경고
의미 체계 커널 프로세스 프레임워크 아직 개발 중이며 변경될 수 있습니다.
개요
이전 섹션에서는 새 제품에 대한 설명서 생성을 자동화하는 데 도움이 되는 간단한 프로세스를 빌드했습니다. 이 섹션에서는 교정 단계를 추가하여 해당 프로세스를 개선합니다. 이 단계에서는 LLM을 사용하여 생성된 설명서를 통과/실패로 채점하고 필요한 경우 권장 변경 내용을 제공합니다. 프로세스 프레임워크의 주기 지원을 활용하여 한 단계 더 나아가 권장되는 변경 내용(있는 경우)을 자동으로 적용한 다음, 반복을 시작하여 콘텐츠가 품질 표시줄을 충족할 때까지 반복할 수 있습니다. 업데이트된 프로세스는 다음과 같습니다.
프로세스 업데이트
새 교정 관리자 단계를 만들고 필요한 경우 제안을 적용할 수 있도록 문서 생성 단계를 몇 가지 변경해야 합니다.
교정 단계 추가
// A process step to proofread documentation
public class ProofreadStep : KernelProcessStep
{
[KernelFunction]
public async Task ProofreadDocumentationAsync(Kernel kernel, KernelProcessStepContext context, string documentation)
{
Console.WriteLine($"{nameof(ProofreadDocumentationAsync)}:\n\tProofreading documentation...");
var systemPrompt =
"""
Your job is to proofread customer facing documentation for a new product from Contoso. You will be provide with proposed documentation
for a product and you must do the following things:
1. Determine if the documentation is passes the following criteria:
1. Documentation must use a professional tone.
1. Documentation should be free of spelling or grammar mistakes.
1. Documentation should be free of any offensive or inappropriate language.
1. Documentation should be technically accurate.
2. If the documentation does not pass 1, you must write detailed feedback of the changes that are needed to improve the documentation.
""";
ChatHistory chatHistory = new ChatHistory(systemPrompt);
chatHistory.AddUserMessage(documentation);
// Use structured output to ensure the response format is easily parsable
OpenAIPromptExecutionSettings settings = new OpenAIPromptExecutionSettings();
settings.ResponseFormat = typeof(ProofreadingResponse);
IChatCompletionService chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();
var proofreadResponse = await chatCompletionService.GetChatMessageContentAsync(chatHistory, executionSettings: settings);
var formattedResponse = JsonSerializer.Deserialize<ProofreadingResponse>(proofreadResponse.Content!.ToString());
Console.WriteLine($"\n\tGrade: {(formattedResponse!.MeetsExpectations ? "Pass" : "Fail")}\n\tExplanation: {formattedResponse.Explanation}\n\tSuggestions: {string.Join("\n\t\t", formattedResponse.Suggestions)}");
if (formattedResponse.MeetsExpectations)
{
await context.EmitEventAsync("DocumentationApproved", data: documentation);
}
else
{
await context.EmitEventAsync("DocumentationRejected", data: new { Explanation = formattedResponse.Explanation, Suggestions = formattedResponse.Suggestions});
}
}
// A class
private class ProofreadingResponse
{
[Description("Specifies if the proposed documentation meets the expected standards for publishing.")]
public bool MeetsExpectations { get; set; }
[Description("An explanation of why the documentation does or does not meet expectations.")]
public string Explanation { get; set; } = "";
[Description("A lis of suggestions, may be empty if there no suggestions for improvement.")]
public List<string> Suggestions { get; set; } = new();
}
}
ProofreadStep 새 단계가 만들어졌습니다. 이 단계에서는 LLM을 사용하여 위에서 설명한 대로 생성된 설명서를 채점합니다. 이 단계에서는 LLM의 응답에 따라 DocumentationApproved 이벤트 또는 DocumentationRejected 이벤트를 조건부로 내보낸다.
DocumentationApproved경우 이벤트는 승인된 설명서를 페이로드로 포함하며, DocumentationRejected 경우 교정 관리자의 제안이 포함됩니다.
# A sample response model for the ProofreadingStep structured output
class ProofreadingResponse(BaseModel):
"""A class to represent the response from the proofreading step."""
meets_expectations: bool = Field(description="Specifies if the proposed docs meets the standards for publishing.")
explanation: str = Field(description="An explanation of why the documentation does or does not meet expectations.")
suggestions: list[str] = Field(description="List of suggestions, empty if there are no suggestions for improvement.")
