mirror of
https://github.com/microsoft/semantic-kernel.git
synced 2026-10-12 02:19:06 +00:00
dependabot/github_actions/github/codeql-action/init-4.37.9
23
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
|
|
003cc4c010 |
Python: Feature python vector stores preb (#12271)
### Motivation and Context <!-- 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. --> Overhaul of the VectorStores to get it matching with dotnet and the latest development there. Closes: - #11938 - #11598 - #11597 - #11517 - #10561 - #10391 - #9911 - #9892 - #10867 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> Many changes, some highlights: - Moved from different vector fields types, to a single with a enum first VectorStoreField() - Renamed several items - Made embeddinggenerrator a part of the vector field spec and do automatic vectorization from there or from the same param on a collection - Adds hybrid search using the same setup - Removed the intermediate TextSeachVectorSearch object need, by allowing `create_search_function` directly on a collection Will write out full changes in a migration guide in the docs. ### 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 - [ ] I didn't break anyone 😄 |
||
|
|
3e31c3bdc6 |
Python: Remove planner-related code and samples. (#12417)
### Motivation and Context Per deprecation method, removing planner-related code after June 1, 2025. <!-- 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 - Removing planner-related code. - Closes #12400 <!-- 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 - [ ] I didn't break anyone 😄 |
||
|
|
1a187b03bc |
Python: Introduce the Copilot Studio Agent (#11851)
### Motivation and Context Semantic Kernel Python currently has a demo showing how to interact with a Copilot Studio Agent; however, that uses the `DirectLine API`. This PR introduces a Semantic Kernel `CoilotStudioAgent` that leverages the team's new `microsoft.agents.copilotstudio.client`. One must first have a Copilot Studio Agent created via the portal; and once ready, they can reference it with the proper App Registration and Agent metadata. Interacting with the Agent can leverage Microsoft Copilot Studio's knowledge sources and internal tools. <!-- 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 Add support for the `CopilotStudioAgent`. - Provide getting started samples - Introduces a detailed README on what is required for setup and interacting with the agent. - The current version of the `CopilotStudioAgent` does not support calling another Copilot Studio Agent via a skill. - Authentication for the agent is limited to interactive right now. Once service-to-service auth is support via the client, we will add this into SK. - Closes #11607 <!-- 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 😄 |
||
|
|
17e63a782b |
Python/.NET: Add a common agent invoke api. (#11116)
### Motivation and Context Being able to different invoke agents using a common API is useful to build higher level code on top of. ### Description Adding a common Invoke method with a common Thread object. ### Contribution Checklist <!-- Before submitting this PR, please make sure: --> - [ ] The code builds clean without any errors or warnings - [ ] 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 - [ ] All unit tests pass, and I have added new tests where possible - [ ] I didn't break anyone 😄 --------- Co-authored-by: Ben Thomas <[email protected]> Co-authored-by: Evan Mattson <[email protected]> Co-authored-by: Tao Chen <[email protected]> Co-authored-by: Ben Thomas <[email protected]> Co-authored-by: Mark Wallace <[email protected]> Co-authored-by: Evan Mattson <[email protected]> |
||
|
|
4d29656780 |
Python: Introduce the chat history reducer (#10190)
### Motivation and Context The SK Python framework has been missing the ability to configure a chat history reducer of type `ChatHistoryTruncationReducer` and `ChatHistorySummarizationReducer` which have existed in the .Net SK Agent framework for some time. The goal of this PR is to introduce the chat history reducers and allow them for use for not only the agent framework, but also anything else that uses a chat history (chat completion, for example). The ChatHistoryReducer extends the ChatHistory class, and so it's simple to include a reducer and logic to reduce messages as one manages the chat history either in an agent framework setting or in a chat completion setting. <!-- 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 This PR: - Introduces the chat history reducer functionality in Python -- both the `ChatHistoryTruncationReducer` and `ChatHistorySummarizationReducer`. - Add unit tests for code coverage. - Adds a sample `Chat Completion History Reducer` to show how to configure both reducers and what each parameter does. - Add chat completion samples showing how to manage a chat history reducer, including how to specify that function call content and function result content should be part of the summarization payload. - Updates the Agent SelectionStrategy, KernelFunctionSelectionStrategy and KernelFunctionTermination strategy to use the reducer. - Additionally updates the classes above to use a new `select_agent` abstract method so that one can define an initial agent to run in a particular scenario. - Removes the deprecated `FunctionCallBehavior` class, and removes some nasty circular dependencies that we had lurking in the code base for some time. This `FunctionCallBehavior` has been marked with a deprecation warning for 6+ months now. All samples and docs have moved over to use `FunctionChoiceBehavior` - developers using `FunctionCallBehavior` should have had enough time to switch. - Closes #7969 - Closes #10102 <!-- 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 😄 |
||
|
|
3bab8486f5 |
Python: improved text_search folder testing (#9984)
### Motivation and Context <!-- 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. --> added unit tests to up the test coverage across the data folder Also redoes exceptions for everything vector. This does introduce some breaking changes on the exceptions returned by the different methods for vector stores, they are still marked experimental and this will go a long way in moving towards release. Closes #9485 ### Description <!-- 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 - [ ] I didn't break anyone 😄 |
||
|
|
e0042afa80 |
Python: graduate filters, add exception during addition and some cleanup (#9856)
### Motivation and Context <!-- 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. --> This PR graduates the filters. This includes some updates to the docstrings. And adds a specific Exception for errors during adding or removing of filters. Closes #9838 Fixes #9641 ### Description <!-- 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 😄 |
||
|
|
c8b4094835 |
Python: Introducing vector and text search (#9345)
### Motivation and Context
<!-- 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.
