler = new(string.Empty, string.Empty);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var options = new ChatOptions
        {
            ContinuationToken = new TestOpenAIResponsesContinuationToken("resp_68d3d2c9ef7c8195863e4e2b2ec226a205007262ecbbfed8"),
            AllowBackgroundResponses = true,
        };
 
        // A try to update a background response with new messages should fail.
        await Assert.ThrowsAsync<InvalidOperationException>(async () =>
        {
            await client.GetResponseAsync("Please book hotel as well", options);
        });
    }
 
    [Fact]
    public async Task GetStreamingResponseAsync_BackgroundResponses()
    {
        const string Input = """
            {
              "model": "gpt-4o-2024-08-06",
              "background": true,
              "input":[{
                "type":"message",
                "role":"user",
                "content":[{
                  "type":"input_text",
                  "text":"hello"
                }]
              }],
              
              "stream": true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_68d401a7b36c81a288600e95a5a119d4073420ed59d5f559","object":"response","created_at":1758724519,"status":"queued","background":true,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-2024-08-06","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
 
            event: response.queued
            data: {"type":"response.queued","sequence_number":1,"response":{"id":"resp_68d401a7b36c81a288600e95a5a119d4073420ed59d5f559","object":"response","created_at":1758724519,"status":"queued","background":true,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-2024-08-06","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","sequence_number":2,"response":{"truncation":"disabled","id":"resp_68d401a7b36c81a288600e95a5a119d4073420ed59d5f559","tool_choice":"auto","temperature":1.0,"top_p":1.0,"status":"in_progress","top_logprobs":0,"usage":null,"object":"response","created_at":1758724519,"prompt_cache_key":null,"text":{"format":{"type":"text"},"verbosity":"medium"},"incomplete_details":null,"model":"gpt-4o-2024-08-06","previous_response_id":null,"safety_identifier":null,"metadata":{},"store":true,"output":[],"parallel_tool_calls":true,"error":null,"background":true,"instructions":null,"service_tier":"auto","max_tool_calls":null,"max_output_tokens":null,"tools":[],"user":null,"reasoning":{"effort":null,"summary":null}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":3,"item":{"id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content":[],"role":"assistant","status":"in_progress","type":"message"},"output_index":0}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","sequence_number":4,"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"part":{"text":"","logprobs":[],"type":"output_text","annotations":[]},"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":5,"delta":"Hello","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":6,"delta":"!","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":7,"delta":" How","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":8,"delta":" can","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":9,"delta":" I","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":10,"delta":" assist","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":11,"delta":" you","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":12,"delta":" today","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":13,"delta":"?","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","sequence_number":14,"text":"Hello! How can I assist you today?","logprobs":[],"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"output_index":0}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","sequence_number":15,"item_id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content_index":0,"part":{"text":"Hello! How can I assist you today?","logprobs":[],"type":"output_text","annotations":[]},"output_index":0}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":16,"item":{"id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content":[{"text":"Hello! How can I assist you today?","logprobs":[],"type":"output_text","annotations":[]}],"role":"assistant","status":"completed","type":"message"},"output_index":0}
 
            event: response.completed
            data: {"type":"response.completed","sequence_number":17,"response":{"truncation":"disabled","id":"resp_68d401a7b36c81a288600e95a5a119d4073420ed59d5f559","tool_choice":"auto","temperature":1.0,"top_p":1.0,"status":"completed","top_logprobs":0,"usage":{"total_tokens":18,"input_tokens_details":{"cached_tokens":0},"output_tokens_details":{"reasoning_tokens":0},"output_tokens":10,"input_tokens":8},"object":"response","created_at":1758724519,"prompt_cache_key":null,"text":{"format":{"type":"text"},"verbosity":"medium"},"incomplete_details":null,"model":"gpt-4o-2024-08-06","previous_response_id":null,"safety_identifier":null,"metadata":{},"store":true,"output":[{"id":"msg_68d401aa78d481a2ab30776a79c691a6073420ed59d5f559","content":[{"text":"Hello! How can I assist you today?","logprobs":[],"type":"output_text","annotations":[]}],"role":"assistant","status":"completed","type":"message"}],"parallel_tool_calls":true,"error":null,"background":true,"instructions":null,"service_tier":"default","max_tool_calls":null,"max_output_tokens":null,"tools":[],"user":null,"reasoning":{"effort":null,"summary":null}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-2024-08-06");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("hello", new()
        {
            AllowBackgroundResponses = true,
        }))
        {
            updates.Add(update);
        }
 
        Assert.Equal("Hello! How can I assist you today?", string.Concat(updates.Select(u => u.Text)));
        Assert.Equal(18, updates.Count);
 
        var createdAt = DateTimeOffset.FromUnixTimeSeconds(1_758_724_519);
 
        for (int i = 0; i < updates.Count; i++)
        {
            Assert.Equal("resp_68d401a7b36c81a288600e95a5a119d4073420ed59d5f559", updates[i].ResponseId);
            Assert.Equal("resp_68d401a7b36c81a288600e95a5a119d4073420ed59d5f559", updates[i].ConversationId);
            Assert.Equal(createdAt, updates[i].CreatedAt);
            Assert.Equal("gpt-4o-2024-08-06", updates[i].ModelId);
            Assert.Null(updates[i].AdditionalProperties);
 
            if (i < updates.Count - 1)
            {
                Assert.NotNull(updates[i].ContinuationToken);
                var responsesContinuationToken = TestOpenAIResponsesContinuationToken.FromToken(updates[i].ContinuationToken!);
                Assert.Equal("resp_68d401a7b36c81a288600e95a5a119d4073420ed59d5f559", responsesContinuationToken.ResponseId);
                Assert.Equal(i, responsesContinuationToken.SequenceNumber);
                Assert.Null(updates[i].FinishReason);
            }
            else
            {
                Assert.Null(updates[i].ContinuationToken);
                Assert.Equal(ChatFinishReason.Stop, updates[i].FinishReason);
            }
 
            Assert.Equal((i >= 5 && i <= 13) || i == 17 ? 1 : 0, updates[i].Contents.Count);
        }
    }
 
