vLLora

vLLora is a tool designed for real-time debugging, tracing, and analysis of AI agents and model workflows. It addresses the need for instant insight into agent performance by enabling users to trace, analyze, and optimize AI agent operations as they occur. The platform is intended for developers and teams working with AI agents who require detailed observability and diagnostics.

The tool integrates seamlessly with frameworks such as LangChain, Google ADK, OpenAI, and other major frameworks, supporting a wide range of AI development environments. vLLora allows users to connect via OpenAI-compatible endpoints and supports the use of personal API keys for access to over 300 models. Its features include capturing detailed traces for deep observability, providing insights on latency, cost, and model output, and enabling benchmarking across different models. The platform also includes a built-in assistant called Lucy, which reads traces, diagnoses agent failures, and suggests concrete fixes. Additionally, the vLLora MCP Server allows users to inspect traces and debug agents directly from their IDE using MCP tools.

vLLora is available for installation via Homebrew, making it accessible on compatible systems. It works out of the box with existing setups, requiring minimal configuration. The tool is free for both personal and work use, and licensing information is available through its website.

As an observability and debugging solution for AI agent workflows, vLLora provides unified tracing, cost tracking, and runtime observability for model calls across supported frameworks. Its capabilities are aimed at improving the efficiency and reliability of AI agents by making silent failures and performance issues visible and actionable.