Python: updated samples

python/samples/learn_resources/README.md

@@ -4,7 +4,11 @@ This project contains a collection of examples used in documentation on [learn.m
 
 ## Prerequisites
 
-- [Python](https://www.python.org/downloads/) 3.8 and above
+- [Python](https://www.python.org/downloads/) 3.10 and above
+- Install Semantic Kernel through PyPi:
+  ```bash
+  pip install semantic-kernel
+  ```
 
 ## Configuring the sample
 
@@ -19,13 +23,13 @@ Copy the `.env.example` file to a new file named `.env`. Then, copy those keys i
 ```
 GLOBAL_LLM_SERVICE="OpenAI" # Toggle between "OpenAI" or "AzureOpenAI"
 
-OPEN_AI_CHAT_COMPLETION_MODEL_ID="gpt-3.5-turbo-0125"
-OPEN_AI_TEXT_COMPLETION_MODEL_ID="gpt-3.5-turbo-instruct"
+OPEN_AI_CHAT_MODEL_ID="gpt-3.5-turbo-0125"
+OPEN_AI_TEXT_MODEL_ID="gpt-3.5-turbo-instruct"
 OPENAI_API_KEY=""
 OPENAI_ORG_ID=""
 
-AZURE_OPEN_AI_CHAT_COMPLETION_DEPLOYMENT_NAME="gpt-35-turbo"
-AZURE_OPEN_AI_TEXT_COMPLETION_DEPLOYMENT_NAME="gpt-35-turbo-instruct"
+AZURE_OPEN_AI_CHAT_DEPLOYMENT_NAME="gpt-35-turbo"
+AZURE_OPEN_AI_TEXT_DEPLOYMENT_NAME="gpt-35-turbo-instruct"
 AZURE_OPENAI_ENDPOINT=""
 AZURE_OPENAI_API_KEY=""
 AZURE_OPENAI_API_VERSION=""

python/samples/learn_resources/__init__.py

@@ -0,0 +1,5 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+from .sk_service_configurator import add_service
+
+__all__ = ["add_service"]

python/samples/learn_resources/ai_services.py

@@ -3,24 +3,25 @@
 import asyncio
 import os
 
-from service_configurator import add_service
+from sk_service_configurator import add_service
 
-import semantic_kernel as sk
+from semantic_kernel.kernel import Kernel
 
 
 async def main():
     # Initialize the kernel
-    kernel = sk.Kernel()
+    kernel = Kernel()
 
     # Add the service to the kernel
     # use_chat: True to use chat completion, False to use text completion
-    kernel = add_service(kernel=kernel, use_chat=True)
+    # use_azure: True to use Azure OpenAI, False to use OpenAI
+    kernel = add_service(kernel, use_chat=True)
 
     script_directory = os.path.dirname(__file__)
     plugins_directory = os.path.join(script_directory, "plugins")
-    writer_plugin = kernel.import_plugin_from_prompt_directory(
+    writer_plugin = kernel.add_plugin(
         parent_directory=plugins_directory,
-        plugin_directory_name="WriterPlugin",
+        plugin_name="WriterPlugin",
     )
 
     # Run the ShortPoem function with the Kernel Argument.

python/samples/learn_resources/configuring_prompts.py

@@ -1,87 +1,86 @@
 # Copyright (c) Microsoft. All rights reserved.
+
 import asyncio
 
-from service_configurator import add_service
+from sk_service_configurator import add_service
 
-import semantic_kernel as sk
-from semantic_kernel.connectors.ai.prompt_execution_settings import PromptExecutionSettings
-from semantic_kernel.contents.chat_history import ChatHistory
+from semantic_kernel.connectors.ai import PromptExecutionSettings
+from semantic_kernel.contents import ChatHistory
 from semantic_kernel.core_plugins import ConversationSummaryPlugin
-from semantic_kernel.prompt_template.input_variable import InputVariable
-from semantic_kernel.prompt_template.prompt_template_config import PromptTemplateConfig
-
-
-async def main():
-    # Initialize the kernel
-    kernel = sk.Kernel()
-
-    # Add the service to the kernel
-    # use_chat: True to use chat completion, False to use text completion
-    kernel = add_service(kernel=kernel, use_chat=True)
-
-    service_id = "default"
-
-    # The following execution settings are used for the ConversationSummaryPlugin
-    execution_settings = PromptExecutionSettings(
-        service_id=service_id, max_tokens=ConversationSummaryPlugin._max_tokens, temperature=0.1, top_p=0.5
-    )
-    prompt_template_config = PromptTemplateConfig(
-        template=ConversationSummaryPlugin._summarize_conversation_prompt_template,
-        description="Given a section of a conversation transcript, summarize the part of" " the conversation.",
-        execution_settings=execution_settings,
-    )
-
-    # Import the ConversationSummaryPlugin
-    kernel.add_plugin(
-        ConversationSummaryPlugin(kernel=kernel, prompt_template_config=prompt_template_config),
-        plugin_name="ConversationSummaryPlugin",
-    )
-
-    # Create the history
-    history = ChatHistory()
-
-    # Create the prompt with the ConversationSummaryPlugin
-    prompt = """{{ConversationSummaryPlugin.SummarizeConversation $history}}
-    User: {{$request}}
-    Assistant:  """
-
-    # These execution settings are tied to the chat function, created below.
-    execution_settings = kernel.get_service(service_id).instantiate_prompt_execution_settings(service_id=service_id)
-    chat_prompt_template_config = PromptTemplateConfig(
-        template=prompt,
+from semantic_kernel.kernel import Kernel
+from semantic_kernel.prompt_template import InputVariable, PromptTemplateConfig
+
+# Initialize the kernel
+kernel = Kernel()
+
+# Add the service to the kernel
+# use_chat: True to use chat completion, False to use text completion
+kernel = add_service(kernel=kernel, use_chat=True)
+
+service_id = "default"
+
+# The following execution settings are used for the ConversationSummaryPlugin
+execution_settings = PromptExecutionSettings(
+    service_id=service_id, max_tokens=ConversationSummaryPlugin._max_tokens, temperature=0.1, top_p=0.5
+)
+prompt_template_config = PromptTemplateConfig(
+    template=ConversationSummaryPlugin._summarize_conversation_prompt_template,
