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NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a better graphsignal-profiler alternative or higher similarity.

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graphsignal-profiler reviews and mentions

Posts with mentions or reviews of graphsignal-profiler. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-04-04.
  • Show HN: CUDA Profiler for Production Inference
    1 project | news.ycombinator.com | 23 Jun 2026
  • Show HN: Python Monitoring for LLMs, OpenAI, Inference, GPUs
    2 projects | news.ycombinator.com | 4 Apr 2023
    We've built it for apps that use LLMs and other ML models. The lightweight Python agent autoinstruments OpenAI, LangChain, Banana, and other APIs and frameworks. Basically by adding one line of code you'll be able to monitor and analyze latency, errors, compute and costs. Profiling using CProfile, PyTorch Kineto or Yappi can be enabled if code-level statistics are necessary.

    Here is a short demo screencast for a LangChain/OpenAI app: https://www.loom.com/share/17ba8aff32b74d74b7ba7f5357ed9250

    In terms of data privacy, we only send metadata and statistics to https://graphsignal.com. So no raw data, such as prompts or images leave your app.

  • Show HN: Python Monitoring for AI: LLMs, OpenAI, Inference, GPUs
    1 project | news.ycombinator.com | 29 Mar 2023
    2 projects | news.ycombinator.com | 28 Mar 2023
    Hi HN. I'm excited to share our AI-focused application monitoring and analytics for Python!

    We've built it for apps that use LLMs and other ML models. The lightweight Python agent autoinstruments OpenAI, LangChain, Banana, and other APIs and frameworks. Basically by adding one line of code you'll be able to monitor and analyze latency, errors, compute and costs. Profiling using CProfile, PyTorch Kineto or Yappi can be enabled if code-level statistics are necessary.

    Here is a short demo screencast for a LangChain/OpenAI app: https://www.loom.com/share/17ba8aff32b74d74b7ba7f5357ed9250

    In terms of data privacy, we only send metadata and statistics to https://graphsignal.com. So no raw data, such as prompts or images leave your app.

    We'd love to hear your feedback or ideas!

  • [N] Monitor OpenAI API Latency, Tokens, Rate Limits, and More with Graphsignal
    1 project | /r/MachineLearning | 31 Jan 2023
    Here is a blog post with more info and screenshots: Monitor OpenAI API Latency, Tokens, Rate Limits, and More. And the GitHub repo.
  • Monitor OpenAI API Latency, Tokens, Rate Limits, and More
    1 project | news.ycombinator.com | 31 Jan 2023
    Relying on hosted inference with LLMs, such as via OpenAI API, in production has some challenges. The use of APIs should be designed around unstable latency, rate limits, token counts, costs, etc. To make it observable we've built tracing and monitoring specifically for AI apps. For example, the OpenAI Python library is monitored automatically, no need to do anything. We'll be adding support for more libraries. If you'd like to give it try, see https://github.com/graphsignal/graphsignal or the docs.
  • [N] Easily profile FastAPI model serving
    1 project | /r/MachineLearning | 13 Oct 2022
    We've added a simple way to profile any model serving endpoint, including FastAPI, to identify bottlenecks and make inference (incl. data processing) faster, especially for big models and data. Wanted to share it here in case someone is struggling with profiling and monitoring of deployed code and models. By default, generic Python profiler will automatically profile some of the inferences (and measure all inferences). You can also specify other profilers for PyTorch, TensorFlow, Jax and ONNX Runtime. All profiles and metrics will be available on the SaaS dashboard, no need to setup anything. A couple of links to get started: Repo: https://github.com/graphsignal/graphsignal FastAPI example: https://graphsignal.com/docs/integrations/fastapi/ Happy for any feedback!
  • [P] Using Sparsity & Clustering to compress your models: Efficient Deep Learning Book
    2 projects | /r/MachineLearning | 1 Aug 2022
    Thanks for sharing! That's a very timely topic. I've actually created a profiler to track and analyze inference optimizations, i.e. enable the optimize-verify-evaluate loop.
  • [N] Accuracy-Aware Inference Optimization Tracking and Profiling
    1 project | /r/MachineLearning | 25 Jul 2022
    To address all these problems, we've built a tool to track inference optimizations, see how accuracy is affected, verify that the optimizations were applied and locate any bottlenecks for further improvements. All in one place.
  • Show HN: Graphsignal – ML profiler to speed up training and inference
    1 project | /r/hypeurls | 4 Jul 2022
  • A note from our sponsor - SaaSHub
    www.saashub.com | 13 Aug 2026
    SaaSHub helps you find the best software and product alternatives Learn more →

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