• I'm curious -- let's say we have claude code hooked up to MCPs for jaeger, grafana, and the usual git/gh CLIs it can use out-of-the-box, and we let claude's planner work through investigations with whatever help we give it. Would TraceRoot do anything clever wrt the AI that such as a setup wouldn't/couldn't?

    (I'm asking b/c we're planning a setup that's basically that, so real question.)

  • I like the idea of this and the use case, but don't love the tight coupling to openai. I'd love to see a framework for allowing BYOM.
    • It's been 2.5 years since ChatGPT came out, and so many projects still don't allow for easy switching of the OPEN_AI_BASE_URL or affiliated parameters.

      There are so many inferencing libraries that serve an OpenAI-compatible API that any new project being locked in to OpenAI only is a large red flag for me.

      • Thanks for the feedback! Totally hear you on the tight OpenAI coupling - we're aware and already working to make BYOM easier. Just to echo what Zecheng said earlier: broader model flexibility is definitely on the roadmap.

        Appreciate you calling it out — helps us stay honest about the gaps.

    • Yes, there is a roadmap to support more models. For now there is a in progress PR to support Anthropic models https://github.com/traceroot-ai/traceroot/pull/21 (contributed by some active open source contributors) Feel free to let us know which (open source) model or framework (VLLM etc.) you want to use :)
      • Why not use something like litellm?
        • That's also one option, we will consider add it later :)
    • Adding model provider abstraction would significantly improve adoption, especially for organizations with specific LLM preferences or air-gapped environments that can't use OpenAI.
      • Yep, you're spot on - and we're hearing this loud and clear across the thread. Model abstraction is on the roadmap, and we're already working on making BYOM smoother.
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