[HN Gopher] Segment for LLM Traces? Seeking Feedback on an Open ...
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       Segment for LLM Traces? Seeking Feedback on an Open Source LLM Log
       Router
        
       Hey everyone, I'm considering starting a new open source project
       and wanted to see if anyone else thinks the idea could be useful.
       The concept is simple: an open source LLM log router that works
       like Segment--but specifically for LLM logs. It would let you
       easily route logs to different analytics, eval, monitoring, and
       data warehouse platforms (think LangFuse, Gentrace, Lattitude,
       etc.) so you can leverage the strengths of each without needing
       separate integrations. I've run into a few recurring challenges
       when integrating multiple eval and monitoring tools.  Conflicting
       Integrations: Many tools use their own forks of popular packages
       (like the OpenAI SDK or LangChain), which often conflict--making it
       nearly impossible to use them together.  Inconsistent Prompt
       Templating: Sometimes different tools require different prompt
       formats, complicating the process of switching between them or
       using multiple tools simultaneously.  Data Migration Challenges:
       Moving logs between systems is a hassle. Testing a new tool often
       means generating new data or deploying changes in production,
       making it hard to evaluate if switching is worthwhile.  While some
       solutions exist (such as LangChain and LiteLLM integrations with
       various eval platforms), they don't fully address these issues--
       especially data migration and integrating with multiple tools at
       once. To solve this, I'm toying with the idea of a new open source
       project--a lightweight, self-hosted server that acts as a "Segment
       for LLM traces and logs". Here are some of the features I envision.
       Self-hosted logging server: Send LLM traces to a single endpoint
       without impacting your app's performance.  Centralized aggregation
       and routing: Gather traces and logs on a single server, then
       forward them to any destination you choose (evals, analytics,
       monitoring, alerting, data warehouses, etc).  Lightweight Framework
       integrations: Support for popular frameworks and SDKs (LangChain,
       LiteLLM, OpenAI SDK, LlamaIndex, etc.) with integrations that never
       block your event loop--so even if the logging server or a
       destination platform goes down your app continues to function as
       expected.  Easy configuration: A simple interface for managing data
       sources and destinations without making code changes or redeploying
       your application.  Data portability: Store logs in a database with
       the option to re-export to new tools in the future--ensuring you
       never face vendor lock-in.  Custom integrations: Webhooks to easily
       set up your own custom destinations.  I'd love to hear if you've
       experienced any similar issues integrating with multiple LLM
       monitoring, eval, and analytics platforms. If so, how did you
       address them? Do you see value in an open source data router like
       this? Please share your thoughts in the comments, and if you're
       interested in contributing or using a project like this in the
       future, it'd be super helpful if you could fill out this survey.
       https://yk1m5yevl9j.typeform.com/to/cQdxF6bN  Thanks in advance for
       your feedback!
        
       Author : patethegreat
       Score  : 4 points
       Date   : 2025-02-21 22:44 UTC (16 minutes ago)
        
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       (page generated 2025-02-21 23:01 UTC)