mirror of
https://github.com/microsoft/agent-framework.git
synced 2026-06-16 21:04:09 +08:00
Dmytro Struk
@@ -78,7 +78,6 @@ Once comfortable with these, explore the rest of the samples below.
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| Human-In-The-Loop (Guessing Game) | [human-in-the-loop/guessing_game_with_human_input.py](./human-in-the-loop/guessing_game_with_human_input.py) | Interactive request/response prompts with a human |
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| Azure Agents Tool Feedback Loop | [agents/azure_chat_agents_tool_calls_with_feedback.py](./agents/azure_chat_agents_tool_calls_with_feedback.py) | Two-agent workflow that streams tool calls and pauses for human guidance between passes |
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| Agents with Approval Requests in Workflows | [human-in-the-loop/agents_with_approval_requests.py](./human-in-the-loop/agents_with_approval_requests.py) | Agents that create approval requests during workflow execution and wait for human approval to proceed |
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### observability
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@@ -97,7 +96,6 @@ Once comfortable with these, explore the rest of the samples below.
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| Group Chat with Simple Function Selector | [orchestration/group_chat_simple_selector.py](./orchestration/group_chat_simple_selector.py) | Group chat with a simple function selector for next speaker |
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| Handoff (Simple) | [orchestration/handoff_simple.py](./orchestration/handoff_simple.py) | Single-tier routing: triage agent routes to specialists, control returns to user after each specialist response |
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| Handoff (Specialist-to-Specialist) | [orchestration/handoff_specialist_to_specialist.py](./orchestration/handoff_specialist_to_specialist.py) | Multi-tier routing: specialists can hand off to other specialists using `.add_handoff()` fluent API |
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| Handoff (Return-to-Previous) | [orchestration/handoff_return_to_previous.py](./orchestration/handoff_return_to_previous.py) | Return-to-previous routing: after user input, routes back to the previous specialist instead of coordinator using `.enable_return_to_previous()` |
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| Magentic Workflow (Multi-Agent) | [orchestration/magentic.py](./orchestration/magentic.py) | Orchestrate multiple agents with Magentic manager and streaming |
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| Magentic + Human Plan Review | [orchestration/magentic_human_plan_update.py](./orchestration/magentic_human_plan_update.py) | Human reviews/updates the plan before execution |
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| Magentic + Checkpoint Resume | [orchestration/magentic_checkpoint.py](./orchestration/magentic_checkpoint.py) | Resume Magentic orchestration from saved checkpoints |
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-340
@@ -1,340 +0,0 @@
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import json
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from dataclasses import dataclass
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from typing import Annotated, Never
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from agent_framework import (
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AgentExecutorResponse,
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ChatMessage,
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Executor,
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FunctionApprovalRequestContent,
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FunctionApprovalResponseContent,
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WorkflowBuilder,
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WorkflowContext,
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ai_function,
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executor,
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handler,
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)
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from agent_framework.openai import OpenAIChatClient
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"""
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Sample: Agents in a workflow with AI functions requiring approval
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This sample creates a workflow that automatically replies to incoming emails.
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If historical email data is needed, it uses an AI function to read the data,
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which requires human approval before execution.
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This sample works as follows:
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1. An incoming email is received by the workflow.
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2. The EmailPreprocessor executor preprocesses the email, adding special notes if the sender is important.
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3. The preprocessed email is sent to the Email Writer agent, which generates a response.
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4. If the agent needs to read historical email data, it calls the read_historical_email_data AI function,
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which triggers an approval request.
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5. The sample automatically approves the request for demonstration purposes.
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6. Once approved, the AI function executes and returns the historical email data to the agent.
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7. The agent uses the historical data to compose a comprehensive email response.
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8. The response is sent to the conclude_workflow_executor, which yields the final response.
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Purpose:
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Show how to integrate AI functions with approval requests into a workflow.
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Demonstrate:
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- Creating AI functions that require approval before execution.
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- Building a workflow that includes an agent and executors.