    [Fact]
    public async Task GetStreamingResponseAsync_BackgroundResponses_StreamResumption()
    {
        var expectedInput = new HttpHandlerExpectedInput
        {
            Uri = new Uri("https://api.openai.com/v1/responses/resp_68d40dc671a0819cb0ee920078333451029e611c3cc4a34b?stream=true&starting_after=9"),
            Method = HttpMethod.Get,
        };
 
        const string Output = """
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":10,"delta":" assist","logprobs":[],"item_id":"msg_68d40dcb2d34819c88f5d6a8ca7b0308029e611c3cc4a34b","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":11,"delta":" you","logprobs":[],"item_id":"msg_68d40dcb2d34819c88f5d6a8ca7b0308029e611c3cc4a34b","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":12,"delta":" today","logprobs":[],"item_id":"msg_68d40dcb2d34819c88f5d6a8ca7b0308029e611c3cc4a34b","content_index":0,"output_index":0}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":13,"delta":"?","logprobs":[],"item_id":"msg_68d40dcb2d34819c88f5d6a8ca7b0308029e611c3cc4a34b","content_index":0,"output_index":0}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","sequence_number":14,"text":"Hello! How can I assist you today?","logprobs":[],"item_id":"msg_68d40dcb2d34819c88f5d6a8ca7b0308029e611c3cc4a34b","content_index":0,"output_index":0}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","sequence_number":15,"item_id":"msg_68d40dcb2d34819c88f5d6a8ca7b0308029e611c3cc4a34b","content_index":0,"part":{"text":"Hello! How can I assist you today?","logprobs":[],"type":"output_text","annotations":[]},"output_index":0}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":16,"item":{"id":"msg_68d40dcb2d34819c88f5d6a8ca7b0308029e611c3cc4a34b","content":[{"text":"Hello! How can I assist you today?","logprobs":[],"type":"output_text","annotations":[]}],"role":"assistant","status":"completed","type":"message"},"output_index":0}
 
            event: response.completed
            data: {"type":"response.completed","sequence_number":17,"response":{"truncation":"disabled","id":"resp_68d40dc671a0819cb0ee920078333451029e611c3cc4a34b","tool_choice":"auto","temperature":1.0,"top_p":1.0,"status":"completed","top_logprobs":0,"usage":{"total_tokens":18,"input_tokens_details":{"cached_tokens":0},"output_tokens_details":{"reasoning_tokens":0},"output_tokens":10,"input_tokens":8},"object":"response","created_at":1758727622,"prompt_cache_key":null,"text":{"format":{"type":"text"},"verbosity":"medium"},"incomplete_details":null,"model":"gpt-4o-2024-08-06","previous_response_id":null,"safety_identifier":null,"metadata":{},"store":true,"output":[{"id":"msg_68d40dcb2d34819c88f5d6a8ca7b0308029e611c3cc4a34b","content":[{"text":"Hello! How can I assist you today?","logprobs":[],"type":"output_text","annotations":[]}],"role":"assistant","status":"completed","type":"message"}],"parallel_tool_calls":true,"error":null,"background":true,"instructions":null,"service_tier":"default","max_tool_calls":null,"max_output_tokens":null,"tools":[],"user":null,"reasoning":{"effort":null,"summary":null}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(expectedInput, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-2024-08-06");
 
        // Emulating resumption of the stream after receiving the first 9 updates that provided the text "Hello! How can I"
        var continuationToken = new TestOpenAIResponsesContinuationToken("resp_68d40dc671a0819cb0ee920078333451029e611c3cc4a34b")
        {
            SequenceNumber = 9
        };
 
        var chatOptions = new ChatOptions
        {
            AllowBackgroundResponses = true,
            ContinuationToken = continuationToken,
        };
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync([], chatOptions))
        {
            updates.Add(update);
        }
 
        // Receiving the remaining updates to complete the response "Hello! How can I assist you today?"
        Assert.Equal(" assist you today?", string.Concat(updates.Select(u => u.Text)));
        Assert.Equal(8, updates.Count);
 
        var createdAt = DateTimeOffset.FromUnixTimeSeconds(1_758_727_622);
 
        for (int i = 0; i < updates.Count; i++)
        {
            Assert.Equal("resp_68d40dc671a0819cb0ee920078333451029e611c3cc4a34b", updates[i].ResponseId);
            Assert.Equal("resp_68d40dc671a0819cb0ee920078333451029e611c3cc4a34b", updates[i].ConversationId);
 
            var sequenceNumber = i + 10;
 
            if (sequenceNumber is (>= 10 and <= 13))
            {
                // Text deltas
                Assert.NotNull(updates[i].ContinuationToken);
                var responsesContinuationToken = TestOpenAIResponsesContinuationToken.FromToken(updates[i].ContinuationToken!);
                Assert.Equal("resp_68d40dc671a0819cb0ee920078333451029e611c3cc4a34b", responsesContinuationToken.ResponseId);
                Assert.Equal(sequenceNumber, responsesContinuationToken.SequenceNumber);
 
                Assert.Single(updates[i].Contents);
            }
            else if (sequenceNumber is (>= 14 and <= 16))
            {
                // Response Complete and Assistant message updates
                Assert.NotNull(updates[i].ContinuationToken);
                var responsesContinuationToken = TestOpenAIResponsesContinuationToken.FromToken(updates[i].ContinuationToken!);
                Assert.Equal("resp_68d40dc671a0819cb0ee920078333451029e611c3cc4a34b", responsesContinuationToken.ResponseId);
                Assert.Equal(sequenceNumber, responsesContinuationToken.SequenceNumber);
 
                Assert.Empty(updates[i].Contents);
            }
            else
            {
                // The last update with the response completion
                Assert.Null(updates[i].ContinuationToken);
                Assert.Single(updates[i].Contents);
            }
        }
    }
 
    [Fact]
    public async Task GetStreamingResponseAsync_BackgroundResponses_StreamResumption_WithMessages()
    {
        using VerbatimHttpHandler handler = new(string.Empty, string.Empty);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-2024-08-06");
 
        // Emulating resumption of the stream after receiving the first 9 updates that provided the text "Hello! How can I"
        var chatOptions = new ChatOptions
        {
            AllowBackgroundResponses = true,
            ContinuationToken = new TestOpenAIResponsesContinuationToken("resp_68d40dc671a0819cb0ee920078333451029e611c3cc4a34b")
            {
                SequenceNumber = 9
            }
        };
 
        await Assert.ThrowsAsync<InvalidOperationException>(async () =>
        {
            await foreach (var update in client.GetStreamingResponseAsync("Please book a hotel for me", chatOptions))
#pragma warning disable S108 // Nested blocks of code should not be left empty
            {
            }
#pragma warning restore S108 // Nested blocks of code should not be left empty
        });
    }
 
