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 azure.core.credentials import TokenCredential
+from azure.identity import AzureCliCredential
+
+from semantic_kernel.agents import AgentGroupChat, AzureAssistantAgent, ChatCompletionAgent
+from semantic_kernel.agents.strategies import TerminationStrategy
+from semantic_kernel.connectors.ai.open_ai import AzureChatCompletion, AzureOpenAISettings
+from semantic_kernel.contents import AuthorRole
+from semantic_kernel.kernel import Kernel
+
+"""
+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.
+
+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+no longer maintained.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
+"""
+
+
+class ApprovalTerminationStrategy(TerminationStrategy):
+    """A strategy for determining when an agent should terminate."""
+
+    async def should_agent_terminate(self, agent, history):
+        """Check if the agent should terminate."""
+        return "approved" in history[-1].content.lower()
+
+
+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 a ChatCompletionAgent
+    agent_reviewer = ChatCompletionAgent(
+        kernel=_create_kernel_with_chat_completion("artdirector", credential),
+        name="ArtDirector",
+        instructions="""
+            You are an art director who has opinions about copywriting born of a love for David Ogilvy.
+            The goal is to determine if the given copy is acceptable to print.
+            If so, state that it is approved. Only include the word "approved" if it is so.
+            If not, provide insight on how to refine suggested copy without example.
+            """,
+    )
+
+    # 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="""
+        You are a copywriter with ten years of experience and are known for brevity and a dry humor.
+        The goal is to refine and decide on the single best copy as an expert in the field.
+        Only provide a single proposal per response.
+        You're laser focused on the goal at hand.
+        Don't waste time with chit chat.
+        Consider suggestions when refining an idea.
+        """,
+    )
+
+    # Create the AzureAssistantAgent instance using the client and the assistant definition
+    agent_writer = AzureAssistantAgent(
+        client=client,
+        definition=definition,
+    )
+
+    # Create the AgentGroupChat object, which will manage the chat between the agents
+    chat = AgentGroupChat(
+        agents=[agent_writer, agent_reviewer],
+        termination_strategy=ApprovalTerminationStrategy(agents=[agent_reviewer], maximum_iterations=10),
+    )
+
+    input = "a slogan for a new line of electric cars."
+
+    try:
+        await chat.add_chat_message(input)
+        print(f"# {AuthorRole.USER}: '{input}'")
+
+        last_agent = None
+        async for message in chat.invoke_stream():
+            if message.content is not None:
+                if last_agent != message.name:
+                    print(f"\n# {message.name}: ", end="", flush=True)
+                    last_agent = message.name
+                print(f"{message.content}", end="", flush=True)
+
+        print()
+        print(f"# IS COMPLETE: {chat.is_complete}")
+    finally:
+        await agent_writer.client.beta.assistants.delete(agent_writer.id)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())