Chat Completions

Chat completions are the core of conversational AI in the Gen AI China plugin. This page covers how to send text-based and multimodal chat requests to the supported Chinese AI providers.

---

1. Basic Text Chat

The simplest way to interact with AI models is through text-only chat completions. Send a series of messages (system prompt, user input, assistant responses) and receive a generated response.

In Blueprints

Use the “Request [Provider] Chat Completion” node for the provider you want, such as Request Alibaba Chat Completion or Request Bytedance Chat. You’ll need to provide:

• Settings: Use a “Make…“ node (e.g., Make GenZhAlibabaChatSettings) to configure model selection, temperature, max tokens, region, etc.
• Messages: An array of GenZh Chat Message structs with role (system/user/assistant) and content.
• OnComplete: An event pin that fires with the Response, Error, and Success values.

A simple setup for testing chat completion with an Alibaba model.

In C++

Use the static function from the provider’s chat class:

#include "Models/Alibaba/GenZhAlibabaChat.h"
#include "Data/Alibaba/GenZhAlibabaChatStructs.h"
#include "Data/GenZhMessageStructs.h"

void AMyActor::SendSimpleChatRequest()
{
    FGenZhAlibabaChatSettings ChatSettings;
    ChatSettings.Model = TEXT("qwen-plus");

    TArray<FGenZhChatMessage> Messages;
    FGenZhChatMessage Message;
    Message.Role = TEXT("user");
    Message.Content.Add(FGenZhMessageContent::FromText(TEXT("Tell me a short story.")));
    Messages.Add(Message);
    ChatSettings.Messages = Messages;

    TWeakObjectPtr<AMyActor> WeakThis(this);

    UGenZhAlibabaChat::SendChatRequest(ChatSettings,
        FOnAlibabaChatCompletionResponse::CreateLambda([WeakThis](const FString& Response, const FString& Error, bool bSuccess)
        {
            if (!WeakThis.IsValid()) return;

            if (bSuccess)
            {
                // Process the response
            }
            else
            {
                // Handle the error
            }
        })
    );
}

---

2. Multimodal Chat (Vision)

Several providers support multimodal inputs, allowing you to include images alongside text in your chat messages. This enables use cases like analyzing in-game screenshots or creating environment-aware NPC interactions.

Supported Providers

• Alibaba (Qwen VL models)
• Bytedance (Seed models)
• ZhipuAI (GLM-V models)

Use the UGenZhContentFactory to construct messages with both text and image content parts.

---

3. Bytedance VolcEngine (China Region): Model ID Prefix

When using the Mainland China (Volcanic Engine) region for Bytedance, the API expects model names with a doubao- prefix. Our catalog auto applies these model names and send something like this below.

Our Catalog Name	Bytedance’s Actual API ID (China)
seed-2-0-mini-260215	doubao-seed-2-0-mini-260215
seed-2-0-lite-260228	doubao-seed-2-0-lite-260228
seed-1-6-250615	doubao-seed-1-6-250615
deepseek-v3-1-250821	doubao-deepseek-v3-1-250821
seedream-4-0-250828	doubao-seedream-4-0-250828
…etc	…etc

Contact our support if you run into any issues

4. Streaming Chat Responses

For real-time chat experiences, use the streaming versions of chat nodes. These provide incremental responses as they’re generated, perfect for typewriter effects and responsive AI companions.

See the Streaming page for detailed information on implementing streaming chat.

---

5. Best Practices

• Message History: Maintain conversation context by including previous messages in the array. See Building Long Conversations.
• System Prompts: Use system messages to set the AI’s behavior and role.
• Token Limits: Monitor token usage to avoid hitting API limits and manage costs.
• Error Handling: Always check the Success boolean and handle errors gracefully.
• Use Streaming: For any real-time chat interface, use streaming to provide immediate feedback.