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Saga_rest_endpoint

Endpoint	processText

Will return a Saga interpretation graph in the format specified
By default, it returns the graph in HTML format which is used by the UI
It also can return JSON or plain text

Parameters

Parameter
summary This is the text to process
name q
required true
Parameter
summary List of tags to use to process the text
name tags
type string array
required true
Parameter
summary Tag to use to process the text
name tag
Parameter
summary Pipeline or pipeline stage to use to process the text
name processor
Parameter
summary Specifies the regex to use to split text into TEXT_BLOCKs
default [\r |\n ]+
name splitRegex
Parameter
summary Specifies the format of the results. It could be one of these values: "ux", "text" or "json"
default ux
name type
- ux - Returns an output useful for Saga to show the graph on a web display.
- text - Returns a "line" with the highest confidence route and a text representation of the graph.
- json - Returns all the semantic tags on the graph.
Parameter
summary Used to pretty format the JSON result
default false
name pretty
type boolean

Request Examples

Code Block

language	powershell
theme	FadeToGrey

curl -X ${method} \
  http://localhost:${port}/${url} \
  -H 'Content-Type: application/json' \
  -d '
{
    "q": "I like traveling with Air Paris",
	"tags": ["airline"],
	"splitRegex": "[\r|\n]+",
	"type": "text",
	"pretty": true
}'

Response

If true, it will combine all the SEMANTIC_TAGs, which has same matching text and same confidence value
default false
name combine
type boolean
- The combination includes the metadata, of every SEMANTIC_TAG
Parameter
summary If true, it will also add the components from the highest route confidence tokens.
default true
name addComponents
type boolean
Parameter
summary Applicable when addComponents is true. Indicates which components to add to the response
name compFields
type string array
- If missing all the components will be added
Parameter
summary If true, it will add the metadata of the entities found in every SEMANTIC_TAG
default false
name metadata
type boolean
Parameter
summary Specifies the format of the results. It could be one of these values: "ux", "text" or "json"
default ux
name type
- ux - Returns an output useful for Saga to show the graph on a web display.
- text - Returns a "line" with the highest confidence route and a text representation of the graph.
- json - Returns all the semantic tags on the graph.

Parameter
summary Used to pretty format the JSON result
default false
name pretty
type boolean

Note

The parameters tags, tag and processor are mutually exclusive, only one is required, and the priority order is:

tags
tag
processor

Request Examples

Code Block

language	powershell
theme	FadeToGrey

curl -X ${method} \
  http://localhost:${port}/${url} \
  -H 'Content-Type: application/json' \
  -d '
{
    "q": "I like traveling with Air Paris",
	"tags": ["airline"],
    "combine": true,
    "addComponents": true,
    "compFields": "paris",
	"splitRegex": "[\r\n]+",
	"type": "text",
	"pretty": true
}'

