Discover Available Models

Model discovery helps you answer “what can this connection use?” before you hard-code model.id in a .prompty file. Providers return ModelInfo records with the model or deployment id and, when available, context-window and modality metadata.

Support matrix

Runtime	OpenAI	Foundry / Azure OpenAI	Anthropic
Python	`list_models()` / `list_models_async()`	`list_models()` / `list_models_async()`	Not yet exposed
TypeScript	`listModels()`	`listAzureModels()`	Not yet exposed
C#	`OpenAIModels.ListModelsAsync()`	`FoundryModels.ListModelsAsync()`	Not yet exposed
Rust	`list_models()` / `list_models_async()`	Not yet exposed	`list_models()` / `list_models_async()`

from prompty.model import ApiKeyConnection
from prompty.providers.openai.models import list_models

connection = ApiKeyConnection.load({
    "kind": "key",
    "apiKey": "${env:OPENAI_API_KEY}",
})

for model in list_models(connection):
    print(model.id, model.context_window)

To target a direct OpenAI-compatible endpoint, set endpoint on the same ApiKeyConnection.

from prompty.model import ApiKeyConnection
from prompty.providers.foundry.models import list_models

connection = ApiKeyConnection.load({
    "kind": "key",
    "endpoint": "${env:AZURE_OPENAI_ENDPOINT}",
    "apiKey": "${env:AZURE_OPENAI_API_KEY}",
})

for deployment in list_models(connection):
    print(deployment.id, deployment.context_window)

For Foundry/Azure OpenAI, model.id in your .prompty file is the deployment id returned by the endpoint, not necessarily the base model name.

TypeScript

OpenAI
Foundry

import { ApiKeyConnection } from "@prompty/core";
import { listModels } from "@prompty/openai";

const models = await listModels(new ApiKeyConnection({
  kind: "key",
  apiKey: process.env.OPENAI_API_KEY,
}));

for (const model of models) {
  console.log(model.id, model.contextWindow);
}

import { ApiKeyConnection } from "@prompty/core";
import { listAzureModels } from "@prompty/foundry";

const models = await listAzureModels(new ApiKeyConnection({
  kind: "key",
  endpoint: process.env.AZURE_OPENAI_ENDPOINT,
  apiKey: process.env.AZURE_OPENAI_API_KEY,
}));

for (const model of models) {
  console.log(model.id, model.contextWindow);
}

C#

using Prompty.Core;
using Prompty.OpenAI;

var connection = new ApiKeyConnection
{
    ApiKey = Environment.GetEnvironmentVariable("OPENAI_API_KEY"),
};

var models = await OpenAIModels.ListModelsAsync(connection);
foreach (var model in models)
{
    Console.WriteLine($"{model.Id} {model.ContextWindow}");
}

For Foundry/Azure OpenAI, use Prompty.Foundry.FoundryModels.ListModelsAsync() with an ApiKeyConnection that includes Endpoint and ApiKey.

Rust

use serde_json::json;

let models = prompty_openai::list_models_async(&json!({
    "kind": "key",
    "apiKey": std::env::var("OPENAI_API_KEY")?,
})).await?;

for model in models {
    println!("{} {:?}", model.id, model.context_window);
}

Anthropic model listing is available through prompty_anthropic::list_models_async().

Using the result

Once you identify the model or deployment id, put it in frontmatter:

---
name: discovered-model
model:
  id: gpt-4o-mini
  provider: openai
  connection:
    kind: key
    apiKey: ${env:OPENAI_API_KEY}
---
system:
You are a helpful assistant.

If the provider returns deployment ids, use the deployment id exactly as returned.