    [Fact]
    public async Task CodeInterpreterTool_NonStreaming()
    {
        const string Input = """
            {
                "model":"gpt-4o-2024-08-06",
                "input":[{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"Calculate the sum of numbers from 1 to 5"}]
                }],
                "tool_choice":"auto",
                "tools":[{
                    "type":"code_interpreter",
                    "container":{"type":"auto"}
                }]
            }
            """;
 
        const string Output = """
            {
              "id": "resp_0e599e83cc6642210068fb7475165481a08efc750483c7048f",
              "object": "response",
              "created_at": 1761309813,
              "status": "completed",
              "background": false,
              "error": null,
              "incomplete_details": null,
              "instructions": null,
              "max_output_tokens": null,
              "max_tool_calls": null,
              "model": "gpt-4o-2024-08-06",
              "output": [
                {
                  "id": "ci_0e599e83cc6642210068fb7477fb9881a0811e8b0dc054b2fa",
                  "type": "code_interpreter_call",
                  "status": "completed",
                  "code": "# Calculating the sum of numbers from 1 to 5\nresult = sum(range(1, 6))\nresult",
                  "container_id": "cntr_68fb7476c384819186524b78cdc3180000a9a0fdd06b3cd4",
                  "outputs": null
                },
                {
                  "id": "msg_0e599e83cc6642210068fb747e118081a08c3ed46daa9d9dcb",
                  "type": "message",
                  "status": "completed",
                  "content": [
                    {
                      "type": "output_text",
                      "annotations": [],
                      "logprobs": [],
                      "text": "15"
                    }
                  ],
                  "role": "assistant"
                }
              ],
              "parallel_tool_calls": true,
              "previous_response_id": null,
              "prompt_cache_key": null,
              "reasoning": {
                "effort": null,
                "summary": null
              },
              "safety_identifier": null,
              "service_tier": "default",
              "store": true,
              "temperature": 1.0,
              "text": {
                "format": {
                  "type": "text"
                },
                "verbosity": "medium"
              },
              "tool_choice": "auto",
              "tools": [
                {
                  "type": "code_interpreter",
                  "container": {
                    "type": "auto"
                  }
                }
              ],
              "top_logprobs": 0,
              "top_p": 1.0,
              "truncation": "disabled",
              "usage": {
                "input_tokens": 225,
                "input_tokens_details": {
                  "cached_tokens": 0
                },
                "output_tokens": 34,
                "output_tokens_details": {
                  "reasoning_tokens": 0
                },
                "total_tokens": 259
              },
              "user": null,
              "metadata": {}
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-2024-08-06");
 
        var response = await client.GetResponseAsync("Calculate the sum of numbers from 1 to 5", new()
        {
            Tools = [new HostedCodeInterpreterTool()],
        });
 
        Assert.NotNull(response);
        Assert.Single(response.Messages);
 
        var message = response.Messages[0];
        Assert.Equal(ChatRole.Assistant, message.Role);
        Assert.Equal(3, message.Contents.Count);
 
        var codeCall = Assert.IsType<CodeInterpreterToolCallContent>(message.Contents[0]);
        Assert.NotNull(codeCall.Inputs);
        var codeInput = Assert.IsType<DataContent>(Assert.Single(codeCall.Inputs));
        Assert.Equal("text/x-python", codeInput.MediaType);
 
        var codeResult = Assert.IsType<CodeInterpreterToolResultContent>(message.Contents[1]);
        Assert.Equal(codeCall.CallId, codeResult.CallId);
 
        var textContent = Assert.IsType<TextContent>(message.Contents[2]);
        Assert.Equal("15", textContent.Text);
    }
 
    [Fact]
    public async Task CodeInterpreterTool_Streaming()
    {
        const string Input = """
            {
                "model":"gpt-4o-2024-08-06",
                "input":[{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"Calculate the sum of numbers from 1 to 10 using Python"}]
                }],
                "tool_choice":"auto",
                "tools":[{
                    "type":"code_interpreter",
                    "container":{"type":"auto"}
                }],
                "stream":true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","sequence_number":0,"response":{"id":"resp_05d8f42f04f94cb80068fc3b7e07bc819eaf0d6e2c1923e564","object":"response","created_at":1761360766,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-2024-08-06","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[{"type":"code_interpreter","container":{"type":"auto"}}],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","sequence_number":1,"response":{"id":"resp_05d8f42f04f94cb80068fc3b7e07bc819eaf0d6e2c1923e564","object":"response","created_at":1761360766,"status":"in_progress","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-2024-08-06","output":[],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"auto","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[{"type":"code_interpreter","container":{"type":"auto"}}],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":2,"output_index":0,"item":{"id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","type":"code_interpreter_call","status":"in_progress","code":"","container_id":"cntr_68fc3b80043c8191990a5837d7617af704511ed77cec9447","outputs":null}}
 
            event: response.code_interpreter_call.in_progress
            data: {"type":"response.code_interpreter_call.in_progress","sequence_number":3,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":4,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"#","obfuscation":"sl1L6kjYGbL3W7b"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":5,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" Calculate","obfuscation":"nXS0Oz"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":6,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" the","obfuscation":"BeywG4wkYSPO"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":7,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" sum","obfuscation":"lQQwYY1jVUku"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":8,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" of","obfuscation":"B7ZYHyd1bTIIr"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":9,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" numbers","obfuscation":"c9P1UFe4"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":10,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" from","obfuscation":"jARdbqvpfdt"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":11,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" ","obfuscation":"wciF7LWnjGSdWPb"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":12,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"1","obfuscation":"KLuWFhT8xPOyTNH"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":13,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" to","obfuscation":"5QCNr2nNt72Hg"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":14,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" ","obfuscation":"F3vctEo2cPUvnhe"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":15,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"10","obfuscation":"JBwcgWLYbSTskz"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":16,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"\n","obfuscation":"AgU5f5WddGwHDJg"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":17,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"sum","obfuscation":"Vey8vqQPTbewO"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":18,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"_of","obfuscation":"Lyrmc5oOwdmsp"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":19,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"_numbers","obfuscation":"YxvseUG4"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":20,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" =","obfuscation":"yoo1CBUhRbgI36"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":21,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" sum","obfuscation":"pKTBmkNEE4SA"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":22,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"(range","obfuscation":"BixU5bs5ms"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":23,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"(","obfuscation":"nsarVNP46dpVYMb"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":24,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"1","obfuscation":"qkth7DCPzS6mfEd"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":25,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":",","obfuscation":"J5uAitISxtjRSQA"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":26,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":" ","obfuscation":"thr4ylmBRbAk0PY"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":27,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"11","obfuscation":"FWxcmwOFHJKEPJ"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":28,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"))\n","obfuscation":"ifI2JoREexe3t"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":29,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"sum","obfuscation":"VI7RlYoKWGMKP"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":30,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"_of","obfuscation":"lkv27YflY8GLq"}
 
            event: response.code_interpreter_call_code.delta
            data: {"type":"response.code_interpreter_call_code.delta","sequence_number":31,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","delta":"_numbers","obfuscation":"xAQFrVav"}
 
            event: response.code_interpreter_call_code.done
            data: {"type":"response.code_interpreter_call_code.done","sequence_number":32,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","code":"# Calculate the sum of numbers from 1 to 10\nsum_of_numbers = sum(range(1, 11))\nsum_of_numbers"}
 
            event: response.code_interpreter_call.interpreting
            data: {"type":"response.code_interpreter_call.interpreting","sequence_number":33,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3"}
 
