Langfuse
Helicone AI
LangSmith
LangChain
PromptLayer
Braintrust.dev
Portkey
Openlayer
UseWebhook
Webhook.site
ngrok
Webhooks.cc
HookReplay.dev
Beeceptor
Hookdeck
CatchKit.online
Langfuse is an open-source LLM engineering platform designed to empower developers by providing insights into user interactions with their LLM applications. We offer tools that help developers understand usage patterns, diagnose issues, and improve application performance based on real user data. By integrating seamlessly into existing workflows, Langfuse streamlines the process of monitoring, debugging, and optimizing LLM applications. Our platform's robust documentation and active community support make it easy for developers to leverage Langfuse for enhancing their LLM projects efficiently. Whether you're troubleshooting interactions or iterating on new features, Langfuse is committed to simplifying your LLM development journey.
UseWebhook is a free tool to capture webhooks from your browser.
โก๏ธ Test webhooks without a server ๐ Inspect and diff incoming requests ๐จโ๐ป Forward to localhost, or replay from history โ Debug webhooks from Stripe, Paddle, Slack, or anywhere else
No sign up required. Just send HTTP requests to your webhook URL.
Langfuse UseWebhookNo features have been listed yet.
No UseWebhook videos yet. You could help us improve this page by suggesting one.
Based on our record, Langfuse seems to be more popular. It has been mentiond 28 times since March 2021. 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.
In this project we will build a Python banking assistant agent using Strands Agents and make it observable and continuously evaluated using Langfuse โ step by step. - Source: dev.to / about 1 month ago
Langfuse is the open-source standard for LLM observability. It traces every LLM interaction โ prompts, completions, latency, token usage, cost โ and provides the tooling to debug, evaluate, and optimize LLM applications in production. Think of it as "Datadog for LLM calls" with a focus on prompt engineering workflows. - Source: dev.to / about 2 months 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 / 2 months ago
Gateway or proxy attribution. A reverse proxy in front of the model-provider API records the request, computes the cost, and exposes per-customer breakdowns. Open-source options include Helicone, LiteLLM, Langfuse, and OpenLLMetry. Hosted equivalents serve as the AI cost observability layer for teams that want centralized visibility: LangSmith, Datadog LLM Observability, Arize Phoenix. Adds a network hop.... - Source: dev.to / 2 months ago
Same approach works with Langfuse, Phoenix, Braintrust, or your existing OTel pipeline โ the metadata.userId pattern is the universal part. - Source: dev.to / 3 months ago
Helicone AI - Open-source LLM Observability for Developers
Webhook.site - Instantly generate a free, unique URL and email address to test, inspect, and automate (with a visual workflow editor and scripts) incoming HTTP requests and emails.
LangSmith - Build and deploy LLM applications with confidence
ngrok - ngrok enables secure introspectable tunnels to localhost webhook development tool and debugging tool.
LangChain - Framework for building applications with LLMs through composability
Webhooks.cc - Capture and inspect webhooks in real time. Send signed provider test webhooks, forward to localhost with the CLI, test in CI with the SDK, and debug faster with MCP.