Python: Fix OpenAI/API plugins based on samples path changes. Black formatting for notebooks.

python/samples/concepts/plugins/openai_plugin_azure_key_vault.py

@@ -17,7 +17,7 @@
 async def add_secret_to_key_vault(kernel: Kernel, plugin: KernelPlugin):
  """Adds a secret to the Azure Key Vault."""
  result = await kernel.invoke(
- functions=plugin["SetSecret"],
+ function=plugin["SetSecret"],
  path_params={"secret-name": "Foo"},
  query_params={"api-version": "7.0"},
  request_body={"value": "Bar", "enabled": True},
@@ -30,9 +30,10 @@ async def add_secret_to_key_vault(kernel: Kernel, plugin: KernelPlugin):
 async def get_secret_from_key_vault(kernel: Kernel, plugin: KernelPlugin):
  """Gets a secret from the Azure Key Vault."""
  result = await kernel.invoke(
- functions=plugin["GetSecret"],
- path_params={"secret-name ": "Foo"},
+ function=plugin["GetSecret"],
+ path_params={"secret-name": "Foo"},
  query_params={"api-version": "7.0"},
+ request_body={},
  headers={},
  )
 
@@ -136,7 +137,7 @@ async def main():
  kernel = Kernel()
 
  openai_spec_file = os.path.join(
- os.path.dirname(os.path.realpath(__file__)), "resources", "open_ai_plugins", "akv-openai.json"
+ os.path.dirname(os.path.dirname(os.path.realpath(__file__))), "resources", "open_ai_plugins", "akv-openai.json"
  )
  with open(openai_spec_file, "r") as file:
  openai_spec = file.read()
@@ -155,6 +156,7 @@ async def main():
  )
 
  await add_secret_to_key_vault(kernel, plugin)
+ await get_secret_from_key_vault(kernel, plugin)
 
 
 if __name__ == "__main__":

python/samples/concepts/plugins/openapi/openapi_client.py

@@ -8,9 +8,7 @@ async def main():
  """Client"""
  kernel = sk.Kernel()
 
- openapi_plugin = kernel.import_plugin_from_openapi(
- plugin_name="openApiPlugin", openapi_document_path="./openapi.yaml"
- )
+ openapi_plugin = kernel.add_plugin_from_openapi(plugin_name="openApiPlugin", openapi_document_path="./openapi.yaml")
 
  arguments = {
  "request_body": '{"input": "hello world"}',

python/samples/concepts/resources/open_ai_plugins/akv-openai.json

@@ -12,7 +12,7 @@
  },
  "api": {
  "type": "openapi",
- "url": "file:///./python/samples/kernel-syntax-examples/resources/open_ai_plugins/akv-openapi.yaml"
+ "url": "file:///./python/samples/concepts/resources/open_ai_plugins/akv-openapi.yaml"
  },
  "logo_url": "",
  "contact_email": "",

python/samples/getting_started/03-prompt-function-inline.ipynb

@@ -61,7 +61,7 @@
  "from services import Service\n",
  "\n",
  "# Select a service to use for this notebook (available services: OpenAI, AzureOpenAI, HuggingFace)\n",
- "selectedService = Service.OpenAI"
+ "selectedService = Service.AzureOpenAI"
  ]
  },
  {
@@ -77,24 +77,24 @@
  "\n",
  "service_id = None\n",
  "if selectedService == Service.OpenAI:\n",
- " from semantic_kernel.connectors.ai.open_ai import OpenAITextCompletion\n",
+ " from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion\n",
  " from semantic_kernel.utils.settings import openai_settings_from_dot_env\n",
  "\n",
  " api_key, org_id = openai_settings_from_dot_env()\n",
- " service_id = \"oai_text_completion\"\n",
+ " service_id = \"oai_chat_completion\"\n",
  " kernel.add_service(\n",
- " OpenAITextCompletion(\n",
+ " OpenAIChatCompletion(\n",
  " service_id=service_id, ai_model_id=\"gpt-3.5-turbo-instruct\", api_key=api_key, org_id=org_id\n",
  " ),\n",
  " )\n",
  "elif selectedService == Service.AzureOpenAI:\n",
- " from semantic_kernel.connectors.ai.open_ai import AzureTextCompletion\n",
+ " from semantic_kernel.connectors.ai.open_ai import AzureChatCompletion\n",
  " from semantic_kernel.utils.settings import azure_openai_settings_from_dot_env\n",
  "\n",
  " deployment, api_key, endpoint = azure_openai_settings_from_dot_env()\n",
- " service_id = \"aoai_text_completion\"\n",
+ " service_id = \"aoai_chat_completion\"\n",
  " kernel.add_service(\n",
- " AzureTextCompletion(service_id=service_id, deployment_name=deployment, endpoint=endpoint, api_key=api_key),\n",
+ " AzureChatCompletion(service_id=service_id, deployment_name=deployment, endpoint=endpoint, api_key=api_key),\n",
  " )"
  ]
  },
@@ -116,7 +116,7 @@
  "metadata": {},
  "outputs": [],
  "source": [
- "from semantic_kernel.connectors.ai.open_ai import OpenAITextPromptExecutionSettings\n",
+ "from semantic_kernel.connectors.ai.open_ai import OpenAIChatPromptExecutionSettings\n",
  "from semantic_kernel.prompt_template import PromptTemplateConfig, InputVariable\n",
  "\n",
  "\n",
@@ -125,14 +125,14 @@
  "\"\"\"\n",
  "\n",
  "if selectedService == Service.OpenAI:\n",
- " execution_settings = OpenAITextPromptExecutionSettings(\n",
+ " execution_settings = OpenAIChatPromptExecutionSettings(\n",
  " service_id=service_id,\n",
  " ai_model_id=\"gpt-3.5-turbo-instruct\",\n",
  " max_tokens=2000,\n",
  " temperature=0.7,\n",
  " )\n",
  "elif selectedService == Service.AzureOpenAI:\n",
- " execution_settings = OpenAITextPromptExecutionSettings(\n",
+ " execution_settings = OpenAIChatPromptExecutionSettings(\n",
  " service_id=service_id,\n",
  " ai_model_id=deployment,\n",
  " max_tokens=2000,\n",
@@ -344,7 +344,7 @@
  "name": "python",
  "nbconvert_exporter": "python",
  "pygments_lexer": "ipython3",
- "version": "3.12.3"
+ "version": "3.11.9"
  }
  },
  "nbformat": 4,