Response

Saga_json

{
  "_success": true,
  "data": {
    "line": [
      {

Saga_json

{
    "_success": true,
    "data": {
        "line": [
            {
                "character": "0:1",
                "components": [
                    "I like traveling with Air Paris"
                ],
                "stage": "WhitespaceTokenizer",
                "confidence": 0.5,
        "match": "I",
        "flags": [
          "ORIGINAL",
          "TOKENALL_UPPER_CASE",
          "TOKEN"
          "ALL_UPPER_CASE"],
           "text": "I",
         "ORIGINALstartPos": 0,
        "endPos": 1
       ]},
      {
          "_itemstage": "IWhitespaceTokenizer",
        "confidence": 0.5,
        "matchingmatch": "Ilike",
        "flags": [
   }       "ORIGINAL",
          "TOKEN",
    {      "ALL_LOWER_CASE"
        ],
        "charactertext": "2:6like",
        "startPos": 2,
        "componentsendPos": [6
      },
      {
        "stage"I like traveling with Air Paris": "WhitespaceTokenizer",
        "confidence": 0.5,
       ] "match": "traveling",
        "flags": [
         "stage": "WhitespaceTokenizerORIGINAL",
          "TOKEN",
          "confidence": 0.5,ALL_LOWER_CASE"
        ],
        "flagstext": ["traveling",
            "startPos": 7,
        "TOKENendPos",: 16
      },
      {
        "ALL_LOWER_CASE"stage": "WhitespaceTokenizer",
        "confidence": 0.4,
        "match":   "ORIGINALwith",
        "flags": [
       ],
    "ORIGINAL",
            "STOP_itemWORD": "like",
          "TOKEN",
        "matching":  "likeALL_LOWER_CASE"
            }],
          "text": "with",
  {
        "startPos": 17,
        "characterendPos": "7:16",21
      },
      {
        "components": [
          {
          "I like traveling with Air Paris""stage": "CaseAnalysis",
                ],
    "confidence": 0.45,
            "stagematch": "WhitespaceTokenizerParis",
                "confidenceflags": 0.5,[
                "flagsORIGINAL": [,
                    "TOKEN"LOWERED",
                    "ALL_LOWER_CASETOKEN",
                    "ORIGINAL"ALL_LOWER_CASE"
                ],
                "_itemtext": "travelingparis",
                "matchingstartPos": "traveling"26,
            }, "endPos": 31
            {}
        ],
        "characterstage": "17:21DictionaryTagger",
        "confidence": 0.6975,
        "componentsdisplay": [ "Air Paris",
        "match": "Air Paris",
          "flags"I: like[
 traveling with Air Paris"
      "SEMANTIC_TAG",
          ],"ENTITY"
        ],
        "stagetext": "WhitespaceTokenizer{airline}",
        "id": "34365531",
        "confidencestartPos": 0.422,
        "endPos": 31,
        "flagstags": [
                    "TOKEN","airline"
        ]
      }
      "ALL_LOWER_CASE"],
    "graph": " V-----------[I like traveling with Air          "SKIP",
  Paris]-----------V \n ^-[I]-V-[like]-V-[traveling]-V-[with]-V-[Air]-V-[Paris]-^ \n ^-[i]-^                  "ORIGINAL"
             ^-[air]-^-[paris]-^ \n  ],
                "_item": "with",
                "matching": "with"
            },
            {
                "character": "22:31",
      ^---[{airline}]---^ \n"
  }
}

Saga_rest_endpoint_legacy

Endpoint	processBatch

Will return a Saga interpretation graph in the format specified
By default, it returns the graph in HTML format which is used by the UI
It also can return JSON or plain text

Parameters

Parameter
summary List of texts to process
name batch
type string array
required true
Parameter
summary List of tags to use to process the text
name tags
type string array
required true
Parameter
summary Tag to use to process the text
name tag
Parameter
summary Pipeline or pipeline stage to use to process the text
name processor
Parameter
summary Specifies the regex to use to split text into TEXT_BLOCKs
default [\r\n ]+
name splitRegex
Parameter
summary If true, it will combine all the SEMANTIC_TAGs, which has same matching text and same confidence value
default false
name combine
type boolean
- The combination includes the metadata, of every SEMANTIC_TAG
Parameter
summary If true, it will also add the components from the highest route confidence tokens.
default true
name addComponents
type boolean
Parameter
summary Applicable when addComponents is true. Indicates which components to add to the response
name compFields
type string array
- If missing all the components will be added
Parameter
summary If true, it will add the metadata of the entities found in every SEMANTIC_TAG
default false
name metadata
type boolean

Note

The parameters tags, tag and processor are mutually exclusive, only one is required, and the priority order is:

tags
tag
processor

Request Examples

Code Block

language	powershell
theme	FadeToGrey

curl -X ${method} \
  http://localhost:${port}/${url} \
  -H 'Content-Type: application/json' \
  -d '
{
    "batch": ["I like traveling with Air Paris", "I enjoy traveling with Delta"],
	"tags": ["airline"],
    "combine": true,
    "addComponents": true,
    "compFields": "paris"
}'

