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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file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since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
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Eduard van Valkenburg
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# Customer Support Workflow Sample
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Multi-agent workflow demonstrating automated troubleshooting with escalation paths.
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## Overview
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Coordinates six specialized agents to handle customer support requests:
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1. **SelfServiceAgent** - Initial troubleshooting with user
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2. **TicketingAgent** - Creates tickets when escalation needed
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3. **TicketRoutingAgent** - Routes to appropriate team
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4. **WindowsSupportAgent** - Windows-specific troubleshooting
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5. **TicketResolutionAgent** - Resolves tickets
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6. **TicketEscalationAgent** - Escalates to human support
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## Files
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- `workflow.yaml` - Workflow definition with conditional routing
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- `main.py` - Agent definitions and workflow execution
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- `ticketing_plugin.py` - Mock ticketing system plugin
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## Running
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```bash
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python main.py
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```
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## Example Input
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```
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My PC keeps rebooting and I can't use it.
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```
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## Requirements
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- Azure OpenAI endpoint configured
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- `az login` for authentication
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@@ -0,0 +1 @@
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# Copyright (c) Microsoft. All rights reserved.
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@@ -0,0 +1,347 @@
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# Copyright (c) Microsoft. All rights reserved.
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"""
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CustomerSupport workflow sample.
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This workflow demonstrates using multiple agents to provide automated
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troubleshooting steps to resolve common issues with escalation options.
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Example input: "My PC keeps rebooting and I can't use it."
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Usage:
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python main.py
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The workflow:
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1. SelfServiceAgent: Works with user to provide troubleshooting steps
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2. TicketingAgent: Creates a ticket if issue needs escalation
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3. TicketRoutingAgent: Determines which team should handle the ticket
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4. WindowsSupportAgent: Provides Windows-specific troubleshooting
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5. TicketResolutionAgent: Resolves the ticket when issue is fixed
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6. TicketEscalationAgent: Escalates to human support if needed
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"""
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import asyncio
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import json
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import logging
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import os
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import uuid
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from pathlib import Path
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from agent_framework.azure import AzureOpenAIResponsesClient
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from agent_framework.declarative import (
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AgentExternalInputRequest,
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AgentExternalInputResponse,
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WorkflowFactory,
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)
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from azure.identity import AzureCliCredential
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from pydantic import BaseModel, Field
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from ticketing_plugin import TicketingPlugin
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logging.basicConfig(level=logging.ERROR)
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# ANSI color codes for output formatting
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CYAN = "\033[36m"
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GREEN = "\033[32m"
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YELLOW = "\033[33m"
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MAGENTA = "\033[35m"
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RESET = "\033[0m"
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# Agent Instructions
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SELF_SERVICE_INSTRUCTIONS = """
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Use your knowledge to work with the user to provide the best possible troubleshooting steps.
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- If the user confirms that the issue is resolved, then the issue is resolved.
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- If the user reports that the issue persists, then escalate.
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""".strip()
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TICKETING_INSTRUCTIONS = """Always create a ticket in Azure DevOps using the available tools.
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Include the following information in the TicketSummary.
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- Issue description: {{IssueDescription}}
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- Attempted resolution steps: {{AttemptedResolutionSteps}}
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After creating the ticket, provide the user with the ticket ID."""
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TICKET_ROUTING_INSTRUCTIONS = """Determine how to route the given issue to the appropriate support team.
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Choose from the available teams and their functions:
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- Windows Activation Support: Windows license activation issues
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- Windows Support: Windows related issues
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- Azure Support: Azure related issues
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- Network Support: Network related issues
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- Hardware Support: Hardware related issues
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- Microsoft Office Support: Microsoft Office related issues
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- General Support: General issues not related to the above categories"""
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WINDOWS_SUPPORT_INSTRUCTIONS = """
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Use your knowledge to work with the user to provide the best possible troubleshooting steps
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for issues related to Windows operating system.
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- Utilize the "Attempted Resolutions Steps" as a starting point for your troubleshooting.
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- Never escalate without troubleshooting with the user.
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- If the user confirms that the issue is resolved, then the issue is resolved.
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- If the user reports that the issue persists, then escalate.
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Issue: {{IssueDescription}}
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Attempted Resolution Steps: {{AttemptedResolutionSteps}}"""
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RESOLUTION_INSTRUCTIONS = """Resolve the following ticket in Azure DevOps.
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Always include the resolution details.
