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 / 21 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

The Google Cloud Shell API empowers organizations to automate cloud operations, accelerate software delivery, and improve efficiency. By providing a programmatic interface for managing Cloud Shell environments, the API unlocks new possibilities for developers, SREs, and data teams. Explore the official documentation and try the hands-on lab to experience the benefits of the Cloud Shell API firsthand. ... - Source: dev.to / about 1 year ago

Command-line (gcloud) -- Those who prefer working in a terminal can enable APIs with a single command in the Cloud Shell or locally on your computer if you installed the Cloud SDK which includes the gcloud command-line tool (CLI) and initialized its use. If this is you, issue this command to enable the API: gcloud services enable youtube.googleapis.com Confirm all the APIs you've enabled with this command:... - Source: dev.to / almost 2 years ago

Gcloud/command-line - Finally, for those more inclined to using the command-line, you can enable APIs with a single command in the Cloud Shell or locally on your computer if you installed the Cloud SDK (which includes the gcloud command-line tool [CLI]) and initialized its use. If this is you, issue the following command to enable all three APIs: gcloud services enable geocoding-backend.googleapis.com... - Source: dev.to / about 2 years ago

While you might find that using the Google Cloud online console or Cloud Shell environment meets your occasional needs, for maximum developer efficiency you will want to install the Google Cloud CLI (gcloud) on your own system where you already have your favorite editor or IDE and git set up. - Source: dev.to / over 3 years ago

Here is the product https://cloud.google.com/shell It has a quick start guide and docs. - Source: Hacker News / over 3 years ago