# A process step to proofread documentation
class ProofreadStep(KernelProcessStep):
@kernel_function
async def proofread_documentation(self, docs: str, context: KernelProcessStepContext, kernel: Kernel) -> None:
print(f"{ProofreadStep.__name__}\n\t Proofreading product documentation...")
system_prompt = """
Your job is to proofread customer facing documentation for a new product from Contoso. You will be provided with
proposed documentation for a product and you must do the following things:
1. Determine if the documentation passes the following criteria:
1. Documentation must use a professional tone.
1. Documentation should be free of spelling or grammar mistakes.
1. Documentation should be free of any offensive or inappropriate language.
1. Documentation should be technically accurate.
2. If the documentation does not pass 1, you must write detailed feedback of the changes that are needed to
improve the documentation.
"""
chat_history = ChatHistory(system_message=system_prompt)
chat_history.add_user_message(docs)
# Use structured output to ensure the response format is easily parsable
chat_service, settings = kernel.select_ai_service(type=ChatCompletionClientBase)
assert isinstance(chat_service, ChatCompletionClientBase) # nosec
assert isinstance(settings, OpenAIChatPromptExecutionSettings) # nosec
settings.response_format = ProofreadingResponse
response = await chat_service.get_chat_message_content(chat_history=chat_history, settings=settings)
formatted_response: ProofreadingResponse = ProofreadingResponse.model_validate_json(response.content)
suggestions_text = "\n\t\t".join(formatted_response.suggestions)
print(
f"\n\tGrade: {'Pass' if formatted_response.meets_expectations else 'Fail'}\n\t"
f"Explanation: {formatted_response.explanation}\n\t"
f"Suggestions: {suggestions_text}"
)
if formatted_response.meets_expectations:
await context.emit_event(process_event="documentation_approved", data=docs)
else:
await context.emit_event(
process_event="documentation_rejected",
data={"explanation": formatted_response.explanation, "suggestions": formatted_response.suggestions},
)
ProofreadStep 새 단계가 만들어졌습니다. 이 단계에서는 LLM을 사용하여 위에서 설명한 대로 생성된 설명서를 채점합니다. 이 단계에서는 LLM의 응답에 따라 documentation_approved 이벤트 또는 documentation_rejected 이벤트를 조건부로 내보낸다.
documentation_approved경우 이벤트는 승인된 설명서를 페이로드로 포함하며, documentation_rejected 경우 교정 관리자의 제안이 포함됩니다.
설명서 생성 단계 업데이트
// Updated process step to generate and edit documentation for a product
public class GenerateDocumentationStep : KernelProcessStep<GeneratedDocumentationState>
{
private GeneratedDocumentationState _state = new();
private string systemPrompt =
"""
Your job is to write high quality and engaging customer facing documentation for a new product from Contoso. You will be provide with information
about the product in the form of internal documentation, specs, and troubleshooting guides and you must use this information and
nothing else to generate the documentation. If suggestions are provided on the documentation you create, take the suggestions into account and
rewrite the documentation. Make sure the product sounds amazing.
""";
override public ValueTask ActivateAsync(KernelProcessStepState<GeneratedDocumentationState> state)
{
this._state = state.State!;
this._state.ChatHistory ??= new ChatHistory(systemPrompt);
return base.ActivateAsync(state);
}
[KernelFunction]
public async Task GenerateDocumentationAsync(Kernel kernel, KernelProcessStepContext context, string productInfo)
{
Console.WriteLine($"{nameof(GenerateDocumentationStep)}:\n\tGenerating documentation for provided productInfo...");
// Add the new product info to the chat history
this._state.ChatHistory!.AddUserMessage($"Product Info:\n\n{productInfo}");
// Get a response from the LLM
IChatCompletionService chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();
var generatedDocumentationResponse = await chatCompletionService.GetChatMessageContentAsync(this._state.ChatHistory!);
await context.EmitEventAsync("DocumentationGenerated", generatedDocumentationResponse.Content!.ToString());
}
[KernelFunction]
public async Task ApplySuggestionsAsync(Kernel kernel, KernelProcessStepContext context, string suggestions)
{
Console.WriteLine($"{nameof(GenerateDocumentationStep)}:\n\tRewriting documentation with provided suggestions...");
// Add the new product info to the chat history
this._state.ChatHistory!.AddUserMessage($"Rewrite the documentation with the following suggestions:\n\n{suggestions}");
// Get a response from the LLM
IChatCompletionService chatCompletionService = kernel.GetRequiredService<IChatCompletionService>();
var generatedDocumentationResponse = await chatCompletionService.GetChatMessageContentAsync(this._state.ChatHistory!);
await context.EmitEventAsync("DocumentationGenerated", generatedDocumentationResponse.Content!.ToString());
}
public class GeneratedDocumentationState
{
public ChatHistory? ChatHistory { get; set; }
}
}
GenerateDocumentationStep 새 KernelFunction을 포함하도록 업데이트되었습니다. 교정 단계에서 필요한 경우 새 함수를 사용하여 설명서에 제안된 변경 내용을 적용합니다. 설명서를 생성하거나 다시 쓰기 위한 두 함수는 새 설명서를 사용할 수 있음을 나타내는 DocumentationGenerated 동일한 이벤트를 내보낸다.
