Tools tagged with "Prompt versioning"

Reef is self-hosted infrastructure for developers who want AI agents to improve through feedback on actual interactions. It connects inference and learning with versioned deployment, so an agent can update its model weights or its prompts, rules, and skills while continuing to serve requests. It's open source under Apache 2.0.

Opik is an open-source LLM observability and evaluation platform for developers building AI agents and RAG applications. Its Apache 2.0 licensed platform can be self-hosted on your own hardware or servers; Comet also offers a hosted service. Self-hosting lets teams keep their observability deployment in their own environment.

Langfuse is an open source observability and evaluation platform for teams building LLM applications and AI agents. It shows the steps behind a response so developers can investigate failures, slow requests, and cost. Teams can run its MIT-licensed core on their own servers with Docker Compose or Kubernetes, or use Langfuse Cloud as a hosted service.

Pezzo is an open-source platform for developers and teams managing prompts and monitoring LLM applications. You can run the full stack locally with Docker Compose, keeping the prompt management and monitoring platform on infrastructure you control. Its source code uses the Apache 2.0 license.

Lunary is a self-hosted LLM observability and prompt management platform for teams building chatbots and AI agents. It brings production traces, user conversations and prompt versions into one place so developers can investigate errors and teams can assess response quality. You can host it in your own infrastructure or use its cloud service.

OpenLIT is a self-hosted platform for developers who need to understand how their LLM applications and AI agents behave. It connects model calls with tool activity, retrieval and agent steps, so teams can investigate errors and compare cost, latency and output quality across a workflow.

Helicone combines an AI gateway with LLM observability for engineers building agents, chatbots, and document processing apps. You can self-host the open source observability platform under Apache 2.0 or use the hosted service. It also integrates with Ollama for apps that run models locally. Its hosted gateway routes requests to external AI providers, so those requests leave your machine.

Arize Phoenix is a self-hosted platform for developers who need to understand why an AI agent failed and test changes before shipping them. It runs on a laptop, in Docker, or on Kubernetes. Self-hosting keeps traces on your infrastructure; Phoenix Cloud provides a hosted alternative. Phoenix uses the Elastic License 2.0 (ELv2), a source-available license.

MLflow brings agent tracing, LLM evaluation, and model experiment tracking into a platform you can run locally or on your own servers. It's for developers and teams who need to understand failures, compare changes, and monitor AI applications in production. It's open source under Apache 2.0.