-->
This PR does the following things:
- Introduces TextSearch abstractions, including implementation for Bing
- This consists of the TextSearch class, which implements three public
search methods, and handles the internals, the search methods are:
'search' returns a string, 'get_text_search_results' returns a
TextSearchResult object and 'get_search_results' returns a object native
to the search service (i.e. BingWebPages for Bing)
- This also has a method called "create_{search_method}' which returns a
KernelFunction based on the search method. This function can be adapted
by setting the parameters and has several adaptability options and
allows you to create a RAG pipeline easily with custom names and
descriptions of both the functions and the parameters!
- Introduces VectorSearch abstractions, including implementation for
Azure AI Search
- This consists of a VectorStoreBase class which handles all the
internal and three public interfaces, vectorized_search (supply a
vector), vectorizable_text_search (supply a string that get's vectorized
downstream), vector_text_search (supply a string), each vector store
record collection can pick and choose which ones they need to support by
importing one or more next to the VectorSearchBase class.
- Introduces VectorStoreTextSearch as a way to leverage text search
against vector stores
- Since this builds on TextSearch this is now the best way to create a
super powerfull RAG setup with your own data model!
- Adds all the related classes, samples and tests for the above.
- Also reorders the data folder, which might cause some slight breaking
changes for the few stores that have the new vector store model.
- Adds additional IndexKinds and DistanceFunctions to stay in sync with
dotnet.
- Renames VolatileStore and VolatileCollection to InMemoryVectorStore
and InMemoryVectorCollection.
Closes #6832 #6833
### 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
- [ ] I didn't break anyone 😄
---------
Co-authored-by: Tao Chen <[email protected]>
|
||
|
|
6eba848e91 |
Python: Add the Python process framework (#9363)
### Motivation and Context An initial PR to add the foundational pieces of the Python Process framework, which holds it design to be similar to dotnet in that step types are added to a process builder, and later on, when the step is run, it is first instantiated and the proper state is provided. <!-- 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 Adding the initial process framework components: - Closes #9354 **TODO** - more unit tests will be added to increase the code coverage. Currently there are several files with no (or low) code coverage. - more samples will either be added to this PR or a subsequent PR <!-- 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 😄 |
||
|
|
ee40e88c13 |
Python: Introduce Agent group chat functionality (#8184)
### Motivation and Context In the next phase of the agent work in Python, we are to introduce the ability to have agents interact with each other. Agent group chat allows developers to create richer and more dynamic agent interactions. <!-- 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 This PR introduces the following: - Agent group chat functionality via an `agent_chat` base class that forms the foundation for group chats. An `agent_group_chat` class extends that underlying functionality and provides an entry point to kick off the group chat either via invoking the chat for the defined agents, or specifying if a provided agent is to join the existing chat. - The required channels for the chat completion agent and assistant agent to properly chat together - Adds more concept samples and getting started with agent samples to enrich the onboarding experiencing for those wanting to see the capability of agents and agent group chat. - Adds unit test for near 100% coverage - Updates some existing imports for agents, which try and make the required import experience more intuitive. - Introduces assistant agent abstractions for working with files and vector stores so we don't directly expose the underlying client types. - Closes #7966 - Closes #7577 <!-- 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 - [ ] I didn't break anyone 😄 |
||
|
|
1356d5f30c |
Python: Feature new memory stores and collections (#7614)
### Motivation and Context <!-- 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. --> This PR adds new vector store and vector store record collections as well as implementations for: - Azure AI Search - Redis - Qdrant - Volatile (in-memory) It also adds samples, tests, and unit-tests for these. Next it adds the vector store record fields, definition and decorator, with tests and samples. All marked experimental. Existing Redis, Azure AI Search, Qdrant and Volatile will be marked as deprecated in the future, once the new collections are feature complete. ### Description <!-- 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 😄 |
||
