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* nextplaid integrate * doc ids fix * multivec fixes * type check * refactor: ship NextPlaid as the lfx-nextplaid extension bundle Convert the in-tree NextPlaid vector store and its companion vLLM multivector embeddings into a standalone `lfx-nextplaid` Extension Bundle, following src/bundles/PORTING.md (cf. lfx-arxiv, lfx-ibm). The whole feature now ships as an additive bundle with no core modifications. - Move both components into src/bundles/nextplaid (components/nextplaid), dropping src/lfx/.../components/nextplaid and reverting the core vllm __init__ multivector additions. - Bundle declares its own runtime deps (langchain-plaid, pillow) and ships extension.json + the langflow.extensions entry point. - Add migration_table entries mapping the legacy class names / import paths to ext:nextplaid:*@official; wire the workspace (root pyproject, uv.lock). - Add the pilot upgrade integration test and bundle-local unit tests. - Declare explicit outputs on NextPlaidVectorStoreComponent so the extension validator can resolve its output methods. * fix: address CodeRabbit review on NextPlaid bundle - nextplaid: derive stable text IDs from source/page+content (not content alone) and fingerprint raw PIL images by bytes (not batch position) so ingests upsert instead of colliding/overwriting unrelated vectors - vllm impl: validate the /pooling response envelope before nested indexing, raising a clear RuntimeError on malformed text/image responses - icon: use the isDark boolean prop contract instead of the isdark string - test: gate the distribution check on package presence (PackageNotFoundError) so genuine import failures surface instead of being skipped --------- Co-authored-by: Meet <meet@dhcp-9-127-22-227.c4p-in.ibm.com> Co-authored-by: Eric Hare <ericrhare@gmail.com>
Langflow is a powerful platform for building and deploying AI-powered agents and workflows. It provides developers with both a visual authoring experience and built-in API and MCP servers that turn every workflow into a tool that can be integrated into applications built on any framework or stack. Langflow comes with batteries included and supports all major LLMs, vector databases and a growing library of AI tools.
✨ Highlight features
- Visual builder interface to quickly get started and iterate.
- Source code access lets you customize any component using Python.
- Interactive playground to immediately test and refine your flows with step-by-step control.
- Multi-agent orchestration with conversation management and retrieval.
- Deploy as an API or export as JSON for Python apps.
- Deploy as an MCP server and turn your flows into tools for MCP clients.
- Observability with LangSmith, LangFuse and other integrations.
- Enterprise-ready security and scalability.
🖥️ Langflow Desktop
Langflow Desktop is the easiest way to get started with Langflow. All dependencies are included, so you don't need to manage Python environments or install packages manually. Available for Windows and macOS.
⚡️ Quickstart
Install locally (recommended)
Requires Python 3.10–3.14 and uv (recommended package manager).
Install
From a fresh directory, run:
uv pip install langflow -U
The latest Langflow package is installed. For more information, see Install and run the Langflow OSS Python package.
Run
To start Langflow, run:
uv run langflow run
Langflow starts at http://127.0.0.1:7860.
That's it! You're ready to build with Langflow! 🎉
📦 Other install options
Run from source
If you've cloned this repository and want to contribute, run this command from the repository root:
make run_cli
For more information, see DEVELOPMENT.md.
Docker
Start a Langflow container with default settings:
docker run -p 7860:7860 langflowai/langflow:latest
Langflow is available at http://localhost:7860/. For configuration options, see the Docker deployment guide.
🛡️ Security
For security information, see our Security Policy.
🚀 Deployment
Langflow is completely open source and you can deploy it to all major deployment clouds. To learn how to deploy Langflow, see our Langflow deployment guides.
⭐ Stay up-to-date
Star Langflow on GitHub to be instantly notified of new releases.
👋 Contribute
We welcome contributions from developers of all levels. If you'd like to contribute, please check our contributing guidelines and help make Langflow more accessible.