
Langfuse
Helicone AI
LangSmith
LangChain
Openlayer
Braintrust.dev
Portkey
PromptLayer
MockServer
Beeceptor
Request inspector
HttpMaster
Webhook.site
Hoppscotch
API Fortress
CurlHub.io
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.
Langfuse
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Based on our record, Langfuse should be more popular than MockServer. 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 / 10 days 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 / 29 days 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
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 / about 1 month 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 / about 2 months ago
There are several strategies to solve this kind of challenge, but today we will see MockServer as a tool to resolve it. - Source: dev.to / over 1 year ago
The open-source examples are mockoon, mock-server.com, etc. Source: about 3 years ago
I've just found out MockServer and it looks awesome ๐คฉ so I wanted to check it out repeating the steps of my previous demo WireMock Testing which (as you can expect) uses WireMock, another fantastic tool to mock APIs. - Source: dev.to / about 4 years ago
I tend to use MockServer. With MockServer you can define inputs, so you can say that the request should look like this with that URL, etc etc. That way you can verify that the request looks okay. Source: over 4 years ago
Helicone AI - Open-source LLM Observability for Developers
Beeceptor - Unblock yourself from API dependencies, and build & integrate with APIs fast. Beeceptor helps you build a mock Rest API in a few seconds.
LangSmith - Build and deploy LLM applications with confidence
Request inspector - Debug web hooks, http clients
LangChain - Framework for building applications with LLMs through composability
HttpMaster - HttpMaster is a professional software tool for testing and debugging HTTP applications, primarily aimed at REST API applications and web services.