Response

Saga_json

[
    {
        "data": {
            "line": [
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.5,
                    "match": "I",
                    "flags": [
                        "ORIGINAL",
                        "ALL_UPPER_CASE",
                        "TOKEN"
                    ],
                    "text": "I",
                    "startPos": 0,
                    "endPos": 1
                },
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.5,
                    "match": "like",
                    "flags": [
                        "ORIGINAL",
                        "ALL_LOWER_CASE",
                        "TOKEN"
                    ],
                    "text": "like",
                    "startPos": 2,
                    "endPos": 6
                },
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.5,
                    "match": "traveling",
                    "flags": [
                        "ORIGINAL",
                        "ALL_LOWER_CASE",
                        "TOKEN"
                    ],
                    "text": "traveling",
                    "startPos": 7,
                    "endPos": 16
                },
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.4,
                    "match": "with",
                    "flags": [
                        "ORIGINAL",
                        "STOP_WORD",
                        "ALL_LOWER_CASE",
                        "TOKEN"
                    ],
                    "text": "with",
                    "startPos": 17,
                    "endPos": 21
                },
                {
                    "components": [
                        {
                            "stage": "CaseAnalysis",
                            "confidence": 0.45,
                            "match": "Paris",
                            "flags": [
                                "ORIGINAL",
                                "ALL_LOWER_CASE",
                                "LOWERED",
                                "TOKEN"
                            ],
                            "text": "paris",
                            "startPos": 26,
                            "endPos": 31
                        }
                    ],
                    "stage": "DictionaryTagger",
                    "confidence": 0.6975,
                    "display": "Air Paris",
                    "match": "Air Paris",
                    "flags": [
                        "ENTITY",
                        "SEMANTIC_TAG"
                    ],
                    "text": "{airline}",
                    "id": "34365531",
                    "startPos": 22,
                    "endPos": 31,
                    "tags": [
                        "airline"
                    ]
                }
            ],
            "matches": [
                {
                    "components": [
                        {
                            "stage": "CaseAnalysis",
                            "confidence": 0.45,
                            "match": "Paris",
                            "flags": [
                                "ORIGINAL",
                                "ALL_LOWER_CASE",
                                "LOWERED",
                                "TOKEN"
                            ],
                            "text": "paris",
                            "startPos": 26,
                            "endPos": 31
                        }
                    ],
                    "stage": "DictionaryTagger",
                    "confidence": 0.6975,
                    "display": "Air Paris",
                    "match": "Air Paris",
                    "flags": [
                        "ENTITY",
                        "SEMANTIC_TAG"
                    ],
                    "text": "{airline}",
                    "id": "34365531",
                    "startPos": 22,
                    "endPos": 31,
                    "tags": [
                        "airline"
                    ]
                }
            ]
        }
    },
    {
        "data": {
            "line": [
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.5,
                    "match": "I",
                    "flags": [
                        "ORIGINAL",
                        "ALL_UPPER_CASE",
                        "TOKEN"
                    ],
                    "text": "I",
                    "startPos": 0,
                    "endPos": 1
                },
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.5,
                    "match": "enjoy",
                    "flags": [
                        "ORIGINAL",
                        "ALL_LOWER_CASE",
                        "TOKEN"
                    ],
                    "text": "enjoy",
                    "startPos": 2,
                    "endPos": 7
                },
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.5,
                    "match": "traveling",
                    "flags": [
                        "ORIGINAL",
                        "ALL_LOWER_CASE",
                        "TOKEN"
                    ],
                    "text": "traveling",
                    "startPos": 8,
                    "endPos": 17
                },
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.4,
                    "match": "with",
                    "flags": [
                        "ORIGINAL",
                        "STOP_WORD",
                        "ALL_LOWER_CASE",
                        "TOKEN"
                    ],
                    "text": "with",
                    "startPos": 18,
                    "endPos": 22
                },
                {
                    "stage": "WhitespaceTokenizer",
                    "confidence": 0.5,
                    "match": "Delta",
                    "flags": [
                        "ORIGINAL",
                        "TOKEN",
                        "TITLE_CASE"
                    ],
                    "text": "Delta",
                    "startPos": 23,
                    "endPos": 28
                }
            ],
            "matches": [
                {
                    "stage": "DictionaryTagger",
                    "confidence": 0.44999999999999996,
                    "display": "Delta Air Lines",
                    "match": "Delta",
                    "flags": [
                        "ENTITY",
                        "SEMANTIC_TAG"
                    ],
                    "text": "{airline}",
                    "id": "188920",
                    "startPos": 23,
                    "endPos": 28,
                    "stagetags": "DictionaryTagger",
[
                        "displayairline":
  "Air Paris",
                "patterns": []
                }
    "Air Orly",
       ]
        }
     "Air Paris"
                ],
                "confidence": 0.6975}
]

Saga_rest_endpoint_legacy

Endpoint	solution
Method	GET

Returns the information of the solution currently being used.
A solution is basically the set of Elasticsearch indices in use

Request Examples

Code Block

language	powershell
theme	FadeToGrey

curl --location --request GET 'http://localhost:${port}/${url}'

Response

Saga_json

    "_success": true,
        "elasticSearch": {
        "flagsretries": [3,
        "delay": 5,
        "scheme":   "SEMANTIC_TAGhttp",
        "hostnamesAndPorts": [
            "ENTITYlocalhost:9200"
                ],
        "indexName": "pii",
        "idencryptionKey": "34365531f123123##c#$#4GGVqFk7L9123123@*^",
        "timeout": 30
    },
    "_itemdisplay": "Saga"

