Introduction
To expose AI services to our system, we need an API to be exposed for the MediaHaven installation. When creating new Plugins having of the following https://mediahaven.atlassian.net/wiki/spaces/CS/pages/edit-v2/4438884395#Categories
Embedding
Generative
then MediaHaven will connect to this plugin using REST API calls, which must implement the following methods depending on the category.
Methods
GET /config-rules ALL CATEGORIES
It gives the possible configuration parameters for this connector
Ex.
{
"Rules": [
{
"Name": "TextModel",
"Type": "String|Integer|Boolean",
"Required": false,
"Default" : "ada2"
}
]
}
POST /text-embedding EMBEDDING
Expected parameters
Text as JSON body in Textproperty and Config based on config rules
Ex.
{
"Text": "Given me pictures of lamas",
"Dimensions": 1536,
"Config": {
"TextModel" : "ada2"
}
}
Expected headers
x-api-key: <optional api key>
Output
Array of float (vector) with size equal to dimensions. The vector MUST BE normalized. When the provided dimensions are 0, the embedding should be in the natural dimensions used by the embedding. If the embeddings cannot be provided in the requested dimensions, then a 400 HTTP error code should be returned.
Ex.
{
"Embedding": [
-0.006929283495992422,
-0.005336422007530928,
... (omitted for spacing)
-4.547132266452536e-05,
-0.024047505110502243]
}
POST /embedding EMBEDDING
Expected parameters
Record as JSON body in Metadata property and Config based on config rules
Ex.
{
"Config": {
"TextModel" : "ada2"
},
"Metadata": {
"RightsManagement": {
"Permissions": {...},
"RecordPhase": "Concept",
"ExpiryDate": null,
"ExpiryStatus": null,
"Zone": {}
},
"Dimensions": 1536
}
}
Expected headers
x-api-key: <optional api key>
Output
Array of float (vector) with size equal to dimensions. The vector MUST BE normalized. When the provided dimensions are 0, the embedding should be in the natural dimensions used by the embedding. If the embeddings cannot be provided in the requested dimensions, then a 400 HTTP error code should be returned.
Ex.
{
"Embedding": [
-0.006929283495992422,
-0.005336422007530928,
... (omitted for spacing)
-4.547132266452536e-05,
-0.024047505110502243]
}
POST /describe
POST /generative-metadata/description GENERATIVE
Expected parameters
Record as JSON body in Metadata property and Config based on config rules
Ex.
{
"Config": {
"TextModel" : "ada2"
},
"Metadata": {
"RightsManagement": {
"Permissions": {...},
"RecordPhase": "Concept",
"ExpiryDate": null,
"ExpiryStatus": null,
"Zone": {}
}
}
}
Expected headers
x-api-key: <optional api key>
Output
Textual string
Ex.
{
"Description": "This is an image of a cat"
}
POST /generative-metadata GENERATIVE
Record as JSON body in Metadata property, Fields with as items dotted keys and AI hint as value, Locale as the requested target locale for the output and finally Config based on config rules
Ex.
{
"Fields": {
"Descriptive.Description": {
"Hint": "Give a description for the image"
},
"Descriptive.Keywords.Keyword": {
"Hint": "Give a list of keywords. Generate around 10.",
"Type": "array"
}
},
"Locale": "en_US",
"Config": {
"TextModel" : "ada2"
},
"Metadata": {
"RightsManagement": {
"Permissions": {...},
"RecordPhase": "Concept",
"ExpiryDate": null,
"ExpiryStatus": null,
"Zone": {}
}
}
}
Expected headers
x-api-key: <optional api key>
Output
A JSON object of generated fields with as keys dotted keys and as value the AI's generated value.
Ex:
{
"GeneratedFields": {
"Descriptive.Description": "This is an image of a cat",
"Descriptive.Keywords.Keyword": ["Animal", "Cat", ...]
}
}