-
Notifications
You must be signed in to change notification settings - Fork 1.1k
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
docs: refactor structure, add tutorials
- Loading branch information
1 parent
3c10c31
commit 5e6633a
Showing
19 changed files
with
113 additions
and
25 deletions.
There are no files selected for viewing
File renamed without changes.
File renamed without changes.
File renamed without changes.
File renamed without changes.
File renamed without changes.
File renamed without changes.
File renamed without changes.
File renamed without changes.
File renamed without changes.
File renamed without changes.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,33 @@ | ||
This is "Hello, World!" example of simple bot implemented in DeepPavlov | ||
======================================================================= | ||
|
||
Import key components to build HelloBot. | ||
|
||
.. code:: python | ||
from deeppavlov.core.agent import Agent, HighestConfidenceSelector | ||
from deeppavlov.skills.pattern_matching_skill import PatternMatchingSkill | ||
Create skills as pre-defined responses for a user's input containing | ||
specific keywords. Every skill returns response and confidence. | ||
|
||
.. code:: python | ||
hello = PatternMatchingSkill(responses=['Hello world! :)'], patterns=["hi", "hello", "good day"]) | ||
bye = PatternMatchingSkill(['Goodbye world! :(', 'See you around.'], ["bye", "chao", "see you"]) | ||
fallback = PatternMatchingSkill(["I don't understand, sorry :/", 'I can say "Hello world!" 8)']) | ||
Agent executes skills and then takes response from the skill with the | ||
highest confidence. | ||
|
||
.. code:: python | ||
HelloBot = Agent([hello, bye, fallback], skills_selector=HighestConfidenceSelector()) | ||
Give the floor to the HelloBot! | ||
|
||
.. code:: python | ||
print(HelloBot(['Hello!', 'Boo...', 'Bye.'])) | ||
`Jupyter notebook with HelloBot example. <https://github.com/deepmipt/DeepPavlov/blob/master/examples/hello_bot.ipynb>`__ |
File renamed without changes.
File renamed without changes.
File renamed without changes.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,53 @@ | ||
DeepPavlov tutorials | ||
==================== | ||
|
||
Introduction to DeepPavlov | ||
-------------------------- | ||
|
||
`Jupyter notebook <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/00_deeppavlov_intro.ipynb>`__ \| | ||
`slides <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/00_deeppavlov_intro.pdf>`__ | ||
|
||
Install the library and understand a simple "Hello World!" Bot written | ||
in 7 lines of code. Experiment with basic pattern matching rule-based | ||
bot. | ||
|
||
Data preparation in DeepPavlov | ||
------------------------------ | ||
|
||
`Jupyter notebook <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/01_deeppavlov_data.ipynb>`__ | ||
|
||
Learn how to read and prepare data for trainable components. | ||
|
||
Named Entity Recognition with DeepPavlov | ||
---------------------------------------- | ||
|
||
`Jupyter notebook <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/02_deeppavlov_ner.ipynb>`__ \| | ||
`slides <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/02_deeppavlov_ner.pdf>`__ \| | ||
`video <https://youtu.be/6HlL87PWxXU>`__ | ||
|
||
Build a simple convolutional neural network to solve the named entity | ||
recognition task. Master data downloading, preprocessing and batching | ||
then train and score the model. | ||
|
||
Task-oriented bot with DeepPavlov | ||
--------------------------------- | ||
|
||
`Jupyter notebook <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/03_deeppavlov_gobot.ipynb>`__ \| | ||
`slides <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/03_deeppavlov_gobot.pdf>`__ \| | ||
`video <https://youtu.be/uvH1zB7qahI>`__ | ||
|
||
Intro to DeepPavlov configs - a powerfull method to stack models. Study | ||
how to train 4 different task-oriented bots on DSTC2 dataset. These | ||
include (1) a basic bot, (2) a bot with a database of restaurants, (3) a | ||
bot with fasttext embeddings, (4) a bot with attention mechanism over | ||
input words. | ||
|
||
Chit-chat bot with DeepPavlov | ||
----------------------------- | ||
|
||
`Jupyter notebook <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/04_deeppavlov_chitchat.ipynb>`__ \| | ||
`slides <https://github.com/deepmipt/DeepPavlov/tree/master/examples/tutorials/04_deeppavlov_chitchat.pdf>`__ \| | ||
`video <https://youtu.be/G1TkCkoghC8>`__ | ||
|
||
Implement in DeepPavlov sequence-to-sequence encoder-decoder model with | ||
attention mechanism and teacher forcing for chit-chat. |
File renamed without changes.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,2 @@ | ||
Pattern Matching Skill | ||
====================== |
This file was deleted.
Oops, something went wrong.