+    description="Given a section of a conversation transcript, summarize the part of" " the conversation.",
+    execution_settings=execution_settings,
+)
+
+# Import the ConversationSummaryPlugin
+kernel.add_plugin(
+    ConversationSummaryPlugin(kernel=kernel, prompt_template_config=prompt_template_config),
+    plugin_name="ConversationSummaryPlugin",
+)
+
+
+# <FunctionFromPrompt>
+# Create the function with the prompt
+kernel.add_function(
+    prompt_template_config=PromptTemplateConfig(
+        template="""{{ConversationSummaryPlugin.SummarizeConversation $history}}
+User: {{$request}}
+Assistant:  """,
         description="Chat with the assistant",
-        execution_settings=execution_settings,
+        execution_settings=[
+            PromptExecutionSettings(service_id="default", temperature=0.0, max_tokens=1000),
+            PromptExecutionSettings(service_id="gpt-3.5-turbo", temperature=0.2, max_tokens=4000),
+            PromptExecutionSettings(service_id="gpt-4", temperature=0.3, max_tokens=8000),
+        ],
         input_variables=[
             InputVariable(name="request", description="The user input", is_required=True),
-            InputVariable(name="history", description="The history of the conversation", is_required=True),
+            InputVariable(
+                name="history",
+                description="The history of the conversation",
+                is_required=True,
+                allow_dangerously_set_content=True,
+            ),
         ],
-    )
+    ),
+    plugin_name="Summarize_Conversation",
+    function_name="Chat",
+    description="Chat with the assistant",
+)
+# </FunctionFromPrompt>
+
+# Create the history
+history = ChatHistory()
 
-    # Create the function
-    chat_function = kernel.add_function(
-        prompt=prompt,
-        plugin_name="Summarize_Conversation",
-        function_name="Chat",
-        description="Chat with the assistant",
-        prompt_template_config=chat_prompt_template_config,
-    )
 
+async def main():
     while True:
         try:
             request = input("User:> ")
-        except KeyboardInterrupt:
-            print("\n\nExiting chat...")
-            return False
-        except EOFError:
-            print("\n\nExiting chat...")
-            return False
-
+        except (KeyboardInterrupt, EOFError):
+            break
         if request == "exit":
-            print("\n\nExiting chat...")
-            return False
+            break
 
         result = await kernel.invoke(
-            chat_function,
+            plugin_name="Summarize_Conversation",
+            function_name="Chat",
             request=request,
             history=history,
         )
@@ -92,6 +91,8 @@ async def main():
 
         print(f"Assistant:> {result}")
 
+    print("\n\nExiting chat...")
+
 
 # Run the main function
 if __name__ == "__main__":

python/samples/learn_resources/creating_functions.py

@@ -3,31 +3,65 @@
 import asyncio
 import os
 
-from service_configurator import add_service
+from sk_service_configurator import add_service
 
-import semantic_kernel as sk
+from semantic_kernel import Kernel
+from semantic_kernel.connectors.ai.function_call_behavior import FunctionCallBehavior
+from semantic_kernel.connectors.ai.open_ai import OpenAIChatPromptExecutionSettings
+from semantic_kernel.contents import ChatHistory
 
 
 async def main():
     # Initialize the kernel
-    kernel = sk.Kernel()
-
-    # Add the service to the kernel
-    # use_chat: True to use chat completion, False to use text completion
-    kernel = add_service(kernel=kernel, use_chat=True)
+    kernel = Kernel()
 
     # Import the MathPlugin.
-    script_directory = os.path.dirname(__file__)
-    plugins_directory = os.path.join(script_directory, "plugins")
-    math_plugin = kernel.import_native_plugin_from_directory(plugins_directory, "MathPlugin")
+    # <RunningNativeFunction>
+    plugins_directory = os.path.join(os.path.dirname(__file__), "plugins")
+    math_plugin = kernel.add_plugin(parent_directory=plugins_directory, plugin_name="MathPlugin")
 
     result = await kernel.invoke(
-        math_plugin["Add"],
-        number1=5,
-        number2=5,
+        math_plugin["Sqrt"],
+        number1=12,
     )
 
     print(result)
+    # </RunningNativeFunction>
+
+    # <Chat>
+    kernel = add_service(kernel, use_chat=True)
+    kernel.add_function(
+        prompt="""{{$chat_history}}{{$input}}""",
+        execution_settings=OpenAIChatPromptExecutionSettings(
+            service_id="default",
+            temperature=0.0,
+            max_tokens=1000,
+            function_call_behavior=FunctionCallBehavior.AutoInvokeKernelFunctions(),
+        ),
+        plugin_name="Chat",
+        function_name="Chat",
+        description="Chat with the assistant",
+    )
+    chat_history = ChatHistory()
+    while True:
+        try:
+            request = input("Your request: ")
+        except (KeyboardInterrupt, EOFError):
+            break
+        if request.lower() == "exit":
+            break
+        result = await kernel.invoke(
+            plugin_name="Chat",
+            function_name="Chat",
+            input=request,
+            chat_history=chat_history,
+        )
+        print(result)
+        chat_history.add_user_message(request)
+        chat_history.add_assistant_message(str(result))
+
+    print("\n\nExiting...")
+    # </Chat>
 
 
 # Run the main function