Python: restructure: Python samples into progressive 01-05 layout (#3862)

* restructure: Python samples into progressive 01-05 layout - 01-get-started/: 6 numbered steps (hello agent → hosting) - 02-agents/: all agent concept samples (tools, middleware, providers, etc.) - 03-workflows/: ALL existing workflow samples preserved as-is - 04-hosting/: azure-functions, durabletask, a2a - 05-end-to-end/: demos, evaluation, hosted agents - Old files moved to _to_delete/ for review - Added AGENTS.md with structure documentation - autogen-migration/ and semantic-kernel-migration/ preserved at root * fix: switch to AzureOpenAI Foundry, fix CI failures - Switch all 01-get-started samples to AzureOpenAIResponsesClient with Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT + AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential) - Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes - Fix test paths in packages/ that referenced old getting_started/ dirs: durabletask conftest + streaming test, azurefunctions conftest, devui conftest + capture_messages + openai_sdk_integration - Fix workflow_as_agent_human_in_the_loop.py import (sibling import) - Update hosting READMEs and tool comment paths - Replace root README.md with new structure overview - Update AGENTS.md to document Azure OpenAI Foundry as default provider * cleanup: remove _to_delete folder, copy resource files to active dirs All files in _to_delete/ were either: - Exact duplicates of files in the new structure (240 files) - Same file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since active samples reference them. * fix: address PR review comments, centralize resources, remove root duplicates - Fix type annotation in 04_memory.py (string union -> proper types) - Fix old sample paths in observability files - Fix grammar/spelling in observability samples - Move sample_assets/ and resources/ to shared/ folder - Remove 8 duplicate observability files from 02-agents root - Update resource path references in multimodal_input and provider samples * fix: update broken links from old getting_started paths to new structure - Update relative paths in READMEs: getting_started/ → 01-get-started/, 02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/ - Fix absolute GitHub URLs in package READMEs - Fix broken link in ollama package README * fix: convert absolute GitHub URLs to relative paths for link checker Absolute URLs to python/samples/ on main branch 404 until PR merges. Converted to relative paths that linkspector can verify locally. * fix: update link for handoff sample moved to orchestrations/ * fix: update chatkit-integration README path from demos/ to 05-end-to-end/ * fix: update broken links in orchestrations README to match flat directory structure
2026-06-16 21:04:09 +08:00 · 2026-02-12 17:36:36 +00:00
parent 69dcfe31ee
commit a2856d3b92
536 changed files with 3816 additions and 1632 deletions
@@ -0,0 +1,73 @@
+# Single Agent
+
+This sample demonstrates how to create a worker-client setup that hosts a single AI agent and provides interactive conversation via the Durable Task Scheduler.
+
+## Key Concepts Demonstrated
+
+- Using the Microsoft Agent Framework to define a simple AI agent with a name and instructions.
+- Registering durable agents with the worker and interacting with them via a client.
+- Conversation management (via threads) for isolated interactions.
+- Worker-client architecture for distributed agent execution.
+
+## Environment Setup
+
+See the [README.md](../README.md) file in the parent directory for more information on how to configure the environment, including how to install and run common sample dependencies.
+
+## Running the Sample
+
+With the environment setup, you can run the sample using the combined approach or separate worker and client processes:
+
+**Option 1: Combined (Recommended for Testing)**
+
+```bash
+cd samples/04-hosting/durabletask/01_single_agent
+python sample.py
+```
+
+**Option 2: Separate Processes**
+
+Start the worker in one terminal:
+
+```bash
+python worker.py
+```
+
+In a new terminal, run the client:
+
+```bash
+python client.py
+```
+
+The client will interact with the Joker agent:
+
+```
+Starting Durable Task Agent Client...
+Using taskhub: default
+Using endpoint: http://localhost:8080
+
+Getting reference to Joker agent...
+Created conversation thread: a1b2c3d4-e5f6-7890-abcd-ef1234567890
+
+User: Tell me a short joke about cloud computing.
+
+Joker: Why did the cloud break up with the server?
+Because it found someone more "uplifting"!
+
+User: Now tell me one about Python programming.
+
+Joker: Why do Python programmers prefer dark mode?
+Because light attracts bugs!
+```
+
+## Viewing Agent State
+
+You can view the state of the agent in the Durable Task Scheduler dashboard:
+
+1. Open your browser and navigate to `http://localhost:8082`
+2. In the dashboard, you can view:
+   - The state of the Joker agent entity (dafx-Joker)
+   - Conversation history and current state
+   - How the durable agents extension manages conversation context
+
+
+
@@ -0,0 +1,121 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Client application for interacting with a Durable Task hosted agent.
+
+This client connects to the Durable Task Scheduler and sends requests to
+registered agents, demonstrating how to interact with agents from external processes.
