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‎samples/19.custom-dialogs/README.md

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# Custom Dialogs
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Bot Framework v4 custom dialogs bot sample
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This bot has been created using [Bot Framework](https://dev.botframework.com), it shows how to sub-class the `Dialog` class to create different bot control mechanism like simple slot filling.
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BotFramework provides a built-in base class called `Dialog`. By subclassing `Dialog`, developers can create new ways to define and control dialog flows used by the bot.
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## Running the sample
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- Clone the repository
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```bash
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git clone https://github.com/Microsoft/botbuilder-python.git
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```
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- Activate your desired virtual environment
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- Bring up a terminal, navigate to `botbuilder-python\samples\19.custom-dialogs` folder
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- In the terminal, type `pip install -r requirements.txt`
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- In the terminal, type `python app.py`
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## Testing the bot using Bot Framework Emulator
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[Microsoft Bot Framework Emulator](https://github.com/microsoft/botframework-emulator) is a desktop application that allows bot developers to test and debug their bots on localhost or running remotely through a tunnel.
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- Install the Bot Framework emulator from [here](https://github.com/Microsoft/BotFramework-Emulator/releases)
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### Connect to bot using Bot Framework Emulator
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- Launch Bot Framework Emulator
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- File -> Open Bot
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- Paste this URL in the emulator window - http://localhost:3978/api/messages
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## Custom Dialogs
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BotFramework provides a built-in base class called `Dialog`. By subclassing Dialog, developers
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can create new ways to define and control dialog flows used by the bot. By adhering to the
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features of this class, developers will create custom dialogs that can be used side-by-side
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with other dialog types, as well as built-in or custom prompts.
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This example demonstrates a custom Dialog class called `SlotFillingDialog`, which takes a
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series of "slots" which define a value the bot needs to collect from the user, as well
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as the prompt it should use. The bot will iterate through all of the slots until they are
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all full, at which point the dialog completes.
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# Further reading
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- [Bot Framework Documentation](https://docs.botframework.com)
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- [Bot Basics](https://docs.microsoft.com/azure/bot-service/bot-builder-basics?view=azure-bot-service-4.0)
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- [Dialogs](https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-concept-dialog?view=azure-bot-service-4.0)
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- [Dialog class reference](https://docs.microsoft.com/en-us/javascript/api/botbuilder-dialogs/dialog)
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- [Manage complex conversation flows with dialogs](https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-dialog-manage-complex-conversation-flow?view=azure-bot-service-4.0)
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- [Activity processing](https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-concept-activity-processing?view=azure-bot-service-4.0)

‎samples/19.custom-dialogs/app.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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import asyncio
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import sys
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from datetime import datetime
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from types import MethodType
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from flask import Flask, request, Response
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from botbuilder.core import (
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BotFrameworkAdapter,
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BotFrameworkAdapterSettings,
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ConversationState,
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MemoryStorage,
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TurnContext,
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UserState,
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)
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from botbuilder.schema import Activity, ActivityTypes
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from bots import DialogBot
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# Create the loop and Flask app
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from dialogs.root_dialog import RootDialog
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LOOP = asyncio.get_event_loop()
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APP = Flask(__name__, instance_relative_config=True)
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APP.config.from_object("config.DefaultConfig")
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# Create adapter.
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# See https://aka.ms/about-bot-adapter to learn more about how bots work.
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SETTINGS = BotFrameworkAdapterSettings(APP.config["APP_ID"], APP.config["APP_PASSWORD"])
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ADAPTER = BotFrameworkAdapter(SETTINGS)
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# Catch-all for errors.
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async def on_error(self, context: TurnContext, error: Exception):
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# This check writes out errors to console log .vs. app insights.
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# NOTE: In production environment, you should consider logging this to Azure
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# application insights.
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print(f"\n [on_turn_error] unhandled error: {error}", file=sys.stderr)
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# Send a message to the user
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await context.send_activity("The bot encountered an error or bug.")
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await context.send_activity("To continue to run this bot, please fix the bot source code.")
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# Send a trace activity if we're talking to the Bot Framework Emulator
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if context.activity.channel_id == 'emulator':
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# Create a trace activity that contains the error object
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trace_activity = Activity(
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label="TurnError",
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name="on_turn_error Trace",
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timestamp=datetime.utcnow(),
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type=ActivityTypes.trace,
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value=f"{error}",
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value_type="https://www.botframework.com/schemas/error"
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)
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# Send a trace activity, which will be displayed in Bot Framework Emulator
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await context.send_activity(trace_activity)
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ADAPTER.on_turn_error = MethodType(on_error, ADAPTER)
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# Create MemoryStorage and state
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MEMORY = MemoryStorage()
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USER_STATE = UserState(MEMORY)
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CONVERSATION_STATE = ConversationState(MEMORY)
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# Create Dialog and Bot
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DIALOG = RootDialog(USER_STATE)
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BOT = DialogBot(CONVERSATION_STATE, USER_STATE, DIALOG)
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# Listen for incoming requests on /api/messages.
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@APP.route("/api/messages", methods=["POST"])
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def messages():
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# Main bot message handler.
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if "application/json" in request.headers["Content-Type"]:
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body = request.json
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else:
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return Response(status=415)
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activity = Activity().deserialize(body)
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auth_header = (
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request.headers["Authorization"] if "Authorization" in request.headers else ""
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)
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try:
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task = LOOP.create_task(
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ADAPTER.process_activity(activity, auth_header, BOT.on_turn)
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)
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LOOP.run_until_complete(task)
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return Response(status=201)
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except Exception as exception:
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raise exception
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if __name__ == "__main__":
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try:
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APP.run(debug=False, port=APP.config["PORT"]) # nosec debug
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except Exception as exception:
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raise exception

