Dev

.github/workflows/format-backend.yaml

@@ -42,10 +42,7 @@ jobs:
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          pip install black
+          pip install "ruff>=0.15.5"
 
-      - name: Format backend
-        run: npm run format:backend
-
-      - name: Check for changes after format
-        run: git diff --exit-code
+      - name: Ruff format check
+        run: ruff format --check . --exclude .venv --exclude venv

.pre-commit-config.yaml

@@ -0,0 +1,8 @@
+repos:
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.15.5
+    hooks:
+      - id: ruff
+        args: [--fix, backend]
+      - id: ruff-format
+        args: [backend]

CHANGELOG_EXTRA.md

@@ -5,6 +5,12 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.8.11.1] - 2026.03.26
+
+### Changed
+
+- 合并官方 0.8.11 改动
+
 ## [0.8.10.2] - 2026.03.18
 
 ### Added

Dockerfile

@@ -136,29 +136,30 @@ RUN apt-get update && \
 # install python dependencies
 COPY --chown=$UID:$GID ./backend/requirements.txt ./requirements.txt
 
-RUN pip3 install --no-cache-dir uv && \
+RUN set -e; \
+    pip3 install --no-cache-dir uv; \
     if [ "$USE_CUDA" = "true" ]; then \
     # If you use CUDA the whisper and embedding model will be downloaded on first use
     # fix: pin torch<=2.9.1 - torch 2.10.0 aarch64 wheels cause SIGILL on ARM devices (RPi 4 Cortex-A72) #21349
-    pip3 install 'torch<=2.9.1' torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir && \
-    uv pip install --system -r requirements.txt --no-cache-dir && \
-    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \
-    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ.get('AUXILIARY_EMBEDDING_MODEL', 'TaylorAI/bge-micro-v2'), device='cpu')" && \
+    pip3 install 'torch<=2.9.1' torchvision torchaudio --index-url https://download.pytorch.org/whl/$USE_CUDA_DOCKER_VER --no-cache-dir; \
+    uv pip install --system -r requirements.txt --no-cache-dir; \
+    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')"; \
+    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ.get('AUXILIARY_EMBEDDING_MODEL', 'TaylorAI/bge-micro-v2'), device='cpu')"; \
     python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; \
     python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
     python -c "import nltk; nltk.download('punkt_tab')"; \
     else \
-    pip3 install 'torch<=2.9.1' torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir && \
-    uv pip install --system -r requirements.txt --no-cache-dir && \
+    pip3 install 'torch<=2.9.1' torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu --no-cache-dir; \
+    uv pip install --system -r requirements.txt --no-cache-dir; \
     if [ "$USE_SLIM" != "true" ]; then \
-    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')" && \
-    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ.get('AUXILIARY_EMBEDDING_MODEL', 'TaylorAI/bge-micro-v2'), device='cpu')" && \
+    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ['RAG_EMBEDDING_MODEL'], device='cpu')"; \
+    python -c "import os; from sentence_transformers import SentenceTransformer; SentenceTransformer(os.environ.get('AUXILIARY_EMBEDDING_MODEL', 'TaylorAI/bge-micro-v2'), device='cpu')"; \
     python -c "import os; from faster_whisper import WhisperModel; WhisperModel(os.environ['WHISPER_MODEL'], device='cpu', compute_type='int8', download_root=os.environ['WHISPER_MODEL_DIR'])"; \
     python -c "import os; import tiktoken; tiktoken.get_encoding(os.environ['TIKTOKEN_ENCODING_NAME'])"; \
     python -c "import nltk; nltk.download('punkt_tab')"; \
     fi; \
     fi; \
-    mkdir -p /app/backend/data && chown -R $UID:$GID /app/backend/data/ && \
+    mkdir -p /app/backend/data; chown -R $UID:$GID /app/backend/data/; \
     rm -rf /var/lib/apt/lists/*;
 
 # Install Ollama if requested

backend/dev.sh

@@ -1,3 +1,3 @@
 export CORS_ALLOW_ORIGIN="http://localhost:5173;http://localhost:8080"
 PORT="${PORT:-8080}"
-uvicorn open_webui.main:app --port $PORT --host 0.0.0.0 --forwarded-allow-ips '*' --reload
+uvicorn open_webui.main:app --port $PORT --host 0.0.0.0 --forwarded-allow-ips "${FORWARDED_ALLOW_IPS:-*}" --reload

backend/open_webui/__init__.py

@@ -2,102 +2,95 @@
 import os
 import random
 from pathlib import Path
+from typing import Annotated
 
 import typer
 import uvicorn
-from typing import Optional
-from typing_extensions import Annotated
 
 app = typer.Typer()
 
-KEY_FILE = Path.cwd() / ".webui_secret_key"
+KEY_FILE = Path.cwd() / '.webui_secret_key'
 
 
-def version_callback(value: bool):
+def version_callback(value: bool) -> None:
     if value:
         from open_webui.env import VERSION
 
