OpenAI Integration

dotnet add package AutoGen.OpenAI

using AutoGen.OpenAI;
using AutoGen.OpenAI.Extension;
using OpenAI;

var openAIClient = new OpenAIClient(apiKey);

var agent = new OpenAIChatAgent(
    chatClient: openAIClient.GetChatClient("gpt-4-turbo"),
    name: "assistant",
    systemMessage: "You are a helpful assistant",
    seed: 0,                    // For reproducible outputs
    temperature: 0.7f,          // Creativity level
    maxTokens: 2000,            // Max response length
    responseFormat: null)       // JSON mode if needed
    .RegisterMessageConnector()
    .RegisterPrintMessage();

using AutoGen.Core;

var agent = new OpenAIChatAgent(
    chatClient: openAIClient.GetChatClient("gpt-4"),
    name: "assistant")
    .RegisterMessageConnector();

var messages = new[]
{
    new TextMessage(Role.User, "Write a long story about a robot")
};

await foreach (var message in agent.GenerateStreamingReplyAsync(messages))
{
    if (message.GetContent() is string content)
    {
        Console.Write(content);
    }
}

using OpenAI.Chat;

var agent = new OpenAIChatAgent(
    chatClient: openAIClient.GetChatClient("gpt-4"),
    name: "assistant",
    systemMessage: "You output valid JSON only",
    responseFormat: ChatResponseFormat.CreateJsonObjectFormat())
    .RegisterMessageConnector();

var response = await agent.SendAsync(@"
    Create a JSON object for a person with name, age, and hobbies.
");

Console.WriteLine(response.GetContent());
// Output: {"name": "John", "age": 30, "hobbies": ["reading", "gaming"]}

using System.Text.Json;
using System.Text.Json.Serialization;
using OpenAI.Chat;

// Define your schema
public class Person
{
    [JsonPropertyName("name")]
    public string Name { get; set; }

    [JsonPropertyName("age")]
    public int Age { get; set; }

    [JsonPropertyName("email")]
    public string Email { get; set; }
}

var jsonSchema = JsonSerializer.Serialize(new
{
    type = "object",
    properties = new
    {
        name = new { type = "string" },
        age = new { type = "integer" },
        email = new { type = "string" }
    },
    required = new[] { "name", "age", "email" },
    additionalProperties = false
});

var agent = new OpenAIChatAgent(
    chatClient: openAIClient.GetChatClient("gpt-4"),
    name: "assistant",
    systemMessage: "Extract person information as JSON",
    responseFormat: ChatResponseFormat.CreateJsonSchemaFormat(
        "person",
        BinaryData.FromString(jsonSchema)))
    .RegisterMessageConnector();

var response = await agent.SendAsync(
    "John Doe is 30 years old. His email is [email protected]");

var person = JsonSerializer.Deserialize<Person>(response.GetContent());
Console.WriteLine($"Name: {person.Name}, Age: {person.Age}");

using AutoGen.Core;
using AutoGen.OpenAI;
using AutoGen.OpenAI.Extension;
using Microsoft.Extensions.AI;

public partial class WeatherFunctions
{
    /// <summary>
    /// Get current weather
    /// </summary>
    /// <param name="location">city name</param>
    [Function]
    public async Task<string> GetWeather(string location)
    {
        return $"Weather in {location}: Sunny, 72°F";
    }
}

var tools = new WeatherFunctions();
var gpt4 = openAIClient.GetChatClient("gpt-4");

var functionCallMiddleware = new FunctionCallMiddleware(
    functions: [tools.GetWeatherFunctionContract],
    functionMap: new Dictionary<string, Func<string, Task<string>>>
    {
        { nameof(tools.GetWeather), tools.GetWeatherWrapper }
    });

var agent = new OpenAIChatAgent(
    chatClient: gpt4,
    name: "assistant")
    .RegisterMessageConnector()
    .RegisterStreamingMiddleware(functionCallMiddleware)
    .RegisterPrintMessage();

var response = await agent.SendAsync("What's the weather in Seattle?");
Console.WriteLine(response.GetContent());
// Output: The weather in Seattle is sunny with a temperature of 72°F.

using AutoGen.Core;

var agent = new OpenAIChatAgent(
    chatClient: openAIClient.GetChatClient("gpt-4-vision-preview"),
    name: "vision_assistant")
    .RegisterMessageConnector();

// Create a multimodal message
var imageMessage = new ImageMessage(
    Role.User,
    "https://example.com/image.jpg",
    from: "user");

var textMessage = new TextMessage(
    Role.User,
    "What's in this image?",
    from: "user");

var response = await agent.SendAsync(
    new[] { imageMessage, textMessage });

Console.WriteLine(response.GetContent());

using AutoGen.OpenAI.Extension;

// Register message connector to handle AutoGen message types
var agent = new OpenAIChatAgent(/*...*/)
    .RegisterMessageConnector();  // Required for AutoGen messages

// Now supports:
// - TextMessage
// - ImageMessage  
// - ToolCallMessage
// - ToolCallResultMessage
// - ToolCallAggregateMessage

using AutoGen;
using AutoGen.OpenAI;

var openAIConfig = new OpenAIConfig(apiKey, "gpt-4");

var agent = new AssistantAgent(
    name: "assistant",
    systemMessage: "You are helpful",
    llmConfig: new ConversableAgentConfig
    {
        Temperature = 0,
        MaxToken = 2000,
        ConfigList = [openAIConfig],
        TimeoutInSeconds = 60,
        StopSequence = ["END"]
    });

using OpenAI;

// Point to Ollama's OpenAI-compatible endpoint
var ollamaClient = new OpenAIClient(
    new ApiKeyCredential("not-used"),
    new OpenAIClientOptions
    {
        Endpoint = new Uri("http://localhost:11434/v1")
    });

var agent = new OpenAIChatAgent(
    chatClient: ollamaClient.GetChatClient("llama2"),
    name: "assistant")
    .RegisterMessageConnector();

var response = await agent.SendAsync("Hello!");