monitor-and-evaluate-llm-agent-traffic-with-helicone

name	Monitor and evaluate LLM agent traffic with Helicone
slug	monitor-and-evaluate-llm-agent-traffic-with-helicone
description	Route model calls through Helicone, inspect costs, latency, traces, prompts, and evaluations, then review changes before they ship.
github_stars	5779
verification	security_reviewed
source	https://github.com/Helicone/helicone
author	Helicone
publisher_type	organization
category	Monitoring & Alerts
framework	Multi-Framework
tool_ecosystem	{"github_repo":"Helicone/helicone","github_stars":5779,"npm_package":"helicone","npm_weekly_downloads":49}

Monitor and evaluate LLM agent traffic with Helicone

Route model calls through Helicone, inspect costs, latency, traces, prompts, and evaluations, then review changes before they ship.

Prerequisites

Helicone account or self-hosted Helicone deployment, LLM application or agent using an OpenAI-compatible client, configured HELICONE_API_KEY or self-hosted environment.

Installation

Use the upstream install or setup path that matches your environment:

• git clone https://github.com/Helicone/helicone.git
• Manual deployment is not recommended. Please use Docker or Helm. If you must, follow the instructions here.

Requirements and caveats from upstream:

• Helicone is simple to self-host and update. To get started locally, just use our docker-compose file.
• cd docker
• | AI Gateway | JS/TS, Python, cURL | Unified API for 100+ providers with intelligent routing, automatic fallbacks, and unified observability

Basic usage or getting-started notes:

• Get your API key by signing up here and add credits at helicone.ai/credits

• Update the baseURL in your code and add your API key.

• typescript

• Source: https://github.com/Helicone/helicone

• Extracted from upstream docs: https://raw.githubusercontent.com/Helicone/helicone/HEAD/README.md

Documentation

• https://docs.helicone.ai/

Source

• Agent Skill Exchange