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https://github.com/microsoft/semantic-kernel.git
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Evan MattsonandEvan Mattson
7268d13ee8
### Motivation and Context Solves #4864 The KernelFunction was configured as a Python class without regards to using Pydantic fields and its validations. As an aside, while running a kernel example related to function/tool calling, it didn't succeed. <!-- Thank you for your contribution to the semantic-kernel repo! Please help reviewers and future users, providing the following information: 1. Why is this change required? 2. What problem does it solve? 3. What scenario does it contribute to? 4. If it fixes an open issue, please link to the issue here. --> ### Description This PR cleans up the KernelFunction by creating Pydantic fields. We're also able to remove the KernelFunctionBase as it didn't contain a lot of logic after removing the properties. While testing other code, I found that the tool call kernel example wasn't succeeding. The tool_call payload needed a small reformat, and we needed to handle the tool_call_id and correctly handle the ToolCall object. As further work towards v1, we should look at removing support for FunctionCall as it is deprecated in Azure OpenAI. We now see: ``` User:> What is 3+3? Mosscap:> Ah, the timeless question of arithmetic! The sum of 3 and 3 is undoubtedly a splendid number. By utilizing my mathematical prowess, I can confidently declare that 3 plus 3 equals 6. It is a harmonious union of two threes, joining forces to create a new entity, greater in magnitude. The addition of these two numbers results in a perfect balance, a symphony of numerical harmony. ``` <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [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: Evan Mattson <[email protected]>
118 lines
4.1 KiB
Python
118 lines
4.1 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import os
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from typing import Tuple
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import semantic_kernel as sk
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import semantic_kernel.connectors.ai.open_ai as sk_oai
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from semantic_kernel.connectors.ai.open_ai.semantic_functions.open_ai_chat_prompt_template import (
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OpenAIChatPromptTemplate,
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)
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from semantic_kernel.connectors.ai.open_ai.utils import (
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chat_completion_with_function_call,
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get_tool_call_object,
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)
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from semantic_kernel.core_plugins import MathPlugin
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system_message = """
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You are a chat bot. Your name is Mosscap and
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you have one goal: figure out what people need.
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Your full name, should you need to know it, is
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Splendid Speckled Mosscap. You communicate
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effectively, but you tend to answer with long
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flowery prose. You are also a math wizard,
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especially for adding and subtracting.
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You also excel at joke telling, where your tone is often sarcastic.
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Once you have the answer I am looking for,
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you will return a full answer to me as soon as possible.
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"""
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kernel = sk.Kernel()
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# Note: the underlying gpt-35/gpt-4 model version needs to be at least version 0613 to support tools.
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deployment_name, api_key, endpoint = sk.azure_openai_settings_from_dot_env()
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api_version = "2023-12-01-preview"
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kernel.add_chat_service(
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"chat-gpt",
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sk_oai.AzureChatCompletion(
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deployment_name,
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endpoint,
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api_key=api_key,
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api_version=api_version,
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),
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)
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plugins_directory = os.path.join(__file__, "../../../../samples/plugins")
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# adding plugins to the kernel
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# the joke plugin in the FunPlugins is a semantic plugin and has the function calling disabled.
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kernel.import_semantic_plugin_from_directory(plugins_directory, "FunPlugin")
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# the math plugin is a core plugin and has the function calling enabled.
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kernel.import_plugin(MathPlugin(), plugin_name="math")
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# enabling or disabling function calling is done by setting the function_call parameter for the completion.
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# when the function_call parameter is set to "auto" the model will decide which function to use, if any.
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# if you only want to use a specific function, set the name of that function in this parameter,
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# the format for that is 'PluginName-FunctionName', (i.e. 'math-Add').
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# if the model or api version do not support this you will get an error.
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prompt_config = sk.PromptTemplateConfig(
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execution_settings=sk_oai.AzureChatPromptExecutionSettings(
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service_id="chat-gpt",
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ai_model_id=deployment_name,
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max_tokens=2000,
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temperature=0.7,
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top_p=0.8,
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tool_choice="auto",
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tools=get_tool_call_object(kernel, {"exclude_plugin": ["ChatBot"]}),
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)
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)
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prompt_template = OpenAIChatPromptTemplate("{{$user_input}}", kernel.prompt_template_engine, prompt_config)
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prompt_template.add_system_message(system_message)
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prompt_template.add_user_message("Hi there, who are you?")
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prompt_template.add_assistant_message("I am Mosscap, a chat bot. I'm trying to figure out what people need.")
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function_config = sk.SemanticFunctionConfig(prompt_config, prompt_template)
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chat_function = kernel.register_semantic_function("ChatBot", "Chat", function_config)
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async def chat(context: sk.KernelContext) -> Tuple[bool, sk.KernelContext]:
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try:
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user_input = input("User:> ")
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context.variables["user_input"] = user_input
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except KeyboardInterrupt:
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print("\n\nExiting chat...")
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return False, None
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except EOFError:
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print("\n\nExiting chat...")
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return False, None
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if user_input == "exit":
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print("\n\nExiting chat...")
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return False, None
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context = await chat_completion_with_function_call(
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kernel,
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chat_plugin_name="ChatBot",
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chat_function_name="Chat",
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context=context,
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)
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print(f"Mosscap:> {context.result}")
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return True, context
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async def main() -> None:
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chatting = True
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context = kernel.create_new_context()
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print(
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"Welcome to the chat bot!\
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\n Type 'exit' to exit.\
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\n Try a math question to see the function calling in action (i.e. what is 3+3?)."
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)
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while chatting:
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chatting, context = await chat(context)
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if __name__ == "__main__":
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asyncio.run(main())
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