Dive AI 工作流

Dive

Dive is a foundational Go library for building AI agents and LLM-powered applications.

Dive gives you three main things: consistent access to 8+ LLM providers, a tool-calling system, and a robust agent loop with hooks. Images, documents, local tools, MCP tools, and structured output all work across providers. Most other libraries have gaps on this front. The agent runs the generate-call-repeat loop for you, with hooks to intercept before and after each step. Tools and hooks are the primary extension points.

The built-in toolkit includes Read, Write, Edit, Glob, Grep, Bash, and more. Use all of them, some of them, or bring your own. The built-in tools align with Claude Code's patterns, so you benefit from any model tuning that Anthropic has done for these tool shapes.

Dive is unopinionated. You provide the system prompt and decide which tools and hooks to install. Your agents do what you tell them. There are no hidden prompts or library-imposed behaviors.

Use the LLM layer when you want direct access to model capabilities. Use the agent layer when you want the tool-calling loop handled for you. Use Dive to build CLIs, add AI to back-end SaaS services, or run agents within a workflow orchestrator.

Everything outside the experimental/ directory is stable, while everything inside experimental/ may change. The experimental packages add more tools, permissions, and a CLI similar to Claude Code. Use experimental code as inspiration, copy and modify it, or use it directly.

Dive is developed by Deep Noodle and is used in multiple production AI deployments.

agent, err := dive.NewAgent(dive.AgentOptions{
    SystemPrompt: "You are a senior software engineer.",
    Model:        anthropic.New(),
    Tools: []dive.Tool{
        toolkit.NewReadFileTool(),
        toolkit.NewTextEditorTool(),
        toolkit.NewListDirectoryTool(),
    },
})

response, err := agent.CreateResponse(ctx, dive.WithInput("Please fix the failing test"))
fmt.Println(response.OutputText())

Experimental Features

Packages under experimental/* have no stability guarantees. APIs may change at any time.

• Compaction — Auto-summarize conversations approaching token limits
• Subagent — Spawn specialized child agents for subtasks
• Sandbox — Docker/Seatbelt isolation for tool execution
• MCP — Model Context Protocol client for external tools
• Settings — Load configuration from .dive/settings.json
• Todo — Real-time todo list tracking during agent execution
• Toolkit — Additional tool packages (extended, firecrawl, google, kagi)
• CLI — Interactive command-line interface (experimental/cmd/dive)