golang/eino eino框架的基础使用 Message以及ChatModel入门

Eino

• 字节基于 Golang 的 AI 应用开发框架
• github
• 文档

Message

• 对话的基本单位
• 定义

  type Message struct {
      Role RoleType `json:"role"`
  
      // 消息内容 用户或者模型的实际输出文本
      Content string `json:"content"`
  
      // MultiContent 多模态消息内容 用户或者模型的多模态输出文本
      // 如果 MultiContent 不为空，使用 MultiContent 而不是 Content
      // Deprecated: Use UserInputMultiContent for user multimodal inputs and AssistantGenMultiContent for model multimodal outputs.
      MultiContent []ChatMessagePart `json:"multi_content,omitempty"`
  
      // UserInputMultiContent passes multimodal content provided by the user to the model.
      UserInputMultiContent []MessageInputPart `json:"user_input_multi_content,omitempty"`
  
      // AssistantGenMultiContent is for receiving multimodal output from the model.
      AssistantGenMultiContent []MessageOutputPart `json:"assistant_output_multi_content,omitempty"`
  
      Name string `json:"name,omitempty"`
  
      // ToolCalls 工具调用列表 仅用于模型回复
      ToolCalls []ToolCall `json:"tool_calls,omitempty"`
  
      // 工具调用ID 仅用于工具调用消息
      ToolCallID string `json:"tool_call_id,omitempty"`
      // 工具名称 仅用于工具调用消息
      ToolName string `json:"tool_name,omitempty"`
  
      ResponseMeta *ResponseMeta `json:"response_meta,omitempty"`
  
      // ReasoningContent is the thinking process of the model, which will be included when the model returns reasoning content.
      ReasoningContent string `json:"reasoning_content,omitempty"`
  
      // customized information for model implementation
      Extra map[string]any `json:"extra,omitempty"`
  }
  

• RoleType
  • Assistant = "assistant"
    模型回复
  • User = "user"
    用户输入
  • System = "system"
    系统提示
  • Tool = "tool"
    工具调用

ChatModel

• 对话模型
• 定义

  type BaseChatModel interface {
      Generate(ctx context.Context, input []*schema.Message, opts ...Option) (*schema.Message, error)
      Stream(ctx context.Context, input []*schema.Message, opts ...Option) (
        *schema.StreamReader[*schema.Message], error)
  }
  

• BaseChatModel 定义了对话模型的基本接口
  • Generate 生成单次消息的完整返回
  • Stream 生成一条消息的流式返回，即模型会实时返回消息的内容（通常是一个token一个token的返回），而不是等待模型完成后再返回
• eino 提供了多个对话模型的实现，如 OpenAI、Claude等，在使用时需要调用对应的实现

  import (
    "github.com/cloudwego/eino-ext/components/model/openai"
  )
  
  chatModel, err := openai.NewChatModel(ctx, &openai.ChatModelConfig{
      Model:   "qwen/qwen3.6-plus:free",
      BaseURL: "https://openrouter.ai/api/v1",
      APIKey:  "",
    })
  

  
  如上述代码所示，chatModel 就是一个 OpenAI 对话模型的实例，可以使用BaseURL来指定模型的 API 地址，来调用OpenAI Compatible API
• Generate 方法使用示例

  ret, err := chatModel.Generate(ctx, messages)
  if err != nil {
    _, _ = fmt.Fprintln(os.Stderr, err)
    os.Exit(1)
  }
  fmt.Println(ret.String())
  

  
  输出示例

  assistant: Hello! How can I assist you today?
  reasoning content:
  "Here's a thinking process:\n\n1.  **Analyze User Input:** The user said \"hello\". This is a simple greeting.\n2.  **Identify Intent:** The user is initiating a conversation.\n3.  **Determine Response Strategy:** \n   - Acknowledge the greeting warmly.\n   - Offer assistance.\n   - Keep it concise and friendly.\n4.  **Draft Response:** \"Hello! How can I assist you today?\" or \"Hi there! What can I help you with?\"\n5.  **Refine Response:** Both are good. I'll go with a friendly, open-ended response that invites the user to ask a question or state their need.\n6.  **Final Output Generation:** \"Hello! How can I assist you today?\" (matches the refined response)✅"
  finish_reason: stop
  usage: &{22 {0} 184 206 {170}}
  