+
+Prerequisites:
+- The worker must be running with the agent registered
+- Set AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_CHAT_DEPLOYMENT_NAME
+  (plus AZURE_OPENAI_API_KEY or Azure CLI authentication)
+- Durable Task Scheduler must be running
+"""
+
+import asyncio
+import logging
+import os
+
+from agent_framework.azure import DurableAIAgentClient
+from azure.identity import DefaultAzureCredential
+from durabletask.azuremanaged.client import DurableTaskSchedulerClient
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+
+def get_client(
+    taskhub: str | None = None,
+    endpoint: str | None = None,
+    log_handler: logging.Handler | None = None
+) -> DurableAIAgentClient:
+    """Create a configured DurableAIAgentClient.
+
+    Args:
+        taskhub: Task hub name (defaults to TASKHUB env var or "default")
+        endpoint: Scheduler endpoint (defaults to ENDPOINT env var or "http://localhost:8080")
+        log_handler: Optional logging handler for client logging
+
+    Returns:
+        Configured DurableAIAgentClient instance
+    """
+    taskhub_name = taskhub or os.getenv("TASKHUB", "default")
+    endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080")
+
+    logger.debug(f"Using taskhub: {taskhub_name}")
+    logger.debug(f"Using endpoint: {endpoint_url}")
+
+    credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential()
+
+    dts_client = DurableTaskSchedulerClient(
+        host_address=endpoint_url,
+        secure_channel=endpoint_url != "http://localhost:8080",
+        taskhub=taskhub_name,
+        token_credential=credential,
+        log_handler=log_handler
+    )
+
+    return DurableAIAgentClient(dts_client)
+
+
+def run_client(agent_client: DurableAIAgentClient) -> None:
+    """Run client interactions with the Joker agent.
+
+    Args:
+        agent_client: The DurableAIAgentClient instance
+    """
+    # Get a reference to the Joker agent
+    logger.debug("Getting reference to Joker agent...")
+    joker = agent_client.get_agent("Joker")
+
+    # Create a new thread for the conversation
+    thread = joker.get_new_thread()
+    logger.debug(f"Thread ID: {thread.session_id}")
+    logger.info("Start chatting with the Joker agent! (Type 'exit' to quit)")
+
+    # Interactive conversation loop
+    while True:
+        # Get user input
+        try:
+            user_message = input("You: ").strip()
+        except (EOFError, KeyboardInterrupt):
+            logger.info("\nExiting...")
+            break
+
+        # Check for exit command
+        if user_message.lower() == "exit":
+            logger.info("Goodbye!")
+            break
+
+        # Skip empty messages
+        if not user_message:
+            continue
+
+        # Send message to agent and get response
+        try:
+            response = joker.run(user_message, thread=thread)
+            logger.info(f"Joker: {response.text} \n")
+        except Exception as e:
+            logger.error(f"Error getting response: {e}")
+
+    logger.info("Conversation completed.")
+
+
+async def main() -> None:
+    """Main entry point for the client application."""
+    logger.debug("Starting Durable Task Agent Client...")
+
+    # Create client using helper function
+    agent_client = get_client()
+
+    try:
+        run_client(agent_client)
+    except Exception as e:
+        logger.exception(f"Error during agent interaction: {e}")
+    finally:
+        logger.debug("Client shutting down")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())
@@ -0,0 +1,12 @@
+# Agent Framework packages
+# To use the deployed version, uncomment the line below and comment out the local installation lines
+# agent-framework-durabletask
+
+# Local installation (for development and testing)
+# Each package must be listed explicitly because pip doesn't resolve uv workspace sources.
+# Without explicit entries, pip would fetch transitive dependencies from PyPI instead of local source.
+-e ../../../../packages/core  # Core framework - base dependency for all packages
+-e ../../../../packages/durabletask  # Durable Task support - the main package for this sample
+
+# Azure authentication
+azure-identity
@@ -0,0 +1,59 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Single Agent Sample - Durable Task Integration (Combined Worker + Client)
+
+This sample demonstrates running both the worker and client in a single process.
+The worker is started first to register the agent, then client operations are
+performed against the running worker.
+
+Prerequisites:
+- Set AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_CHAT_DEPLOYMENT_NAME
+  (plus AZURE_OPENAI_API_KEY or Azure CLI authentication)
+- Durable Task Scheduler must be running (e.g., using Docker)
+
+To run this sample:
+    python sample.py
+"""
+
+import logging
+
+# Import helper functions from worker and client modules
+from client import get_client, run_client
+from dotenv import load_dotenv
+from worker import get_worker, setup_worker
+
+# Configure logging (must be after imports to override their basicConfig)
+logging.basicConfig(level=logging.INFO, force=True)
+logger = logging.getLogger(__name__)
+
+
+def main():
+    """Main entry point - runs both worker and client in single process."""
+    logger.debug("Starting Durable Task Agent Sample (Combined Worker + Client)...")
