mirror of
https://github.com/microsoft/semantic-kernel.git
synced 2026-10-12 02:19:06 +00:00
Jordan Henkel
407fb36e59
### Motivation and Context The `python-preview` branch is under active development and many docs/tests/examples are getting a bit out of sync. There are also a few small cleanup chores/refactors to make _usage_ easier (e.g., to make examples cleaner). I've grouped these small fixes (plus a few bug fixes) into this "cleanup" PR. ### Description This PR does the following: 1. Updates the out-of-date example in `README.md` 2. Fixes all 5 of the notebooks we support right now (1,2,3,4, and 6; notebook 5 is planner, I've blanked out most of the code there so we don't confuse people, especially as the planner API is changing) 3. Fixes a bug w/ `stop_sequences` in `(Azure)OpenAITextCompletion` 4. Fixes a bug introduced in our upgrades to the embeddings cosine-sim check (we should add more thorough tests here) 5. Cleans up tests 6. Ensures end-to-end tests are all runnable 7. Fixes up the `kernel_extensions` to work more naturally (so that end users can use them directly on the `kernel` object and get good type-hinting)
71 lines
2.2 KiB
Python
71 lines
2.2 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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from typing import TYPE_CHECKING, List, Optional
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from uuid import uuid4
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from semantic_kernel.diagnostics.verify import Verify
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from semantic_kernel.kernel_extensions.extends_kernel import ExtendsKernel
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from semantic_kernel.semantic_functions.prompt_template import PromptTemplate
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from semantic_kernel.semantic_functions.prompt_template_config import (
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PromptTemplateConfig,
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)
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from semantic_kernel.semantic_functions.semantic_function_config import (
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SemanticFunctionConfig,
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)
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if TYPE_CHECKING:
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from semantic_kernel.orchestration.sk_function_base import SKFunctionBase
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class InlineDefinition(ExtendsKernel):
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def create_semantic_function(
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self,
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prompt_template: str,
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function_name: Optional[str] = None,
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skill_name: Optional[str] = None,
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description: Optional[str] = None,
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max_tokens: int = 256,
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temperature: float = 0.0,
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top_p: float = 1.0,
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presence_penalty: float = 0.0,
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frequency_penalty: float = 0.0,
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stop_sequences: Optional[List[str]] = None,
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) -> "SKFunctionBase":
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kernel = self.kernel()
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function_name = (
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function_name
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if function_name is not None
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else f"f_{str(uuid4()).replace('-', '_')}"
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)
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config = PromptTemplateConfig(
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description=(
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description
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if description is not None
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else "Generic function, unknown purpose"
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),
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type="completion",
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completion=PromptTemplateConfig.CompletionConfig(
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temperature,
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top_p,
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presence_penalty,
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frequency_penalty,
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max_tokens,
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stop_sequences if stop_sequences is not None else [],
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),
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)
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Verify.valid_function_name(function_name)
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if skill_name is not None:
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Verify.valid_skill_name(skill_name)
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template = PromptTemplate(
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prompt_template, kernel.prompt_template_engine, config
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)
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function_config = SemanticFunctionConfig(config, template)
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return kernel.register_semantic_function(
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skill_name, function_name, function_config
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)
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