Dify
by Community
Production-ready platform for agentic workflow development.
OSS
Dify
Added 1 June 2026
Overview
Dify is an open-source framework for building and deploying agentic workflows in production. It provides a visual interface and API for orchestrating LLM-based agents, RAG pipelines, and multi-step automations without requiring extensive custom code.
Best for
Best for
Teams building production LLM agents who want open-source control and visual workflow design.
Use cases
- Building multi-step LLM workflows with conditional logic and tool integration
- Deploying RAG systems that retrieve and reason over custom knowledge bases
- Creating chatbots and agents that interact with external APIs and databases
Notes
Dify is an open-source framework for building and deploying agentic workflows in production. It provides a visual interface and API for orchestrating LLM-based agents, RAG pipelines, and multi-step automations without requiring extensive custom code.
143,435 stars on GitHub. Last updated 2026-06-01.
Use cases
- Building multi-step LLM workflows with conditional logic and tool integration
- Deploying RAG systems that retrieve and reason over custom knowledge bases
- Creating chatbots and agents that interact with external APIs and databases
Pros
- Active open-source community with 143k+ GitHub stars and regular updates
- Visual workflow builder reduces boilerplate for common agentic patterns
- Self-hosted option provides data privacy and deployment flexibility
Cons
- Requires operational overhead to self-host and maintain infrastructure
- Learning curve for developers unfamiliar with workflow-based abstractions
- Community-driven support rather than commercial SLA guarantees
Indexed from awesome-llm and enriched against its public facts.
Pros
- Active open-source community with 143k+ GitHub stars and regular updates
- Visual workflow builder reduces boilerplate for common agentic patterns
- Self-hosted option provides data privacy and deployment flexibility
Cons
- Requires operational overhead to self-host and maintain infrastructure
- Learning curve for developers unfamiliar with workflow-based abstractions
- Community-driven support rather than commercial SLA guarantees
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