‎samples/19.custom-dialogs/bots/__init__.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from .dialog_bot import DialogBot
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__all__ = ["DialogBot"]

‎samples/19.custom-dialogs/bots/dialog_bot.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from botbuilder.core import ActivityHandler, ConversationState, TurnContext, UserState
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from botbuilder.dialogs import Dialog
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from helpers.dialog_helper import DialogHelper
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class DialogBot(ActivityHandler):
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def __init__(self, conversation_state: ConversationState, user_state: UserState, dialog: Dialog):
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self.conversation_state = conversation_state
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self.user_state = user_state
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self.dialog = dialog
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async def on_turn(self, turn_context: TurnContext):
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await super().on_turn(turn_context)
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# Save any state changes that might have occurred during the turn.
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await self.conversation_state.save_changes(turn_context)
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await self.user_state.save_changes(turn_context)
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async def on_message_activity(self, turn_context: TurnContext):
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# Run the Dialog with the new message Activity.
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await DialogHelper.run_dialog(
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self.dialog,
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turn_context,
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self.conversation_state.create_property("DialogState"),
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)

‎samples/19.custom-dialogs/config.py

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#!/usr/bin/env python3
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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import os
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""" Bot Configuration """
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class DefaultConfig:
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""" Bot Configuration """
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PORT = 3978
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APP_ID = os.environ.get("MicrosoftAppId", "")
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APP_PASSWORD = os.environ.get("MicrosoftAppPassword", "")

‎samples/19.custom-dialogs/dialogs/__init__.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from .slot_filling_dialog import SlotFillingDialog
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from .root_dialog import RootDialog
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__all__ = ["RootDialog", "SlotFillingDialog"]

