Which is more popular, LangChain or LobeHub?

LangChain has more GitHub stars (147,383 vs 82,957).

Which is more actively developed, LangChain or LobeHub?

LobeHub had more commits in the last 90 days (2,429 vs 546).

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

LangChain is growing faster: +23,217 GitHub stars in the last 30 days vs +1,358 for LobeHub.
Pick LangChain for: the agent engineering platform. Pick LobeHub for: open-source platform for building, scheduling, and managing collaborative AI agent teams.

From GitHub data refreshed daily.

LangChainopen-source

The agent engineering platform

Open-source platform for building, scheduling, and managing collaborative AI agent teams

+Extensive ecosystem with seamless integration between LangGraph, LangSmith, and hundreds of third-party components
+Future-proof architecture that adapts to evolving LLM technologies without requiring application rewrites
+Strong community support with 131k+ GitHub stars and comprehensive documentation for both Python and JavaScript

-Significant learning curve due to the framework's extensive feature set and multiple abstraction layers
-Potential over-engineering for simple use cases that might be better served by direct API calls
-Heavy dependency on the LangChain ecosystem which can create vendor lock-in concerns

•Building complex multi-agent systems that require planning, tool use, and coordination between different AI components
•Creating production LLM applications with observability, debugging, and deployment infrastructure via LangSmith
•Developing chatbots and conversational AI with memory, context management, and integration with external data sources

Which is more popular, LangChain or LobeHub?: LangChain has more GitHub stars (147,383 vs 82,957).
Which is more actively developed, LangChain or LobeHub?: LobeHub had more commits in the last 90 days (2,429 vs 546).
Should I use LangChain or LobeHub?: Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.