python/samples/getting_started/06-memory-and-embeddings.ipynb

@@ -218,6 +218,7 @@
  "from semantic_kernel.functions import KernelFunction\n",
  "from semantic_kernel.prompt_template import PromptTemplateConfig\n",
  "\n",
+ "\n",
  "async def setup_chat_with_memory(\n",
  " kernel: Kernel,\n",
  " service_id: str,\n",

python/samples/getting_started/10-multiple-results-per-prompt.ipynb

@@ -183,7 +183,7 @@
  "source": [
  "if selectedService == Service.AzureOpenAI:\n",
  " prompt = \"provide me a list of possible meanings for the acronym 'ORLD'\"\n",
- " \n",
+ "\n",
  " results = await azure_text_service.complete(prompt=prompt, settings=oai_text_prompt_execution_settings)\n",
  " i = 1\n",
  " for result in results:\n",
@@ -226,7 +226,7 @@
  "source": [
  "if selectedService == Service.HuggingFace:\n",
  " prompt = \"The purpose of a rubber duck is\"\n",
- " \n",
+ "\n",
  " results = await hf_text_service.complete(prompt=prompt, prompt_execution_settings=hf_prompt_execution_settings)\n",
  " print(\"\".join(results))"
  ]

python/semantic_kernel/connectors/openapi_plugin/openapi_manager.py

@@ -342,23 +342,33 @@ def _create_function_from_operation(
  name=operation.id,
  )
  async def run_openapi_operation(
- path_params: Annotated[dict | str | None, "A dictionary of path parameters"] = None,
- query_params: Annotated[dict | str | None, "A dictionary of query parameters"] = None,
- headers: Annotated[dict | str | None, "A dictionary of headers"] = None,
- request_body: Annotated[dict | str | None, "A dictionary of the request body"] = None,
+ path_params: Annotated[
+ dict | str | None, "A dictionary of path parameters. If not specified return empty string."
+ ] = None,
+ query_params: Annotated[
+ dict | str | None, "A dictionary of query parameters. If not specified return empty string."
+ ] = None,
+ headers: Annotated[dict | str | None, "A dictionary of headers. If not specified return empty string."] = None,
+ request_body: Annotated[
+ dict | str | None, "A dictionary of the request body. If not specified return empty string."
+ ] = None,
  ) -> str:
+ def parse_params(param):
+ if param == "" or param is None:
+ return {}
+ if isinstance(param, str):
+ try:
+ return json.loads(param)
+ except json.JSONDecodeError:
+ raise ValueError(f"Invalid JSON string: {param}")
+ return param
+
  response = await runner.run_operation(
  operation,
- path_params=(
- json.loads(path_params) if isinstance(path_params, str) else path_params if path_params else None
- ),
- query_params=(
- json.loads(query_params) if isinstance(query_params, str) else query_params if query_params else None
- ),
- headers=json.loads(headers) if isinstance(headers, str) else headers if headers else None,
- request_body=(
- json.loads(request_body) if isinstance(request_body, str) else request_body if request_body else None
- ),
+ path_params=parse_params(path_params),
+ query_params=parse_params(query_params),
+ headers=parse_params(headers),
+ request_body=parse_params(request_body),
  )
  return response