Hands-on Chatbots with Google Dialogflow

Learn to design and deploy chatbots with Google Dialogflow, from account setup to intents and entities. Explore contexts, fulfillment, and Slack integration for a trip planner style bot.

Explore Google Dialogflow, an AI-based platform for building natural language chat bots with a simple UI; compare rule-based and AI-based bots and learn how models tailor to each bot.

Learn the big picture of how Dialogflow processes user expressions, maps intents, and uses server-side fulfillment to answer queries via cloud functions, APIs, and app integrations.

Set up your Google Dialogflow account, sign up on dialogflow dot com, and create your first agent to enable natural language understanding and test conversations in the console.

Learn the building blocks of dialog flow—agents, intents, entities, and contexts. Create an agent from scratch, define custom intents like book rooms, and configure entities and user expressions.

Discover how a Dialogflow agent is a natural language understanding module linked to a Google project, and how to create your first agent with English as the default language.

Explore agent settings in Dialogflow, including general and languages tabs, machine learning modes (hybrid vs ml-only), confidence thresholds, and tokens for client and developer access.

Discover how default intents—fallback and welcome—are created automatically with a new agent and how the fallback is fully configured while the welcome intent remains partially configured.

Enable smalltalk in Dialogflow to make your bot friendly and conversational, delivering greetings, empathy, and natural responses, with prebuilt agents and webhook or cloud function fulfillment.

Explore how custom intents map user requests to backend actions in Dialogflow, configuring user expressions, actions, responses, and contexts to trigger server code for booking rooms or cars.

Explore how Dialogflow uses system, developer, and user entities to extract parameter values for bookings, including city, date, and room type, and understand slot filling and backend requests.

Define developer-defined entities in Dialogflow, configure car and room values for booking, and use synonyms, automated expansion, and real mode with json or csv.

Explore how Dialogflow annotates user expressions to fill intent parameters, configure the user says section, and map entities for book cards and book rooms.

Configure and test the book cars intent in Google Dialogflow by defining required parameters, prompts to elicit values, and placeholders like $cars and $date to drive car bookings.

Configure and test the book rooms intent in Dialogflow by setting required parameters, prompts, and annotations, and verify design data and JSON payloads to ensure complete fulfillment.

Enable natural, long running conversations by using context, linear dialogues to collect information, and nonlinear dialogues to branch intents based on user responses, such as room booking and feedback surveys.

Explore how contexts in Dialogflow use input and output contexts to carry information across intents, enabling room booking data to flow into car bookings and avoid fallbacks.

Understand how follow up intents in Dialogflow enable multi-step conversations through input and output contexts. Learn to link related bookings with custom follow ups that leverage contexts for seamless dialogue.

Learn why linear dialogues are used, with single-intent and multi-intent flows, and how to elicit all required information to fulfill a user's booking.

Explore how non-linear dialogues in Dialogflow branch to different intents based on user responses, using contexts and entities to collect location and facilities ratings for a hotel satisfaction survey.

Explore how a non-linear dialog branches on user feedback, configuring location and facilities intents with input contexts for the customer satisfaction survey so only one branch is invoked.

Create a weatherboard connected to open weather API using Dialogflow, with intents and entities for city and date, fulfilled by a Python Flask webhook, deployed to Heroku with Slack integration.

Learn to create a check weather intent in Dialogflow, collect city and forecast parameters, and fulfill requests via webhook using inline editor and cloud functions.

Learn how to build a Dialogflow webhook using Python and Flask, handling post requests, parsing JSON, querying the open weather API, and returning a correctly formatted JSON response for Dialogflow.

Extract parameter values from Dialogflow's input JSON by accessing result.parameters for city and date, then structure a Dialogflow webhook response with speech, displayText, and source, and wire up Flask server.

Query the open weather map API for a five-day forecast by city name, with JSON or HTML responses. Use Python Flask on Heroku with the requests library and an API key.

Fetch city weather data from the open weather map API, use five day or fifteen day forecasts, parse the JSON list, extract the description, and update the Dialogflow response.

Heroku, among the oldest platform as a service models, lets you deploy apps with no vm setup, supports Java, Python, and Node.js, and deploys via Git, GitHub, Dropbox, or CLI.

Learn how to deploy a Python app to Heroku from GitHub by creating a GitHub repository, adding a requirements.txt and a Procfile, and enabling automatic deployments.

Enable fulfillment with webhooks in Dialogflow by wiring a Heroku-hosted endpoint to a single intent, configuring action strings, and testing with open weather map API.

Configure a Slack bot user and link Slack with Dialogflow to enable weatherboard to respond in Slack by subscribing to message events and authenticating with Slack app credentials.

Integrate Dialogflow with Slack to enable a weatherboard, configure client ID, client secret, and verification token, and test event subscriptions and bot user interactions with the open weather map API.

Learn how to fulfill Dialogflow intents with inline cloud functions in Google Cloud, using Node.js, Firebase functions, webhooks, and parameter handling to respond with open weather map API examples.