| 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:
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:
Documentation
Source