|
|
51f5554b39 |
Python: removed D101 and fixes for it (#7853)
### Motivation and Context <!-- 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. --> Added comments about each of the rules to pyproject.toml Removed D101 from ignore list and fixed that, now docstrings at the class level are required. ### Description <!-- 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 😄 |
||
|
|
9480d807cf |
Python: Introduce the non-chat, non-streaming OpenAIAssistantAgent, samples, and tests (#7477)
### Motivation and Context To align with SK dotnet and to allow SK Python devs to leverage the OpenAI/Azure OpenAI assistants, this code is a required component for SK Python. <!-- 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 We're introducing the code to build non-chat, non-streaming OpenAIAssistantAgents for both the OpenAI and Azure OpenAI styles. This PR introduces: - The required code to create OpenAI/AzureOpenAI assistants using the v2 library. - Samples showing how to create the agent, and how to use the tool resources like the code interpreter and file search. - Unit test coverage at 100% - Full mypy coverage - Closes #7080  One to-do item: - introduce Agent integration tests Note: streaming assistant agent support will come in the next PR. <!-- 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 😄 |
||
|
|
5f49880d52 |
Python: Json schema improvements for Union and Optional (#7367)
### Motivation and Context We have some gaps in how we build the JSON schema for function calling related to Union and Optional types. There is also some work to do related to handling `Optional` versus `param | None = None`. <!-- 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 This PR improves the JSON schema building for the Union and Optional types. It adds additional tests and improves some existing tests. - Closes #7297 - Closes #7298 <!-- 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 😄 |
||
|
|
fbb26b5cf6 |
Python: further improvements to checks and docs in dev_setup (#6445)
### Motivation and Context <!-- 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. --> Added a section on documentation to the DEV_SETUP Added a check for the copyright row to pre-commit Closes #5629 ### Description <!-- 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 😄 |
||
|
|
9e99933a27 |
Python: new pre-commit actions and pre-commit as GHA (#6376)
### Motivation and Context <!-- 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. --> - Added static code checking to pre-commit (check-ast and nbqa-check-ast) - Added Bandit security checking to pre-commit - Added pre-commit step to python-lint workflow, if it works, can delete seperate mypy, ruff and black tests ### Description <!-- 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 😄 |
||
|
|
a894aebaa9 |
Python: implement filters (#5681)
### Motivation and Context <!-- 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. --> This pull request includes significant changes across multiple files, mainly related to the addition of hooks and the modification of function invocations in the `semantic_kernel` module. The changes also include the addition of a new sample and a YAML file, and modifications to the `__init__.py` files. Removals: * [`python/semantic_kernel/events`](diffhunk://#diff-ebda9504832b19ab83239a92c9a6d5f8c744deff9fef86071c13956ec92bb010L1-L11): Removed the previously used events. New Exceptions: * [`python/semantic_kernel/exceptions/kernel_exceptions.py`](diffhunk://#diff-450aaa5595a8b22cd6ee212eb79b7d6b0d4e9c1072063ef32018a3e7d3fdf21dR41-R48): Added new exception classes `OperationCancelledException` and `HookInvalidSignatureError`. [[1]](diffhunk://#diff-450aaa5595a8b22cd6ee212eb79b7d6b0d4e9c1072063ef32018a3e7d3fdf21dR41-R48) [[2]](diffhunk://#diff-450aaa5595a8b22cd6ee212eb79b7d6b0d4e9c1072063ef32018a3e7d3fdf21dR57-R58) Fixes: #3038 Fixes: #6276 ### 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 - [ ] I didn't break anyone 😄 |
||
|
|
46f5ea15a2 |
Python: Introduce Pydantic settings (#6193)
### Motivation and Context SK Python is tightly coupled to the use of a `.env` file to read all secrets, keys, endpoints, and more. This doesn't scale well for users who wish to be able to use environment variables with their SK Applications. By introducing Pydantic Settings, it is possible to use both environment variables as well as have a fall-back to a `.env` file (via a `env_file_path` parameter), if desired. By introducing Pydantic Settings, we are removing the requirement to have to create Text/Embedding/Chat completion objects with an `api_key` or other previously required information (in the case of AzureChatCompletion that means an `endpoint`, an `api_key`, a `deployment_name`, and an `api_version`). When the AI connector is created, the Pydantic settings are loaded either via env vars or the fall-back `.env` file, and that means the user can create a chat completion object like: ```python chat_completion = OpenAIChatCompletion(service_id="test") ``` or, to optionally override the `ai_model_id` env var: ```python chat_completion = OpenAIChatCompletion(service_id="test", ai_model_id="gpt-4-1106") ``` Note: we have left the ability to specific an `api_key`/`org_id` for `OpenAIChatCompletion` or a `deployment_name`, `endpoint`, `base_url`, and `api_version` for `AzureChatCompletion` as before, but if your settings are configured to use env vars/.env file then there is no need to pass this information. <!