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Introducing Repository Access Permissions and Custom Roles
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@inferagraph/azure-foundry-provider
Advanced tools
Azure AI Foundry provider plugin for @inferagraph/core.
Supports any model in the Azure AI model catalog via the Azure AI Inference SDK (@azure-rest/ai-inference).
pnpm add @inferagraph/azure-foundry-provider @inferagraph/core
import { AzureFoundryProvider } from '@inferagraph/azure-foundry-provider';
const provider = new AzureFoundryProvider({
endpoint: 'https://your-endpoint.inference.ai.azure.com',
apiKey: 'your-api-key',
deploymentName: 'gpt-4o', // optional, sent as `model` on the request
maxTokens: 1024, // optional, default 1024
});
| Option | Required | Description |
|---|---|---|
endpoint | Yes | Azure AI Foundry endpoint URL |
apiKey | One of apiKey / credential | Azure key for the deployment |
credential | One of apiKey / credential | Any @azure/core-auth TokenCredential (e.g., DefaultAzureCredential) |
deploymentName | No | Sent as model in the request body when set |
maxTokens | No | Default max_tokens (1024) |
import { DefaultAzureCredential } from '@azure/identity';
new AzureFoundryProvider({
endpoint: 'https://your-endpoint.inference.ai.azure.com',
credential: new DefaultAzureCredential(),
});
The provider implements @inferagraph/core's LLMProvider contract:
| Method | Supported | Notes |
|---|---|---|
complete(prompt, opts?) | Yes | Single-shot completion via /chat/completions. |
stream(prompt, opts?) | Yes | Single-string streaming. Kept for back-compat — new consumers should prefer streamMessages. |
streamMessages(messages, opts?) | Yes | Structured [{role, content}] streaming. system / user / assistant roles map 1:1 onto Foundry's OpenAI-compatible messages array, so system instructions stay separate from user input end-to-end. Honors opts.signal (AbortController), opts.maxTokens, opts.temperature, and opts.tools. |
embed(texts, opts?) | No | The @azure-rest/ai-inference SDK targets chat-completion routes only; this provider has no native embedding endpoint, so embed is intentionally omitted ('embed' in provider === false). Mirrors the @inferagraph/anthropic-provider no-Voyage path. Hosts that need embeddings pair Foundry chat with a separate embedding-capable provider (for example @inferagraph/openai-provider configured with an embeddingDeployment). The structural absence lets AIEngine detect the missing capability and route embedding work elsewhere. |
import { AzureFoundryProvider } from '@inferagraph/azure-foundry-provider';
const provider = new AzureFoundryProvider({
endpoint: 'https://your-endpoint.inference.ai.azure.com',
apiKey: 'your-api-key',
});
for await (const event of provider.streamMessages([
{ role: 'system', content: 'You are a helpful assistant.' },
{ role: 'user', content: 'Hi.' },
])) {
if (event.type === 'text') process.stdout.write(event.delta);
}
MIT
FAQs
Azure AI Foundry provider for InferaGraph
We found that @inferagraph/azure-foundry-provider demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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