DevDocs (open source, free) is a local offline documentation viewer. There is a hosted version that can be used offline in a web browser. - Source: dev.to / 2 months ago

This isn't a new idea for developer tools. DevDocs, Zeal, and Dash have offered offline documentation browsing for years. What's new is applying this architecture to AI agents — giving your coding assistant the same offline, instant, version-accurate access to docs that you'd want for yourself. - Source: dev.to / 5 months ago

DevDocs the minimalist doc reader for when Stack Overflow doesn’t have the answer. - Source: dev.to / about 1 year ago

ID: i26 Tags: Programming, API, Documentation Description: Fast, offline, and free documentation browser for developers. GitHub Link | Website Link. - Source: dev.to / over 1 year ago

Search API documentation effortlessly with DevDocs. - Source: dev.to / over 1 year ago

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 / about 1 month 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 2 months 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 / 4 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 / 5 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