Saga_rest_endpoint_legacy

Endpoint	info
Method	GET

Returns build-specific and configuration information about Saga
Build information contains title, vendor, version, build revision and date
Configuration information contains the solution (Elastic index) and providers configured at the moment

Request Examples

Code Block

language	powershell
theme	FadeToGrey

curl --location --request GET 'http://localhost:${port}/${url}'

Response

Saga_json

    "msg": "Saga API online",
    "_success": true,
    "buildInfo": {{airline}",
                "matching": "Air Paris",
                "tags": [
                    "airline"
                ]
        "Implementation-Title":    }
        ]"Saga Server",
        "graphImplementation-Build": " V-----------[I like traveling with Air Paris]-----------V \n ^-[I]-V-[like]-V-[traveling]-V-[with]-V-[Air]-V-[Paris]-^ \n ^-[i]-^   "6b79d916e8ff9ad9efd742d4fbc8ce186f77c02d",
        "Implementation-Version": "1.2.2",
        "Implementation-Timestamp": "1609253821444",
        "Implementation-Vendor-Id": "com.accenture.saga",
           ^-[air]-^-[paris]-^ \n"Built-By": "mauricio.rizo.sandi",
        "Build-Jdk": "11",
           "Implementation-Branch": "develop"
    },
    "solutions": [
          ^---[{airline}]---^ \n"
    }
}

Saga_rest_endpoint

Endpoint	solution
Method	GET

Returns the information of the solution currently being used.
A solution is basically the set of Elasticsearch indices in use

Request Examples

Code Block

language	powershell
theme	FadeToGrey

curl -X ${method} \
  http://localhost:${port}/${url} \
  -H 'Content-Type: application/json' \
  -d '
{
}'

Response

Saga_json
"_success": true, "elasticSearch": { "indexName": "air" }, "display": "Saga - EN"

Saga_rest_endpoint

Endpoint	info
Method	GET

Returns build-specific and configuration information about Saga
Build information contains title, vendor, version, build revision and date
Configuration information contains the solution (Elastic index) and providers configured at the moment

Request Examples

Code Block
curl -X ${method} \ http://localhost:${port}/${url} \ -H 'Content-Type: application/json' \ -d ' { }'

Response

Saga_json

    "msg": "Saga API online",
    "_success": true,
    "buildInfo": {
{
            "elasticSearch": {
                "retries": 3,
                "delay": 5,
                "scheme": "http",
                "hostnamesAndPorts": [
                    "localhost:9200"
                ],
                "indexName": "pii",
                "Implementation-TitleencryptionKey": "Saga Serverf123123##c#$#4GGVqFk7L9123123@*^",
                "Implementation-Build"timeout": "9dde0a32f17264f7b9004fc8d141e5b1cd0838b0",30
        "Implementation-Version": "1.0.0-SNAPSHOT"    },
        "Implementation-Timestamp    "display": "1550261725668Saga",
        "Implementation-Vendor-Id": "com.accenture.saga",}
    ],
    "Built-ByexportSettings": "ronny.ortega.ugalde",{
        "Build-Jdk": "11.0.2"maxSize": 40,
        "Implementation-BranchbatchSize": "develop"5000
    },
    "ssl": false,
    "solutionsproviders": [
        {
            "elasticSearchbaseDir": {
   "./config",
             "indexNamename": "airfilesystem-provider",
            }"encryptionKey": "f123123##c#$#4GGVqFk7L9123123@*^",
            "displaytype": "Saga - EN"
        }FileSystem"
    ],
    "providers": [ },
        {
            "baseDirscheme": "./confighttp",
            "namehostnamesAndPorts": "filesystem-provider",
[
                "type"localhost: 9200"FileSystem"
        },
        {],
            "hostnamename": "localhostsaga-provider",
            "schemeexclude": "http",[
                "portupdatedAt": 9200,
                "name": "saga-provider"createdAt"
            ],
            "excludeencryptionKey": ["f123123##c#$#4GGVqFk7L9123123@*^",
                "updatedAt"type": "Elastic",
                "createdAt"timestamp": "updatedAt"
        }
    ],
            "type": "Elastic",
            "timestamp": "updatedAt"
        }
    ]

Saga_rest_endpoint_legacy

Endpoint	stopServer
Method	GET

Stops the Saga Server

Warning
If you stop the server via HTTP request, it can only be restarted on-premise

Request Examples

Code Block

language	powershell
theme	FadeToGrey

curl --location --request GET 'http://localhost:${port}/${url}'

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