crewai-go v0.4.0 is live!

The crewai-go project released v0.4.0, bringing multi-agent AI orchestration to Go with custom tools, sequential context flow, structured outputs, flexible provider support, and short-term memory. The release enables developers to build type-safe, production-ready multi-agent systems in Go, with support for offline use via Ollama or integration with OpenAI.

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