Learn how Langflow and Typebot differ in their key features, development activity, technology stack and community adoption, so you can decide which of these low-code/no-code platforms is best for you.
Last 30 days
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Last 30 days
Last commit
Repository age
Version
Self-hosted
Repository

Both Langflow and Typebot have their unique strengths and serve similar purposes effectively. Consider your specific needs regarding popularity, growth, activity, technology, maturity, licensing and features when making your decision.
Langflow significantly outpaces Typebot in community adoption with 153,474 stars compared to 10,269 stars on GitHub. This 14.9x difference suggests Langflow has a much larger and more active community. In terms of developer contributions, Langflow has 9,895 forks, indicating strong developer engagement.
Langflow and Typebot are moving at much the same rate, adding 1,372 stars and adding 97 stars respectively over the last 30 days (+0.9% vs +1%). Neither is pulling away from the other on momentum alone.
Both projects show recent activity, with Langflow last updated 6 hours ago and Typebot 10 hours ago.
Both tools share common technology foundations, being built with JavaScript, CSS, Bash, Typescript, JSX. However, they differ in their additional technology choices: Langflow uses Python while Typebot leverages Next.js, PHP, Tanstack Start.
Typebot has been in development longer, starting 5 years ago, compared to Langflow which began 4 years ago. This 1.2-year head start suggests Typebot may have more mature features and established processes.
Langflow is licensed under MIT, while Typebot's license terms are not publicly specified.
Both tools serve similar use cases in Low-Code/No-Code. However, they also have distinct specializations: Langflow also focuses on AI Agent Platforms, LLM Application Frameworks while Typebot extends into AI Chat Interfaces, Chatbot Platforms.
Both Langflow and Typebot offer self-hosting capabilities, giving you full control over your data and infrastructure.