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understand\nthe user's message.\n\n```js\n// Set up:\nconst ImagoPniClient = require('imago-pni-client');\nconst IMAGO_PNI_KEY = 'e379341be40d46348c4c352523ecb33e';\n\n// Call the Web API - must be inside an async function.\nasync function askImago() {\n  const client = new ImagoPniClient({\n    licenseKey: IMAGO_PNI_KEY,\n    convoId: 'test-conversation-1',\n  });\n  let response = await client.ask('Hey there!');\n}\n\naskImago();\n```\n\n### async getQuota() ###\n\nReturns the total quota granted for your license and the amount of quota used up.\n\nThe data is refreshed once in 10 minutes.\n\n```js\n// Set up:\nconst ImagoPniClient = require('imago-pni-client');\nconst IMAGO_PNI_KEY = 'e379341be40d46348c4c352523ecb33e';\n\n// Call the Web API - must be inside an async function.\nasync function printQuota() {\n  const client = new ImagoPniClient({\n    licenseKey: IMAGO_PNI_KEY,\n    convoId: 'test-conversation-1',\n  });\n  const response = await client.getQuota();\n  const percentageUsed = ((response.data.used / response.data.quota) * 100).toFixed(2);\n  console.log(`Used ${response.data.used}/${response.data.quota} messages (${percentageUsed}%)`);\n}\n\nprintQuota();\n```\n\n### async clearContext() ###\n\nThis function rarely needs to be used; it clears the context information\nstored by the PNI. This information helps the NLP engine understand at which\nstep of the dialog the user is located, and may also contain context variables,\nsomething similar to browser cookies.\n\nThe context is saved separately for each conversation ID.\n\n```js\nconst ImagoPniClient = require('imago-pni-client');\nconst IMAGO_PNI_KEY = 'e379341be40d46348c4c352523ecb33e';\n\nasync function resetContext() {\n    const client = new ImagoPniClient({\n        licenseKey: IMAGO_PNI_KEY,\n        convoId: 'test-conversation-1',\n    });\n\n    let success = await client.clearContext();\n    if (success) {\n        console.log('Context information deleted.');\n    } else {\n        console.log('There was an error removing context information.');\n    }\n}\n\nresetContext();\n```\n\n### async getContext() ###\nGet context variables on the PNI server.\n```js\nconst ImagoPniClient = require('imago-pni-client');\nconst IMAGO_PNI_KEY = 'e379341be40d46348c4c352523ecb33e';\nconst client = new ImagoPniClient({\n  licenseKey: IMAGO_PNI_KEY,\n  convoId: 'test-conversation-1',\n  server: ImagoPniClient.selectServer('dev'),\n});\n  const result = await client.getContext();\n\n```\n\n### async updateContext(updatedVariables) ###\n\nUpdate context variables on the PNI server. The properties in the\n`updatedVariables` will be replaced with these values; other context data will\nnot be updated.\n\nThe maximum supported data amount is around 20KB. Do not updated big chunks\nof context data with this method.\n\n```js\nconst ImagoPniClient = require('imago-pni-client');\nconst IMAGO_PNI_KEY = 'e379341be40d46348c4c352523ecb33e';\n\nasync function setUserNameAndAge(name, age) {\n    const client = new ImagoPniClient({\n        licenseKey: IMAGO_PNI_KEY,\n        convoId: 'test-conversation-1',\n    });\n\n    try {\n        await client.updateContext({\n            userName: name,\n            userAge: age,\n        });\n    } catch (error) {\n        console.log('Error updating context: ', error);\n    }\n}\n\nsetUserNameAndAge('Test', 20);\n```\n\n## Initalization options ##\n\nWhen creating a new instance of the `ImagoPniClient`, you can pass the following options:\n\n* `licenseKey` - required. The license key you obtained from Imago.