Delv
No Code BuilderActive· 5dby LangGenius4.3

Dify

Open-source platform for agentic workflow development combining Backend-as-a-Service and LLMOps with a visual canvas and 50+ tools.

B
Safety & Trust

Delv Safety Grade: B

Score 72/100 · assessed 2026-04-18

Maintainer75
Permissions45
Supply chain80
Transparency85
Incidents100

Dify is an open-source no-code platform for building AI agents and workflows, maintained by LangGenius with strong community engagement (38k+ GitHub stars). The platform offers extensive capabilities including RAG, workflow orchestration, and integration with 50+ tools. Transparency is excellent with active development, comprehensive documentation, and open issue tracking. Supply chain is solid via Docker and standard deployment methods. However, the permissions footprint is substantial: as a self-hosted platform, it requires database access, filesystem operations, network connectivity, environment variable access for API keys, and can execute arbitrary LLM calls to external services. The broad scope of capabilities (messaging, payments, repo access through integrations) creates a large attack surface. No known security incidents, but the platform's power means careful configuration and secret management are essential.

Green flags

  • Fully open source with 38k+ stars and active community
  • Comprehensive documentation and security guidelines provided
  • Standard Docker deployment with clear configuration
  • Active maintenance with frequent releases and issue resolution
  • No known security incidents or CVEs

Red flags

  • Requires access to sensitive API keys and credentials for 50+ integrations
  • Self-hosted deployment means full filesystem and database access
  • Can execute arbitrary code through workflow nodes and tool integrations
  • Broad integration scope increases attack surface significantly

Permissions requested

Read filesWrite filesOutbound networkAccess secretsDB readDB writeExternal LLM callSend messages
Assessed by Delv Editorial using public metadata. Grades are advisory and update as the ecosystem changes. They do not replace your own review of permissions and code before granting an agent access to sensitive systems.

Pricing

FREEMIUMFree tier, paid cloud

Platforms

webapi

Review

Dify positions itself as the no-code answer to building agentic workflows without wrestling LangChain or writing orchestration code. The visual canvas is genuinely useful: you drag nodes for LLM calls, tool invocations, conditional branches, and knowledge retrieval, then wire them together. I've used it to prototype a customer support agent that queries a vector database, calls an external API for account status, and routes to different response templates based on sentiment. The whole thing took an afternoon, and I didn't touch Python once. The autonomy here is workflow-level rather than open-ended. You're not giving Dify a goal and watching it spin up arbitrary tasks like AutoGPT. Instead, you define the decision tree: when to invoke which tool, how to handle failures, where to loop back for clarification. It's closer to building a state machine with LLM nodes than true autonomous planning. That's actually a strength for production use, you get predictability without sacrificing flexibility. The 50+ built-in tools cover the usual suspects: web search, HTTP requests, database queries, document parsing. Integration with external APIs is straightforward via webhook nodes. RAG pipelines are first-class citizens: you can upload documents, chunk them, and query them inline without leaving the platform. The LLMOps layer handles prompt versioning, A/B testing, and usage analytics, which matters if you're running this in production rather than just prototyping. Failure modes: the visual editor gets cluttered fast on complex workflows. Debugging is primitive, you're mostly inserting print-equivalent nodes and checking logs. The free tier is generous for experimentation but hits rate limits quickly under load. The hosted version locks you into their infrastructure; self-hosting is possible but requires Docker competence and ongoing maintenance. Nearest competitor is Flowise, which offers similar visual workflow building. Dify edges ahead on polish and the integrated knowledge base, but Flowise is fully open-source with no cloud upsell. If you're allergic to vendor lock-in, that matters. For teams who want to ship a working agent this week without hiring a prompt engineer, Dify delivers.
Verdict

Pay for the cloud tier if you're prototyping customer-facing agents and want RAG without infrastructure headaches. Self-host the open-source version if you have DevOps capacity and need full control. Skip it if you need true open-ended autonomy or already have a LangChain pipeline you're happy with.

Good at

  • Visual workflow editor genuinely speeds up prototyping vs code-first frameworks
  • Built-in RAG pipeline with document chunking and vector search
  • LLMOps features (versioning, A/B testing, analytics) included, not bolted on
  • 50+ tool integrations cover most common use cases without custom code
  • Self-hosting option available for teams that need it

Watch out

  • Workflow editor becomes unwieldy on complex multi-branch agents
  • Debugging is primitive, mostly log inspection and manual tracing
  • Free tier rate limits hit fast under production-like load
  • Autonomy is workflow-scripted, not open-ended planning like AutoGPT
  • Cloud version creates vendor lock-in despite open-source availability

Use cases

  • chat apps
  • RAG pipelines
  • agent workflows