Langfuse is an open-source observability and evaluation platform designed for language model applications. It provides a centralized system for tracking execution traces, monitoring performance metrics, and managing prompt templates. By capturing hierarchical units of work and telemetry data, the platform enables developers to debug complex application lifecycles and analyze token usage, latency, and model interactions in production environments. The platform distinguishes itself through an integrated evaluation framework that allows for systematic benchmarking and automated scoring of model
Helicone is an AI gateway and observability platform designed to intercept, manage, and monitor interactions with large language models. By acting as a reverse-proxy, it provides a centralized layer for routing requests across multiple AI providers, allowing developers to maintain consistent application logic while gaining deep visibility into model performance, usage, and costs. The platform distinguishes itself through a robust suite of traffic management and prompt engineering tools. It enables policy-driven control, including automatic failover between providers, rate limiting, and edge-b
Opik is an observability and evaluation platform designed for generative AI applications and agentic workflows. It provides a centralized environment for tracing execution flows, managing prompt templates, and monitoring production performance, allowing teams to gain visibility into complex model interactions and tool usage without requiring manual application code changes. The platform distinguishes itself through its integrated approach to the AI development lifecycle, combining distributed trace instrumentation with automated evaluation frameworks. It supports model-as-a-judge scoring, syn
Lmnr is an LLM observability platform and evaluation framework designed for tracing, logging, and monitoring language model executions. It provides the tools necessary to debug agent behavior, analyze performance, and identify failure patterns in AI agents. The platform differentiates itself through a trace-to-dataset pipeline that converts production logs into labeled test sets for regression testing. It includes a prompt-variant replay engine to compare different prompts or models side-by-side and a state-cached debugging system to replay agent loops without restarting the process. The sys
Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. Tracing · Evals · Simulations · Datasets · Gateway · Guardrails. Self-hostable. Apache 2.0.
The main features of future-agi/future-agi are: Agent Frameworks, AI Observability Tools, Model Evaluation and Benchmarking, Monitoring and Observability.
Open-source alternatives to future-agi/future-agi include: lmnr-ai/lmnr — Lmnr is an LLM observability platform and evaluation framework designed for tracing, logging, and monitoring language… langfuse/langfuse — Langfuse is an open-source observability and evaluation platform designed for language model applications. It provides… comet-ml/opik — Opik is an observability and evaluation platform designed for generative AI applications and agentic workflows. It… helicone/helicone — Helicone is an AI gateway and observability platform designed to intercept, manage, and monitor interactions with… facebookresearch/parlai — ParlAI is a conversational AI research framework designed for training, evaluating, and sharing dialogue models using… infrasys-ai/aiinfra.