dify

Latest Version: 1.14.0-rc1

Dify (130k+ stars) is a production-ready agentic AI platform enabling collaborative, sandboxed agent workflows with dynamic skill composition.

Owner: langgenius

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OSSauto-discoveredgithub-searchagent

Stars

130.0k

GitHub star count

Last Release

2 months ago

1.14.0-rc1

Contributors

100

N/A

Health Score

N/A

Key Features

agent
agentic ai
agentic framework
agentic workflow
ai

Tech Stack

TypeScript

auto-discovered

github-search

agent

agentic-ai

agentic-framework

agentic-workflow

automation

gemini

genai

gpt

gpt-4

About

Today Brief

Scope: ExtendedConfidence: LowEvidence: 1

In the last 7 days, DevRadar observed 1 product updates and 0 external community signals for dify.

Why Included

Scope: Extended (direct product + high-impact ecosystem signals).
High-impact product update from related project supabase.

What Changed

Ecosystem (supabase) Release: Developer Update - April 2026

Why It Matters

Recent releases signal active delivery cadence and potential behavior changes.

Suggested Actions

Review release notes and estimate impact on current workflows.

Sources

github.com

Was this brief useful?

Dify (130k+ stars) is a production-ready agentic AI platform enabling collaborative, sandboxed agent workflows with dynamic skill composition.

langgenius/dify is auto-discovered from GitHub Search activity signals. TypeScript repository. Current repository metrics include 130001 stars, 20244 forks, and 756 open issues. Topics: agent, agentic-ai, agentic-framework, agentic-workflow, ai. Matched search heuristics: stars:>=150 pushed:>=2026-02-08 archived:false fork:false mirror:false | topic:ai stars:>=105 pushed:>=2026-02-08 archived:false fork:false mirror:false. Metadata is enriched asynchronously by the refresh pipeline.

Analyst Note

Dify (130k+ stars) is a production-ready agentic AI platform enabling collaborative, sandboxed agent workflows with dynamic skill composition.

Best For

Technical stack evaluation for engineering teams
Dependency governance and upgrade planning in production systems
Track delivery cadence and release quality from langgenius
agent

Not Ideal For

Large open issue backlog.

Typical Use Cases

Technical stack evaluation for engineering teamsDependency governance and upgrade planning in production systemsTrack delivery cadence and release quality from langgenius