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Python : Adding Sample for Azure Cognitive Search Memory (microsoft#2510)
### Motivation and Context This PR resolves microsoft#2493 ### Description The ACS implementation is different from VoltalileMemoryStore and we don't have any samples for Azure Cognitive Search Memory Store. I want to add Python Sample for using AzureCognitiveSearchMemoryStore with OpenAI embeddings. ### 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: Abby Harrison <[email protected]> Co-authored-by: Lee Miller <[email protected]> Co-authored-by: Devis Lucato <[email protected]>
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‎python/samples/kernel-syntax-examples/azure_cognitive_search_memory.py‎

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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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from dotenv import dotenv_values
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import semantic_kernel as sk
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from semantic_kernel.connectors.ai.open_ai import (
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AzureTextCompletion,
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AzureTextEmbedding,
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)
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from semantic_kernel.connectors.memory.azure_cognitive_search import (
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AzureCognitiveSearchMemoryStore,
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)
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COLLECTION_NAME = "acs-index-sample"
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async def populate_memory(kernel: sk.Kernel) -> None:
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# Add some documents to the ACS semantic memory
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await kernel.memory.save_information_async(
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COLLECTION_NAME, id="info1", text="My name is Andrea"
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)
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await kernel.memory.save_information_async(
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COLLECTION_NAME, id="info2", text="I currently work as a tour guide"
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)
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await kernel.memory.save_information_async(
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COLLECTION_NAME, id="info3", text="I've been living in Seattle since 2005"
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)
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await kernel.memory.save_information_async(
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COLLECTION_NAME,
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id="info4",
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text="I visited France and Italy five times since 2015",
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)
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await kernel.memory.save_information_async(
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COLLECTION_NAME, id="info5", text="My family is from New York"
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)
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async def search_acs_memory_questions(kernel: sk.Kernel) -> None:
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questions = [
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"what's my name",
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"where do I live?",
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"where's my family from?",
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"where have I traveled?",
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"what do I do for work",
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]
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for question in questions:
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print(f"Question: {question}")
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result = await kernel.memory.search_async(COLLECTION_NAME, question)
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print(f"Answer: {result[0].text}\n")
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async def main() -> None:
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kernel = sk.Kernel()
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config = dotenv_values(".env")
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AZURE_COGNITIVE_SEARCH_ENDPOINT = config["AZURE_COGNITIVE_SEARCH_ENDPOINT"]
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AZURE_COGNITIVE_SEARCH_ADMIN_KEY = config["AZURE_COGNITIVE_SEARCH_ADMIN_KEY"]
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AZURE_OPENAI_API_KEY = config["AZURE_OPENAI_API_KEY"]
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AZURE_OPENAI_ENDPOINT = config["AZURE_OPENAI_ENDPOINT"]
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vector_size = 1536
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# Setting up OpenAI services for text completion and text embedding
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kernel.add_text_completion_service(
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"dv",
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AzureTextCompletion(
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deployment_name="text-embedding-ada-002",
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endpoint=AZURE_OPENAI_ENDPOINT,
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api_key=AZURE_OPENAI_API_KEY,
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),
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)
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kernel.add_text_embedding_generation_service(
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"ada",
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AzureTextEmbedding(
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deployment_name="text-embedding-ada-002",
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endpoint=AZURE_OPENAI_ENDPOINT,
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api_key=AZURE_OPENAI_API_KEY,
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),
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)
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connector = AzureCognitiveSearchMemoryStore(
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vector_size, AZURE_COGNITIVE_SEARCH_ENDPOINT, AZURE_COGNITIVE_SEARCH_ADMIN_KEY
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)
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# Register the memory store with the kernel
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kernel.register_memory_store(memory_store=connector)
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print("Populating memory...")
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await populate_memory(kernel)
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print("Asking questions... (manually)")
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await search_acs_memory_questions(kernel)
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await connector.close_async()
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if __name__ == "__main__":
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asyncio.run(main())

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