Eino Tutorial: Host Multi-Agent

Host Multi-Agent is a Host that performs intent recognition and then delegates the actual generation task to a specific expert agent.

Take a simple “Journal Assistant” as an example: it can write journals, read journals, and answer questions based on journal entries.

For a full example, see: https://github.com/cloudwego/eino-examples/tree/main/flow/agent/multiagent/host/journal

Host:

func newHost(ctx context.Context, baseURL, apiKey, modelName string) (*host.Host, error) {
    chatModel, err := openai.NewChatModel(ctx, &openai.ChatModelConfig{
       BaseURL: baseURL,
       Model:   modelName,
       ByAzure: true,
       APIKey:  apiKey,
    })
    if err != nil {
       return nil, err
    }

    return &host.Host{
       ChatModel:    chatModel,
       SystemPrompt: "You can read and write journal on behalf of the user. When user asks a question, always answer with journal content.",
    }, nil
}

The “specialist” for writing journals: after the host recognizes that the user’s intent is to write a journal, it delegates the task here, where the user’s intended content is written to a file.

func newWriteJournalSpecialist(ctx context.Context) (*host.Specialist, error) {
    chatModel, err := ollama.NewChatModel(ctx, &ollama.ChatModelConfig{
       BaseURL: "http://localhost:11434",
       Model:   "llama3-groq-tool-use",

       Options: &api.Options{
          Temperature: 0.000001,
       },
    })
    if (err != nil) {
       return nil, err
    }

    // use a chat model to rewrite user query to journal entry
    // for example, the user query might be:
    //
    // write: I got up at 7:00 in the morning.
    // 
    // should be rewritten to:
    //
    // I got up at 7:00 in the morning.
    chain := compose.NewChain[[]*schema.Message, *schema.Message]()
    chain.AppendLambda(compose.InvokableLambda(func(ctx context.Context, input []*schema.Message) ([]*schema.Message, error) {
       systemMsg := &schema.Message{
          Role:    schema._System_,
          Content: "You are responsible for preparing the user query for insertion into journal. The user's query is expected to contain the actual text the user wants to write to the journal, as well as convey the intention that this query should be written to the journal. Your job is to remove that intention from the user query, while preserving as much as possible the user's original query, and output ONLY the text to be written into the journal.",
       }
       return append([]*schema.Message{systemMsg}, input...), nil
    })).
       AppendChatModel(chatModel).
       AppendLambda(compose.InvokableLambda(func(ctx context.Context, input *schema.Message) (*schema.Message, error) {
          err := appendJournal(input.Content)
          if err != nil {
             return nil, err
          }
          return &schema.Message{
             Role:    schema._Assistant_,
             Content: "Journal written successfully: " + input.Content,
          }, nil
       }))

    r, err := chain.Compile(ctx)
    if err != nil {
       return nil, err
    }

    return &host.Specialist{
       AgentMeta: host.AgentMeta{
          Name:        "write_journal",
          IntendedUse: "treat the user query as a sentence of a journal entry, append it to the right journal file",
       },
       Invokable: func(ctx context.Context, input []*schema.Message, opts ...agent.AgentOption) (*schema.Message, error) {
          return r.Invoke(ctx, input, agent.GetComposeOptions(opts...)...)
       },
    }, nil
}

The “specialist” for reading journals: after the host recognizes that the user’s intent is to read a journal, it delegates the task here. This specialist reads the journal file content and outputs it line by line. It functions as a local function.

func newReadJournalSpecialist(ctx context.Context) (*host.Specialist, error) {
    // create a new read journal specialist
    return &host.Specialist{
       AgentMeta: host.AgentMeta{
          Name:        "view_journal_content",
          IntendedUse: "let another agent view the content of the journal",
       },
       Streamable: func(ctx context.Context, input []*schema.Message, opts ...agent.AgentOption) (*schema.StreamReader[*schema.Message], error) {
          now := time.Now()
          dateStr := now.Format("2006-01-02")

          journal, err := readJournal(dateStr)
          if err != nil {
             return nil, err
          }

          reader, writer := schema.Pipe[*schema.Message](0)
          go func() {
             scanner := bufio.NewScanner(journal)
             scanner.Split(bufio.ScanLines)

             for scanner.Scan() {
                line := scanner.Text()
                message := &schema.Message{
                   Role:    schema._Assistant_,
                   Content: line + "\n",
                }
                writer.Send(message, nil)
             }

             if err := scanner.Err(); err != nil {
                writer.Send(nil, err)
             }

             writer.Close()
          }()

          return reader, nil
       },
    }, nil
}

According to the journal answer specialist:

func newAnswerWithJournalSpecialist(ctx context.Context) (*host.Specialist, error) {
    chatModel, err := ollama.NewChatModel(ctx, &ollama.ChatModelConfig{
       BaseURL: "http://localhost:11434",
       Model:   "llama3-groq-tool-use",

