langflow-base
A Python package with a built-in web application
Decision gist · record as of 2026-08-14
Yes. Langflow-base is actively maintained, has no known vulnerabilities, uses a permissive MIT license, and offers low installation friction. It is suitable for developers building AI workflows at any scale, from prototyping to production deployment. The large dependency footprint is justified by its breadth of integrations and should not pose a barrier for most use cases.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10–3.14; uv package manager recommended for installation per documentation.
- Low install friction with a pure-Python wheel distribution.
- The package is actively maintained with a recent release (3 days old) and strong community signal (153249 GitHub stars).
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions, making it suitable for both open-source and proprietary projects.
last release 2026-08-11 (3 days) · last repo commit 2026-08-14 · 153,249 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 133,571 downloads/mo, #11,503 on PyPI
Alternatives
Verify before relying
pip install langflow-base
from langflow.main import run
run()- Whether the 90 runtime dependencies are all required for basic functionality or if many are optional.
- Performance characteristics and scalability limits for production deployments.
- Specific LLM providers and vector databases that are pre-integrated versus requiring custom setup.
What it is and what it does
Langflow-base is the core Python backend for Langflow, a platform for building AI-powered agents and workflows. It provides both a visual builder interface accessible via a web application and programmatic APIs for constructing, testing, and deploying multi-agent systems. The package bundles a large dependency graph including FastAPI for the web server, support for multiple LLM providers (OpenAI, IBM Watsonx, AssemblyAI), vector databases (DuckDB, ClickHouse), and orchestration tools.
Developers use langflow-base to create AI workflows either through the visual UI or by writing Python code, then deploy them as REST APIs or MCP servers. The package includes an interactive playground for testing flows step-by-step, observability integrations with LangSmith and LangFuse, and support for conversation management and retrieval-augmented generation patterns. It is designed for enterprise use with security and scalability considerations.
Use it for
- Build and test multi-agent AI systems using a visual interface without writing boilerplate orchestration code.
- Deploy AI workflows as production REST APIs that can be integrated into web applications or microservices.
- Create MCP (Model Context Protocol) servers from AI workflows to expose them as tools to other applications.
- Prototype and iterate on LLM-based applications with an interactive playground and step-by-step debugging.
- Integrate multiple LLM providers and vector databases into a single workflow management platform.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Langflow-base is actively maintained, has no known vulnerabilities, uses a permissive MIT license, and offers low installation friction. It is suitable for developers building AI workflows at any scale, from prototyping to production deployment. The large dependency footprint is justified by its breadth of integrations and should not pose a barrier for most use cases.
Install
langflow-base on PyPI
Before you install
Low install friction with a pure-Python wheel distribution. The package is actively maintained with a recent release (3 days old) and strong community signal (153249 GitHub stars). Requires Python 3.10–3.14.
Requires Python 3.10–3.14; uv package manager recommended for installation per documentation.
License in practice
MIT license permits commercial and private use with minimal restrictions, making it suitable for both open-source and proprietary projects.
Quickstart
pip install langflow-base
from langflow.main import run
run()Verify before relying
- Whether the 90 runtime dependencies are all required for basic functionality or if many are optional.
- Performance characteristics and scalability limits for production deployments.
- Specific LLM providers and vector databases that are pre-integrated versus requiring custom setup.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <3.15,>=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 90 packagesa2a-sdkag-ui-protocolaiofileaiofilesaiosqlitealembicassemblyaiasyncerbcryptcachetoolschardetclickhouse-connectcryptographydefusedxmldocstring-parserduckdbdynaconfelevenlabsemail-validatoremojifastapi-paginationfastapifilelockgrandalfgreenletgunicornhttpxibm-watsonx-aijaraco-contextjq |
| Maintenance | Actively maintained 3 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 133,571 / month, #11,503 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: langflow_base-0.11.3-py3-none-any.whl
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