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- Ticket ID: #{{TicketId}}
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- Resolution Summary: {{ResolutionSummary}}"""
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ESCALATION_INSTRUCTIONS = """
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You escalate the provided issue to human support team by sending an email.
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Here are some additional details that might help:
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- TicketId : {{TicketId}}
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- IssueDescription : {{IssueDescription}}
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- AttemptedResolutionSteps : {{AttemptedResolutionSteps}}
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Before escalating, gather the user's email address for follow-up.
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If not known, ask the user for their email address so that the support team can reach them when needed.
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When sending the email, include the following details:
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- To: support@contoso.com
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- Cc: user's email address
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- Subject of the email: "Support Ticket - {TicketId} - [Compact Issue Description]"
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- Body:
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- Issue description
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- Attempted resolution steps
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- User's email address
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- Any other relevant information from the conversation history
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Assure the user that their issue will be resolved and provide them with a ticket ID for reference."""
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# Pydantic models for structured outputs
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class SelfServiceResponse(BaseModel):
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"""Response from self-service agent evaluation."""
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IsResolved: bool = Field(description="True if the user issue/ask has been resolved.")
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NeedsTicket: bool = Field(description="True if the user issue/ask requires that a ticket be filed.")
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IssueDescription: str = Field(description="A concise description of the issue.")
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AttemptedResolutionSteps: str = Field(description="An outline of the steps taken to attempt resolution.")
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class TicketingResponse(BaseModel):
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"""Response from ticketing agent."""
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TicketId: str = Field(description="The identifier of the ticket created in response to the user issue.")
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TicketSummary: str = Field(description="The summary of the ticket created in response to the user issue.")
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class RoutingResponse(BaseModel):
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"""Response from routing agent."""
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TeamName: str = Field(description="The name of the team to route the issue")
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class SupportResponse(BaseModel):
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"""Response from support agent."""
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IsResolved: bool = Field(description="True if the user issue/ask has been resolved.")
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NeedsEscalation: bool = Field(
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description="True resolution could not be achieved and the issue/ask requires escalation."
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)
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ResolutionSummary: str = Field(description="The summary of the steps that led to resolution.")
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class EscalationResponse(BaseModel):
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"""Response from escalation agent."""
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IsComplete: bool = Field(description="Has the email been sent and no more user input is required.")
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UserMessage: str = Field(description="A natural language message to the user.")
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async def main() -> None:
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"""Run the customer support workflow."""
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# Create ticketing plugin
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plugin = TicketingPlugin()
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# Create Azure OpenAI client
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client = AzureOpenAIResponsesClient(
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project_endpoint=os.environ["AZURE_AI_PROJECT_ENDPOINT"],
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deployment_name=os.environ["AZURE_AI_MODEL_DEPLOYMENT_NAME"],
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credential=AzureCliCredential(),
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)
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# Create agents with structured outputs
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self_service_agent = client.as_agent(
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name="SelfServiceAgent",
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instructions=SELF_SERVICE_INSTRUCTIONS,
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default_options={"response_format": SelfServiceResponse},
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)
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ticketing_agent = client.as_agent(
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name="TicketingAgent",
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instructions=TICKETING_INSTRUCTIONS,
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tools=plugin.get_functions(),
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default_options={"response_format": TicketingResponse},
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)
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routing_agent = client.as_agent(
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name="TicketRoutingAgent",
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instructions=TICKET_ROUTING_INSTRUCTIONS,
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tools=[plugin.get_ticket],
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default_options={"response_format": RoutingResponse},
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)
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windows_support_agent = client.as_agent(
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name="WindowsSupportAgent",
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instructions=WINDOWS_SUPPORT_INSTRUCTIONS,
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tools=[plugin.get_ticket],
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default_options={"response_format": SupportResponse},
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)
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resolution_agent = client.as_agent(
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name="TicketResolutionAgent",
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instructions=RESOLUTION_INSTRUCTIONS,
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tools=[plugin.resolve_ticket],
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)
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escalation_agent = client.as_agent(
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name="TicketEscalationAgent",
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instructions=ESCALATION_INSTRUCTIONS,
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tools=[plugin.get_ticket, plugin.send_notification],
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default_options={"response_format": EscalationResponse},
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)
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# Agent registry for lookup
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agents = {
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"SelfServiceAgent": self_service_agent,
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"TicketingAgent": ticketing_agent,
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"TicketRoutingAgent": routing_agent,
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"WindowsSupportAgent": windows_support_agent,
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"TicketResolutionAgent": resolution_agent,