       Options: &api.Options{
          Temperature: 0.000001,
       },
    })
    if err != nil {
       return nil, err
    }

    // create a graph: load journal and user query -> chat template -> chat model -> answer

    graph := compose.NewGraph[[]*schema.Message, *schema.Message]()

    if err = graph.AddLambdaNode("journal_loader", compose.InvokableLambda(func(ctx context.Context, input []*schema.Message) (string, error) {
       now := time.Now()
       dateStr := now.Format("2006-01-02")

       return loadJournal(dateStr)
    }), compose.WithOutputKey("journal")); err != nil {
       return nil, err
    }

    if err = graph.AddLambdaNode("query_extractor", compose.InvokableLambda(func(ctx context.Context, input []*schema.Message) (string, error) {
       return input[len(input)-1].Content, nil
    }), compose.WithOutputKey("query")); err != nil {
       return nil, err
    }

    systemTpl := `Answer user's query based on journal content: {journal}'`
    chatTpl := prompt.FromMessages(schema._FString_,
       schema.SystemMessage(systemTpl),
       schema.UserMessage("{query}"),
    )
    if err = graph.AddChatTemplateNode("template", chatTpl); err != nil {
       return nil, err
    }

    if err = graph.AddChatModelNode("model", chatModel); err != nil {
       return nil, err
    }

    if err = graph.AddEdge("journal_loader", "template"); err != nil {
       return nil, err
    }

    if err = graph.AddEdge("query_extractor", "template"); err != nil {
       return nil, err
    }

    if err = graph.AddEdge("template", "model"); err != nil {
       return nil, err
    }

    if err = graph.AddEdge(compose._START_, "journal_loader"); err != nil {
       return nil, err
    }

    if err = graph.AddEdge(compose._START_, "query_extractor"); err != nil {
       return nil, err
    }

    if err = graph.AddEdge("model", compose._END_); err != nil {
       return nil, err
    }

    r, err := graph.Compile(ctx)
    if err != nil {
       return nil, err
    }

    return &host.Specialist{
       AgentMeta: host.AgentMeta{
          Name:        "answer_with_journal",
          IntendedUse: "load journal content and answer user's question with it",
       },
       Invokable: func(ctx context.Context, input []*schema.Message, opts ...agent.AgentOption) (*schema.Message, error) {
          return r.Invoke(ctx, input, agent.GetComposeOptions(opts...)...)
       },
    }, nil
}

Compose into a host multi-agent and start it via command line:

func main() {
    ctx := context.Background()
    h, err := newHost(ctx)
    if err != nil {
       panic(err)
    }

    writer, err := newWriteJournalSpecialist(ctx)
    if err != nil {
       panic(err)
    }

    reader, err := newReadJournalSpecialist(ctx)
    if err != nil {
       panic(err)
    }

    answerer, err := newAnswerWithJournalSpecialist(ctx)
    if err!= nil {
        panic(err)
    }

    hostMA, err := host.NewMultiAgent(ctx, &host.MultiAgentConfig{
       Host: *h,
       Specialists: []*host.Specialist{
          writer,
          reader,
          answerer,
       },
    })
    if err != nil {
       panic(err)
    }

    cb := &logCallback{}

    for { // Multi-turn conversation, loops continuously unless the user inputs "exit"
       println("\n\nYou: ") // Prompting for user input

       var message string
       scanner := bufio.NewScanner(os.Stdin) // Getting user input from command line
       for scanner.Scan() {
          message += scanner.Text()
          break
       }

       if err := scanner.Err(); err != nil {
          panic(err)
       }

       if message == "exit" {
          return
       }

       msg := &schema.Message{
          Role:    schema._User_,
          Content: message,
       }

       out, err := hostMA.Stream(ctx, []*schema.Message{msg}, host.WithAgentCallbacks(cb))
       if err != nil {
          panic(err)
       }

       defer out.Close()

       println("\nAnswer:")

       for {
          msg, err := out.Recv()
          if err != nil {
             if err == io.EOF {
                break
             }
          }

          print(msg.Content)
       }
    }
}

Running console output:

You:
write journal: I got up at 7:00 in the morning

HandOff to write_journal with argument {"reason":"I got up at 7:00 in the morning"}

Answer:
Journal written successfully: I got up at 7:00 in the morning

You:
read journal

HandOff to view_journal_content with argument {"reason":"User wants to read the journal content."}

Answer:
I got up at 7:00 in the morning


You:
when did I get up in the morning?

HandOff to answer_with_journal with argument {"reason":"To find out the user's morning wake-up times"}

Answer:
You got up at 7:00 in the morning.

Last modified February 21, 2025 : doc: add eino english docs (#1255) (4f6a3bd)