Helicone AI
Langfuse
LangSmith
Portkey
liteLLM
OpenRouter
Eden AI
LangChain
Pl@ntNet
PictureThis
iNaturalist
Garden Answers
Gardenia
HortusFox
iPflanzen
Plant Parent
Helicone AI
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Helicone AI might be a bit more popular than Pl@ntNet. We know about 5 links to it since March 2021 and only 4 links to Pl@ntNet. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
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 โ 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 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
There are a number of phone apps that will identify trees from a picture. I personally prefer plantnet.org (non-profit entity / no ads or tracking). Source: about 4 years ago
You can also go directly to plantnet.org and perform the same check. Source: over 4 years ago
Get the app from plantnet.org. It's developed by a non-profit consortium of European organizations. I promise it's completely ad free and won't terrorize you in any way. Source: over 4 years ago
You could scrape them off the plantnet.org site. But unless your problem is purely academic you could skip creating your own engine and just use their API. Source: over 4 years ago
Langfuse - Langfuse is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications.
PictureThis - Instantly identify your plants
LangSmith - Build and deploy LLM applications with confidence
iNaturalist - iNaturalist is known as one of the most popular nature applications that helps you to identify the animals, plants, insects, and lots of other things with just a single click.
Portkey - Build production-grade & reliable AI apps with Portkey
Garden Answers - Garden Answers is an online plant identification application that allows you to get detailed information about any plants or flowers in your garden.