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"TicketEscalationAgent": escalation_agent,
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}
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# Print loaded agents (similar to .NET "PROMPT AGENT: AgentName:1")
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for agent_name in agents:
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print(f"{CYAN}PROMPT AGENT: {agent_name}:1{RESET}")
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# Create workflow factory
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factory = WorkflowFactory(agents=agents)
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# Load workflow from YAML
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samples_root = Path(__file__).parent.parent.parent.parent.parent.parent.parent
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workflow_path = samples_root / "workflow-samples" / "CustomerSupport.yaml"
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if not workflow_path.exists():
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# Fall back to local copy if workflow-samples doesn't exist
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workflow_path = Path(__file__).parent / "workflow.yaml"
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workflow = factory.create_workflow_from_yaml_path(workflow_path)
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print()
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print("=" * 60)
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# Example input
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user_input = "My computer won't boot"
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pending_request_id: str | None = None
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# Track responses for formatting
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accumulated_response: str = ""
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last_agent_name: str | None = None
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print(f"\n{GREEN}INPUT:{RESET} {user_input}\n")
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while True:
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if pending_request_id:
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# Continue workflow with user response
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print(f"\n{YELLOW}WORKFLOW:{RESET} Restore\n")
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response = AgentExternalInputResponse(user_input=user_input)
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stream = workflow.run(stream=True, responses={pending_request_id: response})
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pending_request_id = None
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else:
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# Start workflow
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stream = workflow.run(user_input, stream=True)
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async for event in stream:
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if event.type == "output":
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data = event.data
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# source_executor_id is only available on request_info events.
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# For output events, use executor_id to identify the emitting node.
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source_id = event.executor_id or ""
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# Check if this is a SendActivity output (activity text from log_ticket, log_route, etc.)
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if "log_" in source_id.lower():
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# Print any accumulated agent response first
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if accumulated_response and last_agent_name:
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msg_id = f"msg_{uuid.uuid4().hex[:32]}"
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print(f"{CYAN}{last_agent_name.upper()}:{RESET} [{msg_id}]")
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try:
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parsed = json.loads(accumulated_response)
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print(json.dumps(parsed))
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except (json.JSONDecodeError, TypeError):
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print(accumulated_response)
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accumulated_response = ""
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last_agent_name = None
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# Print activity
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print(f"\n{MAGENTA}ACTIVITY:{RESET}")
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print(data)
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else:
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# Accumulate agent response (streaming text)
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if isinstance(data, str):
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accumulated_response += data
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else:
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accumulated_response += str(data)
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elif event.type == "request_info" and isinstance(event.data, AgentExternalInputRequest):
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request = event.data
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# The agent_response from the request contains the structured response
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agent_name = request.agent_name
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agent_response = request.agent_response
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# Print the agent's response
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if agent_response:
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msg_id = f"msg_{uuid.uuid4().hex[:32]}"
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print(f"{CYAN}{agent_name.upper()}:{RESET} [{msg_id}]")
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try:
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parsed = json.loads(agent_response)
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print(json.dumps(parsed))
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except (json.JSONDecodeError, TypeError):
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print(agent_response)
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# Clear accumulated since we printed from the request
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accumulated_response = ""
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last_agent_name = agent_name
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pending_request_id = event.request_id
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print(f"\n{YELLOW}WORKFLOW:{RESET} Yield")
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# Print any remaining accumulated response at end of stream
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if accumulated_response:
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# Try to identify which agent this came from based on content
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msg_id = f"msg_{uuid.uuid4().hex[:32]}"
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print(f"\nResponse: [{msg_id}]")
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try:
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parsed = json.loads(accumulated_response)
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print(json.dumps(parsed))
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except (json.JSONDecodeError, TypeError):
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print(accumulated_response)
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accumulated_response = ""
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if not pending_request_id:
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break
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# Get next user input
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user_input = input(f"\n{GREEN}INPUT:{RESET} ").strip() # noqa: ASYNC250
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if not user_input:
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print("Exiting...")
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break
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print()
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print("\n" + "=" * 60)
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print("Workflow Complete")
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print("=" * 60)
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if __name__ == "__main__":
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asyncio.run(main())
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@@ -0,0 +1,79 @@
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# Copyright (c) Microsoft. All rights reserved.
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"""Ticketing plugin for CustomerSupport workflow."""