            event: response.code_interpreter_call.completed
            data: {"type":"response.code_interpreter_call.completed","sequence_number":34,"output_index":0,"item_id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3"}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":35,"output_index":0,"item":{"id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","type":"code_interpreter_call","status":"completed","code":"# Calculate the sum of numbers from 1 to 10\nsum_of_numbers = sum(range(1, 11))\nsum_of_numbers","container_id":"cntr_68fc3b80043c8191990a5837d7617af704511ed77cec9447","outputs":null}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","sequence_number":36,"output_index":1,"item":{"id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","type":"message","status":"in_progress","content":[],"role":"assistant"}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","sequence_number":37,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":""}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":38,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":"The","logprobs":[],"obfuscation":"r7iIr1QJ50aER"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":39,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" sum","logprobs":[],"obfuscation":"AQlXzWBYj2nu"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":40,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" of","logprobs":[],"obfuscation":"PpVAep2w6YBTd"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":41,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" numbers","logprobs":[],"obfuscation":"q2oosiA3"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":42,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" from","logprobs":[],"obfuscation":"BBLhSYyDDUG"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":43,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" ","logprobs":[],"obfuscation":"itOENAMFwzo6ESp"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":44,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":"1","logprobs":[],"obfuscation":"g93CJ2MyMSbq26V"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":45,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" to","logprobs":[],"obfuscation":"WyzXmwaUVATTs"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":46,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" ","logprobs":[],"obfuscation":"DBgQSKk2myfDWpq"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":47,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":"10","logprobs":[],"obfuscation":"RA4RYQSLNug4pg"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":48,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" is","logprobs":[],"obfuscation":"CgEfKJVj1DJtz"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":49,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":" ","logprobs":[],"obfuscation":"TVg4ccd4ZMwEiru"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":50,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":"55","logprobs":[],"obfuscation":"CVN92VujTbUiZ0"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","sequence_number":51,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"delta":".","logprobs":[],"obfuscation":"7YegRUzag3K6fdV"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","sequence_number":52,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"text":"The sum of numbers from 1 to 10 is 55.","logprobs":[]}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","sequence_number":53,"item_id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","output_index":1,"content_index":0,"part":{"type":"output_text","annotations":[],"logprobs":[],"text":"The sum of numbers from 1 to 10 is 55."}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","sequence_number":54,"output_index":1,"item":{"id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"The sum of numbers from 1 to 10 is 55."}],"role":"assistant"}}
 
            event: response.completed
            data: {"type":"response.completed","sequence_number":55,"response":{"id":"resp_05d8f42f04f94cb80068fc3b7e07bc819eaf0d6e2c1923e564","object":"response","created_at":1761360766,"status":"completed","background":false,"error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":null,"max_tool_calls":null,"model":"gpt-4o-2024-08-06","output":[{"id":"ci_05d8f42f04f94cb80068fc3b80fba8819ea3bfbdd36e94bcf3","type":"code_interpreter_call","status":"completed","code":"# Calculate the sum of numbers from 1 to 10\nsum_of_numbers = sum(range(1, 11))\nsum_of_numbers","container_id":"cntr_68fc3b80043c8191990a5837d7617af704511ed77cec9447","outputs":null},{"id":"msg_05d8f42f04f94cb80068fc3b86cc0c819ebae29aac8563d48d","type":"message","status":"completed","content":[{"type":"output_text","annotations":[],"logprobs":[],"text":"The sum of numbers from 1 to 10 is 55."}],"role":"assistant"}],"parallel_tool_calls":true,"previous_response_id":null,"prompt_cache_key":null,"reasoning":{"effort":null,"summary":null},"safety_identifier":null,"service_tier":"default","store":true,"temperature":1.0,"text":{"format":{"type":"text"},"verbosity":"medium"},"tool_choice":"auto","tools":[{"type":"code_interpreter","container":{"type":"auto"}}],"top_logprobs":0,"top_p":1.0,"truncation":"disabled","usage":{"input_tokens":219,"input_tokens_details":{"cached_tokens":0},"output_tokens":50,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":269},"user":null,"metadata":{}}}
 
 
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-2024-08-06");
 
        var response = await client.GetStreamingResponseAsync("Calculate the sum of numbers from 1 to 10 using Python", new()
        {
            Tools = [new HostedCodeInterpreterTool()],
        }).ToChatResponseAsync();
 
        Assert.NotNull(response);
        Assert.Single(response.Messages);
 
        var message = response.Messages[0];
        Assert.Equal(ChatRole.Assistant, message.Role);
        Assert.Equal(3, message.Contents.Count);
 
        var codeCall = Assert.IsType<CodeInterpreterToolCallContent>(message.Contents[0]);
        Assert.NotNull(codeCall.Inputs);
        var codeInput = Assert.IsType<DataContent>(Assert.Single(codeCall.Inputs));
        Assert.Equal("text/x-python", codeInput.MediaType);
        Assert.Contains("sum_of_numbers", Encoding.UTF8.GetString(codeInput.Data.ToArray()));
 
        var codeResult = Assert.IsType<CodeInterpreterToolResultContent>(message.Contents[1]);
        Assert.Equal(codeCall.CallId, codeResult.CallId);
 
        var textContent = Assert.IsType<TextContent>(message.Contents[2]);
        Assert.Equal("The sum of numbers from 1 to 10 is 55.", textContent.Text);
 
        Assert.NotNull(response.Usage);
        Assert.Equal(219, response.Usage.InputTokenCount);
        Assert.Equal(50, response.Usage.OutputTokenCount);
        Assert.Equal(269, response.Usage.TotalTokenCount);
    }
 
    [Fact]
    public async Task RequestHeaders_UserAgent_ContainsMEAI()
    {
        using var handler = new ThrowUserAgentExceptionHandler();
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        InvalidOperationException e = await Assert.ThrowsAsync<InvalidOperationException>(() => client.GetResponseAsync("hello"));
 
        Assert.StartsWith("User-Agent header: OpenAI", e.Message);
        Assert.Contains("MEAI", e.Message);
    }
 
    [Fact]
    public async Task ConversationId_AsResponseId_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "previous_response_id":"resp_12345",
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67890",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ConversationId = "resp_12345",
        });
 
        Assert.NotNull(response);
        Assert.Equal("resp_67890", response.ResponseId);
        Assert.Equal("resp_67890", response.ConversationId);
    }
 
    [Fact]
    public async Task ConversationId_AsConversationId_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "conversation":"conv_12345",
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67890",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ConversationId = "conv_12345",
        });
 
        Assert.NotNull(response);
        Assert.Equal("resp_67890", response.ResponseId);
        Assert.Equal("conv_12345", response.ConversationId);
    }
 
    [Fact]
    public async Task ConversationId_WhenStoreDisabled_ReturnsNull_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "store":false,
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67890",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "model": "gpt-4o-mini-2024-07-18",
              "store": false,
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            RawRepresentationFactory = (c) => new ResponseCreationOptions
            {
                StoredOutputEnabled = false
            }
        });
 
        Assert.NotNull(response);
        Assert.Equal("resp_67890", response.ResponseId);
        Assert.Null(response.ConversationId);
    }
 
