Dify¶

What it is¶

Dify is an open-source LLM application development platform. It allows you to visually create and operate AI applications based on various LLMs, and includes tools for prompt engineering, RAG, and agent orchestration.

What problem it solves¶

Lowers the barrier to building LLM-powered applications by providing a visual interface for designing prompts, RAG pipelines, and agent workflows without writing extensive code.

Where it fits in the stack¶

AI & Knowledge — serves as a visual platform for building and deploying LLM applications, potentially connecting to the local Ollama instance.

Typical use cases¶

Building RAG applications with a visual drag-and-drop interface
Rapid prototyping of prompt chains and agent workflows
Setting up local RAG pipelines with Ollama and private data

Strengths¶

Open-source and self-hostable, aligning with the privacy-first approach
Visual interface makes LLM app development accessible to non-developers
Supports multiple LLM backends including local models via Ollama

Limitations¶

Requires running an additional service with its own dependencies
Less flexible than code-first frameworks for highly custom workflows
Smaller community and ecosystem compared to LangChain

When to use it¶

When you want to visually prototype and deploy LLM applications without writing code
When building RAG or agent applications that connect to local LLM infrastructure

When not to use it¶

When you need fine-grained programmatic control over LLM pipelines
When the overhead of running another service is not justified for simple tasks

Getting started¶

Installation¶

Dify is typically deployed via Docker. Once running, you can access its features through the web UI or via its REST API. To use the API, you first need to create an application in the Dify dashboard and generate an API Key.

For programmatic access via Python, install the official client:

pip install dify-client

Minimal Python Example¶

from dify_client import ChatClient

# Initialize the ChatClient
client = ChatClient(api_key="your-api-key")

# Send a message to your Dify application
# Note: In dify-client, the response is already parsed as a dictionary
response = client.create_chat_message(
    inputs={},
    query="Hello Dify!",
    user="unique_user_id"
)
print(response)

API examples¶

Calling a Dify Workflow API¶

Workflows in Dify can be triggered via a POST request to the Workflow API endpoint.

curl -X POST 'https://api.dify.ai/v1/workflows/run' \
--header 'Authorization: Bearer {YOUR_API_KEY}' \
--header 'Content-Type: application/json' \
--data-raw '{
    "inputs": {
        "query": "What are the benefits of self-hosting LLMs?"
    },
    "response_mode": "blocking",
    "user": "unique_user_id_123"
}'

Sources / references¶

Contribution Metadata¶

Last reviewed: 2026-03-03
Confidence: medium