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- Handling approval requests during workflow execution.
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Prerequisites:
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- Azure AI Agent Service configured, along with the required environment variables.
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- Authentication via azure-identity. Use AzureCliCredential and run az login before executing the sample.
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- Basic familiarity with WorkflowBuilder, edges, events, RequestInfoEvent, and streaming runs.
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"""
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@ai_function
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def get_current_date() -> str:
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"""Get the current date in YYYY-MM-DD format."""
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# For demonstration purposes, we return a fixed date.
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return "2025-11-07"
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@ai_function
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def get_team_members_email_addresses() -> list[dict[str, str]]:
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"""Get the email addresses of team members."""
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# In a real implementation, this might query a database or directory service.
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return [
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{
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"name": "Alice",
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"email": "alice@contoso.com",
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"position": "Software Engineer",
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"manager": "John Doe",
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},
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{
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"name": "Bob",
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"email": "bob@contoso.com",
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"position": "Product Manager",
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"manager": "John Doe",
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},
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{
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"name": "Charlie",
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"email": "charlie@contoso.com",
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"position": "Senior Software Engineer",
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"manager": "John Doe",
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},
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{
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"name": "Mike",
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"email": "mike@contoso.com",
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"position": "Principal Software Engineer Manager",
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"manager": "VP of Engineering",
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},
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]
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@ai_function
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def get_my_information() -> dict[str, str]:
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"""Get my personal information."""
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return {
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"name": "John Doe",
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"email": "john@contoso.com",
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"position": "Software Engineer Manager",
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"manager": "Mike",
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}
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@ai_function(approval_mode="always_require")
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async def read_historical_email_data(
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email_address: Annotated[str, "The email address to read historical data from"],
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start_date: Annotated[str, "The start date in YYYY-MM-DD format"],
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end_date: Annotated[str, "The end date in YYYY-MM-DD format"],
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) -> list[dict[str, str]]:
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"""Read historical email data for a given email address and date range."""
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historical_data = {
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"alice@contoso.com": [
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{
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"from": "alice@contoso.com",
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"to": "john@contoso.com",
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"date": "2025-11-05",
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"subject": "Bug Bash Results",
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"body": "We just completed the bug bash and found a few issues that need immediate attention.",
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},
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{
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"from": "alice@contoso.com",
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"to": "john@contoso.com",
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"date": "2025-11-03",
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"subject": "Code Freeze",
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"body": "We are entering code freeze starting tomorrow.",
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},
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],
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"bob@contoso.com": [
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{
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"from": "bob@contoso.com",
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"to": "john@contoso.com",
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"date": "2025-11-04",
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"subject": "Team Outing",
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"body": "Don't forget about the team outing this Friday!",
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},
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{
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"from": "bob@contoso.com",
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"to": "john@contoso.com",
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"date": "2025-11-02",
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"subject": "Requirements Update",
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"body": "The requirements for the new feature have been updated. Please review them.",
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},
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],
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"charlie@contoso.com": [
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{
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"from": "charlie@contoso.com",
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"to": "john@contoso.com",
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"date": "2025-11-05",
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"subject": "Project Update",
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"body": "The bug bash went well. A few critical bugs but should be fixed by the end of the week.",
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},
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{
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"from": "charlie@contoso.com",
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"to": "john@contoso.com",
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"date": "2025-11-06",
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"subject": "Code Review",
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"body": "Please review my latest code changes.",
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},
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],
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}
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emails = historical_data.get(email_address, [])
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return [email for email in emails if start_date <= email["date"] <= end_date]
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@ai_function(approval_mode="always_require")
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async def send_email(
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to: Annotated[str, "The recipient email address"],
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subject: Annotated[str, "The email subject"],
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body: Annotated[str, "The email body"],
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) -> str:
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"""Send an email."""
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await asyncio.sleep(1) # Simulate sending email
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return "Email successfully sent."