    [Fact]
    public async Task ConversationId_ChatOptionsOverridesRawRepresentationResponseId_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "previous_response_id":"resp_override",
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67890",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ConversationId = "resp_override",
            RawRepresentationFactory = (c) => new ResponseCreationOptions
            {
                PreviousResponseId = null
            }
        });
 
        Assert.NotNull(response);
        Assert.Equal("resp_67890", response.ResponseId);
        Assert.Equal("resp_67890", response.ConversationId);
    }
 
    [Fact]
    public async Task ConversationId_RawRepresentationPreviousResponseIdTakesPrecedence_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "previous_response_id":"resp_fromraw",
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67890",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "model": "gpt-4o-mini-2024-07-18",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ConversationId = "conv_ignored",
            RawRepresentationFactory = (c) => new ResponseCreationOptions
            {
                PreviousResponseId = "resp_fromraw"
            }
        });
 
        Assert.NotNull(response);
        Assert.Equal("resp_67890", response.ResponseId);
        Assert.Equal("resp_67890", response.ConversationId);
    }
 
    [Fact]
    public async Task ConversationId_WhenStoreExplicitlyTrue_UsesResponseId_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "store":true,
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67890",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "model": "gpt-4o-mini-2024-07-18",
              "store": true,
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            RawRepresentationFactory = (c) => new ResponseCreationOptions
            {
                StoredOutputEnabled = true
            }
        });
 
        Assert.NotNull(response);
        Assert.Equal("resp_67890", response.ResponseId);
        Assert.Equal("resp_67890", response.ConversationId);
    }
 
    [Fact]
    public async Task ConversationId_WhenStoreExplicitlyTrue_UsesResponseId_Streaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "store":true,
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"hello"}]
                    }
                ],
                "stream":true,
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"in_progress","role":"assistant","content":[]}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"Hello"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"!"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"text":"Hello!"}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hello!","annotations":[]}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"completed","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":{"input_tokens":26,"input_tokens_details":{"cached_tokens":0},"output_tokens":10,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":36},"user":null,"metadata":{}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            RawRepresentationFactory = (c) => new ResponseCreationOptions
            {
                StoredOutputEnabled = true
            }
        }))
        {
            updates.Add(update);
        }
 
        Assert.Equal("Hello!", string.Concat(updates.Select(u => u.Text)));
 
        for (int i = 0; i < updates.Count; i++)
        {
            Assert.Equal("resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77", updates[i].ResponseId);
            Assert.Equal("resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77", updates[i].ConversationId);
        }
    }
 
    [Fact]
    public async Task ConversationId_WhenStoreDisabled_ReturnsNull_Streaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "store":false,
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"hello"}]
                    }
                ],
                "stream":true,
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":false,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":false,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"in_progress","role":"assistant","content":[]}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"Hello"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"!"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"text":"Hello!"}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hello!","annotations":[]}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"completed","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":false,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":{"input_tokens":26,"input_tokens_details":{"cached_tokens":0},"output_tokens":10,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":36},"user":null,"metadata":{}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            RawRepresentationFactory = (c) => new ResponseCreationOptions
            {
                StoredOutputEnabled = false
            }
        }))
        {
            updates.Add(update);
        }
 
        Assert.Equal("Hello!", string.Concat(updates.Select(u => u.Text)));
 
        for (int i = 0; i < updates.Count; i++)
        {
            Assert.Equal("resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77", updates[i].ResponseId);
            Assert.Null(updates[i].ConversationId);
        }
    }
 
    [Fact]
    public async Task ConversationId_AsConversationId_Streaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "conversation":"conv_12345",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"hello"}]
                    }
                ],
                "stream":true,
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"in_progress","role":"assistant","content":[]}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"Hello"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"!"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"text":"Hello!"}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hello!","annotations":[]}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"completed","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":{"input_tokens":26,"input_tokens_details":{"cached_tokens":0},"output_tokens":10,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":36},"user":null,"metadata":{}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ConversationId = "conv_12345",
        }))
        {
            updates.Add(update);
        }
 
        Assert.Equal("Hello!", string.Concat(updates.Select(u => u.Text)));
 
        for (int i = 0; i < updates.Count; i++)
        {
            Assert.Equal("resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77", updates[i].ResponseId);
            Assert.Equal("conv_12345", updates[i].ConversationId);
        }
    }
 
    [Fact]
    public async Task ConversationId_AsResponseId_Streaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o-mini",
                "previous_response_id":"resp_12345",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"hello"}]
                    }
                ],
                "stream":true,
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"in_progress","role":"assistant","content":[]}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"Hello"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"!"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"text":"Hello!"}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hello!","annotations":[]}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"completed","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-mini-2024-07-18","output":[{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":{"input_tokens":26,"input_tokens_details":{"cached_tokens":0},"output_tokens":10,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":36},"user":null,"metadata":{}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ConversationId = "resp_12345",
        }))
        {
            updates.Add(update);
        }
 
        Assert.Equal("Hello!", string.Concat(updates.Select(u => u.Text)));
 
        for (int i = 0; i < updates.Count; i++)
        {
            Assert.Equal("resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77", updates[i].ResponseId);
            Assert.Equal("resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77", updates[i].ConversationId);
        }
    }
 
    [Fact]
    public async Task ConversationId_RawRepresentationConversationIdTakesPrecedence_NonStreaming()
    {
        const string Input = """
        {
            "temperature":0.5,
            "model":"gpt-4o-mini",
            "conversation":"conv_12345",
            "input": [{
                "type":"message",
                "role":"user",
                "content":[{"type":"input_text","text":"hello"}]
            }],
            "max_output_tokens":20
        }
        """;
 
        const string Output = """
        {
            "id": "resp_67890",
            "object": "response",
            "created_at": 1741891428,
            "status": "completed",
            "model": "gpt-4o-mini-2024-07-18",
            "output": [
            {
                "type": "message",
                "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                "status": "completed",
                "role": "assistant",
                "content": [
                {
                    "type": "output_text",
                    "text": "Hello! How can I assist you today?",
                    "annotations": []
                }
                ]
            }
            ]
        }
        """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var rcoJsonModel = (IJsonModel<ResponseCreationOptions>)new ResponseCreationOptions();
        BinaryData rcoJsonBinaryData = rcoJsonModel.Write(ModelReaderWriterOptions.Json);
        JsonObject rcoJsonObject = Assert.IsType<JsonObject>(JsonNode.Parse(rcoJsonBinaryData.ToMemory().Span));
        Assert.Null(rcoJsonObject["conversation"]);
        rcoJsonObject["conversation"] = "conv_12345";
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ConversationId = "conv_ignored",
            RawRepresentationFactory = (c) => rcoJsonModel.Create(
                new BinaryData(JsonSerializer.SerializeToUtf8Bytes(rcoJsonObject)),
                ModelReaderWriterOptions.Json)
        });
 
        Assert.NotNull(response);
        Assert.Equal("resp_67890", response.ResponseId);
        Assert.Equal("conv_12345", response.ConversationId);
    }
 
