llama-stack-mirror/llama_stack/log.py
Francisco Javier Arceo 6620b625f1 adding logo and favicon
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

chore: Enable keyword search for Milvus inline (#3073)

With https://github.com/milvus-io/milvus-lite/pull/294 - Milvus Lite
supports keyword search using BM25. While introducing keyword search we
had explicitly disabled it for inline milvus. This PR removes the need
for the check, and enables `inline::milvus` for tests.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

Run llama stack with `inline::milvus` enabled:

```
pytest tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes --stack-config=http://localhost:8321 --embedding-model=all-MiniLM-L6-v2 -v
```

```
INFO     2025-08-07 17:06:20,932 tests.integration.conftest:64 tests: Setting DISABLE_CODE_SANDBOX=1 for macOS
=========================================================================================== test session starts ============================================================================================
platform darwin -- Python 3.12.11, pytest-7.4.4, pluggy-1.5.0 -- /Users/vnarsing/miniconda3/envs/stack-client/bin/python
cachedir: .pytest_cache
metadata: {'Python': '3.12.11', 'Platform': 'macOS-14.7.6-arm64-arm-64bit', 'Packages': {'pytest': '7.4.4', 'pluggy': '1.5.0'}, 'Plugins': {'asyncio': '0.23.8', 'cov': '6.0.0', 'timeout': '2.2.0', 'socket': '0.7.0', 'html': '3.1.1', 'langsmith': '0.3.39', 'anyio': '4.8.0', 'metadata': '3.0.0'}}
rootdir: /Users/vnarsing/go/src/github/meta-llama/llama-stack
configfile: pyproject.toml
plugins: asyncio-0.23.8, cov-6.0.0, timeout-2.2.0, socket-0.7.0, html-3.1.1, langsmith-0.3.39, anyio-4.8.0, metadata-3.0.0
asyncio: mode=Mode.AUTO
collected 3 items

tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes[None-None-all-MiniLM-L6-v2-None-384-vector] PASSED                                                   [ 33%]
tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes[None-None-all-MiniLM-L6-v2-None-384-keyword] PASSED                                                  [ 66%]
tests/integration/vector_io/test_openai_vector_stores.py::test_openai_vector_store_search_modes[None-None-all-MiniLM-L6-v2-None-384-hybrid] PASSED                                                   [100%]

============================================================================================ 3 passed in 4.75s =============================================================================================
```

Signed-off-by: Varsha Prasad Narsing <varshaprasad96@gmail.com>
Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>

chore: Fixup main pre commit (#3204)

build: Bump version to 0.2.18

chore: Faster npm pre-commit (#3206)

Adds npm to pre-commit.yml installation and caches ui
Removes node installation during pre-commit.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

<!-- Describe the tests you ran to verify your changes with result
summaries. *Provide clear instructions so the plan can be easily
re-executed.* -->

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

chiecking in for tonight, wip moving to agents api

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

remove log

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

updated

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

fix: disable ui-prettier & ui-eslint (#3207)

chore(pre-commit): add pre-commit hook to enforce llama_stack logger usage (#3061)

This PR adds a step in pre-commit to enforce using `llama_stack` logger.

Currently, various parts of the code base uses different loggers. As a
custom `llama_stack` logger exist and used in the codebase, it is better
to standardize its utilization.

Signed-off-by: Mustafa Elbehery <melbeher@redhat.com>
Co-authored-by: Matthew Farrellee <matt@cs.wisc.edu>

fix: fix ```openai_embeddings``` for asymmetric embedding NIMs (#3205)

NVIDIA asymmetric embedding models (e.g.,
`nvidia/llama-3.2-nv-embedqa-1b-v2`) require an `input_type` parameter
not present in the standard OpenAI embeddings API. This PR adds the
`input_type="query"` as default and updates the documentation to suggest
using the `embedding` API for passage embeddings.

<!-- If resolving an issue, uncomment and update the line below -->
Resolves #2892

```
pytest -s -v tests/integration/inference/test_openai_embeddings.py   --stack-config="inference=nvidia"   --embedding-model="nvidia/llama-3.2-nv-embedqa-1b-v2"   --env NVIDIA_API_KEY={nvidia_api_key}   --env NVIDIA_BASE_URL="https://integrate.api.nvidia.com"
```

