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### Motivation and Context Please help reviewers and future users, providing the following information: 1. Why is this change required? `SemanticTextMemory.save_reference_async` do nothing for its storage. 2. What problem does it solve? `save_reference_async` will work appropriately 3. What scenario does it contribute to? embeddings 4. If it fixes an open issue, please link to the issue here. https://github.com/microsoft/semantic-kernel/issues/165 ### Description I add missing codes with references of `SemanticTextMemory.save_information_async` and C# version of `SemanticTextMemory.save_reference_async`
Quickstart with Poetry
Installation
Install the Poetry package manager and create a project virtual environment.
# Install poetry package
pip3 install poetry
# Use poetry to install project deps
poetry install
# Use poetry to activate project venv
poetry shell
Make sure you have an Open AI API Key or Azure Open AI service key
Copy those keys into a .env file in this repo
OPENAI_API_KEY=""
OPENAI_ORG_ID=""
AZURE_OPENAI_API_KEY=""
AZURE_OPENAI_ENDPOINT=""
Quickstart ⚡
import semantic_kernel as sk
kernel = sk.create_kernel()
api_key, org_id = sk.openai_settings_from_dot_env()
kernel.config.add_openai_completion_backend(
"davinci-002", "text-davinci-002", api_key, org_id
)
sk_prompt = """
{{$input}}
Give me the TLDR in 5 words.
"""
text_to_summarize = """
1) A robot may not injure a human being or, through inaction,
allow a human being to come to harm.
2) A robot must obey orders given it by human beings except where
such orders would conflict with the First Law.
3) A robot must protect its own existence as long as such protection
does not conflict with the First or Second Law.
"""
tldr_function = sk.extensions.create_semantic_function(
kernel,
sk_prompt,
max_tokens=200,
temperature=0,
top_p=0.5,
)
summary = await kernel.run_on_str_async(text_to_summarize, tldr_function)
output = str(summary.variables).strip()
print("Output: " + output)
# Output: Protect humans, follow orders, survive.