eb5f83f950
* fix: pin postgres image to bookworm in docker_example to prevent collation mismatch
The postgres:16 tag silently moved its base from Debian Bookworm
(glibc 2.36) to Trixie (glibc 2.41), causing a recurring collation
version mismatch warning on existing langflow-postgres volumes.
Pin to postgres:16-bookworm in both docker-compose files and update
the README so existing data volumes keep matching the OS locale data.
Refs: https://github.com/langflow-ai/langflow/issues/9608
* docs: pin postgres image to bookworm in current docs compose snippets
Mirror the docker_example pin in the four current docs that publish
copyable Compose snippets pairing postgres:16 with a persistent
langflow-postgres volume. Prevents the same Bookworm-to-Trixie
collation version mismatch warning when users follow docs instead
of docker_example.
Versioned historical docs are left as-is.
Refs: https://github.com/langflow-ai/langflow/issues/9608
* fix: switch postgres pin from bookworm to trixie for OS consistency
Aligns the pinned postgres base with the langflow runtime image, which
moved to Debian Trixie in #12990. Keeping postgres on bookworm would
have diverged the stack and locked the database to an aging glibc that
will receive fewer security backports as bookworm ages into oldstable.
The pin itself still solves the original bug — postgres:16 cannot
silently roll its OS underneath an existing volume.
Document the one-time REFRESH COLLATION VERSION step for users
upgrading from a bookworm-initialized volume in docker_example/README.md.
Refs: https://github.com/langflow-ai/langflow/issues/9608
(cherry picked from commit 7504eb4c72)
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
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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 3.10–3.13 and uv (recommended package manager).
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From a fresh directory, run:
uv pip install langflow -U
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To start Langflow, run:
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