‎samples/19.custom-dialogs/dialogs/root_dialog.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from typing import Dict
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from botbuilder.dialogs import (
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ComponentDialog,
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WaterfallDialog,
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WaterfallStepContext,
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DialogTurnResult,
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NumberPrompt, PromptValidatorContext)
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from botbuilder.dialogs.prompts import TextPrompt
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from botbuilder.core import MessageFactory, UserState
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from recognizers_text import Culture
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from dialogs import SlotFillingDialog
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from dialogs.slot_details import SlotDetails
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class RootDialog(ComponentDialog):
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def __init__(
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self, user_state: UserState
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):
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super(RootDialog, self).__init__(RootDialog.__name__)
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self.user_state_accessor = user_state.create_property("result")
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# Rather than explicitly coding a Waterfall we have only to declare what properties we want collected.
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# In this example we will want two text prompts to run, one for the first name and one for the last
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fullname_slots = [
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SlotDetails(
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name="first",
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dialog_id="text",
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prompt="Please enter your first name."
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),
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SlotDetails(
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name="last",
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dialog_id="text",
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prompt="Please enter your last name."
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)
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]
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# This defines an address dialog that collects street, city and zip properties.
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address_slots = [
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SlotDetails(
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name="street",
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dialog_id="text",
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prompt="Please enter the street address."
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),
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SlotDetails(
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name="city",
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dialog_id="text",
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prompt="Please enter the city."
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),
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SlotDetails(
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name="zip",
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dialog_id="text",
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prompt="Please enter the zip."
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)
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]
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# Dialogs can be nested and the slot filling dialog makes use of that. In this example some of the child
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# dialogs are slot filling dialogs themselves.
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slots = [
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SlotDetails(
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name="fullname",
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dialog_id="fullname",
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),
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SlotDetails(
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name="age",
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dialog_id="number",
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prompt="Please enter your age."
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),
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SlotDetails(
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name="shoesize",
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dialog_id="shoesize",
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prompt="Please enter your shoe size.",
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retry_prompt="You must enter a size between 0 and 16. Half sizes are acceptable."
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),
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SlotDetails(
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name="address",
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dialog_id="address"
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)
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]
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# Add the various dialogs that will be used to the DialogSet.
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self.add_dialog(SlotFillingDialog("address", address_slots))
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self.add_dialog(SlotFillingDialog("fullname", fullname_slots))
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self.add_dialog(TextPrompt("text"))
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self.add_dialog(NumberPrompt("number", default_locale=Culture.English))
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self.add_dialog(NumberPrompt("shoesize", RootDialog.shoe_size_validator, default_locale=Culture.English))
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self.add_dialog(SlotFillingDialog("slot-dialog", slots))
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# Defines a simple two step Waterfall to test the slot dialog.
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self.add_dialog(
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WaterfallDialog(
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"waterfall", [self.start_dialog, self.process_result]
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)
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)
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# The initial child Dialog to run.
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self.initial_dialog_id = "waterfall"
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async def start_dialog(self, step_context: WaterfallStepContext) -> DialogTurnResult:
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# Start the child dialog. This will run the top slot dialog than will complete when all the properties are
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# gathered.
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return await step_context.begin_dialog("slot-dialog")
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async def process_result(self, step_context: WaterfallStepContext) -> DialogTurnResult:
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# To demonstrate that the slot dialog collected all the properties we will echo them back to the user.
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if type(step_context.result) is dict and len(step_context.result) > 0:
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fullname: Dict[str, object] = step_context.result["fullname"]
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shoe_size: float = step_context.result["shoesize"]
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address: dict = step_context.result["address"]
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# store the response on UserState
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obj: dict = await self.user_state_accessor.get(step_context.context, dict)
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obj["data"] = {}
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obj["data"]["fullname"] = f"{fullname.get('first')} {fullname.get('last')}"
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obj["data"]["shoesize"] = f"{shoe_size}"
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obj["data"]["address"] = f"{address['street']}, {address['city']}, {address['zip']}"
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# show user the values
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await step_context.context.send_activity(MessageFactory.text(obj["data"]["fullname"]))
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await step_context.context.send_activity(MessageFactory.text(obj["data"]["shoesize"]))
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await step_context.context.send_activity(MessageFactory.text(obj["data"]["address"]))
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return await step_context.end_dialog()
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@staticmethod
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async def shoe_size_validator(prompt_context: PromptValidatorContext) -> bool:
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shoe_size = round(prompt_context.recognized.value, 1)
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# show sizes can range from 0 to 16, whole or half sizes only
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if 0 <= shoe_size <= 16 and (shoe_size * 2) % 1 == 0:
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prompt_context.recognized.value = shoe_size
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return True
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return False

‎samples/19.custom-dialogs/dialogs/slot_details.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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from botbuilder.core import MessageFactory
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from botbuilder.dialogs import PromptOptions
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class SlotDetails:
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def __init__(self,
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name: str,
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dialog_id: str,
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options: PromptOptions = None,
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prompt: str = None,
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retry_prompt: str = None
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):
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self.name = name
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self.dialog_id = dialog_id
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self.options = options if options else PromptOptions(
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prompt=MessageFactory.text(prompt),
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retry_prompt=None if retry_prompt is None else MessageFactory.text(retry_prompt)
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)

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