    [Fact]
    public async Task ChatOptions_ModelId_OverridesClientModel_NonStreaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o",
                "input": [{
                    "type":"message",
                    "role":"user",
                    "content":[{"type":"input_text","text":"hello"}]
                }],
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            {
              "id": "resp_67890",
              "object": "response",
              "created_at": 1741891428,
              "status": "completed",
              "model": "gpt-4o-2024-08-06",
              "output": [
                {
                  "type": "message",
                  "id": "msg_67d32764fcdc8191bcf2e444d4088804058a5e08c46a181d",
                  "status": "completed",
                  "role": "assistant",
                  "content": [
                    {
                      "type": "output_text",
                      "text": "Hello! How can I assist you today?",
                      "annotations": []
                    }
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ModelId = "gpt-4o",
        });
 
        Assert.NotNull(response);
        Assert.Equal("resp_67890", response.ResponseId);
        Assert.Equal("gpt-4o-2024-08-06", response.ModelId);
        Assert.Equal("Hello! How can I assist you today?", response.Text);
    }
 
    [Fact]
    public async Task ChatOptions_ModelId_OverridesClientModel_Streaming()
    {
        const string Input = """
            {
                "temperature":0.5,
                "model":"gpt-4o",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"hello"}]
                    }
                ],
                "stream":true,
                "max_output_tokens":20
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-2024-08-06","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"in_progress","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-2024-08-06","output":[],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":null,"user":null,"metadata":{}}}
 
            event: response.output_item.added
            data: {"type":"response.output_item.added","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"in_progress","role":"assistant","content":[]}}
 
            event: response.content_part.added
            data: {"type":"response.content_part.added","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"","annotations":[]}}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"Hello"}
 
            event: response.output_text.delta
            data: {"type":"response.output_text.delta","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"delta":"!"}
 
            event: response.output_text.done
            data: {"type":"response.output_text.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"text":"Hello!"}
 
            event: response.content_part.done
            data: {"type":"response.content_part.done","item_id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","output_index":0,"content_index":0,"part":{"type":"output_text","text":"Hello!","annotations":[]}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","output_index":0,"item":{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_67d329fbc87c81919f8952fe71dafc96029dabe3ee19bb77","object":"response","created_at":1741892091,"status":"completed","error":null,"incomplete_details":null,"instructions":null,"max_output_tokens":20,"model":"gpt-4o-2024-08-06","output":[{"type":"message","id":"msg_67d329fc0c0081919696b8ab36713a41029dabe3ee19bb77","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello!","annotations":[]}]}],"parallel_tool_calls":true,"previous_response_id":null,"reasoning":{"effort":null,"generate_summary":null},"store":true,"temperature":0.5,"text":{"format":{"type":"text"}},"tool_choice":"auto","tools":[],"top_p":1.0,"usage":{"input_tokens":26,"input_tokens_details":{"cached_tokens":0},"output_tokens":10,"output_tokens_details":{"reasoning_tokens":0},"total_tokens":36},"user":null,"metadata":{}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("hello", new()
        {
            MaxOutputTokens = 20,
            Temperature = 0.5f,
            ModelId = "gpt-4o",
        }))
        {
            updates.Add(update);
        }
 
        Assert.Equal("Hello!", string.Concat(updates.Select(u => u.Text)));
        Assert.All(updates, u => Assert.Equal("gpt-4o-2024-08-06", u.ModelId));
    }
 
    [Fact]
    public async Task ToolCallResult_SingleTextContent_SerializesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_123",
                        "output":[{"type":"input_text","text":"Result text"}]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_001",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_001",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"Done","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [new FunctionResultContent("call_123", new TextContent("Result text"))])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("Done", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_MultipleTextContents_SerializesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_456",
                        "output":[
                            {"type":"input_text","text":"First part. "},
                            {"type":"input_text","text":"Second part."}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_002",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_002",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"Processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_456", new List<AIContent>
                {
                    new TextContent("First part. "),
                    new TextContent("Second part.")
                })
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("Processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_DataContent_SerializesAsInputImage()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_789",
                        "output":[
                            {"type":"input_image","image_url":"data:image/png;base64,iVBORw0KGgo="}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_003",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_003",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"Image processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var imageData = Convert.FromBase64String("iVBORw0KGgo=");
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_789", new DataContent(imageData, "image/png"))
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("Image processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_UriContent_SerializesAsInputImage()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_uri",
                        "output":[
                            {"type":"input_image","image_url":"https://example.com/image.png"}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_004",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_004",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"URI processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_uri", new UriContent(new Uri("https://example.com/image.png"), "image/png"))
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("URI processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_HostedFileContent_SerializesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_file",
                        "output":[
                            {"type":"input_image","file_id":"file-abc123","filename":"result.png"}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_005",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_005",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"File processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_file", new HostedFileContent("file-abc123") { MediaType = "image/png", Name = "result.png" })
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("File processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_MixedContent_SerializesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_mixed",
                        "output":[
                            {"type":"input_text","text":"Text result: "},
                            {"type":"input_image","image_url":"https://example.com/result.png"},
                            {"type":"input_text","text":" - Image uploaded"}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_006",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_006",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"Mixed content processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_mixed", new List<AIContent>
                {
                    new TextContent("Text result: "),
                    new UriContent(new Uri("https://example.com/result.png"), "image/png"),
                    new TextContent(" - Image uploaded")
                })
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("Mixed content processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_DataContentPDF_SerializesAsInputFile()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_pdf",
                        "output":[
                            {"type":"input_file","file_data":"data:application/pdf;base64,cGRmZGF0YQ==","filename":"report.pdf"}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_007",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_007",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"PDF processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var pdfData = Encoding.UTF8.GetBytes("pdfdata");
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_pdf", new DataContent(pdfData, "application/pdf") { Name = "report.pdf" })
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("PDF processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_ObjectSerialization_SerializesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_obj",
                        "output":"{\"name\":\"John\",\"age\":30}"
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_obj",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_obj",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"Object processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_obj", new { name = "John", age = 30 })
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("Object processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_StringFallback_SerializesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_string",
                        "output":"Simple string result"
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_008",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_008",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"String processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_string", "Simple string result")
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("String processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_UriContentNonImage_SerializesAsInputFile()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_file_uri",
                        "output":[
                            {"type":"input_file","file_url":"https://example.com/document.pdf"}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_009",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_009",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"File URI processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_file_uri", new UriContent(new Uri("https://example.com/document.pdf"), "application/pdf"))
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("File URI processed", response.Text);
    }
 
    [Fact]
    public async Task ToolCallResult_HostedFileContentNonImage_SerializesAsInputFile()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[{"type":"input_text","text":"test"}]
                    },
                    {
                        "type":"function_call_output",
                        "call_id":"call_hosted_file",
                        "output":[
                            {"type":"input_file","file_id":"file-xyz789","filename":"document.txt"}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_010",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_010",
                  "status":"completed",
                  "role":"assistant",
                  "content":[{"type":"output_text","text":"Hosted file processed","annotations":[]}]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, "test"),
            new ChatMessage(ChatRole.Tool, [
                new FunctionResultContent("call_hosted_file", new HostedFileContent("file-xyz789") { MediaType = "text/plain", Name = "document.txt" })
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("Hosted file processed", response.Text);
    }
 
