09ae9cf0f2
* fix: enable IBM watsonx.ai bundle on Python 3.14 ibm-watsonx-ai (1.5.13) and langchain-ibm (1.1.0) added Python 3.14 support upstream on 2026-06-03, so the official 3.14 Docker image no longer needs to silently drop the IBM integration. - Lift the `python_version < '3.14'` markers on ibm-watsonx-ai and langchain-ibm in both the lfx-ibm bundle and langflow-base. - Bump langchain-ibm from `~=1.0.2` to `~=1.1.0`; the 3.14-capable release is 1.1.0, which the old `~=1.0.2` pin excluded. - Regenerate uv.lock: the resolver now forks ibm-watsonx-ai into 1.5.13 for py>=3.11 (incl. 3.14) and 1.3.42 for py<3.11, so 3.10 keeps working while 3.14 gains the integration. watsonx-orchestrate (ibm-watsonx-orchestrate-core/clients) stays gated at <3.14 since upstream 2.10.0 still caps there. * test: stop import-skipping IBM watsonx tests on Python 3.14 The watsonx test modules skipped at module load (pytest.skip with allow_module_level=True) when langchain-ibm / ibm-watsonx-ai failed to import, with comments tying the skip to the upstream <3.14 cap. Now that those deps are importable on 3.14 (this PR's dep bump), the import-based skip can hide real import regressions instead of surfacing them. - test_model_utils.py, test_watsonx.py, test_watsonx_embeddings.py: replace the try/except pytest.skip(allow_module_level=True) guards with direct top-level imports so a missing or broken IBM SDK fails loudly. Drop the now-unused `import pytest` in test_model_utils.py. - src/bundles/ibm/README.md: update the platform note to reflect that the watsonx components are now importable on Python 3.10-3.14. The Db2 tests (test_db2*, test_optional_dependency) are left untouched -- they gate on ibm-db's linux/aarch64 platform exclusion, not the Python version, which is still valid. Validated locally (Python 3.13): 63 tests pass (13 + 50), ruff clean.
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.
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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.
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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.
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To start Langflow, run:
uv run langflow run
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