Agenta

Open-source LLMOps platform for building, evaluating, and deploying LLM apps

4.8 (4)

Перевірено Daniel Nikulshyn·Оновлено травень 2026 р.

Огляд

Agenta is an open-source LLMOps platform that helps teams develop, test, and ship applications powered by large language models. It brings prompt engineering, evaluation, observability, and deployment together in one workspace, so developers and subject-matter experts can collaborate on iterating LLM-based products. Users can experiment with prompts and model configurations side by side, run systematic evaluations against custom datasets, and trace requests in production to debug issues. Because it is open source, Agenta can be self-hosted, giving teams full control over their data and infrastructure while integrating with popular model providers and frameworks.

Ключові функції

Prompt playground with side-by-side comparison
Custom and automated evaluations
Production tracing and observability
Versioning for prompts and configurations
Deployment of LLM apps as APIs
Integrations with major LLM providers

Плюси і мінуси

Плюси

Open source and self-hostable
Combines prompt playground, evaluation, and observability
Supports collaboration between developers and non-technical users
Works with multiple LLM providers and frameworks

Мінуси

Requires setup and maintenance if self-hosted
Smaller community than some commercial alternatives
Learning curve for teams new to LLMOps

Відгуки

4.8

Середнє з 4 оцінок.

Увійди, щоб залишити відгук.

Jamal Carter

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on integrations with major LLM providers, and open source and self-hostable caught me off guard. still, I'd recommend giving it a real trial.

Hiroshi Tanaka

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on versioning for prompts and configurations, and supports collaboration between developers and non-technical users caught me off guard. Smaller community than some commercial alternatives is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Yuki Mori

Use it every day

Honestly didn't expect to like it this much. Integrations with major LLM providers is exactly what I needed, and works with multiple LLM providers and frameworks. but I reach for it almost every day now and it just clicks.

Aisha Khan

Solid for our team

We rolled this out across the team last quarter and works with multiple LLM providers and frameworks. Deployment of LLM apps as APIs fits neatly into how we already work, and custom and automated evaluations removed a step we used to do by hand. but it has held up under daily use.