dify and pyspur
About dify
langgenius/dify
Production-ready platform for agentic workflow development.
Combines visual workflow canvas with RAG pipelines, agent capabilities using LLM function calling or ReAct, and 50+ built-in tools for autonomous operations. Integrates 100+ proprietary and open-source LLM providers (GPT, Mistral, Llama3, OpenAI-compatible APIs) with observability tools like Langfuse and Arize Phoenix. Exposes full REST API backend-as-a-service for seamless business logic integration.
About pyspur
PySpur-Dev/pyspur
A visual playground for agentic workflows: Iterate over your agents 10x faster
Provides node-level debugging, human-in-the-loop approval breakpoints, and built-in RAG capabilities (chunking, embedding, vector DB integration). Supports >100 LLM providers and integrations (Slack, GitHub, Google Sheets, Firecrawl), with agents deployable as one-click APIs. Python-based architecture allows extending functionality by writing single Python files as custom nodes.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work