Which is more popular, AgentPilot or LangGraph?

LangGraph has more GitHub stars (42,656 vs 569).

Which is more actively developed, AgentPilot or LangGraph?

LangGraph had more commits in the last 90 days (132 vs 0).

Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.

Side-by-side comparison of two AI agent tools

AgentPilot has had no commit in 16 months; LangGraph is actively maintained (132 commits in the last 90 days).
LangGraph is growing faster: +2,365 GitHub stars in the last 30 days vs +5 for AgentPilot.
Pick AgentPilot for: a versatile workflow automation platform to create, organize, and execute AI workflows, from a single LLM. Pick LangGraph for: build resilient language agents as graphs.

From GitHub data refreshed daily.

A versatile workflow automation platform to create, organize, and execute AI workflows, from a single LLM to complex AI-driven workflows.

LangGraphopen-source

Build resilient language agents as graphs.

+Supports both simple LLM chats and complex multi-agent workflows in a single platform
+Highly customizable interface with generative UI capabilities for creating tailored workflow experiences
+Natural language scheduling system enables intuitive automation setup from simple to complex recurring patterns

+Durable execution ensures agents automatically resume from exactly where they left off after failures or interruptions
+Comprehensive memory system with both short-term working memory for ongoing reasoning and long-term persistent memory across sessions
+Seamless human-in-the-loop capabilities allow for inspection and modification of agent state at any point during execution

-Desktop-only application limits accessibility compared to web-based alternatives
-Early version (0.5.1) suggests the platform may lack enterprise-grade features and stability
-No apparent built-in collaboration or team management features for multi-user environments

-Low-level framework requires more technical expertise and setup compared to high-level agent builders
-Graph-based agent design paradigm may have a steeper learning curve for developers new to agent orchestration
-Production deployment complexity may be overkill for simple chatbot or single-turn use cases

•Automating recurring AI tasks like content generation, data processing, or monitoring with flexible scheduling
•Building interactive AI assistants with branching conversation flows for customer support or internal tools
•Creating custom AI workflow interfaces for specific business processes requiring multi-step agent coordination

•Long-running autonomous agents that need to persist through system failures and operate over days or weeks
•Complex multi-step workflows requiring human oversight, approval, or intervention at specific decision points
•Stateful agents that must maintain context and memory across multiple sessions and interactions

Which is more popular, AgentPilot or LangGraph?: LangGraph has more GitHub stars (42,656 vs 569).
Which is more actively developed, AgentPilot or LangGraph?: LangGraph had more commits in the last 90 days (132 vs 0).
Should I use AgentPilot or LangGraph?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.