LangWatch

LangWatch is an open-source LLMOps platform designed to monitor, evaluate, debug, and optimize large language model (LLM) applications and AI agents. It provides observability into AI workflows, capturing detailed traces, conversations, token usage, and costs, enabling teams to collaborate and improve AI performance efficiently.

LangWatch offers several main features including Experimentation & Optimization, allowing users to test and improve custom LLM pipelines with ease. It provides Monitoring to track AI behavior and performance metrics in real-time with detailed traces and spans of each AI interaction. Evaluation tools are available to assess LLM outputs for accuracy and correctness via datasets and versioned prompt testing. Agent Testing & Simulation enables running scripted simulations and scenario tests to catch failures before production. For Collaboration, it supports both technical and non-technical users through UI and API for prompt management, dataset annotation, and feedback. Lastly, Enterprise Controls offer role-based access, data privacy options like on-prem, VPC, or hybrid, and certifications such as GDPR and ISO27001.

LangWatch can be installed as a Python package using pip (pip install langwatch). After installation, you sign up on their platform, create projects, and set an API key in your environment. You then instrument your code by importing LangWatch and wrapping your LLM logic with trace decorators to automatically capture inputs, outputs, latency, and cost data.

You can create and version prompts, run evaluations on datasets to identify failing examples, iterate on prompts, and compare prompt versions using LangWatch’s evaluation tools. This allows validation before deploying prompts into production applications, preventing regressions and improving response quality.

It integrates smoothly with Python-based chatbots and AI frameworks like Chainlit and OpenAI, supports any LLM app or agent framework, and provides APIs and a web UI for monitoring and managing workflows.

Yes, LangWatch automatically tracks token counts and costs associated with each LLM call, providing analytics to monitor and optimize usage expenses.

Yes, it is designed for collaboration across teams including AI engineers, data scientists, product managers, and domain experts. Both technical and non-technical users can participate via programmatic APIs or user-friendly interfaces.

LangWatch provides documentation, a Discord community for discussions and support, and a troubleshooting section to help resolve issues during usage.