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* feat: upgrade Docker images to Python 3.14 (experimental)
- Update pyproject.toml: requires-python from <3.14 to <3.15
- Update all 5 Dockerfiles to use Python 3.14:
- Builder stage: python3.12-trixie-slim → python3.14-trixie-slim
- Runtime stage: python:3.12-slim-trixie → python:3.14-slim-trixie
- src/backend/base/pyproject.toml
- docker/build_and_push_base.Dockerfile
- docker/build_and_push.Dockerfile
- docker/build_and_push_backend.Dockerfile
- docker/build_and_push_with_extras.Dockerfile
- docker/build_and_push_ep.Dockerfile
Python 3.14.5 was released on May 10, 2026. Upgrading to the latest
Python version should help reduce CVE vulnerabilities in Docker images.
This is an experimental change to test Python 3.14 compatibility:
- Docker images will use Python 3.14
- CI/CD workflows still test on Python 3.10-3.13
- Nightly build will validate if dependencies work with 3.14
- Can be reverted quickly if issues are found
- Monitor nightly build for failures
- If successful, update CI/CD workflows to add Python 3.14 to test matrix
- If failures occur, revert and investigate compatibility issues
* chore: support Python 3.14
Bump requires-python upper bound to <3.15 across langflow, langflow-base,
lfx, and langflow-sdk, and add 3.14 to CI test matrices so PRs are gated
on 3.14 compatibility.
Conditional pins for transitive deps without 3.14 wheels at the existing
caps:
- onnxruntime: >=1.26 on 3.14 (existing <1.24 cap retained for 3.10)
- faiss-cpu: >=1.13.2 on 3.14 (existing ==1.9.0.post1 retained for <3.14)
* chore: marker-gate IBM watsonx packages for Python 3.14
ibm-watsonx-ai 1.3.x cannot import on Python 3.14: its StrEnum subclasses
override __init__ in a way that conflicts with 3.14's reworked enum
__set_name__ path (TypeError on KnowledgeBaseFieldRole class creation).
Cap ibm-watsonx-ai, langchain-ibm, and the ibm-watsonx-orchestrate-*
extras at python_version<'3.14' until upstream adapts. Watsonx component
imports are already lazy, so this surfaces only at component-access time
on 3.14, where the existing ImportError handler in
lfx.components.ibm.__init__ degrades it gracefully.
test_model_utils.py imports ChatWatsonx at module top to verify
get_model_name resolves model_id; guard that import so the test
module skips on 3.14 instead of breaking collection.
* [autofix.ci] apply automated fixes
* chore: upgrade remaining Docker images to Python 3.14
build_and_push*.Dockerfile already moved to 3.14 in the merge from
feat/upgrade-python-3.14-docker-images. Apply the same bump to the
dev, devcontainer, and lfx Docker images so all in-repo Dockerfiles
share one Python version.
* [autofix.ci] apply automated fixes
* chore: gate 3.14-broken extras to python_version<'3.14'
cuga (and its transitive fastembed -> py-rust-stemmers source build),
altk/agent-lifecycle-toolkit (re-pulls ibm-watsonx-ai which was already
gated), langchain-pinecone, langwatch, ragstack-ai-knowledge-store, and
OpenDsStar all pin themselves below 3.14 upstream. Without a marker
guard, the workspace lock still tries to install them and a Docker
`uv sync` then attempts source builds that require Rust (CI Docker
test failure with py-rust-stemmers 0.1.5).
Add python_version<'3.14' (or <'3.13' for ragstack) to each pin so
those packages are simply omitted from the 3.14 install set until
upstream catches up. uv pip check is now clean on 3.14.2.
* test: skip test_altk_agent on Python 3.14
altk (agent-lifecycle-toolkit) is gated to python_version<'3.14'
upstream and now via the langflow-base [altk] extra marker. The test
imports altk at module top to exercise ALTKAgentComponent; guard the
import so collection skips on 3.14 instead of failing.
* test: skip remaining altk tests on Python 3.14
Three more test modules import lfx.base.agents.altk_* at module top,
which transitively imports altk. Add the same module-level skip guard
as test_altk_agent.py:
- test_altk_agent_logic.py
- test_altk_agent_tool_conversion.py
- test_conversation_context_ordering.py
* fix(calculator): replace removed ast.Num with ast.Constant for Python 3.14
ast.Num was deprecated in Python 3.8 in favor of ast.Constant and
removed entirely in 3.14. The calculator tool and its core walker
crashed on 3.14 with 'module ast has no attribute Num'.
Switch the isinstance checks to ast.Constant + isinstance(node.value,
(int, float)), and drop the now-dead ast.Num backwards-compat branch
in calculator_core.py (the ast.Constant branch already handles every
input it would have matched). Update the parser unit-test fixtures
to construct ast.Constant nodes.
