A simple package for interfacing with Dialogflow
Project description
Affability
Affability allows for an easy utilization of Google's DialogFlow for natural language understanding. It allows for calling a single function and returning the result from Dialogflow as a class containing all the pertinent data such as detected intent.
This can be utilized to understand commands and then perform the relevant tasks based from the detected intent. Affability is ultimately designed to have the ability to assist with a quadruped robot project in the future.
Dependencies
Installing using the requirements.txt file:
pip install -r requirements.txt
Installing manually:
pip install SpeechRecognition
pip install dialogflow
Usage
As a standalone file, Brain.py can be run.
Using the understand function:
The understand function contains 5 parameters: text, credentials, projectID, languageCode, and sessionID. Text is text to be analyzed, credentials is the file path of the authentication key, projectID is the project ID, languageCode is the language, and sessionID is the session ID. All parameters are strings.
understand('textToBeAnalyzed', 'filepath', 'projectIDname', 'en-US', 'me')
The understand function returns the results as an organizer class. This class contains detectedIntent, confidence, reply, action, requiredParamsPresent, and replyParams.
class organizer:
def __init__(self, detectedIntent, confidence, reply, action, requiredParamsPresent, replyParams):
self.detectedIntent = detectedIntent
self.confidence = confidence
self.reply = reply
self.action = action
self.requiredParamsPresent = requiredParamsPresent
self.replyParams = replyParams
For example, to extract and print detected intent:
reply = understand('textToBeAnalyzed', 'filepath', 'projectIDname', 'en-US', 'me')
print(reply.detectedIntent)
Project details
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