Amazon Lex Movie Recommendations Chatbot

Introduction

A simple Amazon Lex Chatbot that is able to provide movie recommendations for a given movie genre. This implementation is performed using Amazon Lex V2.

Amazon Lex V2 Slides

AWSLexV2Chatbots.pdf

Integration

Movie recommendation data is provided by The Movie Database (TMDB).

Lambda Function

The chatbot integrates with TMDB API endpoint using a custom AWS Lambda Function developed in Python3:

import os
from tmdbv3api import TMDb, Discover

tmdb = TMDb()
tmdb.api_key = os.getenv('APIKEY')

GENRES = {
"action": 28,
"adventure": 12,
"animation": 16,
"comedy": 35,
"crime": 80,
"documentary": 99,
"drama": 18,
"family": 10751,
"Fantasy": 14,
"history": 36,
"horror": 27,
"music": 10402,
"mystery": 9648,
"romance": 10749,
"science fiction": 878,
"thriller": 53,
"war": 10752,
"western": 37
}

def get_slots(intent_request):
    return intent_request['sessionState']['intent']['slots']
    
def get_slot(intent_request, slotName):
    slots = get_slots(intent_request)
    if slots is not None and slotName in slots and slots[slotName] is not None:
        return slots[slotName]['value']['interpretedValue']
    else:
        return None    

def get_session_attributes(intent_request):
    sessionState = intent_request['sessionState']
    if 'sessionAttributes' in sessionState:
        return sessionState['sessionAttributes']

    return {}

def elicit_intent(intent_request, session_attributes, message):
    return {
        'sessionState': {
            'dialogAction': {
                'type': 'ElicitIntent'
            },
            'sessionAttributes': session_attributes
        },
        'messages': [ message ] if message != None else None,
        'requestAttributes': intent_request['requestAttributes'] if 'requestAttributes' in intent_request else None
    }

def close(intent_request, session_attributes, fulfillment_state, message):
    intent_request['sessionState']['intent']['state'] = fulfillment_state
    return {
        'sessionState': {
            'sessionAttributes': session_attributes,
            'dialogAction': {
                'type': 'Close'
            },
            'intent': intent_request['sessionState']['intent']
        },
        'messages': [message],
        'sessionId': intent_request['sessionId'],
        'requestAttributes': intent_request['requestAttributes'] if 'requestAttributes' in intent_request else None
    }

def MovieRecommendation(intent_request):
    session_attributes = get_session_attributes(intent_request)
    slots = get_slots(intent_request)
    genre = get_slot(intent_request, 'genre')

    discover = Discover()
    movies = discover.discover_movies({
        'primary_release_date.gte': '2019-01-01',
        'primary_release_date.lte': '2021-12-01',
        'with_genres': GENRES.get(genre.lower())
    })

    recs = ""
    for movie in movies:
        recs = recs + f" {movie.title}, "

    text = f"Thank you. Your recommended movies are: {recs}"
    message =  {
            'contentType': 'PlainText',
            'content': text
        }

    fulfillment_state = "Fulfilled"    
    return close(intent_request, session_attributes, fulfillment_state, message)
    
def dispatch(intent_request):
    intent_name = intent_request['sessionState']['intent']['name']
    response = None

    if intent_name == 'MovieRecommendation':
        return MovieRecommendation(intent_request)
    #elif intent_name == 'OtherIntent':
    #    return OtherIntent(intent_request)

    raise Exception('Intent with name ' + intent_name + ' not supported')

def lambda_handler(event, context):
    response = dispatch(event)
    return response

Installation

1. Register for a TMDB API key
2. Within the install.sh file, update the APIKEY variable:

install.sh:

APIKEY=TMDB_API_KEY_HERE

3. Execute the install.sh script
4. Log in to the AWS Lex console and then import the newly created lex-movierecommendations.zip package

Set the following options:

• Bot name, enter MovieRecommendations

• IAM permissions, select create a role with basic Amazon Lex permissions

• Childrens Online Privacy Protection Act, select No

5. After the import has succeeded - in the lefthand menu navigate to Deployment/Aliases for the newly created MovieRecommendations bot and click on the TestBotAlias

6. Within the TestBotAlias click on the English language

7. Select movierecommendations for Source, and $LATEST for Lambda function version or alias. Click Save.

8. In the lefthand menu navigate to Bot versions/Draft version, and then under Languages click on the English language link.

9. In the bottom menu bar click on the build button to compile the MovieRecommendations Chatbot.

10. Confirm that the MovieRecommendations Chatbot build has completed successfully.

11. Confirm that the MovieRecommendations Chatbot build has completed successfully, and then click on the Test button to activate the Chatbot.

12. Within the Chatbot test pane, enter any of the following utterances to start the Chatbot conversation:

recommend a movie
recommend a {genre} movie
recommend a {genre} film
I want to watch a movie
I want to watch a {genre} movie

Note: The following movie genres are supported:

Action
Adventure
Animation
Comedy
Crime
Documentary
Drama
Family
Fantasy
History
Horror
Music
Mystery
Romance
Science Fiction
Thriller
War
Western

Example Chatbot conversation: