chore: import upstream snapshot with attribution

2026-07-13 13:21:23 +08:00
commit b957a53def
5423 changed files with 863745 additions and 0 deletions
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+# Copyright (c) Microsoft. All rights reserved.
+
+import asyncio
+from typing import TYPE_CHECKING
+
+from azure.core.credentials import TokenCredential
+from azure.identity import AzureCliCredential
+
+from semantic_kernel.agents import AgentGroupChat, AzureAssistantAgent, ChatCompletionAgent
+from semantic_kernel.connectors.ai.open_ai import AzureChatCompletion, AzureOpenAISettings
+from semantic_kernel.contents import AuthorRole
+from semantic_kernel.kernel import Kernel
+
+if TYPE_CHECKING:
+    pass
+
+"""
+The following sample demonstrates how to create an OpenAI
+assistant using either Azure OpenAI or OpenAI, a chat completion
+agent and have them participate in a group chat to work towards
+the user's requirement. It also demonstrates how the underlying
+agent reset method is used to clear the current state of the chat
+
+Note: This sample use the `AgentGroupChat` feature of Semantic Kernel, which is
+no longer maintained. For a replacement, consider using the `GroupChatOrchestration`.
+
+Read more about the `GroupChatOrchestration` here:
+https://learn.microsoft.com/semantic-kernel/frameworks/agent/agent-orchestration/group-chat?pivots=programming-language-python
+
+Here is a migration guide from `AgentGroupChat` to `GroupChatOrchestration`:
+https://learn.microsoft.com/semantic-kernel/support/migration/group-chat-orchestration-migration-guide?pivots=programming-language-python
+"""
+
+
+def _create_kernel_with_chat_completion(service_id: str, credential: TokenCredential) -> Kernel:
+    kernel = Kernel()
+    kernel.add_service(AzureChatCompletion(service_id=service_id, credential=credential))
+    return kernel
+
+
+async def main():
+    credential = AzureCliCredential()
+
+    # First create the ChatCompletionAgent
+    chat_agent = ChatCompletionAgent(
+        kernel=_create_kernel_with_chat_completion("chat", credential),
+        name="chat_agent",
+        instructions="""
+            The user may either provide information or query on information previously provided. 
+            If the query does not correspond with information provided, inform the user that their query 
+            cannot be answered.
+            """,
+    )
+
+    # Next, we will create the AzureAssistantAgent
+
+    # Create the client using Azure OpenAI resources and configuration
+    client = AzureAssistantAgent.create_client(credential=credential)
+
+    # Create the assistant definition
+    definition = await client.beta.assistants.create(
+        model=AzureOpenAISettings().chat_deployment_name,
+        name="copywriter",
+        instructions="""
+            The user may either provide information or query on information previously provided. 
+            If the query does not correspond with information provided, inform the user that their query 
+            cannot be answered.
+            """,
+    )
+
+    # Create the AzureAssistantAgent instance using the client and the assistant definition
+    assistant_agent = AzureAssistantAgent(
+        client=client,
+        definition=definition,
+    )
+
+    # Create the AgentGroupChat object, which will manage the chat between the agents
+    # We don't always need to specify the agents in the chat up front
+    # As shown below, calling `chat.invoke(agent=<agent>)` will automatically add the
+    # agent to the chat
+    chat = AgentGroupChat()
+
+    try:
+        user_inputs = [
+            "What is my favorite color?",
+            "I like green.",
+            "What is my favorite color?",
+            "[RESET]",
+            "What is my favorite color?",
+        ]
+
+        for user_input in user_inputs:
+            # Check for reset indicator
+            if user_input == "[RESET]":
+                print("\nResetting chat...")
+                await chat.reset()
+                continue
+
+            # First agent (assistant_agent) receives the user input
+            await chat.add_chat_message(user_input)
+            print(f"\n{AuthorRole.USER}: '{user_input}'")
+            async for message in chat.invoke(agent=assistant_agent):
+                if message.content is not None:
+                    print(f"\n# {message.role} - {message.name or '*'}: '{message.content}'")
+
+            # Second agent (chat_agent) just responds without new user input
+            async for message in chat.invoke(agent=chat_agent):
+                if message.content is not None:
+                    print(f"\n# {message.role} - {message.name or '*'}: '{message.content}'")
+    finally:
+        await chat.reset()
+        await assistant_agent.client.beta.assistants.delete(assistant_agent.id)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())