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›Natural Language Processing

Documentation

  • Overview
  • I. Chatbot Introduction

    • What is Chatbot
    • Chatbot's purposes
    • Popular types of Chatbot
    • Benefits of using FPT.AI Chatbot
    • Starting with FPT.AI

    II. Building Chatbot on FPT.AI Platform

    • Working Mechanism
    • Bot building process
    • Creating your Chatbot
    • Natural Language Processing - NLP
    • Answer scenarios
    • New Bot scenarios - Bot Builder
    • Answer cards
    • Step connecting buttons
    • Getting customer's information using Form cards
    • Variable settings and management
    • Variable condition review
    • Memories
    • Send/get information via JSON API card
    • Reminder
    • Advanced functions
    • Persistent menu

    III. History

    • History - Updating Bot knowledge

    IV. Multi-channel Integration

    • Integrate with Facebook
    • Integrate with Facebook at Work
    • Integrate with Viber
    • Integrate with Zalo
    • Integrate with website
    • Webhook

    V. Broadcast

    • Broadcast

    VI. Auto Comment

    • Auto comment on Facebook

    VII. Automation Test

    • Check base on testcases
    • Auto create testcases

    VIII. Analytics

    • Introduction
    • Number of user's requests
    • Top matched intents
    • Chat with Bot
    • Number of new users
    • Top scenarios
    • Number of messages bot answered
    • Number of user's requests per hour
    • Number of active users per hour
    • Real-time analytics
    • Broadcast report

    X. Rating and Survey

    • Rating
    • Survey

    XI. Bot Setting - Management

    • Introduction
    • Bot information
    • Messages management
    • Data management
    • Bot intent confidence
    • Delete Bot data
    • Delete bot
    • Transfer bot ownership
    • Version

    XII. Bot Roles

    • Bot roles

    XIII. Chatbot SDK

    • Chat Bot SDK
  • Appendices

Live Support

  • Introduction
  • Customer list interface
  • Customer support flow
  • Note feature
  • Suppoter chat
  • KPI report feature
  • Ticket config
  • Ticket report
  • Archive conversation
  • Ticket management
  • Auto assign to supporters

Tutorials (Videos)

  • 1. Brief overview of FPT.AI
  • 2. Using QnA feature to create a Chatbot
  • 3. Creating Chatbot with complicated scenarios
  • 4. Precondition fucntion in Scenarios
  • 5. Random answer function in Scenarios
  • 6. NLP feature
  • 7. Exact match and Predictive Match in NLP
  • 8. History of Recognition
  • 9. Broadcast feature
  • 10. Live Support feature
  • 11. Persistent Menu
  • 12. Auto-comment feature on Facebook
  • 13. Bot roles
  • 14. Bot configuration in Settings section
  • 15. Integration Chatbot with Facebook
  • 16. Integration Chatbot with Facebook at Work

API Reference

  • Introduction
  • General
  • Natural Language Processing

    • Intent
    • Entity
    • Sample
    • Train
    • Predict
    • Keyword
    • Dictionary

    Dialogue Management

    • Get Answer
    • JSON Card
    • Types of the message

API Reference

Train

All

Requests FPT.AI to train/re-retrain for both intent model and entity model for the application.

Note: You MUST have at least 2 intents and 2 samples to train.

Example request

curl -X POST \
  https://v3-api.fpt.ai/api/v3/train \
  -H 'Authorization: Bearer your_application_token' \

Example response

{
    "message": "training request is accepted",
    "status": [
        {
            "code": "mlne8hmzfy4jmgvpn3itoh7w8jyks1ut",
            "app_code": "dfd6908df08cf9d825f9ca9d38bf4677",
            "type": 1,
            "state": 0,
            "message": "",
            "model_file": "",
            "accuracy": 0,
            "precision": 0,
            "recall": 0,
            "f1": 0,
            "created_time": "2018-10-08T03:33:09Z",
            "finished_time": "2018-10-08T03:33:10Z",
            "started_time": "2018-10-08T03:33:10Z"
        },
        {
            "code": "g0a50948j6dd0asshcgszrhtaeeg807h",
            "app_code": "dfd6908df08cf9d825f9ca9d38bf4677",
            "type": 2,
            "state": 1,
            "message": "training",
            "model_file": "",
            "accuracy": 0,
            "precision": 0,
            "recall": 0,
            "f1": 0,
            "created_time": "2018-10-08T03:33:09Z",
            "finished_time": "2018-10-08T03:33:10Z",
            "started_time": "2018-10-08T03:33:10Z"
        }
    ]
}

Request

POST https://v3-api.fpt.ai/api/v3/train

Parameters

ParameterRequiredDescription
n/an/an/a

Response

Returns a JSON message represents the training status.