cleaning up

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

updating session manager to cache messages locally

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

fix linter

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>

more cleanup

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
2025-08-21 16:06:30 -04:00

260 lines
8.4 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import logging # allow-direct-logging
import os
import re
from logging.config import dictConfig # allow-direct-logging
from rich.console import Console
from rich.errors import MarkupError
from rich.logging import RichHandler
from llama_stack.core.datatypes import LoggingConfig
# Default log level
DEFAULT_LOG_LEVEL = logging.INFO
# Predefined categories
CATEGORIES = [
"core",
"server",
"router",
"inference",
"agents",
"safety",
"eval",
"tools",
"client",
"telemetry",
"openai_responses",
]
# Initialize category levels with default level
_category_levels: dict[str, int] = dict.fromkeys(CATEGORIES, DEFAULT_LOG_LEVEL)
def config_to_category_levels(category: str, level: str):
"""
Helper function to be called either by environment parsing or yaml parsing to go from a list of categories and levels to a dictionary ready to be
used by the logger dictConfig.
Parameters:
category (str): logging category to apply the level to
level (str): logging level to be used in the category
Returns:
Dict[str, int]: A dictionary mapping categories to their log levels.
"""
category_levels: dict[str, int] = {}
level_value = logging._nameToLevel.get(str(level).upper())
if level_value is None:
logging.warning(f"Unknown log level '{level}' for category '{category}'. Falling back to default 'INFO'.")
return category_levels
if category == "all":
# Apply the log level to all categories and the root logger
for cat in CATEGORIES:
category_levels[cat] = level_value
# Set the root logger's level to the specified level
category_levels["root"] = level_value
elif category in CATEGORIES:
category_levels[category] = level_value
else:
logging.warning(f"Unknown logging category: {category}. No changes made.")
return category_levels
def parse_yaml_config(yaml_config: LoggingConfig) -> dict[str, int]:
"""
Helper function to parse a yaml logging configuration found in the run.yaml
Parameters:
yaml_config (Logging): the logger config object found in the run.yaml
Returns:
Dict[str, int]: A dictionary mapping categories to their log levels.
"""
category_levels = {}
for category, level in yaml_config.category_levels.items():
category_levels.update(config_to_category_levels(category=category, level=level))
return category_levels
def parse_environment_config(env_config: str) -> dict[str, int]:
"""
Parse the LLAMA_STACK_LOGGING environment variable and return a dictionary of category log levels.
Parameters:
env_config (str): The value of the LLAMA_STACK_LOGGING environment variable.
Returns:
Dict[str, int]: A dictionary mapping categories to their log levels.
"""
category_levels = {}
delimiter = ","
for pair in env_config.split(delimiter):
if not pair.strip():
continue
try:
category, level = pair.split("=", 1)
category = category.strip().lower()
level = level.strip().upper() # Convert to uppercase for logging._nameToLevel
category_levels.update(config_to_category_levels(category=category, level=level))
except ValueError:
logging.warning(f"Invalid logging configuration: '{pair}'. Expected format: 'category=level'.")
return category_levels
def strip_rich_markup(text):
"""Remove Rich markup tags like [dim], [bold magenta], etc."""
return re.sub(r"\[/?[a-zA-Z0-9 _#=,]+\]", "", text)
class CustomRichHandler(RichHandler):
def __init__(self, *args, **kwargs):
kwargs["console"] = Console(width=150)
super().__init__(*args, **kwargs)
def emit(self, record):
"""Override emit to handle markup errors gracefully."""
try:
super().emit(record)
except MarkupError:
original_markup = self.markup
self.markup = False
try:
super().emit(record)
finally:
self.markup = original_markup
class CustomFileHandler(logging.FileHandler):
def __init__(self, filename, mode="a", encoding=None, delay=False):
super().__init__(filename, mode, encoding, delay)
# Default formatter to match console output
self.default_formatter = logging.Formatter("%(asctime)s %(name)s:%(lineno)d %(category)s: %(message)s")
self.setFormatter(self.default_formatter)
def emit(self, record):
if hasattr(record, "msg"):
record.msg = strip_rich_markup(str(record.msg))
super().emit(record)
def setup_logging(category_levels: dict[str, int], log_file: str | None) -> None:
"""
Configure logging based on the provided category log levels and an optional log file.
Parameters:
category_levels (Dict[str, int]): A dictionary mapping categories to their log levels.
log_file (str): Path to a log file to additionally pipe the logs into
"""
log_format = "%(asctime)s %(name)s:%(lineno)d %(category)s: %(message)s"
class CategoryFilter(logging.Filter):
"""Ensure category is always present in log records."""
def filter(self, record):
if not hasattr(record, "category"):
record.category = "uncategorized" # Default to 'uncategorized' if no category found
return True
# Determine the root logger's level (default to WARNING if not specified)
root_level = category_levels.get("root", logging.WARNING)
handlers = {
"console": {
"()": CustomRichHandler, # Use custom console handler
"formatter": "rich",
"rich_tracebacks": True,
"show_time": False,
"show_path": False,
"markup": True,
"filters": ["category_filter"],
}
}
# Add a file handler if log_file is set
if log_file:
handlers["file"] = {
"()": CustomFileHandler,
"filename": log_file,
"mode": "a",
"encoding": "utf-8",
}
logging_config = {
"version": 1,
"disable_existing_loggers": False,
"formatters": {
"rich": {
"()": logging.Formatter,
"format": log_format,
}
},
"handlers": handlers,
"filters": {
"category_filter": {
"()": CategoryFilter,
}
},
"loggers": {
category: {
"handlers": list(handlers.keys()), # Apply all handlers
"level": category_levels.get(category, DEFAULT_LOG_LEVEL),
"propagate": False, # Disable propagation to root logger
}
for category in CATEGORIES
},
"root": {
"handlers": list(handlers.keys()),
"level": root_level, # Set root logger's level dynamically
},
}
dictConfig(logging_config)
# Ensure third-party libraries follow the root log level
for _, logger in logging.root.manager.loggerDict.items():
if isinstance(logger, logging.Logger):
logger.setLevel(root_level)
def get_logger(
name: str, category: str = "uncategorized", config: LoggingConfig | None | None = None
) -> logging.LoggerAdapter:
"""
Returns a logger with the specified name and category.
If no category is provided, defaults to 'uncategorized'.
Parameters:
name (str): The name of the logger (e.g., module or filename).
category (str): The category of the logger (default 'uncategorized').
config (Logging): optional yaml config to override the existing logger configuration
Returns:
logging.LoggerAdapter: Configured logger with category support.
"""
if config:
_category_levels.update(parse_yaml_config(config))
logger = logging.getLogger(name)
logger.setLevel(_category_levels.get(category, DEFAULT_LOG_LEVEL))
return logging.LoggerAdapter(logger, {"category": category})
env_config = os.environ.get("LLAMA_STACK_LOGGING", "")
if env_config:
_category_levels.update(parse_environment_config(env_config))
log_file = os.environ.get("LLAMA_STACK_LOG_FILE")
setup_logging(_category_levels, log_file)