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 / 27 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 / about 1 month 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

One of the most famous talks in computer science is Simple Made Easy by Rich Hickey, The creator of the programming language Clojure. In it, he explains that, "simple" and "easy" are not the same thing. He refers to the word origins of the two words:. - Source: dev.to / 7 days ago

This series of post will try to explain a complex topic: concurrent and parallel programming, in Dart. I think the only way to deal with that is using the Erlang VM (BEAM), but Clojure and other functional languages are usually doing better job on this part. Unfortunately, to me, most of other languages using OOP don't offer a great abstraction to concurrency and parallelism, but during the last decade, things are... - Source: dev.to / about 2 months ago

Oversimplifying, there are three big variants: Common Lisp, Scheme, Clojure. Each of them has a lot of somewhat similar implementations: * Clojure: A lot of support for immutable data. It runs in the JVM so you will have a lot of the libraries you are use to. Probably the best option for you. https://clojure.org/ * Scheme, in particular Racket: Mostly functional, and in particular Racket has a lot of support to... - Source: Hacker News / about 1 year ago

Another project of mine Bob can be seen as an example of spec-first design. All its tooling follow that idea and its CLI inspired Climate. A lot of Bob uses Clojure a language that I cherish and who's ideas make me think better in every other place too. - Source: dev.to / over 1 year ago

Clojure is a LISP for the Java Virtual Machine (JVM). As a schemer, I wondered if I should give Clojure a go professionally. After all, I enjoy Rich Hickey's talks and even Uncle Bob is a Clojure fan. So I considered strength and weaknesses from my point of view:. - Source: dev.to / over 1 year ago