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@dataclass
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class Email:
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sender: str
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subject: str
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body: str
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class EmailPreprocessor(Executor):
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def __init__(self, special_email_addresses: set[str]) -> None:
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super().__init__(id="email_preprocessor")
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self.special_email_addresses = special_email_addresses
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@handler
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async def preprocess(self, email: Email, ctx: WorkflowContext[str]) -> None:
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"""Preprocess the incoming email."""
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message = str(email)
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if email.sender in self.special_email_addresses:
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note = (
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"Pay special attention to this sender. This email is very important. "
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"Gather relevant information from all previous emails within my team before responding."
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)
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message = f"{note}\n\n{message}"
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await ctx.send_message(message)
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@executor(id="conclude_workflow_executor")
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async def conclude_workflow(
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email_response: AgentExecutorResponse,
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ctx: WorkflowContext[Never, str],
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) -> None:
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"""Conclude the workflow by yielding the final email response."""
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await ctx.yield_output(email_response.agent_run_response.text)
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async def main() -> None:
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# Create the agent and executors
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chat_client = OpenAIChatClient()
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email_writer = chat_client.create_agent(
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name="Email Writer",
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instructions=("You are an excellent email assistant. You respond to incoming emails."),
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# tools with `approval_mode="always_require"` will trigger approval requests
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tools=[
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read_historical_email_data,
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send_email,
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get_current_date,
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get_team_members_email_addresses,
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get_my_information,
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],
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)
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email_preprocessor = EmailPreprocessor(special_email_addresses={"mike@contoso.com"})
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# Build the workflow
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workflow = (
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WorkflowBuilder()
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.set_start_executor(email_preprocessor)
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.add_edge(email_preprocessor, email_writer)
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.add_edge(email_writer, conclude_workflow)
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.build()
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)
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# Simulate an incoming email
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incoming_email = Email(
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sender="mike@contoso.com",
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subject="Important: Project Update",
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body="Please provide your team's status update on the project since last week.",
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)
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responses: dict[str, FunctionApprovalResponseContent] = {}
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output: list[ChatMessage] | None = None
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while True:
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if responses:
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events = await workflow.send_responses(responses)
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responses.clear()
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else:
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events = await workflow.run(incoming_email)
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request_info_events = events.get_request_info_events()
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for request_info_event in request_info_events:
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# We should only expect FunctionApprovalRequestContent in this sample
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if not isinstance(request_info_event.data, FunctionApprovalRequestContent):
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raise ValueError(f"Unexpected request info content type: {type(request_info_event.data)}")
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# Pretty print the function call details
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arguments = json.dumps(request_info_event.data.function_call.parse_arguments(), indent=2)
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print(
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f"Received approval request for function: {request_info_event.data.function_call.name} "
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f"with args:\n{arguments}"
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)
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# For demo purposes, we automatically approve the request
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# The expected response type of the request is `FunctionApprovalResponseContent`,
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# which can be created via `create_response` method on the request content
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print("Performing automatic approval for demo purposes...")
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responses[request_info_event.request_id] = request_info_event.data.create_response(approved=True)
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# Once we get an output event, we can conclude the workflow
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# Outputs can only be produced by the conclude_workflow_executor in this sample
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if outputs := events.get_outputs():
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# We expect only one output from the conclude_workflow_executor
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output = outputs[0]
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break
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if not output:
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raise RuntimeError("Workflow did not produce any output event.")
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print("Final email response conversation:")
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print(output)
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"""
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Sample Output:
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Received approval request for function: read_historical_email_data with args:
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{
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"email_address": "alice@contoso.com",
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"start_date": "2025-10-31",
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"end_date": "2025-11-07"
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}
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Performing automatic approval for demo purposes...
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Received approval request for function: read_historical_email_data with args:
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{
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"email_address": "bob@contoso.com",
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"start_date": "2025-10-31",
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"end_date": "2025-11-07"
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}
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Performing automatic approval for demo purposes...
