chore: import upstream snapshot with attribution

examples/integrations/ms-agent-framework-python/agent/.python-version

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+3.12

examples/integrations/ms-agent-framework-python/agent/pyproject.toml

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+[project]
+name = "agent"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = ["agent-framework-ag-ui>=1.0.0b251117", "python-dotenv"]

examples/integrations/ms-agent-framework-python/agent/src/agent.py

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+from __future__ import annotations
+
+from textwrap import dedent
+from typing import Annotated
+
+from agent_framework import ChatAgent, ChatClientProtocol, ai_function
+from agent_framework_ag_ui import AgentFrameworkAgent
+from pydantic import Field
+
+STATE_SCHEMA: dict[str, object] = {
+    "proverbs": {
+        "type": "array",
+        "items": {"type": "string"},
+        "description": "Ordered list of the user's saved proverbs.",
+    }
+}
+
+PREDICT_STATE_CONFIG: dict[str, dict[str, str]] = {
+    "proverbs": {
+        "tool": "update_proverbs",
+        "tool_argument": "proverbs",
+    }
+}
+
+
+@ai_function(
+    name="update_proverbs",
+    description=(
+        "Replace the entire list of proverbs with the provided values. "
+        "Always include every proverb you want to keep."
+    ),
+)
+def update_proverbs(
+    proverbs: Annotated[
+        list[str],
+        Field(
+            description=(
+                "The complete source of truth for the user's proverbs. "
+                "Maintain ordering and include the full list on each call."
+            )
+        ),
+    ],
+) -> str:
+    """Persist the provided set of proverbs."""
+    return f"Proverbs updated. Tracking {len(proverbs)} item(s)."
+
+
+@ai_function(
+    name="get_weather",
+    description="Share a quick weather update for a location. Use this to render the frontend weather card.",
+)
+def get_weather(
+    location: Annotated[
+        str,
+        Field(
+            description="The city or region to describe. Use fully spelled out names."
+        ),
+    ],
+) -> str:
+    """Return a short natural language weather summary."""
+    normalized = location.strip().title() or "the requested location"
+    return (
+        f"The weather in {normalized} is mild with a light breeze. "
+        "Skies are mostly clear—perfect for planning something fun."
+    )
+
+
+@ai_function(
+    name="go_to_moon",
+    description="Request a playful human-in-the-loop confirmation before launching a mission to the moon.",
+    approval_mode="always_require",
+)
+def go_to_moon() -> str:
+    """Request human approval before continuing."""
+    return "Mission control requested. Awaiting human approval for the lunar launch."
+
+
+def create_agent(chat_client: ChatClientProtocol) -> AgentFrameworkAgent:
+    """Instantiate the CopilotKit demo agent backed by Microsoft Agent Framework."""
+    base_agent = ChatAgent(
+        name="proverbs_agent",
+        instructions=dedent(
+            """
+            You help users brainstorm, organize, and refine proverbs while coordinating UI updates.
+
+            State sync:
+            - The current list of proverbs is provided in the conversation context.
+            - When you add, remove, or reorder proverbs, call `update_proverbs` with the full list.
+              Never send partial updates—always include every proverb that should exist.
+            - CRITICAL: When asked to "add" a proverb, you must:
+              1. First, identify ALL existing proverbs from the conversation history
+              2. Create EXACTLY ONE new proverb (never more than one unless explicitly requested)
+              3. Call update_proverbs with: [all existing proverbs] + [the one new proverb]
+              Example: Current: ["A", "B"] -> After adding: ["A", "B", "C"] (NOT ["A", "B", "C", "D", "E"])
+            - When asked to "remove" a proverb, remove exactly ONE item unless user specifies otherwise.
+
+            Tool usage rules:
+            - When user asks to go to the moon, you MUST call the `go_to_moon` tool immediately. Do NOT ask for approval
+              yourself—the tool's approval workflow and the client UI will handle it.
+
+            Frontend integrations:
+            - `get_weather` renders a weather card in the UI. Only call this tool when the user explicitly
+              asks for weather. Do NOT call it after unrelated tasks or approvals.
+            - `go_to_moon` requires explicit user approval before you proceed. Only use it when a
+              user asks to launch or travel to the moon. Always call the tool instead of asking manually.
+
+            Conversation tips:
+            - Reference the latest proverb list before suggesting changes.
+            - Keep responses concise and friendly unless the user requests otherwise.
+            - After you finish executing tools for the user's request, provide a brief, final assistant
+              message summarizing exactly what changed. Do NOT call additional tools or switch topics
+              after that summary unless the user asks. ALWAYS send this conversational summary so the message persists.
+            """.strip()
+        ),
+        chat_client=chat_client,
+        tools=[update_proverbs, get_weather, go_to_moon],
+    )
+
+    return AgentFrameworkAgent(
+        agent=base_agent,
+        name="CopilotKitMicrosoftAgentFrameworkAgent",
+        description="Manages proverbs, weather snippets, and human-in-the-loop moon launches.",
+        state_schema=STATE_SCHEMA,
+        predict_state_config=PREDICT_STATE_CONFIG,
+        require_confirmation=False,  # Allow immediate state updates with follow-up messages
+    )

examples/integrations/ms-agent-framework-python/agent/src/main.py

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+from __future__ import annotations
+
+import os
+
+import uvicorn
+from agent_framework._clients import ChatClientProtocol
+from azure.identity import DefaultAzureCredential
+from agent_framework.azure import AzureOpenAIChatClient
+from agent_framework.openai import OpenAIChatClient
+from agent_framework_ag_ui import add_agent_framework_fastapi_endpoint
+from dotenv import load_dotenv
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+
+from agent import create_agent
+
+load_dotenv()
+
+
+def _build_chat_client() -> ChatClientProtocol:
+    try:
+        if bool(os.getenv("AZURE_OPENAI_ENDPOINT")):
+            # Azure OpenAI setup - uses environment variables by default
+            # Optionally can pass deployment_name explicitly
+            deployment_name = os.getenv(
+                "AZURE_OPENAI_CHAT_DEPLOYMENT_NAME", "gpt-4o-mini"
+            )
+            return AzureOpenAIChatClient(
+                credential=DefaultAzureCredential(),
+                deployment_name=deployment_name,
+                endpoint=os.getenv("AZURE_OPENAI_ENDPOINT"),
+            )
+
+        if bool(os.getenv("OPENAI_API_KEY")):
+            # OpenAI setup - requires explicit model_id and api_key
+            return OpenAIChatClient(
+                model_id=os.getenv("OPENAI_CHAT_MODEL_ID", "gpt-4o-mini"),
+                api_key=os.getenv("OPENAI_API_KEY"),
+            )
+
+        raise ValueError(
+            "Either AZURE_OPENAI_ENDPOINT or OPENAI_API_KEY environment variable is required"
+        )
+
+    except Exception as exc:  # pragma: no cover
+        raise RuntimeError(
+            "Unable to initialize the chat client. Double-check your API credentials as documented in README.md."
+        ) from exc
+
+
+chat_client = _build_chat_client()
+my_agent = create_agent(chat_client)
+
+app = FastAPI(title="CopilotKit + Microsoft Agent Framework (Python)")
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+
+add_agent_framework_fastapi_endpoint(
+    app=app,
+    agent=my_agent,
+    path="/",
+)
+
+
+@app.get("/health")
+async def health():
+    return {"status": "ok"}
+
+
+if __name__ == "__main__":
+    host = os.getenv("AGENT_HOST", "0.0.0.0")
+    port = int(os.getenv("AGENT_PORT", "8000"))
+    uvicorn.run("main:app", host=host, port=port, reload=True)