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    "info": {
        "author": "Intelligent Artifacts",
        "author_email": "support@intelligent-artifacts.com",
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            "License :: OSI Approved :: MIT License",
            "Operating System :: OS Independent",
            "Programming Language :: Python :: 3"
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        "description": "# Genie Python SDK\nA Python SDK for Intelligent Artifacts' Genie.\n\n## What is Genie?\nGenie is a General Evolving Networked Intelligence Engine.  It is an Artificial General Intelligence platform for rapidly building machine intelligence solutions for any problem domain.\n\nGenie requires an account on Intelligent Artifacts.\n\n## What is Genie Python SDK?\nThis package, Genie Python SDK, is a software development kit for interacting with \"genies\" and \"bottles\" from Python.  It provides useful tools and services.\n\n## Install\n`pip install ia-genie-sdk`\n\nProvides:\n\n    - GenomeInfo\n    - BottleClient\n    - BackTesting\n\n#### To use GenomeInfo:\n\nYou will need to download your genie's genome file from your Intelligent Artifacts account.\n\n~~~\nfrom ialib.GenomeInfo import Genome\nimport json\n\ngenome_topology = json.loads(genome_json_string)\ngenome = Genome(genome_topology)\n~~~\n\nIf you want to have the topology displayed, you need to install cyjupter:\n\n`pip3 install cyjupyter`\n\n\n##### The useful functions are:\n~~~\ngenome.agent - returns the name of the agent.\n    ex: 'focusgenie'\n\ngenome.getNodes() - returns 2-tuple of primitives and manipulatives genomic data.\n\ngenome.getActions() - returns dictionary of primitives with lists of action IDs.\n    ex: {'P1': ['ma23b1323',\n                'm390d053c']}\n\ngenome.getActionManipulatives() - returns a list of action manipulative IDs.\n    ex: ['m390d053c',\n         'ma23b1323']\n\ngenome.getPrimitiveMap() - returns a dictionary of primitive names to primitive IDs.\n    ex: {'P1': 'p464b64bc'}\n\ngenome.getManipulativeMap() - returns a dictionary of manipulative IDs to manipulative names.\n    ex: {'m390d053c': 'ACTIONPath',\n         'ma23b1323': 'ACTIONPath',\n         'mcd6d4d68': 'negateContext',\n         'm40aaf174': 'vectorFilter',\n         'med2ed537': 'vectorPassthrough',\n         'm89aa2c7e': 'reduceVectorsBySubtraction'}\n\ngenome.display() - graphically displays the topology.\n~~~\n\n\n\n#### To use BottleClient:\n\nYou will need to have an active bottle running on Intelligent Artifacts.  The bottle's information such as 'name' and secrete 'api_key' can be found in your IA account.\n\nIf on IA cloud:\n\n~~~\nfrom ialib.BottleClient import BottleClient\n\nbottle_info = {'api_key': 'ABCD-1234',\n               'name': 'genie-bottle',\n               'domain': 'intelligent-artifacts.com',\n               'secure': True}\n\ntest_bottle = BottleClient(bottle_info)\ntest_bottle\n~~~\n\n\nIf local:\n\n~~~\nfrom ialib.BottleClient import BottleClient\n\nbottle_info = {'api_key': 'ABCD-1234',\n               'name': 'genie-bottle',\n               'domain': ':8181',\n               'secure': False}\n\ntest_bottle = BottleClient(bottle_info)\ntest_bottle\n~~~\n\nInject your genie's genome into the bottle:\n\n~~~\ntest_bottle.injectGenome(genome)\n~~~\n\nWait for return status.\n\nOnce you have a running genie, set ingress and query nodes by passing the node names in a list:\n\n~~~\ntest_bottle.setIngressNodes(['P1'])\ntest_bottle.setQueryNodes(['P1'])\n~~~\n\nSend data to bottle:\n\n~~~\ndata = {\"strings\": [\"Hello\"], \"vectors\": [], \"determinants\": []}\ntest_bottle.observe(data)\n~~~\n\nQuery the bottle nodes:\n\n~~~\nprint(test_bottle.query('showStatus'))\npredictions = test_bottle.query('getPredictions')\n~~~\n\nYou can also pass GenieMetalanguage data to the genie:\n\n~~~\nfrom ialib.GenieMetalanguage import CLEAR_ALL_MEMORY, CLEAR_WM, LEARN, SET_PREDICTIONS_ON, SET_PREDICTIONS_OFF\ntest_bottle.observe(LEARN)\n~~~\n\nWhen sending classifications to a genie, it is best practice to send the classification as a singular symbol in the last event of a sequence.  This allows for querying the last event in the prediction's 'future' field for the answer.  The classification, though, should be sent to all the query nodes along with the ingress nodes.  The `observeClassification` function of the `BottleClient` class does that for us:\n\n~~~\ndata = {\"strings\": [\"World!\"], \"vectors\": [], \"determinants\": []}\ntest_bottle.observeClassification(data)\n~~~\n\n#### To use Backtesting:\n\nThere are 3 built-in backtesting reports:\n    - classification:\n        - Train and predict a string value to be a classification of observed data.\n    - utility - polarity:\n        - Polarity is basically a +/- binary classification test using the prediction's 'utility' value.  It scores correct if the polarity of the prediction matches the polarity of the expected.\n    - utility - value:\n        - Value tests for the actual predicted value against the expected and scores correct if within a provided `tolerance_threshold`.\n\nFor each, the observed data can be a sequence of one or more events, containing any vectors or strings.\n\n",
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