Langflow is a low-code AI builder for agentic and retrieval-augmented generation (RAG) apps. Code in Python and use any LLM or vector database. Free cloud deployment (DataStax) or self-host. Extensive integrations.
Hi everyone!
Sharing Langflow, a powerful open-source, low-code platform for building AI applications, and it's not just another drag-and-drop tool. It's specifically designed for Retrieval-Augmented Generation (RAG) and multi-agent systems, and it's built on Python, so you have complete control and customization options.
What makes Langflow stand out:
🏗️ Visual Flow Builder: Design complex workflows with a drag-and-drop interface. No need to write tons of boilerplate code.
🐍 Python Under the Hood: It's all Python, so you can customize anything if you need to.
🔌 Model & Data Agnostic: Connect to OpenAI, Anthropic, local models (via Ollama), various vector stores, and tons of other services. (Seriously, check out their integrations list!).
☁️ Free Cloud Option: DataStax offers a free, production-grade cloud service (DataStax Langflow) for easy deployment. You can also self-host.
🔬 Observability: Integrates with LangSmith, LangFuse, and LangWatch.
🤖 Multi-agent Support: Build and manage multiple agents.
🧩 Rich Integrations: Connect to many data sources, models, vector stores, etc.
While Langflow has been around for a bit, they're pushing hard into multi-agent systems. Plus, the free cloud option and expanding integrations (like Ollama, DeepSeek, and Groq) make it super accessible for building all sorts of AI applications.
Thrilled to see an open-source tool that truly simplifies RAG and multi-agent system development, especially with Python at its core for serious customization. The free cloud option and broad integrations (Ollama, etc.) are a great touch for easier deployment and experimentation!
Langflow is a solid tool for anyone diving into multi-agent systems or RAG workflows. I love how it keeps Python at the core, offering the flexibility to customize everything while making it super accessible with a drag-and-drop interface.
Congrats on the launch!
Best wishes and sending lots of wins to the team :) @ogabrielluiz
As someone who's been wrestling with RAG implementations and agent architectures, I literally got goosebumps seeing this! 🎯
The democratization of AI development is something I'm deeply passionate about, and what you've built here is absolutely revolutionary. That moment when you realize you don't have to write hundreds of lines of code just to get a basic RAG system running... it's pure joy!
The way you've made this both low-code AND flexible enough to use any LLM or vector database is brilliant. It's like you've found that perfect sweet spot between accessibility and power. No more being locked into specific vendors or struggling with complex infrastructure - this is freedom!
And making it open source? That's not just generous, it's transformative. You're not just building a tool; you're nurturing an entire ecosystem of AI innovation. The fact that developers can either deploy on DataStax for free or self-host shows such deep understanding of what the community needs.
The visual flow builder brings back memories of when I first discovered visual programming - that "aha!" moment when complex concepts suddenly become clear and tangible. But this time, it's for cutting-edge AI development!
What really touches me is thinking about all the developers, researchers, and creators who can now bring their AI ideas to life without getting bogged down in implementation details. You're not just saving time; you're enabling dreams to become reality.
This feels like one of those tools that will be looked back on as a turning point - when building sophisticated AI applications became truly accessible to the broader development community.
Keep building, keep innovating - you're literally shaping the future of AI development! ⚡️✨
Replies
Kerno [Public Beta]
@zaczuo @masump how does it compare with Zerve and Digital Ocean's builder?
Permit.io
Thrilled to see an open-source tool that truly simplifies RAG and multi-agent system development, especially with Python at its core for serious customization. The free cloud option and broad integrations (Ollama, etc.) are a great touch for easier deployment and experimentation!
nice tool
Langflow is a solid tool for anyone diving into multi-agent systems or RAG workflows. I love how it keeps Python at the core, offering the flexibility to customize everything while making it super accessible with a drag-and-drop interface.
Congrats on the launch!
Best wishes and sending lots of wins to the team :) @ogabrielluiz
Chance AI
As someone who's been wrestling with RAG implementations and agent architectures, I literally got goosebumps seeing this! 🎯
The democratization of AI development is something I'm deeply passionate about, and what you've built here is absolutely revolutionary. That moment when you realize you don't have to write hundreds of lines of code just to get a basic RAG system running... it's pure joy!
The way you've made this both low-code AND flexible enough to use any LLM or vector database is brilliant. It's like you've found that perfect sweet spot between accessibility and power. No more being locked into specific vendors or struggling with complex infrastructure - this is freedom!
And making it open source? That's not just generous, it's transformative. You're not just building a tool; you're nurturing an entire ecosystem of AI innovation. The fact that developers can either deploy on DataStax for free or self-host shows such deep understanding of what the community needs.
The visual flow builder brings back memories of when I first discovered visual programming - that "aha!" moment when complex concepts suddenly become clear and tangible. But this time, it's for cutting-edge AI development!
What really touches me is thinking about all the developers, researchers, and creators who can now bring their AI ideas to life without getting bogged down in implementation details. You're not just saving time; you're enabling dreams to become reality.
This feels like one of those tools that will be looked back on as a turning point - when building sophisticated AI applications became truly accessible to the broader development community.
Keep building, keep innovating - you're literally shaping the future of AI development! ⚡️✨