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 / 29 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

Reasonably, that language is MicroPython [1] which is the special pared-down version of Python for memory-constrained embedded targets. [1]: https://micropython.org/. - Source: Hacker News / 5 months ago

In this post, we’ll walk through how to use MicroPython on the popular ESP8266 microcontroller to stream sensor data (like temperature and humidity) directly to a real-time web dashboard — no cloud platform, no third-party services, and no cost beyond your WiFi and coffee. - Source: dev.to / 9 months ago

Welcome to the world of MicroPython, an efficient and lightweight implementation of Python 3 that runs directly on microcontrollers like the ESP32. This blog post is a deep dive into building a real-world smart sensor project in under 15 minutes using MicroPython – no Arduino IDE, no C++, and no nonsense. - Source: dev.to / 9 months ago

I'll link to it because many people don't know a version of Python runs on microcontrollers: https://micropython.org/. - Source: Hacker News / over 1 year ago

I'm personally working on something like this for the ESP32, but written on top of micropython [1]. A few things are written in C such as the display driver, but otherwise most things are in micropython. We chose the T-Watch 2020 V3 microphone variant as the platform [2]. Our objective is to build a modern PDA device via a mostly stand-alone watch that can be synced across devices (initially the Linux desktop). We... - Source: Hacker News / over 1 year ago