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‎Module 4 - Machine Learning/02. Working with Text Data/6. Chatbots Development using RASA/images/rasa_visualize.png

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‎Module 4 - Machine Learning/02. Working with Text Data/6. Chatbots Development using RASA/intro_to_rasa.ipynb

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" - RASA Command Line Interface (CLI)\n",
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" - Important Terminologies\n",
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"3. Building the First RASA Project\n",
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" - Initial Setup\n",
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" - Stories Visualization\n",
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" - Creating NLU Training Data\n",
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" - Customizing Dialogue Management\n",
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"4. RASA Developer Certificate Exam\n",
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"\n",
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"### **Important Terminology**\n",
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"Let's learn the foundational components used for structuring conversations within Rasa, such as an intent, entity, slot, form, response, action, rule, or story.\n",
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"1. **Story:** Training data format for the dialogue model, consisting of a conversation between a user and a bot. The user's messages are represented as annotated intents and entities, and the bot’s responses are represented as a sequence of actions.\n",
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"2. **Intent:** In a given user message, the thing that a user is trying to convey or accomplish (e,g., greeting, specifying a location).\n",
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"3. **Entity:** Keywords that can be extracted from a user message. For example: a telephone number, a person's name, a location, the name of a product.\n",
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"4. **Slot:** A key-value store that Rasa uses to track information over the course of a conversation.\n",
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"5. **Forms:** One of the most common conversation patterns is to collect a few pieces of information from a user in order to do something (book a restaurant, call an API, search a database, etc.). This is also called **slot filling**.\n",
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"6. **Response / Template / Utterance:** A message that an assistant sends to a user. This can include text, buttons, images, and other content.\n",
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"7. **Rules:** Special training data to specify rule-like behavior, where a specific condition always predicts a specific next action. Examples include answering FAQs, filling Forms, or handling Fallbacks."
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"1. **Story: (defined inside `data/stories.yml`)** Training data format for the dialogue model, consisting of a conversation between a user and a bot. The user's messages are represented as annotated intents and entities, and the bot’s responses are represented as a sequence of actions.\n",
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"2. **Intent: (defined inside `data/nlu.yml`)** In a given user message, the thing that a user is trying to convey or accomplish (e,g., greeting, specifying a location).\n",
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"3. **Entity: (defined inside `data/nlu.yml`)** Keywords that can be extracted from a user message. For example: a telephone number, a person's name, a location, the name of a product.\n",
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"4. **Response / Template / Utterance: (defined inside `domain.yml`)** A message that an assistant sends to a user. This can include text, buttons, images, and other content.\n",
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"5. **Slot: (defined inside `domain.yml`)** A key-value store that Rasa uses to track information over the course of a conversation. There are various slot types like: text, categorical, float, bool and list.\n",
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"6. **Slot Mapping: (defined inside `domain.yml`)** Slot mappings allow you to define how each slot will be filled in. Slot mappings are applied after each user message. There are various slot mapping types like: from_entity, from_intent, etc...\n",
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"7. **Forms: (defined inside `domain.yml`)** One of the most common conversation patterns is to collect a few pieces of information from a user in order to do something (book a restaurant, call an API, search a database, etc.). This is also called **slot filling**.\n",
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"8. **Rules: (defined inside `data/rules.yml`)** Special training data to specify rule-like behavior, where a specific condition always predicts a specific next action. Examples include answering FAQs, filling Forms, or handling Fallbacks."
