🚀 crewai-go v0.4.0 is live!

If you love the multi-agent AI orchestration concepts from Python’s CrewAI, but want the performance, native concurrency, and low memory footprint of Go, check out crewai-go.

The v0.4.0 release brings key capabilities to make building multi-agent systems in Go fast, type-safe, and production-ready.

✨ Key Highlights:

🛠️ Custom Tools: Easily create and bind custom tools using tools.NewTool(...).

🔄 Sequential Context Flow: Outputs from previous tasks flow directly into subsequent tasks as context.

📦 Structured Outputs: Map LLM responses straight into native Go structs using standard json:"..." tags.

🏠 Flexible Provider Support: Run fully offline with Ollama or integrate seamlessly with OpenAI.

🧠 Short-Term Memory: Agents keep context across complex task executions.

💡 Quick Example:

package main

import (
    "context"
    "fmt"
    "log"

    "github.com/rhgs/crewai-go/crew"
)

func main() {
    researcher := crew.NewAgent(crew.AgentConfig{
        Role:      "AI Researcher",
        Goal:      "Analyze tech trends",
        Backstory: "An expert in discovering high-impact open-source Go tools.",
    })

    task := crew.NewTask(crew.TaskConfig{
        Description:    "Summarize the main benefits of using Go for AI agent orchestration.",
        ExpectedOutput: "3 concise bullet points.",
        Agent:          researcher,
    })

    c := crew.NewCrew(crew.CrewConfig{
        Agents: []*crew.Agent{researcher},
        Tasks:  []*crew.Task{task},
    })

    result, err := c.Kickoff(context.Background())
    if err != nil {
        log.Fatal(err)
    }

    fmt.Println(result.Raw)
}

🔗 Release details & GitHub repo:
github.com/rhgs/crewai-go/releases/tag/v0.4.0