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Received approval request for function: read_historical_email_data with args:
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{
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"email_address": "charlie@contoso.com",
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"start_date": "2025-10-31",
|
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"end_date": "2025-11-07"
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}
|
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Performing automatic approval for demo purposes...
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Received approval request for function: send_email with args:
|
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{
|
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"to": "mike@contoso.com",
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"subject": "Team's Status Update on the Project",
|
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"body": "
|
||||
Hi Mike,
|
||||
|
||||
Here's the status update from our team:
|
||||
- **Bug Bash and Code Freeze:**
|
||||
- We recently completed a bug bash, during which several issues were identified. Alice and Charlie are working on fixing these critical bugs, and we anticipate resolving them by the end of this week.
|
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- We have entered a code freeze as of November 4, 2025.
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|
||||
- **Requirements Update:**
|
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- Bob has updated the requirements for a new feature, and all team members are reviewing these changes to ensure alignment.
|
||||
|
||||
- **Ongoing Reviews:**
|
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- Charlie has submitted his latest code changes for review to ensure they meet our quality standards.
|
||||
|
||||
Please let me know if you need more detailed information or have any questions.
|
||||
|
||||
Best regards,
|
||||
John"
|
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}
|
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Performing automatic approval for demo purposes...
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Final email response conversation:
|
||||
I've sent the status update to Mike with the relevant information from the team. Let me know if there's anything else you need
|
||||
""" # noqa: E501
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
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asyncio.run(main())
|
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@@ -1,294 +0,0 @@
|
||||
# Copyright (c) Microsoft. All rights reserved.
|
||||
|
||||
import asyncio
|
||||
from collections.abc import AsyncIterable
|
||||
from typing import cast
|
||||
|
||||
from agent_framework import (
|
||||
ChatAgent,
|
||||
HandoffBuilder,
|
||||
HandoffUserInputRequest,
|
||||
RequestInfoEvent,
|
||||
WorkflowEvent,
|
||||
WorkflowOutputEvent,
|
||||
)
|
||||
from agent_framework.azure import AzureOpenAIChatClient
|
||||
from azure.identity import AzureCliCredential
|
||||
|
||||
"""Sample: Handoff workflow with return-to-previous routing enabled.
|
||||
|
||||
This interactive sample demonstrates the return-to-previous feature where user inputs
|
||||
route directly back to the specialist currently handling their request, rather than
|
||||
always going through the coordinator for re-evaluation.
|
||||
|
||||
Routing Pattern (with return-to-previous enabled):
|
||||
User -> Coordinator -> Technical Support -> User -> Technical Support -> ...
|
||||
|
||||
Routing Pattern (default, without return-to-previous):
|
||||
User -> Coordinator -> Technical Support -> User -> Coordinator -> Technical Support -> ...
|
||||
|
||||
This is useful when a specialist needs multiple turns with the user to gather
|
||||
information or resolve an issue, avoiding unnecessary coordinator involvement.
|
||||
|
||||
Specialist-to-Specialist Handoff:
|
||||
When a user's request changes to a topic outside the current specialist's domain,
|
||||
the specialist can hand off DIRECTLY to another specialist without going back through
|
||||
the coordinator:
|
||||
|
||||
User -> Coordinator -> Technical Support -> User -> Technical Support (billing question)
|
||||
-> Billing -> User -> Billing ...
|
||||
|
||||
Example Interaction:
|
||||
1. User reports a technical issue
|
||||
2. Coordinator routes to technical support specialist
|
||||
3. Technical support asks clarifying questions
|
||||
4. User provides details (routes directly back to technical support)
|
||||
5. Technical support continues troubleshooting with full context
|
||||
6. Issue resolved, user asks about billing
|
||||
7. Technical support hands off DIRECTLY to billing specialist
|
||||
8. Billing specialist helps with payment
|
||||
9. User continues with billing (routes directly to billing)
|
||||
|
||||
Prerequisites:
|
||||
- `az login` (Azure CLI authentication)
|
||||
- Environment variables configured for AzureOpenAIChatClient (AZURE_OPENAI_ENDPOINT, etc.)