\n* `convoId` - required. An arbitrary conversation ID that helps you track the conversation. It must be the same for conversations with the same user. For example, you can use the Facebook ID of the user who is talking to the bot.\n* `server` - optional. The server running Imago PNI software. See `ImagoPniClient.servers` for the list.\n* `apiVerion` - optional. The version level of the Imago PNI API. Default is 'v1'.\n* `includeRawResponse` - optional. Whether to attach the original NLP engine's response to the returned data. This can be useful for examining the data returned by the NLP engine in more details.\n* `logger` - optional. A logging function. Default: console.log.\n\n## Servers ##\n\nThere are three available servers for the PNI. The default is the production server.\nThe list of servers is stored inside `ImagoPniClient.servers`. Example initialization\nwith a specific server name:\n\n```js\nconst ImagoPniClient = require('imago-pni-client');\nconst IMAGO_PNI_KEY = 'e379341be40d46348c4c352523ecb33e';\n\nlet client1 = new ImagoPniClient({\n    server: ImagoPniClient.servers.UAT,\n    licenseKey: IMAGO_PNI_KEY,\n    convoId: 'test-conversation-1',\n});\n\nlet client2 = new ImagoPniClient({\n    server: ImagoPniClient.servers.DEVELOPMENT,\n    licenseKey: IMAGO_PNI_KEY,\n    convoId: 'test-conversation-1',\n});\n\nlet client3 = new ImagoPniClient({\n    server: ImagoPniClient.servers.PRODUCTION, // this is default\n    licenseKey: IMAGO_PNI_KEY,\n    convoId: 'test-conversation-1',\n});\n\nlet client4 = new ImagoPniClient({\n    server: ImagoPniClient.servers.LOCALHOST, // http://localhost:3000\n    licenseKey: IMAGO_PNI_KEY,\n    convoId: 'test-conversation-1',\n});\n\nlet client5 = new ImagoPniClient({\n    server: 'example.com', // if any other server becomes available\n    licenseKey: IMAGO_PNI_KEY,\n    convoId: 'test-conversation-1',\n});\n```\n\n### Selecting the server automatically ###\n\nYou can select the server automatically based on your environment type. The\nmethod `static selectServer(environment)` takes the environment type string\n(for example, \"LOCALHOST\", \"local\", \"DEV\", \"development\", \"UAT\", \"prod\", \"production\")\nand returns the appropriate server type.\n\n```js\nlet environment = process.env.NODE_ENV; // 'production'\n\nlet client = new ImagoPniClient({\n    server: ImagoPniClient.selectServer(environment),\n    // other initialization parameters\n});\n```\n\n## Response format ##\n\nThe response format is EIF (Engine Independent Format).\n\nIt includes the `originalQuery`, `rawOriginalQuery`, `topIntent`, `topIntentScore`, `intents[]`, `entities[]`, `answer` (for IBM Watson Conversation only), and the original NLP engine's response under `raw`.\n\nThe difference between `originalQuery` and `rawOriginalQuery` is that the former\nis the message sent to the NLP engine (perhaps modified by our preprocessor),\nand the `rawOriginalQuery` is the exact text sent by the user (before any\npreprocessing).\n\nExample of an EIF response:\n\n```json\n{\n  \"originalQuery\": \"hey there!\",\n  \"rawOriginalQuery\": \"hey there!\",\n  \"topIntent\": \"Greetings\",\n  \"topIntentScore\": 0.9852514743804932,\n  \"intents\": [\n    {\n      \"intent\": \"Greetings\",\n      \"confidence\": 0.9852514743804932\n    }\n  ],\n  \"entities\": [\n    {\n      \"type\": \"greeting\",\n      \"value\": \"hi\",\n      \"location\": [0, 2],\n    }\n  ],\n  \"answer\": \"Hi! I'm a bot, nice talking to you.