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Dial Rasa for Dinner - Chatbot Language Learning
William Galindez Arias
Senior Consultant / Advisor, Octesoft
Rasa Developer Summit - 2019
William Galindez Arias
@WilliamAriasZ
Dial Rasa for Dinner
1. Learn Czech (a bit)
Rasa Developer Summit - William Galindez Ariaz, Octesoft - Dial Rasa for Dinner
Process the information and reply back
One Direction
You learn how to say things, but hardly
how to react
Me
Real life(Test Data?)
2. Problems I want to Solve
Learn Czech
To survive
Build
Technical Skills
Have fun
Learn Czech
To survive
What is relevant to your
context ?
Immediate Impact
Achieve a Goal
Learn Czech
To survive
Build
Technical Skills
Have fun
Relevant Context = Closed - Domain
Vocabulary = Dataset or Corpus
Achieve a goal = Goal-Oriented
2.1 The making (New/ Better Problems)
2. Problems I want to Solve
Improved problems… starting to Have fun
https://spacy.io/usage/models
Word2Vec?
Embeddings for Deep Learning? Rank Intents
https://github.com/UFAL-DSG/cs_restaurant_dataset
Department of Linguistics
Label
Intent
PDF - CSV - Pandas DataFrame Have fun
Consolidated
Dataset
trn_data = json.dumps(czech) Rasa NLU
Supervised Embeddings
{'intent':
{
'name': 'order_food_main_dish',
'confidence': 0.8891581892967224},
'entities': [{'start': 23, 'end': 34,
'value': 'Smažený sýr', 'entity': 'dish',
'confidence': 0.6718105031002314,
'extractor': 'ner_crf’
}
]
One Context: not Enough
Food dialogue See a Doctor Complain
…+ + Flirt?
Let’s give it a face:
Receptionist Bot
['BotUttered (text: Hello, or should I say Ahoj?,
data:
{"elements": null,
"quick_replies": null,
"buttons":
[{"payload": "call doctor program training",
"title": "suggestion_1"},
{"payload": "I want to complain",
"title": "suggestion_2"},
{"payload": "Food Program",
"title": "suggestion_3"}]
Or Add Context Manually
Ordering Food, Doctor, Flirt?
Surviving:
Asking Beer
Fluent Waiter, many combinations
of utterances (Jabs, uppercuts,
hooks)
6/10
Rasa Developer Summit - William Galindez Ariaz, Octesoft - Dial Rasa for Dinner
Architecture v1.0
Food
Doctor
Complains
Waiter
Doctor
ISP
5055
5056
Context Selector
5057
Front Rasa
CustomActions
DB
ReceptionistBot
(English)
NoSQL
Key Spaces
Rasa Action
Server
Manual Selector
Intent Driven
Selector
2.1 The making (New/ Better Problems)
2. Problems I want to Solve
2.2 Language beyond my use case
Robots
Architecture for RPA (Automation)
Front Rasa SDK
CustomActions
InvoicesBot
RPA Cloud
Orchestrator
Rasa
Build
TechnicalSkills
POST:
Entities from SLOTS along
with Token
Cloud ERP
Problem: I can’t afford Named users Licenses for ERP or Windows
Proposed Solution: One Bot facing the systems (1 license)
”Hey Chatbot please process pending invoices from August 2019”
Windows VMs
Entities=Arguments
Architecture for Searching Staff HR
Web
NLU
APIM
Rasa
NLU
Build
TechnicalSkills
POST:
Intent/Entities from search to
API Gateway
API
GW
µ_1 µ_2 µ_n
Cassandra Cluster
k1 k2 k3
Microservices
Problem: Time consuming to find Staff in legacy tools
Proposed Solution: Search with natural queries:
”Find me candidates with Python Skills available to start next week”
</end>
Decision Makers of Tomorrow

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