Agents & Orchestration ★ 86.0k

Dify

Self-hostable LLMOps platform with visual workflows, RAG and prompt management in one box.

Dify gives non-engineers a visual workflow builder while keeping an API and self-hosting story intact. For internal-tool teams it often removes months of glue work, at the cost of some flexibility versus building on raw frameworks.

Best for: Internal tools, self-hosted no-code/low-code AI apps

Deploy: Self-hostable

What to do about it

  • Self-hostable
  • Visual workflow builder
  • Prompt management

What it is

Dify is a self-hostable platform that provides a visual workflow builder and manages prompts, among other features. It aims to simplify the process for non-engineers while maintaining an API and self-hosting capabilities. This approach allows internal tool teams to potentially save time and effort.

The platform's focus on visual workflows and prompt management suggests it is designed to streamline certain tasks. Its self-hosted nature gives users control over their environment and data.

Where it fits in a deployment stack

Agents like Dify typically sit between the application layer and the data or service providers, managing interactions and workflows. They often handle tasks such as tool calling, workflow management, and prompt handling, which can be complex and time-consuming to implement from scratch.

In a production system, an agent would normally be responsible for orchestrating the flow of data and requests between different components. This can involve integrating with various tools and services, managing workflows, and handling prompts or requests from users or other systems.

The use of agents can help simplify the development and maintenance of applications by encapsulating complex logic and workflows, making it easier to manage and update these processes over time.

How to evaluate it

To evaluate Dify, you should consider how it handles specific tasks and workflows, as well as its performance under various conditions. This involves looking at concrete artifacts such as the data it processes, the workflows it manages, and the prompts it handles. You should also consider how it integrates with other tools and services in your deployment stack.

  • Feed it a dataset with varied prompt types to see how it manages different inputs.
  • Inspect the output of its workflow builder to ensure it meets your requirements.
  • Measure the latency of its retrieval step under a high number of concurrent sessions.
  • Inject failures into its workflow to observe its error handling and recovery capabilities.
  • Verify its ability to integrate with other tools and services in your stack.
  • Monitor its resource usage to understand its operational cost.

What to verify before you commit

Before committing to Dify, you need to verify several aspects of its functionality, security, and operational implications. This includes checking its licence terms, data handling practices, and potential lock-in effects. You should also consider its failure behavior and how it might impact your overall system.

  • Check the licence terms to ensure they align with your organization's requirements.
  • Verify how it handles sensitive data and whether it meets your security standards.
  • Assess the potential for vendor lock-in and its implications for your system.
  • Evaluate its failure behavior and how it might affect your application's uptime and reliability.
  • Review its operational costs, including resource usage and any potential scalability limitations.
  • Confirm its compatibility with your existing tools and services.

Where this fits in the FDE path