Helicone takes the simplest possible approach to LLM monitoring: it's a proxy. Change your OpenAI base URL from api.openai.com to oai.helicone.ai, add your Helicone API key as a header, and every LLM request is logged — latency, tokens, cost, prompts, and completions. No SDK integration, no code changes beyond a URL swap. - Source: dev.to / 19 days ago

You're monitoring production traffic. You need Langfuse / Phoenix / Helicone / Braintrust for that. Online eval is a different problem class: implicit feedback, drift detection, hallucination rates on your data, not on HellaSwag. - Source: dev.to / 29 days ago

For many teams, especially those starting out or with simpler needs, commercial solutions like Portkey, Helicone, OpenPipe, or LiteLLM Proxy offer off-the-shelf capabilities that cover many common proxy use cases (caching, logging, cost tracking). NeuroLink itself can be seen as an SDK that complements these, allowing you to integrate with them or build similar features on top. - Source: dev.to / 3 months ago

TL;DR: Go with Langfuse if you want open-source and self-hosted. Pick Helicone if you want the fastest setup (2 minutes, no SDK). Stick with LangSmith if your stack already runs on LangChain. And if your org already pays for Datadog, their LLM module slots right in. - Source: dev.to / 4 months ago

Hey HN, we're Justin and Cole, the founders of Helicone (https://helicone.ai) or self-deploy with our new fully open-source helm chart (https://helicone.ai/selfhost). Yet even with detailed traces, probabilistic systems are notoriously hard to debug at scale. So, we released evaluators (either via LLM-as-judge or custom Python evaluators leveraging the CodeSandbox SDK - https://codesandbox.io/docs/sdk/sandboxes).... - Source: Hacker News / over 1 year ago

To some extent it extends the concept of tasks which only can be reasonably executed after the completion of other ones (though results of branches eventually may join each other) and offers an additional assisting birds' eye visual of projects. So far, I'm aware about the documentation on worg interfacing org-taskjuggler and taskjuggler, as well as a video tutorial interfacing gnuplot instead. Source: about 3 years ago

Gnuplot is a program to plot diagrams. The Commands issued to use it don't change regardless if it is used in Linux/Windows/MacOS and it comes with less dependencies than a Spread sheet, or a statistics program. This is why I started to Become comfortable with it, and venture out some of its features. Here, "conditional plot" referred to "the diagram only displays a Thing/uses a pixel if the value in the table... Source: over 3 years ago

Or, does drawing diagrams refers to plotting data, but neither using matplotlib, nor gnuplot (export to .svg, .pdf, .png; pstricks, tikz to mention a few options)? Source: over 3 years ago

There may the occasion you actually need the data from a publication, and want to plot them altogether with data newly collected data in one diagram in common. An overlay, though possible, can become tricky (scaling, centering, alignment, etc.) and plotting all data in a diagram generated from scratch (gnuplot/octave, matplotlib, Origin, ...) exported as an illustration in the usual formats (.pdf/.png), or... Source: over 3 years ago

Have you looked at the graphing capabilities of Octave or Gnuplot? Gnuplot in particular has a lot of options, and a GUI for those who want it. Source: over 3 years ago