llama-stack-mirror/pyproject.toml
Sébastien Han 7cf1e24c4e
feat(logging): implement category-based logging (#1362)
# What does this PR do?

This commit introduces a new logging system that allows loggers to be
assigned
a category while retaining the logger name based on the file name. The
log
format includes both the logger name and the category, producing output
like:

```
INFO     2025-03-03 21:44:11,323 llama_stack.distribution.stack:103 [core]: Tool_groups: builtin::websearch served by
         tavily-search
```

Key features include:

- Category-based logging: Loggers can be assigned a category (e.g.,
  "core", "server") when programming. The logger can be loaded like
  this: `logger = get_logger(name=__name__, category="server")`
- Environment variable control: Log levels can be configured
per-category using the
  `LLAMA_STACK_LOGGING` environment variable. For example:
`LLAMA_STACK_LOGGING="server=DEBUG;core=debug"` enables DEBUG level for
the "server"
    and "core" categories.
- `LLAMA_STACK_LOGGING="all=debug"` sets DEBUG level globally for all
categories and
    third-party libraries.

This provides fine-grained control over logging levels while maintaining
a clean and
informative log format.

The formatter uses the rich library which provides nice colors better
stack traces like so:

```
ERROR    2025-03-03 21:49:37,124 asyncio:1758 [uncategorized]: unhandled exception during asyncio.run() shutdown
         task: <Task finished name='Task-16' coro=<handle_signal.<locals>.shutdown() done, defined at
         /Users/leseb/Documents/AI/llama-stack/llama_stack/distribution/server/server.py:146>
         exception=UnboundLocalError("local variable 'loop' referenced before assignment")>
         ╭────────────────────────────────────── Traceback (most recent call last) ───────────────────────────────────────╮
         │ /Users/leseb/Documents/AI/llama-stack/llama_stack/distribution/server/server.py:178 in shutdown                │
         │                                                                                                                │
         │   175 │   │   except asyncio.CancelledError:                                                                   │
         │   176 │   │   │   pass                                                                                         │
         │   177 │   │   finally:                                                                                         │
         │ ❱ 178 │   │   │   loop.stop()                                                                                  │
         │   179 │                                                                                                        │
         │   180 │   loop = asyncio.get_running_loop()                                                                    │
         │   181 │   loop.create_task(shutdown())                                                                         │
         ╰────────────────────────────────────────────────────────────────────────────────────────────────────────────────╯
         UnboundLocalError: local variable 'loop' referenced before assignment
```

Co-authored-by: Ashwin Bharambe <@ashwinb>
Signed-off-by: Sébastien Han <seb@redhat.com>

[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])

## Test Plan

```
python -m llama_stack.distribution.server.server --yaml-config ./llama_stack/templates/ollama/run.yaml
INFO     2025-03-03 21:55:35,918 __main__:365 [server]: Using config file: llama_stack/templates/ollama/run.yaml           
INFO     2025-03-03 21:55:35,925 __main__:378 [server]: Run configuration:                                                 
INFO     2025-03-03 21:55:35,928 __main__:380 [server]: apis:                                                              
         - agents                                                     
``` 
[//]: # (## Documentation)

---------

Signed-off-by: Sébastien Han <seb@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
2025-03-07 11:34:30 -08:00

166 lines
4.1 KiB
TOML

[build-system]
requires = ["setuptools>=61.0"]
build-backend = "setuptools.build_meta"
[project]
name = "llama_stack"
version = "0.1.5"
authors = [{ name = "Meta Llama", email = "llama-oss@meta.com" }]
description = "Llama Stack"
readme = "README.md"
requires-python = ">=3.10"
license = { "text" = "MIT" }
classifiers = [
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Operating System :: OS Independent",
"Intended Audience :: Developers",
"Intended Audience :: Information Technology",
"Intended Audience :: Science/Research",
"Topic :: Scientific/Engineering :: Artificial Intelligence",
"Topic :: Scientific/Engineering :: Information Analysis",
]
dependencies = [
"blobfile",
"fire",
"httpx",
"huggingface-hub",
"jsonschema",
"llama-stack-client>=0.1.4",
"prompt-toolkit",
"python-dotenv",
"pydantic>=2",
"requests",
"rich",
"setuptools",
"termcolor",
]
[project.optional-dependencies]
dev = [
"pytest",
"pytest-asyncio",
"pytest-html",
"nbval", # For notebook testing
"black",
"ruff",
"types-requests",
"types-setuptools",
"pre-commit",
"uvicorn",
"fastapi",
"ruamel.yaml", # needed for openapi generator
]
test = [
"openai",
"aiosqlite",
"sqlite-vec",
"ollama",
"torch>=2.6.0",
"fairscale>=0.4.13",
"torchvision>=0.21.0",
"lm-format-enforcer>=0.10.9",
"groq",
"opentelemetry-sdk",
"opentelemetry-exporter-otlp-proto-http",
"tiktoken",
"chardet",
"pypdf",
]
docs = [
"sphinx-autobuild",
"myst-parser",
"sphinx-rtd-theme",
"sphinx-copybutton",
"sphinx-tabs",
"sphinx-design",
"sphinxcontrib.redoc",
"sphinxcontrib.video",
"sphinxcontrib.mermaid",
"tomli",
]
codegen = ["rich", "pydantic", "jinja2>=3.1.6"]
[project.urls]
Homepage = "https://github.com/meta-llama/llama-stack"
[project.scripts]
llama = "llama_stack.cli.llama:main"
install-wheel-from-presigned = "llama_stack.cli.scripts.run:install_wheel_from_presigned"
[tool.setuptools]
packages = { find = {} }
license-files = []
[[tool.uv.index]]
name = "pytorch-cpu"
url = "https://download.pytorch.org/whl/cpu"
explicit = true
[tool.uv.sources]
torch = [{ index = "pytorch-cpu" }]
torchvision = [{ index = "pytorch-cpu" }]
[tool.ruff]
line-length = 120
exclude = [
"./.git",
"./docs/*",
"./build",
"./scripts",
"./venv",
"*.pyi",
".pre-commit-config.yaml",
"*.md",
".flake8",
]
[tool.ruff.lint]
select = [
"B", # flake8-bugbear
"B9", # flake8-bugbear subset
"C", # comprehensions
"E", # pycodestyle
"F", # Pyflakes
"N", # Naming
"W", # Warnings
"I", # isort
]
ignore = [
# The following ignores are desired by the project maintainers.
"E402", # Module level import not at top of file
"E501", # Line too long
"F405", # Maybe undefined or defined from star import
"C408", # Ignored because we like the dict keyword argument syntax
"N812", # Ignored because import torch.nn.functional as F is PyTorch convention
# These are the additional ones we started ignoring after moving to ruff. We should look into each one of them later.
"C901", # Complexity of the function is too high
]
[tool.mypy]
mypy_path = ["llama_stack"]
packages = ["llama_stack"]
disable_error_code = []
warn_return_any = true
# # honor excludes by not following there through imports
follow_imports = "silent"
exclude = [
# As we fix more and more of these, we should remove them from the list
"llama_stack/providers",
"llama_stack/distribution",
"llama_stack/apis",
"llama_stack/cli",
"llama_stack/models",
"llama_stack/strong_typing",
"llama_stack/templates",
]
[[tool.mypy.overrides]]
# packages that lack typing annotations, do not have stubs, or are unavailable.
module = ["yaml", "fire"]
ignore_missing_imports = true
[[tool.mypy.overrides]]
module = ["llama_stack.distribution.resolver", "llama_stack.log"]
follow_imports = "normal" # This will force type checking on this module