\",\n  \"raw\": {\n    \"intents\": [\n      {\n        \"intent\": \"Greetings\",\n        \"confidence\": 0.9852514743804932\n      }\n    ],\n    \"entities\": [{\n      \"entity\": \"greeting\",\n      \"location\": [0, 2],\n      \"value\": \"hi\",\n      \"confidence\": 1\n    }],\n    \"input\": {\n      \"text\": \"hey there\"\n    },\n    \"output\": {\n      \"text\": [\n        \"Hi! I'm a bot, nice talking to you.\"\n      ],\n      \"nodes_visited\": [\n        \"Welcome\"\n      ],\n      \"log_messages\": [\n        \n      ]\n    },\n    \"context\": {\n      \"conversation_id\": \"c3924ae7-9e4c-441f-b2ff-fec70d3bc9ad\",\n      \"system\": {\n        \"dialog_stack\": [\n          {\n            \"dialog_node\": \"root\"\n          }\n        ],\n        \"dialog_turn_counter\": 1,\n        \"dialog_request_counter\": 1,\n        \"_node_output_map\": {\n          \"node_16_1503017179283\": [\n            0\n          ]\n        },\n        \"branch_exited\": true,\n        \"branch_exited_reason\": \"completed\"\n      }\n    }\n  },\n  \"elapsed\": \"125 ms, including 16 ms for the NLP engine.\"\n}\n```\n\n## Usage - Importing data into the NLP engine ##\n\n### async importApp(options) ###\n\nThe PNI client can also be used to import the bot training data from the SQL\ndatabase into the NLP engine.\n\nTo do that, you need to first fetch the data from four tables in SQL, and then\ncall the PNI client as follows:\n\n```js\nconst ImagoPniClient = require('imago-pni-client');\nconst IMAGO_PNI_KEY = 'e379341be40d46348c4c352523ecb33e';\n\nasync function importApp() {\n    const client = new ImagoPniClient({\n        licenseKey: IMAGO_PNI_KEY,\n        convoId: 'test-conversation-1',\n    });\n\n    // This function should be written by you and return an array of four items,\n    // each of which represents all rows from one of the four SQL tables:\n    let [intents, utterances, entityTypes, entities] = await fetchDataFromSql();\n\n    let jobId = await client.importApp({\n        appLanguage: 'en',\n        intents, utterances, entityTypes, entities,\n    });\n\n    // This jobId is returned before the import job is completed. The frontend\n    // or backend can then use this jobId to check for the job status using\n    // another endpoint.\n    return jobId;\n}\n\nimportApp();\n```\n\n### async checkJobStatus(jobId) ###\n\nThe `async importApp()` function returns a `jobId` that can be used to check\nthe status of the import job. The job typically takes from 10 seconds to 2 \nminutes.\n\nYou can check the status of the job to view the status messages and check\nwhether it is completed.\n\nThe response contains three properties: `success`, `log` and `done`. `success`\nbeing equal to `true` means that the job status was fetched successful. The\n`log` contains the text of the log as string. If `done` is `true`, that means\nthe job has completed.\n\n```js\n// This should have been obtained from the importApp() function:\nconst jobId = '70ae5e08-fc75-46ee-8bc7-67a0d63badd6';\n\n// licenseKey and convoId can be set to any non-empty string, e.g. 'not required',\n// because the endpoint for checking the job status does not require a license\n// or a conversation ID.\nconst client = new ImagoPniClient({\n    licenseKey: IMAGO_PNI_KEY,\n    convoId: 'test-conversation-1',\n});\n\n// Make request to server to fetch job status:\nlet response = await client.checkJobStatus(jobId);\n\n// Output results to console:\nif (response && response.success) {\n    if (response.done) {\n        console.log(`Job completed!