-- 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 The PR introduces the use of Pydantic settings and removes the use of the python-dotenv library. - Closes #1779 - Updates notebooks, samples, code and tests to remove the explicit config of api_key or other previous .env files values. - Adds new unit test config using monkeypatch to simulate env variables for testing - All unit and integration tests passing <!-- 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 - [ ] I didn't break anyone 😄 |
||
|
|
c4c7464f07 |
Python: Introduce operations to handle OpenAI plugins, improve OpenAPI plugins, and allow for auth (#5695)
### Motivation and Context Python had the ability to handle operations for OpenAPI plugins, but at a basic level. It did not have the ability to handle OpenAI plugins, nor did it allow the user to configure an authentication callback. This PR brings in that functionality. <!-- 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 This PR: - Allows a user to handle OpenAI plugins with/without auth. Closes #5355 - Improves the functionality around handling OpenAPI specs. - Introduces an auth callback mechanism to allow for REST API calls to use auth - Introduces OpenAI/OpenAPI function execution settings. - Provides two new kernel examples that show how to handle a simple OpenAI plugin (Klarna) as well as a more complex plugin (Azure Key Vault) that requires auth. - Updates unit tests. <!-- 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 😄 |
||
|
|
0a1a7cabe8 |
Python: support Jinja2 templating (#5483)
### Motivation and Context Jinja2 is a heavily supported Python templating language and we're introducing it to SK Python. <!-- 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 This PR brings in the ability to specify Jinja2 templates for use within SK Python: - Closes #5343 <!-- 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 😄 |
||
|
|
3af69df7ea |
Python: Handlebars template support (#5466)
### Motivation and Context <!-- 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. --> Introducing Handlebars templating to the Python Semantic Kernel! Closes: #5446 Prework for: #4641 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> Adds HandlebarsPromptTemplate as a subclass of PromptTemplateBase Adds second literal to the PromptTemplateConfig definition Adds helpers for Handlebars (system_helpers) and `create_helper_from_function` function Moves fully_qualified_name into KernelFunctionMetadata instead of in different extensions. Defaults are still 'semantic-kernel' templates, and without making explicit changes that still is the norm. Adds a azure_chat_gpt_handlebars.py sample ### 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 😄 |
||
|
|
555a7c8436 |
Python: fix for streaming openai responses, and first parts of fixes for Chat With Your Data (#5387)
### Motivation and Context <!-- 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 <!-- 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: --> - [ ] The code builds clean without any errors or warnings - [ ] 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 - [ ] All unit tests pass, and I have added new tests where possible - [ ] I didn't break anyone 😄 |
||
|
|
739e7f0e2a |
Python: rebuilt exceptions structure; pythonic version (#5231)
### Motivation and Context <!-- 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. --> The existing Exceptions structure was very much inspired by dotnet, this is now replaced with a pythonic implementations. This means all Exceptions derive from KernelException and then specialise for different purposes. Closes #2194 ### Description <!-- Describe your changes, the overall approach, the underlying design. These notes will help understanding how your code works. Thanks! --> Added folder for all exception types, all can be imported through `from semantic_kernel.exceptions import ...` no need for a user to know which file the relevant one is in, but keeps things tidy for developers. Removed old KernelException, added back subtypes for the errorcodes. Went through everything to make sure the `raise ... from exc` pattern is used as much as possible as that returns a better stacktrace. ### 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 😄 |