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]
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},
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{
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"source": [
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"## **Building the First RASA Project**\n",
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"\n",
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"### **Initial Setup**\n",
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"1. **Create a new RASA Project:**\n",
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"```bash\n",
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"rasa init # Initialize a new project\n",
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"```"
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]
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},
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{
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"cell_type": "markdown",
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"id": "92e11e92-eda3-4952-8ee7-6371145449a1",
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"metadata": {},
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"source": [
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"### **Stories Visualization**\n",
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"\n",
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"<img src=\"images/rasa_visualize.png\">"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0aa4529f-1fc3-46dc-b2dc-9c1ecdc71a4e",
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"\n",
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"Define intents and entities in `data/nlu.yml`:\n",
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"```yaml\n",
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"version: \"2.0\"\n",
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"version: \"3.1\"\n",
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"\n",
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"nlu:\n",
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"- intent: greet\n",
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" examples: |\n",
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" - hello\n",
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" - hi\n",
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" - hey\n",
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" - good morning\n",
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" - good evening\n",
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" - hey there\n",
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"\n",
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"- intent: goodbye\n",
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" examples: |\n",
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" - bye\n",
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" - goodbye\n",
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" - see you later\n",
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" - see you soon\n",
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" - catch you later\n",
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"\n",
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"- intent: thankyou\n",
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" examples: |\n",
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" - thanks\n",
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" - thank you\n",
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" - thank you very much\n",
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" - thanks a lot\n",
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" - much appreciated\n",
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"\n",
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"- intent: book_flight\n",
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" examples: |\n",
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" - I want to book a flight to [Paris](location)\n",
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" - Book a flight to [New York](location)\n",
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" - I want to book a flight\n",
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" - I need to book a flight\n",
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" - Can you help me book a flight?\n",
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" - I'd like to book a flight\n",
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" - Help me book a flight\n",
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"\n",
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"- intent: inform\n",
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" examples: |\n",
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" - I'm departing from [San Francisco](departure_city)\n",
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" - I want to fly to [New York](destination_city)\n",
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" - My departure city is [Los Angeles](departure_city)\n",
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" - I'm going to [Miami](destination_city)\n",
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" - I'll be leaving from [Chicago](departure_city)\n",
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" - I need a flight to [Dallas](destination_city)\n",
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" - My destination is [Boston](destination_city)\n",
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" - I'll be traveling to [Seattle](destination_city)\n",
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" - The departure date is [June 15th](departure_date)\n",
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" - I'm leaving on [July 20th](departure_date)\n",
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" - [June 10th](departure_date) for departure\n",
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" - The departure date is [2024-06-15](departure_date)\n",
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" - I'm leaving on [2025-07-01](departure_date)\n",
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" - [2024-01-10](departure_date) for departure\n",
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" - The return date is [June 30th](return_date)\n",
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" - I'll be back on [August 5th](return_date)\n",
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" - Return on [July 25th](return_date)\n",
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" - The return date is [2024-06-15](return_date)\n",
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" - I'll be back on [2025-07-01](return_date)\n",
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" - Return on [2024-01-10](return_date)\n",
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"\n",
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"- intent: stop\n",
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" examples: |\n",
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" - stop\n",
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" - cancel\n",
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" - never mind\n",
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" - forget it\n",
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" - no more\n",
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"\n",
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"- intent: out_of_scope\n",
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" examples: |\n",
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" - Tell me a joke\n",
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" - What's the weather like?\n",
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" - How are you?\n",
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" - Who won the game last night?\n",
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" - Do you know any good restaurants?\n",
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"```\n",
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"\n",
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"For every **new intent** created, add it in `domain.yml`. \n",
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"For every **new intent and entity** created in nlu, add it in `domain.yml`. \n",
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"\n",
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"```yaml\n",
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"intents:\n",
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" - greet\n",
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" - goodbye\n",
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" - thankyou\n",
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" - book_flight\n",
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" - inform\n",
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" - stop\n",
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" - out_of_scope\n",
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"\n",
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"entities:\n",
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" - departure_city\n",
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" - destination_city\n",
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" - departure_date\n",
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" - return_date\n",
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"```"
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]
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},
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"Define stories in `data/stories.yml`:\n",
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"```yaml\n",
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"version: \"2.0\"\n",
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"\n",
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"stories:\n",
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"- story: greet and respond\n",
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" steps:\n",
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" - intent: greet\n",
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" - action: utter_greet\n",
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"\n",
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"- story: book a flight\n",
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" steps:\n",
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" - intent: book_flight\n",
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" - action: utter_ask_location\n",
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" - intent: inform\n",
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" - action: utter_confirm_booking\n",
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" # Happy path\n",
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" - story: happy path\n",
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" steps:\n",
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" - intent: greet\n",
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" - action: utter_greet\n",
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" - intent: book_flight\n",
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" - action: utter_ask_departure_city\n",
