Original Summary

Hey everyone, Recently I came across this challenge where I had to move my project from one Agentic framework to another and moving the whole application is such a hassle. You prototype an agent in one framework, then want to try another. Your tools, result handling, and streaming code can become tied to your original choice, making comparison or migration more work than it should be. To solve this, I’m building AgentBridge , an open-source compatibility layer between your application and agent frameworks. AgentBridge lets you define instructions, tools, and expected output in a shared AgentSpec, then select the framework when running it. https://github.com/0sparsh2/AgentBridge Today, the project includes: - LangGraph and Pydantic AI adapters, verified locally. - A shared interface for results and streaming events. - CLI tools to inspect capabilities and validate backend fit. - Partial integrations for OpenAI Agents SDK, Strands, LangChain, and Google ADK. The tricky part is preserving what makes each framework useful. I’m handling that through explicit capability reports, framework-specific extensions, and access to native objects. If you’ve switched agent frameworks, what required the most rewriting: tools, state, orchestration, or something else? I’d especially appreciate examples that would stress-test this approach.   submitted by   /u/0sparsh2 [link]   [comments]

  • 情报分类：商业与市场研究
  • 分类依据：内容涉及商业、投资或市场动态
  • 信息来源：Reddit · SideProject
  • 发布时间：2026/9/15 21:37:15