    [Fact]
    public async Task ResponseWithEndUserId_IncludesInAdditionalProperties()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_001",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Done","annotations":[]}]}],
              "user":"user_123"
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("test");
 
        Assert.NotNull(response.AdditionalProperties);
        Assert.Equal("user_123", response.AdditionalProperties["EndUserId"]);
    }
 
    [Fact]
    public async Task ResponseWithError_IncludesInAdditionalPropertiesAndMessage()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_001",
              "object":"response",
              "created_at":1741892091,
              "status":"failed",
              "model":"gpt-4o-mini",
              "output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Processing","annotations":[]}]}],
              "error":{"code":"rate_limit_exceeded","message":"Rate limit exceeded"}
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("test");
 
        Assert.NotNull(response.AdditionalProperties);
        Assert.NotNull(response.AdditionalProperties["Error"]);
 
        var lastMessage = response.Messages.Last();
        var errorContent = lastMessage.Contents.OfType<ErrorContent>().FirstOrDefault();
        Assert.NotNull(errorContent);
        Assert.Equal("Rate limit exceeded", errorContent.Message);
        Assert.Equal("rate_limit_exceeded", errorContent.ErrorCode);
    }
 
    [Fact]
    public async Task ResponseWithUsageDetails_ParsesTokenCounts()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_001",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Done","annotations":[]}]}],
              "usage":{
                "input_tokens":50,
                "input_tokens_details":{"cached_tokens":10},
                "output_tokens":25,
                "output_tokens_details":{"reasoning_tokens":5},
                "total_tokens":75
              }
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("test");
 
        Assert.NotNull(response.Usage);
        Assert.Equal(50, response.Usage.InputTokenCount);
        Assert.Equal(25, response.Usage.OutputTokenCount);
        Assert.Equal(75, response.Usage.TotalTokenCount);
        Assert.NotNull(response.Usage.AdditionalCounts);
        Assert.Equal(10, response.Usage.AdditionalCounts["InputTokenDetails.CachedTokenCount"]);
        Assert.Equal(5, response.Usage.AdditionalCounts["OutputTokenDetails.ReasoningTokenCount"]);
    }
 
    [Fact]
    public async Task UserMessageWithVariousContentTypes_ConvertsCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[
                    {
                        "type":"message",
                        "role":"user",
                        "content":[
                            {"type":"input_text","text":"Check this image: "},
                            {"type":"input_image","image_url":"https://example.com/image.png"},
                            {"type":"input_image","image_url":"data:image/png;base64,iVBORw0KGgo="},
                            {"type":"input_file","file_data":"data:application/pdf;base64,cGRmZGF0YQ==","filename":"doc.pdf"},
                            {"type":"input_file","file_id":"file-123"},
                            {"type":"refusal","refusal":"I cannot process this"}
                        ]
                    }
                ]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_001",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Done","annotations":[]}]}]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var imageData = Convert.FromBase64String("iVBORw0KGgo=");
        var pdfData = Convert.FromBase64String("cGRmZGF0YQ==");
 
        var response = await client.GetResponseAsync([
            new ChatMessage(ChatRole.User, [
                new TextContent("Check this image: "),
                new UriContent(new Uri("https://example.com/image.png"), "image/png"),
                new DataContent(imageData, "image/png"),
                new DataContent(pdfData, "application/pdf") { Name = "doc.pdf" },
                new HostedFileContent("file-123"),
                new ErrorContent("I cannot process this") { ErrorCode = "Refusal" }
            ])
        ]);
 
        Assert.NotNull(response);
        Assert.Equal("Done", response.Text);
    }
 
    [Fact]
    public async Task NonStreamingResponseWithIncompleteReason_MapsFinishReason()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_001",
              "object":"response",
              "created_at":1741892091,
              "status":"incomplete",
              "model":"gpt-4o-mini",
              "output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Partial","annotations":[]}]}],
              "incomplete_details":{"reason":"max_output_tokens"}
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("test");
 
        Assert.NotNull(response);
        Assert.Equal("Partial", response.Text);
        Assert.Equal(ChatFinishReason.Length, response.FinishReason);
    }
 
    [Fact]
    public async Task StreamingResponseWithQueuedUpdate_HandlesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}],
                "stream":true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"in_progress","model":"gpt-4o-mini","output":[]}}
 
            event: response.queued
            data: {"type":"response.queued","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"queued","model":"gpt-4o-mini","output":[]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"completed","model":"gpt-4o-mini","output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Done","annotations":[]}]}]}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("test"))
        {
            updates.Add(update);
        }
 
        Assert.True(updates.Count >= 3);
        Assert.All(updates, u => Assert.Equal("resp_001", u.ResponseId));
    }
 
    [Fact]
    public async Task StreamingResponseWithFailedUpdate_HandlesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}],
                "stream":true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"in_progress","model":"gpt-4o-mini","output":[]}}
 
            event: response.failed
            data: {"type":"response.failed","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"failed","model":"gpt-4o-mini","output":[],"error":{"code":"internal_error","message":"Internal error"}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("test"))
        {
            updates.Add(update);
        }
 
        Assert.True(updates.Count >= 2);
        Assert.All(updates, u => Assert.Equal("resp_001", u.ResponseId));
    }
 
    [Fact]
    public async Task StreamingResponseWithIncompleteUpdate_HandlesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}],
                "stream":true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"in_progress","model":"gpt-4o-mini","output":[]}}
 
            event: response.incomplete
            data: {"type":"response.incomplete","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"incomplete","model":"gpt-4o-mini","output":[],"incomplete_details":{"reason":"max_output_tokens"}}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("test"))
        {
            updates.Add(update);
        }
 
        Assert.True(updates.Count >= 2);
        Assert.All(updates, u => Assert.Equal("resp_001", u.ResponseId));
    }
 
    [Fact]
    public async Task StreamingResponseWithInProgressUpdate_HandlesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}],
                "stream":true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"in_progress","model":"gpt-4o-mini","output":[]}}
 
            event: response.in_progress
            data: {"type":"response.in_progress","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"in_progress","model":"gpt-4o-mini","output":[]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"completed","model":"gpt-4o-mini","output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Done","annotations":[]}]}]}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("test"))
        {
            updates.Add(update);
        }
 
        Assert.True(updates.Count >= 3);
        Assert.All(updates, u => Assert.Equal("resp_001", u.ResponseId));
    }
 