+
+    silent_handler = logging.NullHandler()
+
+    # Create and start the worker using helper function and context manager
+    with get_worker(log_handler=silent_handler) as dts_worker:
+        # Register agents using helper function
+        setup_worker(dts_worker)
+
+        # Start the worker
+        dts_worker.start()
+        logger.debug("Worker started and listening for requests...")
+
+        # Create the client using helper function
+        agent_client = get_client(log_handler=silent_handler)
+
+        try:
+            # Run client interactions using helper function
+            run_client(agent_client)
+        except Exception as e:
+            logger.exception(f"Error during agent interaction: {e}")
+
+        logger.debug("Sample completed. Worker shutting down...")
+
+
+if __name__ == "__main__":
+    load_dotenv()
+    main()
@@ -0,0 +1,123 @@
+# Copyright (c) Microsoft. All rights reserved.
+
+"""Worker process for hosting a single Azure OpenAI-powered agent using Durable Task.
+
+This worker registers agents as durable entities and continuously listens for requests.
+The worker should run as a background service, processing incoming agent requests.
+
+Prerequisites:
+- Set AZURE_OPENAI_ENDPOINT and AZURE_OPENAI_CHAT_DEPLOYMENT_NAME
+  (plus AZURE_OPENAI_API_KEY or Azure CLI authentication)
+- Start a Durable Task Scheduler (e.g., using Docker)
+"""
+
+import asyncio
+import logging
+import os
+
+from agent_framework import Agent
+from agent_framework.azure import AzureOpenAIChatClient, DurableAIAgentWorker
+from azure.identity import AzureCliCredential, DefaultAzureCredential
+from durabletask.azuremanaged.worker import DurableTaskSchedulerWorker
+
+# Configure logging
+logging.basicConfig(level=logging.WARNING)
+logger = logging.getLogger(__name__)
+
+
+def create_joker_agent() -> Agent:
+    """Create the Joker agent using Azure OpenAI.
+
+    Returns:
+        Agent: The configured Joker agent
+    """
+    return AzureOpenAIChatClient(credential=AzureCliCredential()).as_agent(
+        name="Joker",
+        instructions="You are good at telling jokes.",
+    )
+
+
+def get_worker(
+    taskhub: str | None = None,
+    endpoint: str | None = None,
+    log_handler: logging.Handler | None = None
+) -> DurableTaskSchedulerWorker:
+    """Create a configured DurableTaskSchedulerWorker.
+
+    Args:
+        taskhub: Task hub name (defaults to TASKHUB env var or "default")
+        endpoint: Scheduler endpoint (defaults to ENDPOINT env var or "http://localhost:8080")
+        log_handler: Optional logging handler for worker logging
+
+    Returns:
+        Configured DurableTaskSchedulerWorker instance
+    """
+    taskhub_name = taskhub or os.getenv("TASKHUB", "default")
+    endpoint_url = endpoint or os.getenv("ENDPOINT", "http://localhost:8080")
+
+    logger.debug(f"Using taskhub: {taskhub_name}")
+    logger.debug(f"Using endpoint: {endpoint_url}")
+
+    credential = None if endpoint_url == "http://localhost:8080" else DefaultAzureCredential()
+
+    return DurableTaskSchedulerWorker(
+        host_address=endpoint_url,
+        secure_channel=endpoint_url != "http://localhost:8080",
+        taskhub=taskhub_name,
+        token_credential=credential,
+        log_handler=log_handler
+    )
+
+
+def setup_worker(worker: DurableTaskSchedulerWorker) -> DurableAIAgentWorker:
+    """Set up the worker with agents registered.
+
+    Args:
+        worker: The DurableTaskSchedulerWorker instance
+
+    Returns:
+        DurableAIAgentWorker with agents registered
+    """
+    # Wrap it with the agent worker
+    agent_worker = DurableAIAgentWorker(worker)
+
+    # Create and register the Joker agent
+    logger.debug("Creating and registering Joker agent...")
+    joker_agent = create_joker_agent()
+    agent_worker.add_agent(joker_agent)
+
+    logger.debug(f"✓ Registered agent: {joker_agent.name}")
+    logger.debug(f"  Entity name: dafx-{joker_agent.name}")
+
+    return agent_worker
+
+
+async def main():
+    """Main entry point for the worker process."""
+    logger.debug("Starting Durable Task Agent Worker...")
+
+    # Create a worker using the helper function
+    worker = get_worker()
+
+    # Setup worker with agents
+    setup_worker(worker)
+
+    logger.info("Worker is ready and listening for requests...")
+    logger.info("Press Ctrl+C to stop.")
+    logger.info("")
+
+    try:
+        # Start the worker (this blocks until stopped)
+        worker.start()
+
+        # Keep the worker running
+        while True:
+            await asyncio.sleep(1)
+    except KeyboardInterrupt:
+        logger.debug("Worker shutdown initiated")
+
+    logger.debug("Worker stopped")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())