|
||||
|
||||
Usage:
|
||||
Run the script and interact with the support workflow by typing your requests.
|
||||
Type 'exit' or 'quit' to end the conversation.
|
||||
|
||||
Key Concepts:
|
||||
- Return-to-previous: Direct routing to current agent handling the conversation
|
||||
- Current agent tracking: Framework remembers which agent is actively helping the user
|
||||
- Context preservation: Specialist maintains full conversation context
|
||||
- Domain switching: Specialists can hand back to coordinator when topic changes
|
||||
"""
|
||||
|
||||
|
||||
def create_agents(chat_client: AzureOpenAIChatClient) -> tuple[ChatAgent, ChatAgent, ChatAgent, ChatAgent]:
|
||||
"""Create and configure the coordinator and specialist agents.
|
||||
|
||||
Returns:
|
||||
Tuple of (coordinator, technical_support, account_specialist, billing_agent)
|
||||
"""
|
||||
coordinator = chat_client.create_agent(
|
||||
instructions=(
|
||||
"You are a customer support coordinator. Analyze the user's request and route to "
|
||||
"the appropriate specialist:\n"
|
||||
"- technical_support for technical issues, troubleshooting, repairs, hardware/software problems\n"
|
||||
"- account_specialist for account changes, profile updates, settings, login issues\n"
|
||||
"- billing_agent for payments, invoices, refunds, charges, billing questions\n"
|
||||
"\n"
|
||||
"When you receive a request, immediately call the matching handoff tool without explaining. "
|
||||
"Read the most recent user message to determine the correct specialist."
|
||||
),
|
||||
name="coordinator",
|
||||
)
|
||||
|
||||
technical_support = chat_client.create_agent(
|
||||
instructions=(
|
||||
"You provide technical support. Help users troubleshoot technical issues, "
|
||||
"arrange repairs, and answer technical questions. "
|
||||
"Gather information through conversation. "
|
||||
"If the user asks about billing, payments, invoices, or refunds, hand off to billing_agent. "
|
||||
"If the user asks about account settings or profile changes, hand off to account_specialist."
|
||||
),
|
||||
name="technical_support",
|
||||
)
|
||||
|
||||
account_specialist = chat_client.create_agent(
|
||||
instructions=(
|
||||
"You handle account management. Help with profile updates, account settings, "
|
||||
"and preferences. Gather information through conversation. "
|
||||
"If the user asks about technical issues or troubleshooting, hand off to technical_support. "
|
||||
"If the user asks about billing, payments, invoices, or refunds, hand off to billing_agent."
|
||||
),
|
||||
name="account_specialist",
|
||||
)
|
||||
|
||||
billing_agent = chat_client.create_agent(
|
||||
instructions=(
|
||||
"You handle billing only. Process payments, explain invoices, handle refunds. "
|
||||
"If the user asks about technical issues or troubleshooting, hand off to technical_support. "
|
||||
"If the user asks about account settings or profile changes, hand off to account_specialist."
|
||||
),
|
||||
name="billing_agent",
|
||||
)
|
||||
|
||||
return coordinator, technical_support, account_specialist, billing_agent
|
||||
|
||||
|
||||
def handle_events(events: list[WorkflowEvent]) -> list[RequestInfoEvent]:
|
||||
"""Process events and return pending input requests."""
