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AgentaOdprtokodna LLMOps platforma za gradnjo, ocenjevanje in uvajanje LLM aplikacij.

4.8 (4)
Daniel NikulshynPregledal Daniel Nikulshyn·Posodobljeno julij 2026

Pregled

Agenta je odprtokodna LLMOps platforma, ki ekipam pomaga razvijati, testirati in pošiljati aplikacije, poganjane z velikimi jezikovnimi modeli. Povezuje prompt engineering, evaluation, observability in deployment v enem delovnem prostoru, tako da lahko razvijalci in strokovnjaki na področju sodelujejo pri iteriranju izdelkov, ki temeljijo na LLM-ih. Uporabniki lahko hkrati eksperimentirajo s prompti in konfiguracijami modelov, izvajajo sistematične ocene na prilagojenih podatkovnih zbirkah ter sledenje poizvedbam v proizvodnji za odpravljanje napak. Ker je odprtokoden, Agenta omogoča samostojno gostovanje, kar ekipam daje polni nadzor nad njihovimi podatki in infrastrukturom ter se integrira s priljubljenimi ponudniki modelov in okvirji.

Ključne funkcije

  • Igralna polja za povpraševanje z božemo primerjavo poleg poleg
  • Prilagojena in avtomatizirana ocenjevanja
  • Sledenje in opazovanje v produkciji
  • Versioniranje povpraševanj in nastavitev
  • Vdražanje LLM aplikacij kot API-je
  • Integracije z glavnimi ponudniki LLM

Cene

Model
Freemium
Kategorija
Agnosti AI
Ocena
4.8 / 5 (4)

Primeri uporabe

Poenostavljanje LLMOps za ekipe

Agenta pomaga ekipam preiti od razpršenih delovnih tokov k strukturiranim procesom z zagotavljanjem orodij za centralizirano upravljanje, sodelovanje in ocenjevanje LLM aplikacij.

Iteriranje oblikovanja povpraševanja z celotno ekipo

Zunaj združene funkcije igranja omogočajo ekipam primerjavo povpraševanj in modelov poleg poleg, medtem ko možnost ustvarjanja sistematičnega procesa za izvajanje eksperimentov in sledenje rezultatov poenostavlja razvojni proces.

Odpravljanje napak in preverjanje LLM aplikacij

Funkcije Agente za avtomatizirano ocenjevanje, integrirano povratno informacijo strokovnjakov iz področja in primerjavo celih sledov omogočajo ekipam nadomestiti domneve z dokazom ter sprejemati odločitve na podlagi podatkov.

Prednosti in slabosti

Prednosti

  • Odprtokodna in samostojno gostljiva
  • Združuje igralno polje za povpraševanje, ocenjevanje in opazovanje
  • Omogoča sodelovanje med razvijalci in uporabniki brez tehničnega znanja
  • Deluje z večimi ponudniki LLM in okvirji

Slabosti

  • Zahteva nastavitve in vzdrževanje, če je gostljeno samostojno
  • Manjša skupnost kot pri nekaterih komercialnih alternativah
  • Učenje za ekipe, ki so nove v LLMOps

Ocene

4.8

Povprečje iz 4 ocen.

5
3
4
1
3
0
2
0
1
0

Prijavi se za oddajo ocene.

Jamal Carter

Jamal Carter

Jan 14, 2026

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.

HT

Hiroshi Tanaka

Dec 17, 2025

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

Yuki Mori

Jul 6, 2025

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.

AK

Aisha Khan

Jun 16, 2025

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.

Vprašanja

What is included in the free open-source edition?

The open-source edition includes the core agent workspace: chat, projects, agent configuration, instructions, skills, tools, integrations, MCP servers, files, schedules, event triggers, tracing, evaluations, version history, role-based access control, and SSO. You can create unlimited users, projects, agents, and workflows on your own infrastructure.

Asked by Farah Rahimi · Jan 13, 2026

What is the difference between Agenta Cloud and self-hosted Agenta?

Agenta Cloud is operated by us. We run the application, storage, agent runner, upgrades, and backups. With self-hosted Agenta, you deploy and operate those components in your own infrastructure, connect your own model and integration accounts, and control where your data is stored.

Asked by Ravi Kapoor · Jan 1, 2026

What does trace data retention cover?

Trace data retention controls how long Agenta Cloud keeps technical execution records, including model calls, tool calls, timing, outputs, errors, evaluations, and annotations. Hobby retains trace data for one week, Pro for one month, and Business for three months. Enterprise retention is configurable. Trace data retention does not describe the retention of chats, project files, or persistent agent context. With self-hosted Agenta, you manage trace storage and retention in your own infrastructure.

Asked by Grzegorz Lewandowski · Dec 27, 2025

How can I estimate how many agent runs I need?

Count each message sent to an agent, each annotation, and each invocation started by a schedule or event. For example, one daily scheduled agent uses about 30 or 31 runs per month, one agent triggered every hour uses about 720 to 744 runs per month, and a chat with 20 user messages uses 20 runs.

Asked by Petra Vogel · Dec 25, 2025

Where can I monitor usage?

Open Settings, then Billing to see your current agent-run usage and plan allowance.

Asked by Giulia Conti · Dec 17, 2025

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