Langtrace AI

What is Langtrace AI

Langtrace AI is an open-source observability tool that helps developers monitor, evaluate, and improve their Large Language Model (LLM) applications. It provides advanced security, non-intrusive setup, and supports popular LLMs and frameworks. It collects and analyzes traces and metrics from LLM applications, providing end-to-end observability and insights into the entire ML pipeline, allowing developers to identify bottlenecks, optimize performance, and enhance their AI applications.

How to use Langtrace AI

Users can use Langtrace AI to monitor, evaluate, and improve their Large Language Model (LLM) applications by collecting and analyzing traces and metrics, providing end-to-end observability and insights into the entire ML pipeline. This helps developers identify bottlenecks, optimize performance, and enhance their AI applications.

Key Features

• Advanced security certified by a third-party auditor - Non-intrusive setup with just two lines of code - Supports popular LLMs and frameworks and vector databases

Frequently Asked Questions

What is Langtrace AI's primary function in the context of AI applications?

Langtrace AI is an open-source observability tool designed to collect and analyze traces and metrics from Large Language Model (LLM) applications, providing end-to-end observability and insights into the entire ML pipeline.

### How does Langtrace AI help developers evaluate and improve their LLM applications?
Langtrace AI allows developers to identify bottlenecks, optimize performance, and enhance their AI applications. It provides built-in evaluations and annotations for manual evaluation of LLM requests, and can be used to create golden datasets and establish a feedback loop for continuous testing and enhancement.

### What are some of the key benefits of using Langtrace AI for AI development?
Langtrace AI provides real-time visibility into ML pipelines, allowing developers to track cost and latency at project, model, and user levels. It also supports popular LLMs and frameworks, making it a versatile tool for a wide range of use cases.

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