Best Open Source LLM Application Frameworks

Langfuse provides tracing, evaluations, prompt management, and analytics to debug and improve LLM applications.

Open-source platform for LLM tracing, evaluation, and optimization. Features automatic instrumentation, prompt playground, and real-time AI application monitoring.

Open-source observability platform for GenAI and LLM applications. Real-time monitoring, distributed tracing, prompt management, and AI model evaluation built on OpenTelemetry.

Trieve offers an all-in-one solution for search, recommendations, and RAG with automatic continuous improvement based on user feedback.

Universal memory layer for LLM applications that learns from user interactions, reduces token costs by 80%, and delivers personalized AI experiences.

Add persistent memory to LLM apps with millisecond recall times. Store, retrieve, and personalize user data across sessions with enterprise-grade security.

Laminar is an open-source platform that helps collect, understand, and utilize data for building high-quality LLM applications.

Open-source platform that enables developers to create, deploy and monitor AI agents with built-in memory, knowledge integration, and external tool connectivity.

Create, deploy, and manage AI-native apps effortlessly with a user-friendly platform that combines LLMs and your data

Low-code platform for building agentic and RAG applications with drag-and-drop components, Python customization, and support for any LLM or vector database.

Integrate production-ready AI copilots into any product quickly and easily with CopilotKit's open-source platform.