|
||||
pending_requests: list[RequestInfoEvent] = []
|
||||
for event in events:
|
||||
if isinstance(event, RequestInfoEvent):
|
||||
pending_requests.append(event)
|
||||
request_data = cast(HandoffUserInputRequest, event.data)
|
||||
print(f"\n{'=' * 60}")
|
||||
print(f"AWAITING INPUT FROM: {request_data.awaiting_agent_id.upper()}")
|
||||
print(f"{'=' * 60}")
|
||||
for msg in request_data.conversation[-3:]:
|
||||
author = msg.author_name or msg.role.value
|
||||
prefix = ">>> " if author == request_data.awaiting_agent_id else " "
|
||||
print(f"{prefix}[{author}]: {msg.text}")
|
||||
elif isinstance(event, WorkflowOutputEvent):
|
||||
print(f"\n{'=' * 60}")
|
||||
print("[WORKFLOW COMPLETE]")
|
||||
print(f"{'=' * 60}")
|
||||
return pending_requests
|
||||
|
||||
|
||||
async def _drain(stream: AsyncIterable[WorkflowEvent]) -> list[WorkflowEvent]:
|
||||
"""Drain an async iterable into a list."""
|
||||
events: list[WorkflowEvent] = []
|
||||
async for event in stream:
|
||||
events.append(event)
|
||||
return events
|
||||
|
||||
|
||||
async def main() -> None:
|
||||
"""Demonstrate return-to-previous routing in a handoff workflow."""
|
||||
chat_client = AzureOpenAIChatClient(credential=AzureCliCredential())
|
||||
coordinator, technical, account, billing = create_agents(chat_client)
|
||||
|
||||
print("Handoff Workflow with Return-to-Previous Routing")
|
||||
print("=" * 60)
|
||||
print("\nThis interactive demo shows how user inputs route directly")
|
||||
print("to the specialist handling your request, avoiding unnecessary")
|
||||
print("coordinator re-evaluation on each turn.")
|
||||
print("\nSpecialists can hand off directly to other specialists when")
|
||||
print("your request changes topics (e.g., from technical to billing).")
|
||||
print("\nType 'exit' or 'quit' to end the conversation.\n")
|
||||
|
||||
# Configure handoffs with return-to-previous enabled
|
||||
# Specialists can hand off directly to other specialists when topic changes
|
||||
workflow = (
|
||||
HandoffBuilder(
|
||||
name="return_to_previous_demo",
|
||||
participants=[coordinator, technical, account, billing],
|
||||
)
|
||||
.set_coordinator(coordinator)
|
||||
.add_handoff(coordinator, [technical, account, billing]) # Coordinator routes to all specialists
|
||||
.add_handoff(technical, [billing, account]) # Technical can route to billing or account
|
||||
.add_handoff(account, [technical, billing]) # Account can route to technical or billing
|
||||
.add_handoff(billing, [technical, account]) # Billing can route to technical or account
|
||||
.enable_return_to_previous(True) # Enable the `return to previous handoff` feature
|
||||
.with_termination_condition(lambda conv: sum(1 for msg in conv if msg.role.value == "user") >= 10)
|
||||
.build()
|
||||
)
|
||||
|
||||
# Get initial user request
|
||||
initial_request = input("You: ").strip() # noqa: ASYNC250
|
||||
if not initial_request or initial_request.lower() in ["exit", "quit"]:
|
||||
print("Goodbye!")
|
||||
return
|
||||
|
||||
# Start workflow with initial message
|
||||
events = await _drain(workflow.run_stream(initial_request))
|
||||
pending_requests = handle_events(events)
|
||||
|
||||
# Interactive loop: keep prompting for user input
|
||||
while pending_requests:
|
||||
user_input = input("\nYou: ").strip() # noqa: ASYNC250
|
||||
|
||||
if not user_input or user_input.lower() in ["exit", "quit"]:
|
||||
print("\nEnding conversation. Goodbye!")
|
||||
break
|
||||
|
||||
responses = {req.request_id: user_input for req in pending_requests}
|
||||
events = await _drain(workflow.send_responses_streaming(responses))
|
||||
pending_requests = handle_events(events)
|
||||
|
||||
print("\n" + "=" * 60)
|
||||
print("Conversation ended.")
|
||||
|
||||
"""
|
||||
Sample Output:
|
||||
|
||||
Handoff Workflow with Return-to-Previous Routing
|
||||
============================================================
|
||||
|
||||
This interactive demo shows how user inputs route directly
|
||||
to the specialist handling your request, avoiding unnecessary
|
||||
coordinator re-evaluation on each turn.