-        typer.echo(f"Open WebUI version: {VERSION}")
+        typer.echo(f'Open WebUI version: {VERSION}')
         raise typer.Exit()
 
 
 @app.command()
 def main(
-    version: Annotated[
-        Optional[bool], typer.Option("--version", callback=version_callback)
-    ] = None,
+    version: Annotated[bool | None, typer.Option('--version', callback=version_callback)] = None,
 ):
     pass
 
 
 @app.command()
 def serve(
-    host: str = "0.0.0.0",
+    host: str = '0.0.0.0',
     port: int = 8080,
 ):
-    os.environ["FROM_INIT_PY"] = "true"
-    if os.getenv("WEBUI_SECRET_KEY") is None:
-        typer.echo(
-            "Loading WEBUI_SECRET_KEY from file, not provided as an environment variable."
-        )
+    os.environ['FROM_INIT_PY'] = 'true'
+    if os.getenv('WEBUI_SECRET_KEY') is None:
+        typer.echo('Loading WEBUI_SECRET_KEY from file, not provided as an environment variable.')
         if not KEY_FILE.exists():
-            typer.echo(f"Generating a new secret key and saving it to {KEY_FILE}")
+            typer.echo(f'Generating a new secret key and saving it to {KEY_FILE}')
             KEY_FILE.write_bytes(base64.b64encode(random.randbytes(12)))
-        typer.echo(f"Loading WEBUI_SECRET_KEY from {KEY_FILE}")
-        os.environ["WEBUI_SECRET_KEY"] = KEY_FILE.read_text()
+        typer.echo(f'Loading WEBUI_SECRET_KEY from {KEY_FILE}')
+        os.environ['WEBUI_SECRET_KEY'] = KEY_FILE.read_text()
 
-    if os.getenv("USE_CUDA_DOCKER", "false") == "true":
-        typer.echo(
-            "CUDA is enabled, appending LD_LIBRARY_PATH to include torch/cudnn & cublas libraries."
-        )
-        LD_LIBRARY_PATH = os.getenv("LD_LIBRARY_PATH", "").split(":")
-        os.environ["LD_LIBRARY_PATH"] = ":".join(
+    if os.getenv('USE_CUDA_DOCKER', 'false') == 'true':
+        typer.echo('CUDA is enabled, appending LD_LIBRARY_PATH to include torch/cudnn & cublas libraries.')
+        LD_LIBRARY_PATH = os.getenv('LD_LIBRARY_PATH', '').split(':')
+        os.environ['LD_LIBRARY_PATH'] = ':'.join(
             LD_LIBRARY_PATH
             + [
-                "/usr/local/lib/python3.11/site-packages/torch/lib",
-                "/usr/local/lib/python3.11/site-packages/nvidia/cudnn/lib",
+                '/usr/local/lib/python3.11/site-packages/torch/lib',
+                '/usr/local/lib/python3.11/site-packages/nvidia/cudnn/lib',
             ]
         )
         try:
             import torch
 
-            assert torch.cuda.is_available(), "CUDA not available"
-            typer.echo("CUDA seems to be working")
+            assert torch.cuda.is_available(), 'CUDA not available'
+            typer.echo('CUDA seems to be working')
         except Exception as e:
             typer.echo(
-                "Error when testing CUDA but USE_CUDA_DOCKER is true. "
-                "Resetting USE_CUDA_DOCKER to false and removing "
-                f"LD_LIBRARY_PATH modifications: {e}"
+                'Error when testing CUDA but USE_CUDA_DOCKER is true. '
+                'Resetting USE_CUDA_DOCKER to false and removing '
+                f'LD_LIBRARY_PATH modifications: {e}'
             )
-            os.environ["USE_CUDA_DOCKER"] = "false"
-            os.environ["LD_LIBRARY_PATH"] = ":".join(LD_LIBRARY_PATH)
+            os.environ['USE_CUDA_DOCKER'] = 'false'
+            os.environ['LD_LIBRARY_PATH'] = ':'.join(LD_LIBRARY_PATH)
 
-    import open_webui.main  # we need set environment variables before importing main
+    import open_webui.main  # noqa: F401
     from open_webui.env import UVICORN_WORKERS  # Import the workers setting
 
     uvicorn.run(
-        "open_webui.main:app",
+        'open_webui.main:app',
         host=host,
         port=port,
-        forwarded_allow_ips="*",
+        forwarded_allow_ips='*',
         workers=UVICORN_WORKERS,
     )
 
 
 @app.command()
 def dev(
-    host: str = "0.0.0.0",
+    host: str = '0.0.0.0',
     port: int = 8080,
     reload: bool = True,
 ):
     uvicorn.run(
-        "open_webui.main:app",
+        'open_webui.main:app',
         host=host,
         port=port,
         reload=reload,
-        forwarded_allow_ips="*",
+        forwarded_allow_ips='*',
     )
 
 
-if __name__ == "__main__":
+if __name__ == '__main__':
     app()