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import uuid
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from collections.abc import Callable
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from dataclasses import dataclass
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from enum import Enum
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# ANSI color codes
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MAGENTA = "\033[35m"
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RESET = "\033[0m"
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class TicketStatus(Enum):
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"""Status of a support ticket."""
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OPEN = "open"
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IN_PROGRESS = "in_progress"
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RESOLVED = "resolved"
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CLOSED = "closed"
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@dataclass
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class TicketItem:
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"""A support ticket."""
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id: str
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subject: str = ""
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description: str = ""
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notes: str = ""
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status: TicketStatus = TicketStatus.OPEN
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class TicketingPlugin:
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"""Mock ticketing plugin for customer support workflow."""
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def __init__(self) -> None:
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self._ticket_store: dict[str, TicketItem] = {}
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def _trace(self, function_name: str) -> None:
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print(f"\n{MAGENTA}FUNCTION: {function_name}{RESET}")
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def get_ticket(self, id: str) -> TicketItem | None:
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"""Retrieve a ticket by identifier from Azure DevOps."""
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self._trace("get_ticket")
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return self._ticket_store.get(id)
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def create_ticket(self, subject: str, description: str, notes: str) -> str:
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"""Create a ticket in Azure DevOps and return its identifier."""
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self._trace("create_ticket")
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ticket_id = uuid.uuid4().hex
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ticket = TicketItem(
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id=ticket_id,
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subject=subject,
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description=description,
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notes=notes,
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)
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self._ticket_store[ticket_id] = ticket
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return ticket_id
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def resolve_ticket(self, id: str, resolution_summary: str) -> None:
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"""Resolve an existing ticket in Azure DevOps given its identifier."""
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self._trace("resolve_ticket")
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if ticket := self._ticket_store.get(id):
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||||
ticket.status = TicketStatus.RESOLVED
|
||||
|
||||
def send_notification(self, id: str, email: str, cc: str, body: str) -> None:
|
||||
"""Send an email notification to escalate ticket engagement."""
|
||||
self._trace("send_notification")
|
||||
|
||||
def get_functions(self) -> list[Callable[..., object]]:
|
||||
"""Return all plugin functions for registration."""
|
||||
return [
|
||||
self.get_ticket,
|
||||
self.create_ticket,
|
||||
self.resolve_ticket,
|
||||
self.send_notification,
|
||||
]
|
||||
@@ -0,0 +1,164 @@
|
||||
#
|
||||
# This workflow demonstrates using multiple agents to provide automated
|
||||
# troubleshooting steps to resolve common issues with escalation options.
|
||||
#
|
||||
# Example input:
|
||||
# My PC keeps rebooting and I can't use it.
|
||||
#
|
||||
kind: Workflow
|
||||
trigger:
|
||||
|
||||
kind: OnConversationStart
|
||||
id: workflow_demo
|
||||
actions:
|
||||
|
||||
# Interact with user until the issue has been resolved or
|
||||
# a determination is made that a ticket is required.
|
||||
- kind: InvokeAzureAgent
|
||||
id: service_agent
|
||||
conversationId: =System.ConversationId
|
||||
agent:
|
||||
name: SelfServiceAgent
|
||||
input:
|
||||
externalLoop:
|
||||
when: |-
|
||||
=Not(Local.ServiceParameters.IsResolved)
|
||||
And
|
||||
Not(Local.ServiceParameters.NeedsTicket)
|
||||
output:
|
||||
responseObject: Local.ServiceParameters
|
||||
|
||||
# All done if issue is resolved.
|
||||
- kind: ConditionGroup
|
||||
id: check_if_resolved
|
||||
conditions:
|
||||
|
||||
- condition: =Local.ServiceParameters.IsResolved
|
||||
id: test_if_resolved
|
||||
actions:
|
||||
- kind: GotoAction
|
||||
id: end_when_resolved
|
||||
actionId: all_done
|
||||
|
||||
# Create the ticket.
|
||||
- kind: InvokeAzureAgent
|
||||
id: ticket_agent
|
||||
agent:
|
||||
name: TicketingAgent
|
||||
input:
|
||||
arguments:
|
||||
IssueDescription: =Local.ServiceParameters.IssueDescription
|
||||
AttemptedResolutionSteps: =Local.ServiceParameters.AttemptedResolutionSteps
|
||||
output:
|
||||
responseObject: Local.TicketParameters
|
||||
|
||||
# Capture the attempted resolution steps.
|
||||
- kind: SetVariable
|
||||
id: capture_attempted_resolution
|
||||
variable: Local.ResolutionSteps
|
||||
value: =Local.ServiceParameters.AttemptedResolutionSteps
|
||||
|
||||
# Notify user of ticket identifier.
|
||||
- kind: SendActivity
|
||||
id: log_ticket
|
||||
activity: "Created ticket #{Local.TicketParameters.TicketId}"
|
||||
|
||||
# Determine which team for which route the ticket.
|
||||
- kind: InvokeAzureAgent
|
||||
id: routing_agent
|
||||
agent:
|
||||
name: TicketRoutingAgent
|
||||
input:
|
||||
messages: =UserMessage(Local.ServiceParameters.IssueDescription)
|
||||
output:
|
||||
responseObject: Local.RoutingParameters
|
||||
|
||||
# Notify user of routing decision.
|
||||
- kind: SendActivity
|
||||
id: log_route
|
||||
activity: Routing to {Local.RoutingParameters.TeamName}
|
||||
|
||||
- kind: ConditionGroup
|
||||
id: check_routing
|
||||
conditions:
|
||||
|
||||
- condition: =Local.RoutingParameters.TeamName = "Windows Support"
|
||||
id: route_to_support
|
||||
actions:
|
||||
|
||||
# Invoke the support agent to attempt to resolve the issue.
|
||||
- kind: CreateConversation
|
||||
id: conversation_support
|
||||
conversationId: Local.SupportConversationId
|
||||
|
||||
- kind: InvokeAzureAgent
|
||||
id: support_agent
|
||||
conversationId: =Local.SupportConversationId
|
||||
agent:
|
||||
name: WindowsSupportAgent
|
||||
input:
|
||||
arguments:
|
||||
IssueDescription: =Local.ServiceParameters.IssueDescription
|
||||
AttemptedResolutionSteps: =Local.ServiceParameters.AttemptedResolutionSteps
|
||||
externalLoop:
|
||||
when: |-
|
||||
=Not(Local.SupportParameters.IsResolved)
|
||||
And
|
||||
Not(Local.SupportParameters.NeedsEscalation)
|
||||
output:
|
||||
autoSend: true
|
||||
responseObject: Local.SupportParameters
|
||||
|
||||
# Capture the attempted resolution steps.
|
||||
- kind: SetVariable
|
||||
id: capture_support_resolution
|
||||
variable: Local.ResolutionSteps
|
||||
value: =Local.SupportParameters.ResolutionSummary
|
||||
|
||||
# Check if the issue was resolved by support.
|
||||
- kind: ConditionGroup
|
||||
id: check_resolved
|
||||
conditions:
|
||||
|
||||
# Resolve ticket
|
||||
- condition: =Local.SupportParameters.IsResolved
|
||||
id: handle_if_resolved
|
||||
actions:
|
||||
|
||||
- kind: InvokeAzureAgent
|
||||
id: resolution_agent
|
||||
agent:
|
||||
name: TicketResolutionAgent
|
||||
input:
|
||||
arguments:
|
||||
TicketId: =Local.TicketParameters.TicketId
|
||||
ResolutionSummary: =Local.SupportParameters.ResolutionSummary
|
||||
|
||||
- kind: GotoAction
|
||||
id: end_when_solved
|
||||
actionId: all_done
|
||||
|
||||
# Escalate the ticket by sending an email notification.
|
||||
- kind: CreateConversation
|
||||
id: conversation_escalate
|
||||
conversationId: Local.EscalationConversationId
|
||||
|
||||
- kind: InvokeAzureAgent
|
||||
id: escalate_agent
|
||||
conversationId: =Local.EscalationConversationId
|
||||
agent:
|
||||
name: TicketEscalationAgent
|
||||
input:
|
||||
arguments:
|
||||
TicketId: =Local.TicketParameters.TicketId
|
||||
IssueDescription: =Local.ServiceParameters.IssueDescription
|
||||
ResolutionSummary: =Local.ResolutionSteps
|
||||
externalLoop:
|
||||
when: =Not(Local.EscalationParameters.IsComplete)
|
||||
output:
|
||||
autoSend: true
|
||||
responseObject: Local.EscalationParameters
|
||||
|
||||
# All done
|
||||
- kind: EndWorkflow
|
||||
id: all_done
|
||||
Reference in New Issue
Block a user