wehub-resource-sync
77 lines
2.9 KiB
Python
77 lines
2.9 KiB
Python
# Copyright (c) Microsoft. All rights reserved.
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import semantic_kernel.connectors.ai.open_ai as sk_oai
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from semantic_kernel.connectors.ai.prompt_execution_settings import PromptExecutionSettings
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from semantic_kernel.core_plugins.conversation_summary_plugin import ConversationSummaryPlugin
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from semantic_kernel.functions.kernel_arguments import KernelArguments
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from semantic_kernel.prompt_template.prompt_template_config import PromptTemplateConfig
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from tests.utils import retry
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CHAT_TRANSCRIPT = """John: Hello, how are you?
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Jane: I'm fine, thanks. How are you?
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John: I'm doing well, writing some example code.
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Jane: That's great! I'm writing some example code too.
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John: What are you writing?
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Jane: I'm writing a chatbot.
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John: That's cool. I'm writing a chatbot too.
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Jane: What language are you writing it in?
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John: I'm writing it in C#.
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Jane: I'm writing it in Python.
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John: That's cool. I need to learn Python.
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Jane: I need to learn C#.
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John: Can I try out your chatbot?
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Jane: Sure, here's the link.
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John: Thanks!
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Jane: You're welcome.
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Jane: Look at this poem my chatbot wrote:
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Jane: Roses are red
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Jane: Violets are blue
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Jane: I'm writing a chatbot
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Jane: What about you?
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John: That's cool. Let me see if mine will write a poem, too.
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John: Here's a poem my chatbot wrote:
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John: The singularity of the universe is a mystery.
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Jane: You might want to try using a different model.
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John: I'm using the GPT-2 model. That makes sense.
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John: Here is a new poem after updating the model.
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John: The universe is a mystery.
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John: The universe is a mystery.
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John: The universe is a mystery.
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Jane: Sure, what's the problem?
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John: Thanks for the help!
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Jane: I'm now writing a bot to summarize conversations.
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Jane: I have some bad news, we're only half way there.
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John: Maybe there is a large piece of text we can use to generate a long conversation.
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Jane: That's a good idea. Let me see if I can find one. Maybe Lorem Ipsum?
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John: Yeah, that's a good idea."""
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async def test_azure_summarize_conversation_using_plugin(kernel):
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service_id = "text_completion"
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execution_settings = PromptExecutionSettings(
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service_id=service_id, max_tokens=ConversationSummaryPlugin._max_tokens, temperature=0.1, top_p=0.5
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)
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prompt_template_config = PromptTemplateConfig(
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description="Given a section of a conversation transcript, summarize the part of the conversation.",
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execution_settings={service_id: execution_settings},
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)
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kernel.add_service(sk_oai.OpenAIChatCompletion(service_id=service_id))
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conversationSummaryPlugin = kernel.add_plugin(
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ConversationSummaryPlugin(prompt_template_config), "conversationSummary"
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)
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arguments = KernelArguments(input=CHAT_TRANSCRIPT)
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summary = await retry(
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lambda: kernel.invoke(conversationSummaryPlugin["SummarizeConversation"], arguments), retries=5
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)
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output = str(summary).strip().lower()
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print(output)
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assert "john" in output and "jane" in output
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assert len(output) < len(CHAT_TRANSCRIPT)
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