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Evan Mattson
ff1997047d
### Motivation and Context This PR builds on the initial work/abstractions from #11982. The `AzureAssistantAgent` / `OpenAIAssistantAgent` as well as the `AzureResponsesAgent` / `OpenAIResponsesAgent` now support declarative specs. Several examples on how to declare the spec are shown in the respective dirs in `samples/concepts/agents`, as well as a simple getting started example for each agent type. To further simplify working with these two agents, the `setup_resources()` methods for each agent type have been marked with a deprecation tag. The new method to use is `OpenAIAssistantAgent.create_client()` or `OpenAIResponsesAgent.create_client()`. Further, when one needs to access the underlying setting's, it's simple to do so with a settings object and accessing the attribute. In the previous PR for the AzureAIAgent, it lacked support for templating - this is included in this current PR. <!-- 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 Bring in support for the declarative single agent spec for these agent types. - Add samples - Add unit tests - Add support for prompt templates for all current agent types - Closes #11979 <!-- 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 😄
SK Python Documentation Examples
This project contains a collection of examples used in documentation on learn.microsoft.com.
Prerequisites
- Python 3.10 and above
- Install Semantic Kernel through PyPi:
pip install semantic-kernel
Configuring the sample
The samples can be configured with a .env file in the project which holds api keys and other secrets and configurations.
Make sure you have an Open AI API Key or Azure Open AI service key
Copy the .env.example file to a new file named .env. Then, copy those keys into the .env file:
GLOBAL_LLM_SERVICE="OpenAI" # Toggle between "OpenAI" or "AzureOpenAI"
OPENAI_CHAT_MODEL_ID="gpt-3.5-turbo-0125"
OPENAI_TEXT_MODEL_ID="gpt-3.5-turbo-instruct"
OPENAI_API_KEY=""
OPENAI_ORG_ID=""
AZURE_OPENAI_CHAT_DEPLOYMENT_NAME="gpt-35-turbo"
AZURE_OPENAI_TEXT_DEPLOYMENT_NAME="gpt-35-turbo-instruct"
AZURE_OPENAI_ENDPOINT=""
AZURE_OPENAI_API_KEY=""
AZURE_OPENAI_API_VERSION=""
Note: if running the examples with VSCode, it will look for your .env file at the main root of the repository.
Running the sample
To run the console application within Visual Studio Code, just hit F5.
Otherwise the sample can be run via the command line:
python.exe <absolute_path_to_sk_code>/python/samples/documentation_examples/planner.py