GoodMemGet an embedder by ID
GET /v1/embedders/{id}: Retrieves the details of a specific embedder configuration by its unique identifier.
Retrieves the details of a specific embedder configuration by its unique identifier. Requires READ_EMBEDDER on the requested embedder. The service distinguishes a missing embedder from an existing embedder the caller cannot read. This is a read-only operation with no side effects.
x-api-key<token>
In: header
Path Parameters
idstring
The unique identifier of the embedder to retrieve
Query Parameters
includeCredentials?boolean
Whether to return stored credentials. Also accepts include_credentials. Requires READ_EMBEDDER_CREDENTIALS in addition to READ_EMBEDDER.
Default
falseResponse Body
curl -X GET "https://your-goodmem-server.example.com/v1/embedders/550e8400-e29b-41d4-a716-446655440000?includeCredentials=true"{
"embedderId": "550e8400-e29b-41d4-a716-446655440000",
"displayName": "OpenAI Ada-2",
"description": "OpenAI's text embedding model with 1536 dimensions",
"providerType": "OPENAI",
"endpointUrl": "https://api.openai.com/v1",
"apiPath": "/embeddings",
"modelIdentifier": "text-embedding-3-small",
"dimensionality": 1536,
"distributionType": "DENSE",
"maxSequenceLength": 8192,
"supportedModalities": [
"TEXT"
],
"credentials": {
"apiKey": {
"inlineSecret": "sk-1234567890abcdef",
"secretRef": {
"uri": "vault://path/to/secret"
},
"headerName": "Authorization",
"prefix": "Bearer "
},
"gcpAdc": {
"scopes": [
"https://www.googleapis.com/auth/cloud-platform"
],
"quotaProjectId": "my-quota-project"
}
},
"labels": {
"environment": "production",
"team": "nlp"
},
"version": "1.0.0",
"monitoringEndpoint": "https://monitoring.example.com/embedders/status",
"ownerId": "550e8400-e29b-41d4-a716-446655440000",
"createdAt": 1617293472000,
"updatedAt": 1617293472000,
"createdById": "550e8400-e29b-41d4-a716-446655440000",
"updatedById": "550e8400-e29b-41d4-a716-446655440000"
}Empty
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