Zentara-Code
dify
| Zentara-Code | dify | |
|---|---|---|
| 2 | 46 | |
| 85 | 143,689 | |
| - | 2.8% | |
| 10.0 | 10.0 | |
| 3 months ago | 5 days ago | |
| TypeScript | TypeScript | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Zentara-Code
dify
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Bringing MongoDB Atlas and Voyage AI to Dify: Build RAG Workflows and Data Agents Without Heavy Glue Code
The MongoDB extensions for Dify help close that gap.
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Agent-Ready Engineering Infrastructure
Dify AGENTS.md
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Dify Now Supports IRIS as a Vector Store — Setup Guide
This integration was contributed to Dify as an OSS pull request and merged in Dify v1.11.2 (#29480). Several follow-up fixes have been merged since — covered below. This article walks through the setup.
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Reading list (29th March to April 20th)
Dify is an open-source LLM app development platform. Its intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features (including Opik, Langfuse, and Arize Phoenix) and more, letting you quickly go from prototype to production. - link [tool] - ( Added: 2026-03-29 11:20:22 )
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I Tested Flowise, Dify, and n8n Across 30+ Client Deployments. Here Is My Verdict.
Citation Capsule: n8n's GitHub community reached 182,000+ stars across a 7-year development history, with 70+ AI-specific nodes added in 2024 to 2025. Source: n8n GitHub. Dify crossed 106,000 stars on GitHub with an Apache 2.0 license. Source: Dify GitHub. Flowise reached 51,000+ stars with MIT license. Source: Flowise GitHub. Dify's minimum recommended RAM is 4 GB versus Flowise's 1 GB and n8n's 300 MB. Source: Dify Docs.
- 25 Trending Self-Hosted Projects on GitHub
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Top 7 AI Agent Frameworks for Developers in 2026
Dify is a no-code/low-code platform for building agent workflows visually. It recently raised $30 million and is used by 280 enterprises across 1.4 million deployments.
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Building RAG & Knowledge Bases with seekdb: Three Paths, One Stack
The real headache in RAG isn’t retrieval or generation—it’s the layer in between. Where does the data live? How do you keep it in sync? Who glues it all together? seekdb and Dify are both open-source. Your RAG stack—from storage to orchestration—can be self-hosted, auditable, and customizable, without locking you into closed services. This post walks through three paths, all built on one stack: RAG from scratch with seekdb, Dify + seekdb, and a knowledge base desktop app. Pick the one that fits and get it running.
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Top 5 AI Agent Frameworks for 2026 (Honest Guide)
TL;DR: Pick LangGraph if you want maximum control over agent architecture. Go with CrewAI for structured role-based multi-agent pipelines. Choose AutoGen if you're in the Microsoft ecosystem and need research-grade flexibility. Try Dify if you want to build AI apps visually without writing orchestration code. And if you need production agents connected to 1,000+ tools with scheduling and memory built in, Nebula gets you there fastest.
- Dify: Production-ready platform for agentic workflow development
What are some alternatives?
deer-flow - An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.
langchain-llm-katas - This is a an open-source project designed to help you improve your skills with AI engineering using LLMs and the langchain library
activepieces - AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents
n8n - n8n is a workflow automation platform for building AI-powered workflows and agents, connecting any AI model to any business system with full control over data, security, and deployment. Build visually or in code while n8n handles infrastructure from prototype to production with fully auditable executions.
llm-code-interpreter - [DEPRECATED] Powered by AI Playgrounds by E2B. Code interpreter on steroids for ChatGPT. Run any language, any terminal process, use filesystem freely. All with access to the internet.
chainlit - Build Conversational AI in minutes ⚡️