README

The Mirage API NodeJS wrapper. Access AI inference services.

📝 Implements: API Reference (V1) at revision: 19/12/2023
😘 Maintainer: @valeriansaliou

Usage

Install the library:

composer require mirage-ai/php-mirage-api

Then, import it:

require __DIR__."/vendor/autoload.php";

Construct a new authenticated Mirage client with your user_id and secret_key tokens.

$client = new Mirage("ui_xxxxxx", "sk_xxxxxx");

Then, consume the client eg. to transcribe a audio file containing speech to text:

$data = $client->task->transcribeSpeech([
  "locale" => [
    "to" => "en"
  ],

  "media" => [
    "type" => "audio/webm",
    "url" => "https://files.mirage-ai.com/dash/terminal/samples/transcribe-speech/hey-there.weba"
  ]
]);

Authentication

To authenticate against the API, get your tokens (user_id and secret_key).

Then, pass those tokens once when you instanciate the Mirage client as following:

# Make sure to replace 'user_id' and 'secret_key' with your tokens
$client = new Mirage("user_id", "secret_key");

Resource Methods

This library implements all methods the Mirage API provides. See the API docs for a reference of available methods, as well as how returned data is formatted.

Task API

➡️ Transcribe Speech

Method: $client->task->transcribeSpeech(data)
Reference: Transcribe Speech
Request:

$client->task->transcribeSpeech([
  "locale" => [
    "to" => "en"
  ],

  "media" => [
    "type" => "audio/webm",
    "url" => "https://files.mirage-ai.com/dash/terminal/samples/transcribe-speech/hey-there.weba"
  ]
]);

Response:

{
  "reason": "processed",

  "data": {
    "locale": "en",

    "parts": [
      {
        "start": 5.0,
        "end": 9.0,
        "text": " I'm just speaking some seconds to see if the translation is correct"
      }
    ]
  }
}

➡️ Answer Prompt

Method: $client->task->answerPrompt(data)
Reference: Answer Prompt
Request:

$client->task->answerPrompt([
  "prompt" => "Generate an article about Alpacas"
]);

Response:

{
  "reason": "processed",

  "data": {
    "answer": "The alpaca (Lama pacos) is a species of South American camelid mammal. It is similar to, and often confused with, the llama. However, alpacas are often noticeably smaller than llamas. The two animals are closely related and can successfully crossbreed. Both species are believed to have been domesticated from their wild relatives, the vicuña and guanaco. There are two breeds of alpaca: the Suri alpaca and the Huacaya alpaca."
  }
}

➡️ Answer Question

Method: $client->task->answerQuestion(data)
Reference: Answer Question
Request:

$client->task->answerQuestion([
  "question" => "Should I pay more for that?",

  "answer" => [
    "start" => "Sure,"
  ],

  "context" => [
    "primary_id" => "cf4ccdb5-df44-4668-a9e7-3ab31bebf89b",

    "conversation" => [
      "messages" => [
        [
          "from" => "customer",
          "text" => "Hey there!"
        ],

        [
          "from" => "agent",
          "text" => "Hi. How can I help?"
        ],

        [
          "from" => "customer",
          "text" => "I want to add more sub-domains to my website."
        ]
      ]
    ]
  ]
]);

Response:

{
  "reason": "processed",

  "data": {
    "answer": "You can add the Crisp chatbox to your website by following this guide: https://help.crisp.chat/en/article/how-to-add-crisp-chatbox-to-your-website-dkrg1d/ :)",
    "sources": []
  }
}

➡️ Summarize Paragraphs

Method: $client->task->summarizeParagraphs(data)
Reference: Summarize Paragraphs
Request:

$client->task->summarizeParagraphs([
  "paragraphs" => [
    [
      "text" => "GPT-4 is getting worse over time, not better."
    ],

    [
      "text" => "Many people have reported noticing a significant degradation in the quality of the model responses, but so far, it was all anecdotal."
    ]
  ]
]);

Response:

{
  "reason": "processed",

  "data": {
    "summary": "GPT-4 is getting worse over time, not better. We have a new version of GPT-4 that is not improving, but it is regressing."
  }
}

➡️ Summarize Conversation

Method: $client->task->summarizeConversation(data)
Reference: Summarize Conversation
Request:

$client->task->summarizeConversation([
  "transcript" => [
    [
      "name" => "Valerian",
      "text" => "Hello! I have a question about the Crisp chatbot, I am trying to setup a week-end auto-responder, how can I do that?"
    ],

    [
      "name" => "Baptiste",
      "text" => "Hi. Baptiste here. I can provide you an example bot scenario that does just that if you'd like?"
    ]
  ]
]);

Response:

{
  "reason": "processed",

  "data": {
    "summary": "Valerian wants to set up a week-end auto-responder on Crisp chatbot. Baptiste can give him an example."
  }
}

➡️ Categorize Conversations

Method: $client->task->categorizeConversations(data)
Reference: Categorize Conversations
Request:

$client->task->categorizeConversations([
  "conversations" => [
    [
      "transcript" => [
        [
          "from" => "customer",
          "text" => "Hello! I have a question about the Crisp chatbot, I am trying to setup a week-end auto-responder, how can I do that?"
        ],

        [
          "from" => "agent",
          "text" => "Hi. Baptiste here. I can provide you an example bot scenario that does just that if you'd like?"
        ]
      ]
    ]
  ]
]);

Response:

{
  "reason": "processed",

  "data": {
    "categories": [
      "Chatbot Configuration Issue"
    ]
  }
}

➡️ Rank Question

Method: $client->task->rankQuestion(data)
Reference: Rank Question
Request:

$client->task->rankQuestion([
  "question" => "Hi! I am having issues setting up DNS records for my Crisp helpdesk. Can you help?",

  "context" => [
    "source" => "helpdesk",
    "primary_id" => "cf4ccdb5-df44-4668-a9e7-3ab31bebf89b"
  ]
]);

Response:

{
  "reason": "processed",

  "data": {
    "results": [
      {
        "id": "15fd3f24-56c8-435e-af8e-c47d4cd6115c",
        "score": 9,
        "grouped_text": "Setup your Helpdesk domain name\ntutorials for most providers",

        "items": [
          {
            "source": "helpdesk",
            "primary_id": "51a32e4c-1cb5-47c9-bcc0-3e06f0dce90a",
            "secondary_id": "15fd3f24-56c8-435e-af8e-c47d4cd6115c",
            "text": "Setup your Helpdesk domain name\ntutorials for most providers",
            "timestamp": 1682002198552,

            "metadata": {
              "title": "Setup your Helpdesk domain name"
            }
          }
        ]
      }
    ]
  }
}

➡️ Translate Text

Method: $client->task->translateText(data)
Reference: Translate Text
Request:

$client->task->translateText([
  "locale" => [
    "from" => "fr",
    "to" => "en"
  ],

  "type" => "html",
  "text" => "Bonjour, comment puis-je vous aider <span translate=\"no\">Mr Saliou</span> ?"
]);

Response:

{
  "reason": "processed",

  "data": {
    "translation": "Hi, how can I help you Mr Saliou?"
  }
}

➡️ Fraud Spamicity

Method: $client->task->fraudSpamicity(data)
Reference: Fraud Spamicity
Request:

$client->task->fraudSpamicity([
  "name" => "Crisp",
  "domain" => "crisp.chat",
  "email_domain" => "mail.crisp.chat"
]);

Response:

{
  "reason": "processed",

  "data": {
    "fraud": false,
    "score": 0.13
  }
}

Data API

➡️ Context Ingest

Method: $client->data->contextIngest(data)
Reference: Ingest Context Data
Request:

$client->data->contextIngest([
  "items" => [
    [
      "operation": "index",
      "primary_id" => "pri_cf44dd72-4ba9-4754-8fb3-83c4261243c4",
      "secondary_id" => "sec_6693a4a2-e33f-4cce-ba90-b7b5b0922c46",
      "tertiary_id" => "ter_de2bd6e7-74e1-440d-9a23-01964cd4b7da",

      "text" => "Text to index here...",
      "source" => "chat",
      "timestamp" => 1682002198552,

      "metadata" => [
        "custom_key" => "custom_value",
        "another_key" => "another_value"
      ]
    ]
  ]
]);

Response:

{
  "reason": "processed",

  "data": {
    "imported": true
  }
}

mirage-ai / php-mirage-api

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