Helicone
Lightweight LLM observability via a proxy URL swap — get cost tracking, request logging, and caching with a one-line integration.
Why Helicone?
You want minimal-friction observability — just change your base URL
Caching identical LLM requests to cut costs
Quick cost and latency dashboards without SDK changes
Signal Breakdown
What drives the Trust Score
Download Trend
Last 12 months
Tradeoffs & Caveats
Know before you commitYou need deep trace trees across multi-step agent chains — use Langfuse
Self-hosting is a hard requirement
Pricing
Free tier & paid plans
Free: 10k requests/mo
Pro: $20/mo for 100k requests
Alternative Tools
Other options worth considering
Open-source LLM observability platform for tracing, evaluating, and debugging AI applications — self-host or use the cloud.
LangChain's observability and evaluation platform — trace, debug, and evaluate LLM applications with deep LangChain ecosystem integration.
Often Used Together
Complementary tools that pair well with Helicone
Learning Resources
Docs, videos, tutorials, and courses
Get Started
Repository and installation options
View on GitHub
github.com/Helicone/helicone
npm install heliconeQuick Start
Copy and adapt to get going fast
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.OPENAI_API_KEY,
baseURL: 'https://oai.helicone.ai/v1',
defaultHeaders: { 'Helicone-Auth': `Bearer ${process.env.HELICONE_API_KEY}` },
});
// All calls are now logged automaticallyCommunity Notes
Real experiences from developers who've used this tool