Features and Specifications
For those already familiar with LLM application tech stacks, this document serves as a shortcut to understand Dify's unique advantages
We adopt transparent policies around product specifications to ensure decisions are made based on complete understanding. Such transparency not only benefits your technical selection, but also promotes deeper comprehension within the community for active contributions.
Project Basics
Established
March 2023
Open Source License
Official R&D Team
Over 15 full-time employees
Community Contributors
Over 290 people(As of Q2 2024)
Backend Technology
Python/Flask/PostgreSQL
Frontend Technology
Next.js
Codebase Size
Over 130,000 lines
Release Frequency
Average once per week
Technical Features
LLM Inference Engines
Dify Runtime (LangChain removed since v0.4)
Commercial Models Supported
10+, including OpenAI and Anthropic Onboard new mainstream models within 48 hours
MaaS Vendor Supported
7, Hugging Face, Replicate, AWS Bedrock, NVIDIA, GroqCloud, together.ai,, OpenRouter
Local Model Inference Runtimes Supported
6, Xoribits (recommended), OpenLLM, LocalAI, ChatGLM,Ollama, NVIDIA TIS
OpenAI Interface Standard Model Integration Supported
∞
Multimodal Capabilities
ASR Models
Rich-text models up to GPT-4o specs
Built-in App Types
Text generation, Chatbot, Agent, Workflow, Chatflow
Prompt-as-a-Service Orchestration
Visual orchestration interface widely praised, modify Prompts and preview effects in one place.
Orchestration Modes
Simple orchestration
Assistant orchestration
Flow orchestration
Prompt Variable Types
String
Radio enum
External API
File (Q3 2024)
Agentic Workflow Features
Industry-leading visual workflow orchestration interface, live-editing node debugging, modular DSL, and native code runtime, designed for building more complex, reliable, and stable LLM applications.
Supported Nodes
LLM
Knowledge Retrieval
Question Classifier
IF/ELSE
CODE
Template
HTTP Request
Tool
RAG Features
Industry-first visual knowledge base management interface, supporting snippet previews and recall testing.
Indexing Methods
Keywords
Text vectors
LLM-assisted question-snippet model
Retrieval Methods
Keywords
Text similarity matching
Hybrid Search
N choose 1(Legacy)
Multi-path retrieval
Recall Optimization
Rerank models
ETL Capabilities
Automated cleaning for TXT, Markdown, PDF, HTML, DOC, CSV formats. Unstructured service enables maximum support.
Sync Notion docs as knowledge bases. Sync Webpages as knowledge bases.
Vector Databases Supported
Qdrant (recommended), Weaviate,Zilliz/Milvus, Pgvector, Pgvector-rs,Chroma, OpenSearch, TiDB, Tencent Vector, Oracle, Relyt, Analyticdb, Couchbase
Agent Technologies
ReAct, Function Call.
Tooling Support
Invoke OpenAI Plugin standard tools
Directly load OpenAPI Specification APIs as tools
Built-in Tools
40+ tools(As of Q2 2024)
Logging
Supported, annotations based on logs
Annotation Reply
Based on human-annotated Q&As, used for similarity-based replies. Exportable as data format for model fine-tuning.
Content Moderation
OpenAI Moderation or external APIs
Team Collaboration
Workspaces, multi-member management
API Specs
RESTful, most features covered
Deployment Methods
Docker, Helm
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