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" - intent: inform\n",
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" entities:\n",
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" - departure_city\n",
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" - slot_was_set:\n",
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" - departure_city: \"San Francisco\"\n",
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" - action: utter_ask_destination_city\n",
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" - intent: inform\n",
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" entities:\n",
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" - destination_city\n",
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" - slot_was_set:\n",
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" - destination_city: \"New York\"\n",
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" - action: utter_ask_departure_date\n",
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" - intent: inform\n",
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" entities:\n",
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" - departure_date\n",
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" - slot_was_set:\n",
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" - departure_date: \"2024-06-15\"\n",
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" - action: utter_ask_return_date\n",
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" - intent: inform\n",
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" entities:\n",
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" - return_date\n",
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" - slot_was_set:\n",
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" - return_date: \"2024-06-20\"\n",
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" - action: utter_submit\n",
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"\n",
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" # User decides not to book a flight\n",
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" - story: user decides not to book a flight\n",
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" steps:\n",
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" - intent: greet\n",
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" - action: utter_greet\n",
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" - intent: book_flight\n",
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" - action: utter_ask_departure_city\n",
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" - intent: inform\n",
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" entities:\n",
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" - departure_city\n",
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" - slot_was_set:\n",
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" - departure_city: \"San Francisco\"\n",
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" - action: utter_ask_destination_city\n",
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" - intent: inform\n",
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" entities:\n",
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" - destination_city\n",
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" - slot_was_set:\n",
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" - destination_city: \"New York\"\n",
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" - action: utter_ask_departure_date\n",
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" - intent: stop\n",
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" - action: utter_goodbye\n",
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"\n",
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" # User goes out of scope\n",
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" - story: user goes out of scope\n",
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" steps:\n",
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" - intent: greet\n",
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" - action: utter_greet\n",
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" - intent: out_of_scope\n",
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" - action: utter_out_of_scope\n",
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"\n",
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" # User thanks the bot\n",
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" - story: user thanks the bot\n",
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" steps:\n",
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" - intent: greet\n",
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" - action: utter_greet\n",
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" - intent: thankyou\n",
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" - action: utter_thankyou\n",
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"\n",
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" # User says goodbye\n",
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" - story: user says goodbye\n",
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" steps:\n",
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" - intent: greet\n",
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" - action: utter_greet\n",
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" - intent: goodbye\n",
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" - action: utter_goodbye\n",
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"\n",
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"```\n",
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"\n",
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"Define actions, slots and responses in `domain.yml`:\n",
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"```yaml\n",
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"version: \"2.0\"\n",
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"intents:\n",
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" - greet\n",
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" - goodbye\n",
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" - thankyou\n",
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" - book_flight\n",
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" - inform\n",
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" - stop\n",
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" - out_of_scope\n",
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"\n",
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"entities:\n",
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" - location\n",
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" - departure_city\n",
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" - destination_city\n",
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" - departure_date\n",
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" - return_date\n",
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"\n",
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"slots:\n",
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" location:\n",
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" departure_city:\n",
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" type: text\n",
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" mappings:\n",
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" - type: from_entity\n",
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" entity: departure_city\n",
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" destination_city:\n",
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" type: text\n",
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" mappings:\n",
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" - type: from_entity\n",
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" entity: destination_city\n",
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" departure_date:\n",
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" type: text\n",
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" mappings:\n",
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" - type: from_entity\n",
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" entity: departure_date\n",
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" return_date:\n",
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" type: text\n",
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" mappings:\n",
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" - type: from_entity\n",
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" entity: return_date\n",
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"\n",
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"\n",
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"responses:\n",
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" utter_greet:\n",
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" - text: \"Hello! How can I assist you today?\"\n",
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"\n",
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" utter_ask_location:\n",
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" - text: \"Where would you like to fly to?\"\n",
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"\n",
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" utter_confirm_booking:\n",
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" - text: \"Your flight to {location} is booked!\"\n",
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" - text: \"Hi, I am a helpful assistant who can help you book a flight at your convinience.\"\n",
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" utter_ask_departure_city:\n",
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" - text: \"From which city are you departing?\"\n",
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" utter_ask_destination_city:\n",
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" - text: \"What is your destination city?\"\n",
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" utter_ask_departure_date:\n",
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" - text: \"What is your departure date?\"\n",
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" utter_ask_return_date:\n",
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" - text: \"What is your return date?\"\n",
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" utter_submit:\n",
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" - text: \"Your flight from {departure_city} to {destination_city} has been booked. Departure on {departure_date} and return on {return_date}.\"\n",
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" utter_goodbye:\n",
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" - text: \"Bye. Happy to help!\"\n",
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" utter_out_of_scope:\n",
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" - text: \"Hi, I am a helpful assistant who can help you book a flight at your convinience.\"\n",
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" utter_thankyou:\n",
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" - text: \"Happy to help! Is there anything else?\"\n",
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"```"
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]
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},

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