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FlowiseOdprtokodni vizualni graditelj za aplikacije LLM, agente in klepetalne bote z uporabo vozlišč povleci‑in‑spusti.

4.5 (4)
Daniel NikulshynPregledal Daniel Nikulshyn·Posodobljeno maj 2026

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Pregled

Flowise je odprtokodna low‑code platforma za oblikovanje AI delovnih tokov z povezovanjem vozlišč na vizualnem platnu. Vključuje priljubljena ogrodja, kot sta LangChain in LlamaIndex, in razvijalcem omogoča prototipiranje klepetalnih robotov, verig za generiranje z dodatkom iskanja in avtonomnih agentov, brez pisanja obsežne lepilne kode. Zgrajene tokove je mogoče izpostaviti kot API-je, vdelati kot klepetalne gradnike ali integrirati v obstoječe aplikacije. Flowise podpira širok spekter ponudnikov modelov, vektorskih baz podatkov in orodij ter ga je mogoče samostojno gostovati prek Dockerja ali poganjati v oblaku za ekipe, ki potrebujejo več nadzora nad podatki in namestitvijo.

Ključne funkcije

  • Graditelj tokov povleci‑in‑spusti
  • Podpora za vozlišča LangChain in LlamaIndex
  • Integracije RAG in vektorske baze podatkov
  • Orkestracija agentov in orodij
  • API končne točke in vdelava klepeta
  • Samostojno gostovanje na osnovi Dockerja

Cene

Model
Freemium
Ocena
4.5 / 5 (4)

Primeri uporabe

Vizualno prototipiranje RAG klepetalnih botov

Povežite vozlišča LLM, embedding in vektorske baze podatkov na platnu, da hitro ustvarite klepetalne bote, podprte z iskanjem, brez potrebe po obsežni lepilni kodi LangChain ali LlamaIndex.

Vdelajte AI asistente v aplikacije

Razkrijte ustvarjene tokove kot API končne točke ali vstavne klepetalne gradnike, da integrirate prilagojene AI asistente v obstoječe spletne strani in interne orodja.

Orkestrirajte avtonomne agente

Uporabite vozlišča agentov in orodij za oblikovanje večkorakovnih delovnih tokov, kjer LLM-ji kličočo orodja, poizvedujejo podatke in sprejemajo odločitve v vizualnem poteku.

Samostojno gostite LLM delovne tokove v Dockerju

Namestite Flowise prek Dockerja, da ohranite interakcije modela, podatke in logiko toka pod nadzorom vaše ekipe v okoljih, ki zahtevajo zasebnost ali so regulirana.

Prednosti in slabosti

Prednosti

  • Odprtokoden in samostojno gostljiv
  • Vizualno platno pospeši prototipiranje
  • Široke integracije z LLM-ji in vektorskimi shramami
  • Izvozi tokove kot API-je in vdelljive gradnike

Slabosti

  • Kompleksni tokovi lahko postanejo težko upravljivi
  • Zahteva osnovno razumevanje konceptov LLM
  • Samostojno gostovanje prinaša dodatno vzdrževalno breme

Ocene

4.5

Povprečje iz 4 ocen.

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4
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Prijavi se za oddajo ocene.

Esther Adeyemi

Esther Adeyemi

Apr 4, 2026

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on langChain and LlamaIndex node support, and broad integrations with LLMs and vector stores caught me off guard. still, I'd recommend giving it a real trial.

GE

Gunnar Eriksson

Mar 15, 2026

Compared a few options

Evaluated this against two competitors. Where it wins: docker-based self-hosting and visual canvas speeds up prototyping. Where it lags: complex flows can become hard to manage. On balance the feature set — especially drag-and-drop flow builder — justifies the 4 stars for our use case.

Carlos Mendoza

Carlos Mendoza

Jan 22, 2026

Solid for our team

We rolled this out across the team last quarter and broad integrations with LLMs and vector stores. Docker-based self-hosting fits neatly into how we already work, and docker-based self-hosting removed a step we used to do by hand. Requires some understanding of LLM concepts, which is the main caveat, but it has held up under daily use.

Priya Nair

Priya Nair

Jul 14, 2025

Use it every day

Honestly didn't expect to like it this much. LangChain and LlamaIndex node support is exactly what I needed, and visual canvas speeds up prototyping. I do wish requires some understanding of LLM concepts, but I reach for it almost every day now and it just clicks.

Vprašanja

How can I expose a Flowise workflow to my existing application?

Built flows can be exported as API endpoints, embedded chat widgets, or accessed via the provided TypeScript and Python SDKs, allowing easy integration into web, mobile, or backend services.

Asked by Bianca Ferreira · Nov 8, 2025

Which AI frameworks and vector databases does Flowise integrate with?

Flowise wraps popular frameworks such as LangChain and LlamaIndex, and supports a wide range of LLM providers, embeddings models, and vector databases, enabling RAG pipelines and tool orchestration without custom glue code.

Asked by Priya Nair · Oct 30, 2025

Can Flowise be self‑hosted, and what deployment options are available?

Yes, Flowise is open source and can be self‑hosted via Docker for on‑premise deployments. It also offers cloud deployments that scale horizontally with message queues and workers for production use.

Asked by Greta Nowak · Oct 17, 2025

What pricing tiers does Flowise offer for individual vs. team use?

Flowise has a free tier with up to 2 flows, 100 predictions per month, and 5 MB storage. The paid “Starter” plan costs $35/month and includes unlimited flows, 10 000 predictions per month, and 1 GB storage, plus custom branding and evaluation metrics.

Asked by Sami Virtanen · Aug 8, 2025

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