DEPRECATED: THESE APIs ARE NOT SUPPORTED ANY MORE.

This repo will be deleted shortly.

pymyra

The Python SDK for the Myra Conversational AI REST API. Myra's APIs are trained on over a billion news articles, conversational logs, and targeted web pages, and are paired with the latest AI research to deliver industry-leading intent parsing and entity extraction.

Install

Using pip:

pip install pymyra

From source:

git clone https://github.com/myralabs/pymyra
cd pymyra
pip install .

Overview

pymyra provides access to the Myra RESTful APIs. It currently supports Python 2.7.

To continue, copy your API credentials from the Explore API tab. You can then replace the empty account_id and account_secret fields in the example below with your own.

See the tutorial directory for a step by step tutorial and examples.

Minimal Example

Put this in test.py:

from pymyra.api import client
import json

# Connect API
config = {
  "account_id": "...",  # Replace with the correct IDs after creating an account.
  "account_secret": "..."
}
api = client.connect(config)

# Set intent model
api.set_intent_model("...")  # Fill in intent model id from dashboard.

# Set entity model
api.set_entity_model("...")  # Fill in entity model id from dashboard.

# Get results
sentence = "Create a meeting with Alan Turing and Von Neumann next friday at 10am in Princeton"
result = api.get(sentence)

print("Sentence: %s" % sentence)
print("Inferred intent is '%s' with confidence %s" % (result.intent.label, result.intent.score))
print("Recognized entities are:\n%s" % json.dumps(result.entities.entity_dict, indent=4))

and you'll get:

$ python test.py 
Sentence: Create a meeting with Alan Turing and Von Neumann next friday at 10am in Princeton
Inferred intent is 'create' with confidence 0.885836362839
Recognized entities are:
{
    "status": {
        "status_code": 200
    }, 
    "builtin": {
        "DATE": [
            {
                "date": "Fri, 28 Oct 2016 10:00:00 GMT", 
                "start": 9, 
                "end": 12, 
                "label": "next friday at 10am"
            }
        ], 
        "GPE": [
            {
                "start": 15, 
                "text": "Princeton", 
                "end": 16, 
                "label": "GPE"
            }
        ], 
        "TIME": [
            {
                "start": 12, 
                "text": "10am", 
                "end": 14, 
                "label": "TIME"
            }
        ], 
        "search_query": "Create meeting Alan Turing Von Neumann next friday 10 am Princeton", 
        "PERSON": [
            {
                "start": 4, 
                "text": "Alan Turing", 
                "end": 6, 
                "label": "PERSON"
            }, 
            {
                "start": 7, 
                "text": "Von Neumann", 
                "end": 9, 
                "label": "PERSON"
            }
        ]
    }, 
    "user_defined": {}
}
$