# Source: https://deepinfra.com/docs/advanced/webhooks

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  1. [Getting Started](/docs)

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     4. Webhooks

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     1. [Containers](/docs/gpu-instances/containers)

  5. [Custom Deployments](/docs/custom-deployments)

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     2. [Whisper (Speech to Text)](/docs/tutorials/whisper)

     3. [Deprecated Models](/docs/advanced/deprecated)

  8. [Miscellaneous](/docs/misc)

     1. [Data Subprocessors](/docs/misc/subprocessors)

# Webhooks

Webhooks are an exclusive feature of the DeepInfra API. They don't work with
the OpenAI API.

Webhooks deliver inference results and notify you about inference errors.

Using them is simple. You just supply the optional webhook param like in the
following examples

Here is an example with text generation.

JavaScriptbash

    
    
    import { TextGeneration } from "deepinfra";
    
    const DEEPINFRA_API_KEY = "$DEEPINFRA_TOKEN";
    const MODEL_URL = 'https://api.deepinfra.com/v1/inference/meta-llama/Meta-Llama-3-8B-Instruct';
    
    async function main() {
      const client = new TextGeneration(MODEL_URL, DEEPINFRA_API_KEY);
      const res = await client.generate({
        "input": "<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\nHello!<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
        "stop": [
          "<|eot_id|>"
        ],
        "webhook": "https://your-app.com/deepinfra-webhook"
      });
    
      console.log(res.inference_status.status); // queued
    }
    
    main();
    
    
    copy

Here is another example with embeddings.

JavaScriptbash

    
    
    import { Embeddings } from "deepinfra";
    
    const DEEPINFRA_API_KEY = "$DEEPINFRA_TOKEN";
    const MODEL = "BAAI/bge-large-en-v1.5";
    
    const main = async () => {
      const client = new Embeddings(MODEL, DEEPINFRA_API_KEY);
      const body = {
        inputs: [
          "I like chocolate",
        ],
        webhook: "https://your-app.com/deepinfra-webhook",
      };
      const output = await client.generate(body);
      console.log(output.inference_status.status); // queued
    };
    
    main();
    
    
    copy

When you provide a webhook the API server will respond with a **queued**
status and will call the webhook with the actual result. Delivered response
will contain inference result, cost estimate and runtime and/or an error in a
JSON body. It is the same JSON response that you get in a regular inference
calls.

    
    
    {
        "request_id": "R7X9fdlIaF5GlVisBAi5xR3E",
        "inference_status": {
            "status": "succeeded",
            "runtime_ms": 228,
            "cost": 0.0001140000022132881
        },
        "results": {...}
    }
    
    
    copy

Errors will have the following format

    
    
    {
        "request_id": "RHNShFanUP5ExA8rzgyDWH88",
        "inference_status": {
            "status": "failed",
            "runtime_ms": 0,
            "cost": 0.0
        }
    }
    
    
    copy

We will make a few attempts if your webhook endpoint returns 400+ status.

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Tokens](/docs/advanced/scoped_jwt)

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