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Langflow vs LiveKit

Learn how Langflow and LiveKit differ in their key features, development activity, technology stack and community adoption, so you can decide which of these ai agent platforms is best for you.

vs

Langflow

AI
Build, deploy, and iterate on AI agents, RAG applications, and MCP servers using a drag-and-drop visual interface backed by Python.
156,432stars+999(+0.6%)

Last 30 days

Screenshot of Langflow

LiveKit

AI
Build, test, deploy, and scale voice and video AI agents with an open source framework, inference gateway, telephony integrations, and full observability.
22,086stars+738(+3.5%)

Last 30 days

Screenshot of LiveKit

Detailed Comparison

Both Langflow and LiveKit 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 wins
Community & Popularity

Langflow significantly outpaces LiveKit in community adoption with 156,432 stars compared to 22,086 stars on GitHub. This 7.1x difference suggests Langflow has a much larger and more active community. In terms of developer contributions, Langflow has 10,356 forks, indicating strong developer engagement.

LiveKit wins
Growth Momentum

LiveKit is growing faster, adding 738 stars in the last 30 days (+3.5%) against adding 999 stars for Langflow (+0.6%). LiveKit is the smaller project of the two, so it is closing the gap rather than extending a lead.

Comparable
Development Activity

Both projects show recent activity, with Langflow last updated 11 hours ago and LiveKit 12 hours ago.

Comparable
Technology Stack

Both tools share common technology foundations, being built with Bash. However, they differ in their additional technology choices: Langflow uses JavaScript, CSS, Typescript, JSX, Python while LiveKit leverages Golang.

LiveKit wins
Project Maturity

LiveKit has been in development longer, starting 6 years ago, compared to Langflow which began 4 years ago. This 2.4-year head start suggests LiveKit may have more mature features and established processes.

Langflow wins
Licensing

Langflow uses the MIT license, which is more permissive than LiveKit's Apache-2.0 license, potentially offering greater flexibility for commercial use and integration.

Comparable
Use Cases & Features

Both tools serve similar use cases in AI Agent Platforms. However, they also have distinct specializations: Langflow also focuses on Low-Code/No-Code, LLM Application Frameworks while LiveKit extends into Chatbot Platforms.

Langflow wins
Hosting & Deployment

Langflow provides self-hosting options for complete data control and customization, while LiveKit may be primarily cloud-based or require different deployment approaches.