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https://github.com/microsoft/semantic-kernel.git
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Python: Uses Python standard logging (#4115)
### Motivation and Context This replaces passing Logger instances as arguments around with the preferred Python way of having each module define a module-wide `logger` instance at the top of the module. Fixes #3711 ### Description Removes any `log` argument and argument documentation. Replaces usage of those `log` arguments with the module-wide `logger` instance. ### Contribution Checklist - [x] The code builds clean without any errors or warnings - [x] The PR follows the [SK Contribution Guidelines](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md) and the [pre-submission formatting script](https://github.com/microsoft/semantic-kernel/blob/main/CONTRIBUTING.md#development-scripts) raises no violations - [x] All unit tests pass, and I have added new tests where possible - [x] I didn't break anyone 😄 --------- Co-authored-by: Eduard van Valkenburg <[email protected]>
This commit is contained in:
Julio Carlos Menendez
co-authored by
Eduard van Valkenburg
Eduard van Valkenburg
parent
24a099965e
commit
d3dd5c8e7e
@@ -3,8 +3,8 @@
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import glob
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import importlib
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import inspect
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import logging
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import os
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from logging import Logger
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from typing import Any, Callable, Dict, List, Optional, Type, TypeVar, Union
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from uuid import uuid4
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@@ -53,14 +53,14 @@ from semantic_kernel.template_engine.prompt_template_engine import PromptTemplat
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from semantic_kernel.template_engine.protocols.prompt_templating_engine import (
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PromptTemplatingEngine,
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)
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from semantic_kernel.utils.null_logger import NullLogger
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from semantic_kernel.utils.validation import validate_function_name, validate_skill_name
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T = TypeVar("T")
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logger: logging.Logger = logging.getLogger(__name__)
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class Kernel:
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_log: Logger
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_skill_collection: SkillCollectionBase
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_prompt_template_engine: PromptTemplatingEngine
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_memory: SemanticTextMemoryBase
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@@ -70,16 +70,17 @@ class Kernel:
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skill_collection: Optional[SkillCollectionBase] = None,
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prompt_template_engine: Optional[PromptTemplatingEngine] = None,
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memory: Optional[SemanticTextMemoryBase] = None,
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log: Optional[Logger] = None,
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log: Optional[Any] = None,
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) -> None:
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self._log = log if log else NullLogger()
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if log:
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logger.warning(
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"The `log` parameter is deprecated. Please use the `logging` module instead."
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)
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self._skill_collection = (
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skill_collection if skill_collection else SkillCollection(self._log)
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skill_collection if skill_collection else SkillCollection()
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)
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self._prompt_template_engine = (
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prompt_template_engine
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if prompt_template_engine
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else PromptTemplateEngine(self._log)
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prompt_template_engine if prompt_template_engine else PromptTemplateEngine()
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)
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self._memory = memory if memory else NullMemory()
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@@ -102,10 +103,6 @@ class Kernel:
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self._function_invoking_handlers = {}
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self._function_invoked_handlers = {}
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@property
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def logger(self) -> Logger:
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return self._log
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@property
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def memory(self) -> SemanticTextMemoryBase:
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return self._memory
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@@ -157,7 +154,7 @@ class Kernel:
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validate_skill_name(skill_name)
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validate_function_name(function_name)
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function = SKFunction.from_native_method(sk_function, skill_name, self.logger)
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function = SKFunction.from_native_method(sk_function, skill_name)
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if self.skills.has_function(skill_name, function_name):
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raise KernelException(
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@@ -222,7 +219,6 @@ class Kernel:
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variables,
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self._memory,
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self._skill_collection.read_only_skill_collection,
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self._log,
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)
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else:
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raise ValueError("No functions passed to run")
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@@ -237,7 +233,7 @@ class Kernel:
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except Exception as ex:
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# TODO: "critical exceptions"
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self._log.error(
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logger.error(
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"Something went wrong in stream function. During function invocation:"
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f" '{stream_function.skill_name}.{stream_function.name}'. Error"
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f" description: '{str(ex)}'"
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@@ -286,7 +282,6 @@ class Kernel:
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variables,
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self._memory,
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self._skill_collection.read_only_skill_collection,
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self._log,
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)
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pipeline_step = 0
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@@ -298,7 +293,7 @@ class Kernel:
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)
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if context.error_occurred:
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self._log.error(
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logger.error(
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f"Something went wrong in pipeline step {pipeline_step}. "
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f"Error description: '{context.last_error_description}'"
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)
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@@ -315,7 +310,7 @@ class Kernel:
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and function_invoking_args.is_cancel_requested
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):
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cancel_message = "Execution was cancelled on function invoking event of pipeline step"
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self._log.info(
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logger.info(
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f"{cancel_message} {pipeline_step}: {func.skill_name}.{func.name}."
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)
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return context
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@@ -325,7 +320,7 @@ class Kernel:
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and function_invoking_args.is_skip_requested
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):
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skip_message = "Execution was skipped on function invoking event of pipeline step"
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self._log.info(
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logger.info(
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f"{skip_message} {pipeline_step}: {func.skill_name}.{func.name}."
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)
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break
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@@ -335,7 +330,7 @@ class Kernel:
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)
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if context.error_occurred:
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self._log.error(
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logger.error(
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f"Something went wrong in pipeline step {pipeline_step}. "
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f"During function invocation: '{func.skill_name}.{func.name}'. "
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f"Error description: '{context.last_error_description}'"
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@@ -351,7 +346,7 @@ class Kernel:
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and function_invoked_args.is_cancel_requested
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):
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cancel_message = "Execution was cancelled on function invoked event of pipeline step"
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self._log.info(
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logger.info(
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f"{cancel_message} {pipeline_step}: {func.skill_name}.{func.name}."
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)
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return context
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@@ -360,7 +355,7 @@ class Kernel:
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and function_invoked_args.is_repeat_requested
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):
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repeat_message = "Execution was repeated on function invoked event of pipeline step"
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self._log.info(
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logger.info(
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f"{repeat_message} {pipeline_step}: {func.skill_name}.{func.name}."
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)
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continue
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@@ -368,7 +363,7 @@ class Kernel:
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break
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except Exception as ex:
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self._log.error(
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logger.error(
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f"Something went wrong in pipeline step {pipeline_step}. "
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f"During function invocation: '{func.skill_name}.{func.name}'. "
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f"Error description: '{str(ex)}'"
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@@ -422,7 +417,6 @@ class Kernel:
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ContextVariables() if not variables else variables,
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self._memory,
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self.skills,
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self._log,
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)
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def on_function_invoking(
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@@ -450,9 +444,9 @@ class Kernel:
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) -> Dict[str, SKFunctionBase]:
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if skill_name.strip() == "":
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skill_name = SkillCollection.GLOBAL_SKILL
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self._log.debug(f"Importing skill {skill_name} into the global namespace")
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logger.debug(f"Importing skill {skill_name} into the global namespace")
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else:
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self._log.debug(f"Importing skill {skill_name}")
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logger.debug(f"Importing skill {skill_name}")
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functions = []
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@@ -466,11 +460,9 @@ class Kernel:
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if not hasattr(candidate, "__sk_function__"):
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continue
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functions.append(
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SKFunction.from_native_method(candidate, skill_name, self.logger)
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)
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functions.append(SKFunction.from_native_method(candidate, skill_name))
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self.logger.debug(f"Methods imported: {len(functions)}")
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logger.debug(f"Methods imported: {len(functions)}")
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# Uniqueness check on function names
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function_names = [f.name for f in functions]
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