Settings of models.

GET 
/model-settings

Only models available to the client will be listed.

Responses

200

OK

application/json

Schema

Schema

Array [
namestring
statusstring
The current availability status of the model. Currently supported states are:
• available: The model is configured and a matching worker is connected to serve it.
• unavailable: The model is configured but no worker has shown recent activity to serve it.
Possible values: [available, unavailable]
worker_typestring
The worker type that is used to serve the configured model. The following fields are supported:
• luminous: The model is served by a Luminous worker.
• vllm: The model is served by a vLLM worker.
• translation: Worker type to serve translation requests.
• transcription: Worker type to serve transcription requests.
Possible values: [luminous, vllm, transcription, translation]
descriptionstring
multimodalboolean
Feature flag for whether or not multimodal prompts are available to users.
max_context_sizenumber
The maximum context size of this model.
semantic_embeddingboolean
True if this model supports semantic embeddings.
completion_typestring
The completion type supported by the model.
• none: The model has not been trained to support completions. Trying to trigger a completion request will lead to a validation error.
• full: The model has been trained to support completions.
Possible values: [none, full]
embedding_typestring
The embedding type supported by the model.
• none: The model cannot be used for embeddings. The scheduler will reject requests for embeddings to this model.
• raw: The model has not explicitly been trained to support embeddings. However, it is possible to retrieve the embedding details technically. This option maps to the /embed endpoint.
• semantic: The model has been trained with a switchable set of weights usable for semantic embedding retrieval. This option maps to the /semantic_embed endpoint.
• instructable: The model has been trained to support any custom instruction for embedding retrieval. This option maps to the /instructable_embed endpoint.
This flag replaces semantic_embedding_enabled and should always be set. If embedding_type is unset, semantic_embedding_enabled will take control. If both embedding_type and semantic_embedding_enabled are used, implausible combinations are rejected.
Possible values: [none, raw, semantic, instructable]
alignedboolean
Specifies whether the model is aligned s.t. end users can be warned about the model's limitations.
chatboolean
True if this model is supported by the chat endpoint.
prompt_templatestring
A prompt template that can be used for this model.
]

Example (auto)

[
  {
    "name": "string",
    "status": "available",
    "worker_type": "luminous",
    "description": "string",
    "multimodal": true,
    "max_context_size": 0,
    "semantic_embedding": true,
    "completion_type": "none",
    "embedding_type": "none",
    "aligned": true,
    "chat": true,
    "prompt_template": "string"
  }
]

Authorization: http

name: tokentype: httpscheme: bearerdescription: Can be generated in your [Aleph Alpha profile](https://app.aleph-alpha.com/profile)

• csharp
• curl
• dart
• go
• http
• java
• javascript
• kotlin
• c
• nodejs
• objective-c
• ocaml
• php
• powershell
• python
• r
• ruby
• rust
• shell
• swift

• HTTPCLIENT
• RESTSHARP

var client = new HttpClient();
var request = new HttpRequestMessage(HttpMethod.Get, "https://docs.aleph-alpha.com/model-settings");
request.Headers.Add("Accept", "application/json");
request.Headers.Add("Authorization", "Bearer <token>");
var response = await client.SendAsync(request);
response.EnsureSuccessStatusCode();
Console.WriteLine(await response.Content.ReadAsStringAsync());

Request Collapse all

Auth

Bearer Token