# Updated process step to generate and edit documentation for a product
class GenerateDocumentationStep(KernelProcessStep[GeneratedDocumentationState]):
state: GeneratedDocumentationState = Field(default_factory=GeneratedDocumentationState)
system_prompt: ClassVar[str] = """
Your job is to write high quality and engaging customer facing documentation for a new product from Contoso. You will
be provided with information about the product in the form of internal documentation, specs, and troubleshooting guides
and you must use this information and nothing else to generate the documentation. If suggestions are provided on the
documentation you create, take the suggestions into account and rewrite the documentation. Make sure the product
sounds amazing.
"""
async def activate(self, state: KernelProcessStepState[GeneratedDocumentationState]):
self.state = state.state
if self.state.chat_history is None:
self.state.chat_history = ChatHistory(system_message=self.system_prompt)
self.state.chat_history
@kernel_function
async def generate_documentation(
self, context: KernelProcessStepContext, product_info: str, kernel: Kernel
) -> None:
print(f"{GenerateDocumentationStep.__name__}\n\t Generating documentation for provided product_info...")
self.state.chat_history.add_user_message(f"Product Information:\n{product_info}")
chat_service, settings = kernel.select_ai_service(type=ChatCompletionClientBase)
assert isinstance(chat_service, ChatCompletionClientBase) # nosec
response = await chat_service.get_chat_message_content(chat_history=self.state.chat_history, settings=settings)
await context.emit_event(process_event="documentation_generated", data=str(response))
@kernel_function
async def apply_suggestions(self, suggestions: str, context: KernelProcessStepContext, kernel: Kernel) -> None:
print(f"{GenerateDocumentationStep.__name__}\n\t Rewriting documentation with provided suggestions...")
self.state.chat_history.add_user_message(
f"Rewrite the documentation with the following suggestions:\n\n{suggestions}"
)
chat_service, settings = kernel.select_ai_service(type=ChatCompletionClientBase)
assert isinstance(chat_service, ChatCompletionClientBase) # nosec
generated_documentation_response = await chat_service.get_chat_message_content(
chat_history=self.state.chat_history, settings=settings
)
await context.emit_event(process_event="documentation_generated", data=str(generated_documentation_response))
GenerateDocumentationStep 새 KernelFunction을 포함하도록 업데이트되었습니다. 교정 단계에서 필요한 경우 새 함수를 사용하여 설명서에 제안된 변경 내용을 적용합니다. 설명서를 생성하거나 다시 쓰기 위한 두 함수는 새 설명서를 사용할 수 있음을 나타내는 documentation_generated 동일한 이벤트를 내보낸다.
흐름 업데이트
// Create the process builder
ProcessBuilder processBuilder = new("DocumentationGeneration");
// Add the steps
var infoGatheringStep = processBuilder.AddStepFromType<GatherProductInfoStep>();
var docsGenerationStep = processBuilder.AddStepFromType<GenerateDocumentationStepV2>();
var docsProofreadStep = processBuilder.AddStepFromType<ProofreadStep>(); // Add new step here
var docsPublishStep = processBuilder.AddStepFromType<PublishDocumentationStep>();
// Orchestrate the events
processBuilder
.OnInputEvent("Start")
.SendEventTo(new(infoGatheringStep));
infoGatheringStep
.OnFunctionResult()
.SendEventTo(new(docsGenerationStep, functionName: "GenerateDocumentation"));
docsGenerationStep
.OnEvent("DocumentationGenerated")
.SendEventTo(new(docsProofreadStep));
docsProofreadStep
.OnEvent("DocumentationRejected")
.SendEventTo(new(docsGenerationStep, functionName: "ApplySuggestions"));
docsProofreadStep
.OnEvent("DocumentationApproved")
.SendEventTo(new(docsPublishStep));
var process = processBuilder.Build();
return process;
업데이트된 프로세스 라우팅은 이제 다음을 수행합니다.