`);\n    } else {\n        console.log(response.log);\n    }\n} else {\n    console.log('Failed to check job status.');\n}\n\n```\n\n## Usage - Utterance Requests ## \n\nCustomer can request to add a new utterance to the training data. To create and manage the requests, use the methods below:\n\n### async requestNewUtterance(utterance) ###\n\nSends a request to Imago to add a new utterance (sentence) to the training\ndata set.\n\nThe `utterance` is an arbitrary object containing at least a `text` property.\n\n```js\nawait client.requestNewUtterance({\n\ttext: 'Hey there', // this is required\n\tintent: 'Greeting', // an arbitrary optional field\n\trequestedBy: 'user1@example.com', // an arbitrary optional field\n});\n```\n\n### async getAllUtteranceRequests() ### \n### async getCompletedUtteranceRequests() ###\n### async getPendingUtteranceRequests() ###\n\nReturns all utterance requests for the given license key (the first method), or only completed or only pending requests (the other two methods).\n\nThe return value is an array of objects, each of which represents an utterance request.\n\n### async cancelPendingUtteranceRequest(id) ###\n\nCancels a pending utterance request if it hasn't been completed yet.\n\nThe `id` is the value of the `RowKey` property that you can get from inside the utterance request object by using one of the three `get...` methods above.\n\n```js\nconst allPendingRequests = await client.getPendingUtteranceRequests();\n\n// Cancel all pending requests:\nfor (const r of allPendingRequests) {\n  // For better performance, we are not awaiting this\n  // function here:\n  client.cancelPendingUtteranceRequest(r.RowKey);\n}\n\n```","maintainers":[{"name":"imago.ai","email":"developers@imago.ai"}],"time":{"modified":"2022-05-05T19:15:35.260Z","created":"2017-11-29T11:20:38.710Z","1.0.0":"2017-11-29T11:20:38.710Z","1.1.0":"2017-12-11T07:29:58.766Z","1.2.0":"2017-12-19T06:39:17.448Z","1.2.1":"2017-12-21T04:59:49.275Z","2.0.0":"2017-12-21T09:20:22.481Z","2.0.1":"2017-12-21T09:29:40.705Z","2.0.2":"2017-12-21T09:30:21.581Z","2.0.3":"2017-12-21T09:32:04.972Z","2.0.4":"2017-12-28T10:12:59.092Z","2.0.5":"2017-12-28T10:25:39.444Z","2.1.0":"2017-12-28T10:54:51.023Z","2.2.0":"2018-01-04T09:17:38.627Z","2.3.0":"2018-01-18T07:49:35.472Z","2.3.1":"2018-01-18T09:15:09.694Z","2.4.0":"2018-01-23T09:01:22.499Z","2.5.0":"2018-02-01T07:48:52.005Z","2.6.0":"2018-02-13T06:57:44.479Z","2.7.0":"2018-02-14T08:41:57.585Z","2.8.0":"2018-02-18T08:48:04.944Z","2.9.0":"2018-04-18T13:40:23.714Z","2.9.1":"2018-04-19T04:20:14.163Z","2.10.0":"2018-04-23T04:34:15.303Z","2.11.0":"2018-05-16T07:47:46.356Z","2.12.0":"2018-05-24T06:50:06.035Z","2.14.0":"2018-07-16T09:07:48.631Z","2.15.0":"2018-07-23T07:50:19.160Z","2.15.1":"2018-07-23T08:20:04.902Z","2.16.0":"2018-08-06T13:01:58.147Z","2.17.0":"2018-08-27T12:02:44.558Z","2.18.0":"2018-09-21T06:52:11.700Z","2.19.0":"2018-09-28T08:31:19.380Z","2.20.0":"2018-10-08T09:39:59.986Z","2.20.1":"2018-10-10T04:11:40.776Z","2.21.0":"2018-10-19T11:24:29.462Z","2.22.0":"2019-01-31T07:31:47.289Z","2.23.0":"2019-02-19T11:22:21.296Z","2.21.1":"2019-04-23T08:33:32.385Z","2.23.1":"2019-04-24T01:44:40.863Z","2.23.2":"2019-04-29T08:09:31.847Z","2.24.0":"2021-03-17T13:53:30.517Z","2.24.1":"2021-03-17T14:06:19.785Z","2.24.2":"2021-04-27T00:28:45.562Z","2.24.3":"2021-10-11T08:52:36.831Z","2.24.4":"2021-10-11T08:59:32.889Z","2.24.5":"2022-03-28T13:53:19.887Z"},"keywords":["imago","imago.ai","nlp","bots"],"author":{"name":"Imago.ai","email":"developers@imago.ai"},"license":"Unlicense","readmeFilename":"README.md","homepage":"https://bitbucket.org/imagoai/imago-pni-client#readme","repository":{"type":"git","url":"git+https://bitbucket.org/imagoai/imago-pni-client.git"}}