|
||||
|
||||
Specialists can hand off directly to other specialists when
|
||||
your request changes topics (e.g., from technical to billing).
|
||||
|
||||
Type 'exit' or 'quit' to end the conversation.
|
||||
|
||||
You: I need help with my bill, I was charged twice by mistake.
|
||||
|
||||
============================================================
|
||||
AWAITING INPUT FROM: BILLING_AGENT
|
||||
============================================================
|
||||
[user]: I need help with my bill, I was charged twice by mistake.
|
||||
[coordinator]: You will be connected to a billing agent who can assist you with the double charge on your bill.
|
||||
>>> [billing_agent]: I'm here to help with billing concerns! I'm sorry you were charged twice. Could you
|
||||
please provide the invoice number or your account email so I can look into this and begin processing a refund?
|
||||
|
||||
You: Invoice 1234
|
||||
|
||||
============================================================
|
||||
AWAITING INPUT FROM: BILLING_AGENT
|
||||
============================================================
|
||||
>>> [billing_agent]: I'm here to help with billing concerns! I'm sorry you were charged twice.
|
||||
Could you please provide the invoice number or your account email so I can look into this and begin
|
||||
processing a refund?
|
||||
[user]: Invoice 1234
|
||||
>>> [billing_agent]: Thank you for providing the invoice number (1234). I will review the details and work
|
||||
on processing a refund for the duplicate charge.
|
||||
|
||||
Can you confirm which payment method you used for this bill (e.g., credit card, PayPal)?
|
||||
This helps ensure your refund is processed to the correct account.
|
||||
|
||||
You: I used my credit card, which is on autopay.
|
||||
|
||||
============================================================
|
||||
AWAITING INPUT FROM: BILLING_AGENT
|
||||
============================================================
|
||||
>>> [billing_agent]: Thank you for providing the invoice number (1234). I will review the details and work on
|
||||
processing a refund for the duplicate charge.
|
||||
|
||||
Can you confirm which payment method you used for this bill (e.g., credit card, PayPal)? This helps ensure
|
||||
your refund is processed to the correct account.
|
||||
[user]: I used my credit card, which is on autopay.
|
||||
>>> [billing_agent]: Thank you for confirming your payment method. I will look into invoice 1234 and
|
||||
process a refund for the duplicate charge to your credit card.
|
||||
|
||||
You will receive a notification once the refund is completed. If you have any further questions about your billing
|
||||
or need an update, please let me know!
|
||||
|
||||
You: Actually I also can't turn on my modem. It reset and now won't turn on.
|
||||
|
||||
============================================================
|
||||
AWAITING INPUT FROM: TECHNICAL_SUPPORT
|
||||
============================================================
|
||||
[user]: Actually I also can't turn on my modem. It reset and now won't turn on.
|
||||
[billing_agent]: I'm connecting you with technical support for assistance with your modem not turning on after
|
||||
the reset. They'll be able to help troubleshoot and resolve this issue.
|
||||
|
||||
At the same time, technical support will also handle your refund request for the duplicate charge on invoice 1234
|
||||
to your credit card on autopay.
|
||||
|
||||
You will receive updates from the appropriate teams shortly.
|
||||
>>> [technical_support]: Thanks for letting me know about your modem issue! To help you further, could you tell me:
|
||||
|
||||
1. Is there any light showing on the modem at all, or is it completely off?
|
||||
2. Have you tried unplugging the modem from power and plugging it back in?
|
||||
3. Do you hear or feel anything (like a slight hum or vibration) when the modem is plugged in?
|
||||
|
||||
Let me know, and I'll guide you through troubleshooting or arrange a repair if needed.
|
||||
|
||||
You: exit
|
||||
|
||||
Ending conversation. Goodbye!
|
||||
|
||||
============================================================
|
||||
Conversation ended.
|
||||
"""
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
asyncio.run(main())
|
||||
Reference in New Issue
Block a user