Training status

Requests FPT.AI get current train status of the application.

Example request

curl -X POST \
  https://v3-api.fpt.ai/api/v3/train/status \
  -H 'Authorization: Bearer your_application_token' \

Example response

{
    "last_success_time": "0001-01-01T00:00:00Z",
    "status": 1,
    "trainable": false
}

Request

POST https://v3-api.fpt.ai/api/v3/train/status

Parameters

ParameterRequiredDescription
n/an/an/a

Response

Returns a JSON message represents the training status.

Status valueDescription
0Waiting to train
1Training
2Train Success
3Train Failed

Intent

Requests FPT.AI to train/re-retrain intent model for the application.

Note: You MUST have at least 2 intents to train.

Example request

curl -X POST \
  https://v3-api.fpt.ai/api/v3/train/intent \
  -H 'Authorization: Bearer your_application_token' \

Example response

{
    "message": "training request is accepted",
    "status": [
        {
            "code": "cxx6gfj2pypbp8s2ohxyiufw807bl34r",
            "app_code": "dfd6908df08cf9d825f9ca9d38bf4677",
            "type": 1,
            "state": 0,
            "message": "",
            "model_file": "",
            "accuracy": 0,
            "precision": 0,
            "recall": 0,
            "f1": 0,
            "created_time": "2018-10-08T04:02:04Z",
            "finished_time": "2018-10-08T04:02:05Z",
            "started_time": "2018-10-08T04:02:05Z"
        },
        {
            "code": "g0a50948j6dd0asshcgszrhtaeeg807h",
            "app_code": "dfd6908df08cf9d825f9ca9d38bf4677",
            "type": 2,
            "state": 2,
            "message": "Model trained successfully with engine v2_entity and took 1034 seconds.",
            "model_file": "2018-10-08_10-33-17__v2_entity",
            "accuracy": 100,
            "precision": 100,
            "recall": 100,
            "f1": 100,
            "created_time": "2018-10-08T03:33:09Z",
            "finished_time": "2018-10-08T03:50:35Z",
            "started_time": "2018-10-08T03:33:10Z"
        }
    ]
}

Request

POST https://v3-api.fpt.ai/api/v3/train/intent

Parameters

ParameterRequiredDescription
n/an/an/a

Response

Returns a JSON message represents the training status.

Entity

Requests FPT.AI to train/re-retrain entity model for the application.

Example request

curl -X POST \
  https://v3-api.fpt.ai/api/v3/train/entity \
  -H 'Authorization: Bearer your_application_token' \

Example response

{
    "message": "training request is accepted",
    "status": [
        {
            "code": "cxx6gfj2pypbp8s2ohxyiufw807bl34r",
            "app_code": "dfd6908df08cf9d825f9ca9d38bf4677",
            "type": 1,
            "state": 1,
            "message": "training",
            "model_file": "",
            "accuracy": 0,
            "precision": 0,
            "recall": 0,
            "f1": 0,
            "created_time": "2018-10-08T04:02:04Z",
            "finished_time": "2018-10-08T04:02:05Z",
            "started_time": "2018-10-08T04:02:29Z"
        },
        {
            "code": "pxkaxumjdkqkr6ojd73a3upsvwfkvbg5",
            "app_code": "dfd6908df08cf9d825f9ca9d38bf4677",
            "type": 2,
            "state": 0,
            "message": "",
            "model_file": "",
            "accuracy": 0,
            "precision": 0,
            "recall": 0,
            "f1": 0,
            "created_time": "2018-10-08T04:03:40Z",
            "finished_time": "2018-10-08T04:03:41Z",
            "started_time": "2018-10-08T04:03:41Z"
        }
    ]
}

Request

POST https://v3-api.fpt.ai/api/v3/train/entity

Parameters

ParameterRequiredDescription
n/an/an/a

Response

Returns a JSON message represents the training status.

← SamplePredict →
  • All
    • Request
    • Response
  • Training status
    • Request
    • Response
  • Intent
    • Request
    • Response
  • Entity
    • Request
    • Response
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