• Stream 方法使用示例

  stream, err := cm.Stream(ctx, messages)
    if err != nil {
      _, _ = fmt.Fprintln(os.Stderr, err)
      os.Exit(1)
    }
    defer stream.Close()
  
    for {
      frame, err := stream.Recv()
      if errors.Is(err, io.EOF) {
        break
      }
      if err != nil {
        _, _ = fmt.Fprintln(os.Stderr, err)
        os.Exit(1)
      }
      if frame != nil {
        _, _ = fmt.Fprint(os.Stdout, frame.Content)
      }
    }
    _, _ = fmt.Fprintln(os.Stdout)
  

  
  输出示例

  [assistant] Hello! How can I assist you today?
  

交互式完整示例

package main

import (
    "bufio"
    "context"
    "errors"
    "flag"
    "fmt"
    "io"
    "os"
    "strings"

    "github.com/cloudwego/eino-ext/components/model/openai"
    "github.com/cloudwego/eino/components/model"
    "github.com/cloudwego/eino/schema"
)

func main() {
    var instruction string
    flag.StringVar(&instruction, "instruction", "You are a helpful assistant.", "")
    flag.Parse()

    ctx := context.Background()
    cm, err := newChatModel(ctx)
    if err != nil {
        _, _ = fmt.Fprintln(os.Stderr, err)
        os.Exit(1)
    }

    fmt.Println("Chat session started. Type 'exit' or 'quit' to end.")
    scanner := bufio.NewScanner(os.Stdin)

    messages := []*schema.Message{
        schema.SystemMessage(instruction),
    }
    for {
        fmt.Print("\n[User] ")
        if !scanner.Scan() {
            break
        }

        query := strings.TrimSpace(scanner.Text())
        if query == "" {
            continue
        }

        if query == "exit" || query == "quit" {
            break
        }

        messages = append(messages, schema.UserMessage(query))

        fmt.Print("[Assistant] ")
        stream, err := cm.Stream(ctx, messages)
        if err != nil {
            fmt.Fprintf(os.Stderr, "\nError: %v\n", err)
            continue
        }

        var response string
        for {
            frame, err := stream.Recv()
            if errors.Is(err, io.EOF) {
                break
            }
            if err != nil {
                fmt.Fprintf(os.Stderr, "\nStream error: %v\n", err)
                break
            }
            if frame != nil {
                fmt.Print(frame.Content)
                response += frame.Content
            }
        }

        messages = append(messages, schema.AssistantMessage(response, nil))

        fmt.Println()
        stream.Close()
    }
}

func newChatModel(ctx context.Context) (model.ToolCallingChatModel, error) {
    return openai.NewChatModel(ctx, &openai.ChatModelConfig{
        APIKey:  "",
        Model:   "qwen/qwen3.6-plus:free",
        BaseURL: "https://openrouter.ai/api/v1",
    })
}

Chat session started. Type 'exit' or 'quit' to end.

[User] hello
[Assistant] Hello! How can I help you today?

[User] i am spider man, remember this!
[Assistant] Got it, Spider-Man! 🕷️ I'll keep that in mind for the rest of our conversation. Just a quick heads-up: I don't haave persistent memory between chats, so if you start a new session later, I might need a quick reminder. But for now, your web-slinger status is officially noted! 

What's on your mind today? Stopping villains, working through some Parker-level science homework, or just swinging by to chat?

[User] who am i
[Assistant] You're Spider-Man! 🕷️ You told me just a moment ago, and I've got it noted for this chat. 

What's up, web-head? Need help tracking down a villain, troubleshooting some web-fluid chemistry, or just working through the daily superhero life balance? 😄

[User]