* [autofix.ci] apply automated fixes
* [autofix.ci] apply automated fixes (attempt 2/3)
* test: skip LangWatch HTTP instrumentation tests on Python 3.14
langwatch is gated to python_version<'3.14' upstream. The
TestLangWatchHttpInstrumentation class patches langwatch.setup and
langwatch.trace inside a fixture, which requires langwatch to be
importable; on 3.14 the test errors with ModuleNotFoundError.
Guard the class with a skipif on langwatch availability.
* test: allow IBM and altk components to be missing on Python 3.14
test_all_modules_importable enforces that every component in __all__
imports cleanly. On 3.14 the ibm-watsonx-ai, langchain-ibm, and altk
packages are gated upstream and intentionally not installed, so the
WatsonxAI, WatsonxEmbeddings, and ALTKAgent components fail to import
as designed.
- test_all_components_in_categories_importable: accept a known-gated
deny-list on 3.14 instead of failing.
- test_all_lfx_component_modules_directly_importable: extend the
existing 'missing optional dependency' allowlist with altk,
langchain_ibm, and ibm_watsonx_ai.
* fix(lfx): pass ensure_exists to user_cache_dir for Python 3.14
Python 3.14 tightened PurePath.__init__ to reject unknown keyword
arguments. The KeyedWorkerLockManager constructor was passing
ensure_exists=True to Path() instead of user_cache_dir(), which
silently worked on 3.10-3.13 but raises TypeError on 3.14 and also
meant the cache directory was never actually being created.
Move the kwarg to user_cache_dir() where it belongs and update the
two unit tests that asserted the buggy call shape.
* [autofix.ci] apply automated fixes
* test: accept either ZIP or JSON error path on Python 3.14
Python 3.14's zipfile.is_zipfile() now validates the central-directory
signature in addition to EOCD, so the garbage+EOCD payload no longer
passes the is_zipfile() dispatch in the /flows/upload/ route. The
endpoint still returns 400 with a descriptive detail (now from the JSON
branch); only the message wording differs, which the test was asserting
verbatim.
* fix(lfx): normalize cors_origins ['*'] back to '*' on Python 3.14
Pydantic-settings on Python 3.14 parses the env var '*' into ['*']
before the cors_origins field validator runs (the list[str] | str union
resolves differently than on 3.10-3.13). Collapse that back to the
bare-string wildcard so downstream consumers — including
warn_about_future_cors_changes and the test suite — see the same shape
on every supported Python version.
---------
Co-authored-by: vijay kumar katuri <vijay.katuri@ibm.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
(cherry picked from commit 1955f8fae5)
Langflow Demo Codespace Readme
These instructions will walk you through the process of running a Langflow demo via GitHub Codespaces.
If you want a faster and easier demo experience with Langflow, download and install Langflow Desktop for the least complicated setup experience.
Create a Codespace in GitHub
To setup the demo in Codespace:
- Navigate to the Langflow repo
- On the "Code <>" button, select the "Codespaces" tab
- Click the green "Create codespace on..." button (or "+" icon if you want more options) to create a new Codespace
Wait for everything to install
After the codespace is opened, there will be two phases to the process. It will take ≈5-10 minutes to complete.
- Phase 1: Building Container; you can click on the "Building Codespace" link to watch the logs
- Phase 2: Building Langflow; the terminal will now show
Running postCreateCommand..., similar to:
✔ Finishing up...
⠸ Running postCreateCommand...
› sudo chown -R langflow .venv .mypy_cache src/frontend/node_modules src/frontend/build src/backend/base/langflow/frontend && make install_frontend && mak…
Once completed, this terminal window will close.
You now need to manually build the frontend. Open a new Terminal and run command:
make build_frontend
This will take a short period of time, you should have a message similar to Building frontend static files and the command will complete successfully.
Installation is now complete.
Start up the Service
Open a new Terminal, and type uv run langflow run.
The service will start, and you will may notice a dialog in the lower right indicating there is a port available to connect to. However, the service will not be ready until you see the welcome banner:
╭───────────────────────────────────────────────────────────────────────╮
│ Welcome to Langflow │
│ │
│ 🌟 GitHub: Star for updates → https://github.com/langflow-ai/langflow │
│ 💬 Discord: Join for support → https://discord.com/invite/EqksyE2EX9 │
│ │
│ We collect anonymous usage data to improve Langflow. │
│ To opt out, set: DO_NOT_TRACK=true in your environment. │
│ │
│ 🟢 Open Langflow → http://localhost:7860 │
╰───────────────────────────────────────────────────────────────────────╯
At this point you can connect to the service via the port, or if the dialog is gone you can find the "Forwarded Address" on the "Ports" tab (which is next the "Terminal" tab). If there is no port forwarded, you can click the "Forward a Port" button on the "Ports" tab, and forward 7860.