- 외부 이벤트가
id = Start과 함께 프로세스로 전송되면, 이 이벤트와 관련 데이터는infoGatheringStep로 전송됩니다. - 실행이
infoGatheringStep완료되면 반환된 개체를docsGenerationStep에 보냅니다. -
docsGenerationStep의 실행이 완료되면 생성된 문서를docsProofreadStep에 보냅니다. -
docsProofreadStep설명서를 거부하고 제안을 제공하면 제안을 다시docsGenerationStep보냅니다. - 마침내, 문서
docsProofreadStep가 승인될 때 반환된 객체를docsPublishStep에 보냅니다.
# Create the process builder
process_builder = ProcessBuilder(name="DocumentationGeneration")
# Add the steps
info_gathering_step = process_builder.add_step(GatherProductInfoStep)
docs_generation_step = process_builder.add_step(GenerateDocumentationStep)
docs_proofread_step = process_builder.add_step(ProofreadStep) # Add new step here
docs_publish_step = process_builder.add_step(PublishDocumentationStep)
# Orchestrate the events
process_builder.on_input_event("Start").send_event_to(target=info_gathering_step)
info_gathering_step.on_function_result().send_event_to(
target=docs_generation_step, function_name="generate_documentation", parameter_name="product_info"
)
docs_generation_step.on_event("documentation_generated").send_event_to(
target=docs_proofread_step, parameter_name="docs"
)
docs_proofread_step.on_event("documentation_rejected").send_event_to(
target=docs_generation_step,
function_name="apply_suggestions",
parameter_name="suggestions",
)
docs_proofread_step.on_event("documentation_approved").send_event_to(target=docs_publish_step)
업데이트된 프로세스 라우팅은 이제 다음을 수행합니다.
- 외부 이벤트가
id = Start과 함께 프로세스로 전송되면, 이 이벤트와 관련 데이터는info_gathering_step로 전송됩니다. - 실행이
info_gathering_step완료되면 반환된 개체를docs_generation_step에 보냅니다. - 실행이
docs_generation_step완료되면 생성된 문서를docs_proofread_step에 보냅니다. -
docs_proofread_step설명서를 거부하고 제안을 제공하면 제안을 다시docs_generation_step보냅니다. - 마지막으로
docs_proofread_step이 문서를 승인하면 반환된 개체를docs_publish_step에 보냅니다.
프로세스 빌드 및 실행
업데이트된 프로세스를 실행하면 콘솔에서 다음 출력이 표시됩니다.
GatherProductInfoStep:
Gathering product information for product named Contoso GlowBrew
GenerateDocumentationStep:
Generating documentation for provided productInfo...
ProofreadDocumentationAsync:
Proofreading documentation...
Grade: Fail
Explanation: The proposed documentation has an overly casual tone and uses informal expressions that might not suit all customers. Additionally, some phrases may detract from the professionalism expected in customer-facing documentation. There are minor areas that could benefit from clarity and conciseness.
Suggestions: Adjust the tone to be more professional and less casual; phrases like 'dazzling light show' and 'coffee performing' could be simplified.
Remove informal phrases such as 'who knew coffee could be so... illuminating?'
Consider editing out overly whimsical phrases like 'it's like a warm hug for your nose!' for a more straightforward description.
Clarify the troubleshooting section for better customer understanding; avoid metaphorical language like 'secure that coffee cup when you realize Monday is still a thing.'
GenerateDocumentationStep:
Rewriting documentation with provided suggestions...
ProofreadDocumentationAsync:
Proofreading documentation...
Grade: Fail
Explanation: The documentation generally maintains a professional tone but contains minor phrasing issues that could be improved. There are no spelling or grammar mistakes noted, and it excludes any offensive language. However, the content could be more concise, and some phrases can be streamlined for clarity. Additionally, technical accuracy regarding troubleshooting solutions may require more details for the user's understanding. For example, clarifying how to 'reset the lighting settings through the designated app' would enhance user experience.
Suggestions: Rephrase 'Join us as we elevate your coffee experience to new heights!' to make it more straightforward, such as 'Experience an elevated coffee journey with us.'
In the 'Solution' section for the LED lights malfunction, add specific instructions on how to find and use the 'designated app' for resetting the lighting settings.
Consider simplifying sentences such as 'Meet your new personal barista!' to be more straightforward, for example, 'Introducing your personal barista.'
Ensure clarity in troubleshooting steps by elaborating on what a 'factory reset' entails.
GenerateDocumentationStep:
Rewriting documentation with provided suggestions...
ProofreadDocumentationAsync:
Proofreading documentation...