    [Fact]
    public async Task StreamingResponseWithRefusalUpdate_HandlesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}],
                "stream":true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"in_progress","model":"gpt-4o-mini","output":[]}}
 
            event: response.refusal.done
            data: {"type":"response.refusal.done","refusal":"I cannot provide that information"}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"completed","model":"gpt-4o-mini","output":[]}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("test"))
        {
            updates.Add(update);
        }
 
        var refusalUpdate = updates.FirstOrDefault(u => u.Contents.Any(c => c is ErrorContent ec && ec.ErrorCode == "Refusal"));
        Assert.NotNull(refusalUpdate);
 
        var errorContent = refusalUpdate.Contents.OfType<ErrorContent>().First();
        Assert.Equal("I cannot provide that information", errorContent.Message);
        Assert.Equal("Refusal", errorContent.ErrorCode);
    }
 
    [Fact]
    public async Task GetContinuationToken_WithMessages_ThrowsException()
    {
        using HttpClient httpClient = new();
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var token = new TestOpenAIResponsesContinuationToken("resp_123");
 
        await Assert.ThrowsAsync<InvalidOperationException>(async () =>
        {
            await client.GetResponseAsync(
                [new ChatMessage(ChatRole.User, "test")],
                new ChatOptions { ContinuationToken = token });
        });
    }
 
    [Fact]
    public async Task StreamingResponseWithAnnotations_HandlesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"test"}]}],
                "stream":true
            }
            """;
 
        const string Output = """
            event: response.created
            data: {"type":"response.created","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"in_progress","model":"gpt-4o-mini","output":[]}}
 
            event: response.output_item.done
            data: {"type":"response.output_item.done","response_id":"resp_001","output_index":0,"item":{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Annotated text","annotations":[{"type":"file_citation","file_id":"file_123","start_index":0,"end_index":14}]}]}}
 
            event: response.completed
            data: {"type":"response.completed","response":{"id":"resp_001","object":"response","created_at":1741892091,"status":"completed","model":"gpt-4o-mini","output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Annotated text","annotations":[{"type":"file_citation","file_id":"file_123","start_index":0,"end_index":14}]}]}]}}
 
            
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        List<ChatResponseUpdate> updates = [];
        await foreach (var update in client.GetStreamingResponseAsync("test"))
        {
            updates.Add(update);
        }
 
        var annotatedUpdate = updates.FirstOrDefault(u => u.Contents.Any(c => c.Annotations?.Count > 0));
        Assert.NotNull(annotatedUpdate);
        Assert.NotEmpty(annotatedUpdate.Contents.First().Annotations!);
    }
 
    [Fact]
    public async Task UserMessageWithEmptyText_CreatesEmptyInputPart()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":""}]}]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_001",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[{"type":"message","id":"msg_001","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Ok","annotations":[]}]}]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync([new ChatMessage(ChatRole.User, "")]);
 
        Assert.NotNull(response);
        Assert.Equal("Ok", response.Text);
    }
 
    [Fact]
    public async Task ResponseWithRefusalContent_ParsesCorrectly()
    {
        const string Input = """
            {
                "model":"gpt-4o-mini",
                "input":[{"type":"message","role":"user","content":[{"type":"input_text","text":"harmful request"}]}]
            }
            """;
 
        const string Output = """
            {
              "id":"resp_001",
              "object":"response",
              "created_at":1741892091,
              "status":"completed",
              "model":"gpt-4o-mini",
              "output":[
                {
                  "type":"message",
                  "id":"msg_001",
                  "status":"completed",
                  "role":"assistant",
                  "content":[
                    {"type":"refusal","refusal":"I cannot help with that request"}
                  ]
                }
              ]
            }
            """;
 
        using VerbatimHttpHandler handler = new(Input, Output);
        using HttpClient httpClient = new(handler);
        using IChatClient client = CreateResponseClient(httpClient, "gpt-4o-mini");
 
        var response = await client.GetResponseAsync("harmful request");
 
        Assert.NotNull(response);
        var errorContent = response.Messages.Last().Contents.OfType<ErrorContent>().FirstOrDefault();
        Assert.NotNull(errorContent);
        Assert.Equal("I cannot help with that request", errorContent.Message);
        Assert.Equal("Refusal", errorContent.ErrorCode);
    }
 
    private static IChatClient CreateResponseClient(HttpClient httpClient, string modelId) =>
        new OpenAIClient(
            new ApiKeyCredential("apikey"),
            new OpenAIClientOptions { Transport = new HttpClientPipelineTransport(httpClient) })
        .GetOpenAIResponseClient(modelId)
        .AsIChatClient();
 
    private static string ResponseStatusToRequestValue(ResponseStatus status)
    {
        if (status == ResponseStatus.InProgress)
        {
            return "in_progress";
        }
 
        return status.ToString().ToLowerInvariant();
    }
 
    private sealed class TestOpenAIResponsesContinuationToken : ResponseContinuationToken
    {
        internal TestOpenAIResponsesContinuationToken(string responseId)
        {
            ResponseId = responseId;
        }
 
        /// <summary>Gets or sets the Id of the response.</summary>
        internal string ResponseId { get; set; }
 
        /// <summary>Gets or sets the sequence number of a streamed update.</summary>
        internal int? SequenceNumber { get; set; }
 
        internal static TestOpenAIResponsesContinuationToken FromToken(object token)
        {
            if (token is TestOpenAIResponsesContinuationToken testOpenAIResponsesContinuationToken)
            {
                return testOpenAIResponsesContinuationToken;
            }
 
            if (token is not ResponseContinuationToken)
            {
                throw new ArgumentException("Failed to create OpenAIResponsesResumptionToken from provided token because it is not of type ResponseContinuationToken.", nameof(token));
            }
 
            ReadOnlyMemory<byte> data = ((ResponseContinuationToken)token).ToBytes();
 
            Utf8JsonReader reader = new(data.Span);
 
            string responseId = null!;
            int? startAfter = null;
 
            _ = reader.Read();
 
            while (reader.Read())
            {
                if (reader.TokenType == JsonTokenType.EndObject)
                {
                    break;
                }
 
                string propertyName = reader.GetString()!;
 
                switch (propertyName)
                {
                    case "responseId":
                        _ = reader.Read();
                        responseId = reader.GetString()!;
                        break;
                    case "sequenceNumber":
                        _ = reader.Read();
                        startAfter = reader.GetInt32();
                        break;
                    default:
                        throw new JsonException($"Unrecognized property '{propertyName}'.");
                }
            }
 
            return new(responseId)
            {
                SequenceNumber = startAfter
            };
        }
 
        public override ReadOnlyMemory<byte> ToBytes()
        {
            using MemoryStream stream = new();
            using Utf8JsonWriter writer = new(stream);
 
            writer.WriteStartObject();
 
            writer.WriteString("responseId", ResponseId);
 
            if (SequenceNumber.HasValue)
            {
                writer.WriteNumber("sequenceNumber", SequenceNumber.Value);
            }
 
            writer.WriteEndObject();
 
            writer.Flush();
            stream.Position = 0;
 
            return stream.ToArray();
        }
    }
}