langfuse and langtrace
Both are open-source LLM observability platforms built on OpenTelemetry standards that compete for the same use case (tracing, metrics, and evals for LLM applications), though Langfuse has significantly broader adoption and additional features like prompt management and datasets.
About langfuse
langfuse/langfuse
🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23
This platform helps AI application developers build, test, and improve their large language model (LLM) powered products. It takes data from your LLM application's usage and provides tools for debugging, evaluating performance, and managing prompts. The end users are developers, machine learning engineers, and product managers working on AI applications.
About langtrace
Scale3-Labs/langtrace
Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊
This tool helps developers understand and improve their AI applications that use large language models (LLMs). It takes information about how your LLM application is running, including its interactions with LLM APIs, vector databases, and frameworks. In return, you get real-time traces, performance insights like latency and cost, and debugging tools to identify issues. This is for software developers and AI engineers building and maintaining LLM-powered applications.
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