Grade: Pass
Explanation: The documentation presents a professional tone, contains no spelling or grammar mistakes, is free of offensive language, and is technically accurate regarding the product's features and troubleshooting guidance.
Suggestions:
PublishDocumentationStep:
Publishing product documentation:
# GlowBrew User Documentation
## Product Overview
Introducing GlowBrew-your new partner in coffee brewing that brings together advanced technology and aesthetic appeal. This innovative AI-driven coffee machine not only brews your favorite coffee but also features the industry's leading number of customizable LEDs and programmable light shows.
## Key Features
1. **Luminous Brew Technology**: Transform your morning routine with our customizable LED lights that synchronize with your brewing process, creating the perfect ambiance to start your day.
2. **AI Taste Assistant**: Our intelligent system learns your preferences over time, recommending exciting new brew combinations tailored to your unique taste.
3. **Gourmet Aroma Diffusion**: Experience an enhanced aroma with built-in aroma diffusers that elevate your coffee's scent profile, invigorating your senses before that all-important first sip.
## Troubleshooting
### Issue: LED Lights Malfunctioning
**Solution**:
- Begin by resetting the lighting settings via the designated app. Open the app, navigate to the settings menu, and select "Reset LED Lights."
- Ensure that all LED connections inside the GlowBrew are secure and properly connected.
- If issues persist, you may consider performing a factory reset. To do this, hold down the reset button located on the machine's back panel for 10 seconds while the device is powered on.
We hope you enjoy your GlowBrew experience and that it brings a delightful blend of flavor and brightness to your coffee moments!
GatherProductInfoStep
Gathering product information for Product Name: Contoso GlowBrew
GenerateDocumentationStep
Generating documentation for provided product_info...
ProofreadStep
Proofreading product documentation...
Grade: Pass
Explanation: The GlowBrew AI Coffee Machine User Guide meets all the required criteria for publishing. The document maintains a professional tone throughout, is free from spelling and grammatical errors, contains no offensive or inappropriate content, and appears to be technically accurate in its description of the product features and troubleshooting advice.
Suggestions:
PublishDocumentationStep
Publishing product documentation:
# GlowBrew AI Coffee Machine User Guide
Welcome to the future of coffee making with the GlowBrew AI Coffee Machine! Step into a world where cutting-edge technology meets exquisite taste, creating a coffee experience like no other. Designed for coffee aficionados and tech enthusiasts alike, the GlowBrew promises not just a cup of coffee, but an adventure for your senses.
## Key Features
### Luminous Brew Technology
Illuminate your mornings with the GlowBrew's mesmerizing programmable LED light shows. With an unmatched number of LEDs, the GlowBrew can transform your kitchen ambiance to sync perfectly with each stage of the brewing process. Choose from a spectrum of colors and patterns to set the perfect mood, whether you're winding down with a rich decaf or kick-starting your day with a bold espresso.
### AI Taste Assistant
Expand your coffee horizons with the AI Taste Assistant, your personal barista that learns and evolves with your palate. Over time, GlowBrew adapts to your preferences, suggesting new and exciting brew combinations. Experience a variety of flavors, from single-origin specialties to intricate blend recipes, tailored to your unique taste.
### Gourmet Aroma Diffusion
Enhance your coffee experience with unrivaled aromatic pleasure. The GlowBrew's built-in aroma diffusers release a carefully calibrated scent profile that awakens your senses, heightening anticipation for your first sip. It's not just a coffee machine, it's an indulgent sensory journey.
## Troubleshooting
### LED Lights Malfunctioning
If you experience issues with your LED lights:
1. **Reset the LED Settings**: Use the GlowBrew app to navigate to the lighting settings and perform a reset.
2. **Check LED Connections**: Open the GlowBrew machine and ensure all LED wiring connections are secure.
3. **Perform a Factory Reset**: As a last resort, a full factory reset can resolve persistent issues. Follow the instructions in the user manual to perform this reset safely.
## Experience the Glow
With GlowBrew, every cup of coffee is an art form that combines luminous aesthetics, an intuitive learning AI, and the intoxicating allure of rich aromas. Make each morning magical and every break a celebration with the GlowBrew AI Coffee Machine. Brew brilliantly, taste innovatively, and glow endlessly.
For more support, explore our comprehensive FAQ section or contact our dedicated customer service team.
다음 단계는 무엇인가요?
이제 프로세스는 정의된 표준을 충족하는 문서를 안정적으로 생성합니다. 이것은 훌륭하지만 문서를 공개적으로 게시하기 전에 실제로 사람이 검토하고 승인하도록 요구해야합니다. 다음으로 수행해 보겠습니다.